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Electronic Poster
Weekend and Oral

Traditional Posters (no CME credit)

Electronic Power Pitch Poster (no CME credit)

Electronic Poster

Diffusion: In Vivo & Ex Vivo Applications: CNS

Exhibition Hall Monday 8:15 - 9:15

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2-year-old human brain DTI atlas with comprehensive gray and white matter labels
Limei Song1,2, Yun Peng3, Qinmu Peng2, Lei Feng1, Minhui Ouyang2, Huiying Kang3, Shuwei Liu1, and Hao Huang2,4

1Shandong University School of Medicine, Jinan, China, 2The Children’s Hospital of Philadelphia, Philadelphia, PA, United States, 3Beijing Children’s Hospital Affiliated to Capital Medical University, Beijing, China, 4Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States

2-year-old, marking the end of infancy, is critical for understanding not only precisely organized normal brain development but also serving as clinical anatomical references for neurodevelopmental disorders such as autism. The 2-year-old brain labels transformed from adult atlases lead to relatively large offsets due to dramatic and nonlinear neuroanatomical differences of the brains between these two populations. With DTI data from nineteen healthy 2-year-old subjects, we created a 2-year-old brain DTI atlas with comprehensive labels of 124 gray and white matter structures. The test results suggested the established atlas can be applied to label 2-year-old brain images automatically and accurately.

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Children with Sickle Cell Disease treated with Hydroxyurea show increased CVR and White Matter Integrity: a quantitative MRI study
Daniel Kapustin1,2, Jackie Leung1, Isaac Odame1, Suzan Williams1, and Andrea Kassner1,2

1SickKids Hospital, Toronto, ON, Canada, 2University of Toronto, Toronto, ON, Canada

Sickle cell disease (SCD) is a devastating genetic blood disorder leading to chronic anemia and cerebral infarctions. We sought to assess microstructural properties in the WM using diffusion tensor MRI and compare them to measures of cerebrovascular reactivity (CVR). Specifically, we investigated the effect of hydroxyurea (HU) treatment in SCD. Our results show that non-HU patients had increased skew and kurtosis of mean diffusivity in the WM compared to HU patients and healthy controls, and these parameters were correlated to WM CVR in this group. This suggests HU may have beneficial effects on WM microstructural integrity in patients with SCD.

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Feasibility and benefits of 3-tissue constrained spherical deconvolution for studying the brains of babies
Thijs Dhollander1, Julien Zanin2,3, Bryony A. Nayagam2, Gary Rance2,3, and Alan Connelly1,4

1The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia, 2Department of Audiology and Speech Pathology, University of Melbourne, Melbourne, Australia, 3The HEARing Cooperative Research Centre, Melbourne, Australia, 4The Florey Department of Neuroscience, University of Melbourne, Melbourne, Australia

When studying white matter in baby brains with diffusion-weighted imaging, we face a range of challenges, including larger water-content, lower anisotropy, differentiated maturation and a (relatively) larger proportion of the brain being comprised of grey matter.  We attempt to apply single-tissue, 2-tissue and 3-tissue constrained spherical deconvolution (CSD) to single-shell data of two 5 month old babies.  3-tissue CSD still worked successfully.  The nature of benefits was in line with those obtained previously in adults, but they were greater in the babies, mostly due to a much larger presence of GM-like tissue.

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Location-wise Harmonization along White Matter Tracts on Neonatal Brain from Multiple Acquisition Protocols
Simin Liu1,2,3, Xianjun Li1, Miaomiao Wang1, Chao Jin1, Hua Guo3, and Jian Yang1,2

1Department of Diagnostic Radiology, the First Affiliated Hospital of Xi’an Jiaotong University, Xi'an, China, 2Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China, 3Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China

In this work, we proposed white matter location-wise harmonization of DTI measurement on neonatal brain based on tract quantification from multiple acquisition protocols. A total of 120 term neonates examined by two DTI acquisition protocols, including 38 neonates with punctate white matter lesions and 82 without MRI abnormalities, were enrolled. Two methods, Scaling and ComBat, were adopted, each carried out also on global-wise and ROI-wise in addition to location-wise. We also proposed an evaluation framework to systematically compare the adopted harmonization approaches, which suggests the way to select the utmost harmonization level and the specific method.

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DTI Assessment of Regional White Matter Changes in the Cervical and Thoracic Spinal Cord in Pediatric Subjects
Sona Saksena1, Devon M Middleton1, Laura Krisa2, Mahdi Alizadeh1,3, Chris C Conklin1, Adam Flanders1, MJ Mulcahey2, Feroze B Mohamed1, and Scott H Faro4

1Radiology, Thomas Jefferson University, Philadelphia, PA, United States, 2Occupational Therapy, Thomas Jefferson University, Philadelphia, PA, United States, 3Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States, 4Radiology, Johns Hopkins School of Medicine, Baltimore, MD, United States

Synopsis: Prior adult studies have shown that DTI allows for noninvasive assessment of the severity of spinal cord injury (SCI). The aim of this study was to determine whether DTI at sites cephalad and caudal to the injury provides measures of injury severity in pediatric subjects with chronic SCI and compared these data with normative DTI data of typically developing subjects. ROIs were drawn on whole cord and spinal cord white matter (WM) areas: ventral, dorsal, and both right and left lateral regions along the entire cervical and thoracic SC. For each SCI subject, DTI parameters for each WM region were measured at the levels cephalad and caudal relative to MR injury. We demonstrated changes in FA and AD in WM regions at levels both cephalad and caudal to the injury site. This suggests that FA and AD has the potential to be sensitive marker of true extent of cord injury and might be useful in detecting remote injuries.

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Application of Reduced Field-of-View Diffusion-Weighted Imaging in Evaluation of Normal Pituitary Glands and Pituitary Macroadenomas
Miaomiao Wang1, Heng Liu1, Congcong Liu1, Ting Liang1, Xianghui Zhang1, Xianjun Li1, Chao Jin1, and Jian Yang1

1Department of Diagnostic Radiology, the First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China

Field-of-view optimized and constrained undistorted single-shot (FOCUS) imaging provides relatively high resolution images with few artifacts. However, application of this technique for evaluation of normal pituitary glands and pituitary macroadenomas has not been reported to date. The study aims to evaluate the image quality and value of FOCUS DWI in evaluation of normal pituitary glands and pituitary macroadenomas. Our results suggest that FOCUS DWI exhibited obviously superior image quality both in normal pituitary glands and macroadenomas in a clinically feasible scan time. Moreover, it might be helpful for evaluating the consistency of pituitary macroadenomas.

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Apparent diffusion coefficient for molecular subtyping of non-Gadolinium-enhancing WHO grade II/III glioma
Laura Mancini1,2, Sara Hassanein2,3, Sotirios Bisdas1,2, Jeremy H Rees2,4, Harpreet Hyare2,3, John A Maynard3, Sebastian Brandner5, Carmen Tur6, H Rolf Jager1,2,3, Tarek Yousry1,2,3, and Steffi C Thust1,2,3

1Lysholm Department of Neuroradiology, National Hospital for Neurology & Neurosurgery UCLH NHS FT, London, United Kingdom, 2Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, United Kingdom, 3Imaging Department, University College Hospital UCLH NHS FT, London, United Kingdom, 4Neurology Department, Natl Hosp for Neurology & Neurosurgery UCLH NHS FT, London, United Kingdom, 5Department of Neurodegenerative Disease, UCL Institute of Neurology and Division of Neuropathology, London, United Kingdom, 6Department of Neuroinflammation, Queen Square MS Centre, UCL Institute of Neurology, London, United Kingdom

A proportion of non-enhancing intrinsic presumed low-grade-gliomas(LGG), rapidly progresses. Hypothesis: ADC can predict glioma molecular subtypes of the revised 2016 World_Health_Organization brain tumours classification. Methods..44 non-Gadolinium-enhancing LGG divided in three molecular subgroups. 2D and 3D T2-derived tumour and normal-appearing-white-matter (NAWM) masks co-registered to ADC_maps(b=1000s/mm2). Linear-regression, ROC-analysis and logistic-regression compared ADC_values with tumour type. Results..ADCmean and ADCratio(tumour/NAWM) were lowest (p<0.001) in the most malignant tumour type (IDHwt). An ADCmean(ADCratio) threshold of 1201*10-6mm2/s(1.65) identified IDHwt with sensitivity=83%(80%) and specificity=86%(92%) (AUC=0.9-0.94). Between-observers (2D-versus-3D) intraclass-correlation-coefficient=0.98(0.92). Conclusions..ADC measurements can support the distinction of non-enhancing glioma subtypes. 3D and 2D measurements were both accurate.

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Thalamic nuclei segmentation on dementia using tractography and population-specific priors
Carla Semedo1, M. Jorge Cardoso1,2, S. B. Vos1,3,4, Carole H. Sudre1,2, Martina Bocchetta2, Annemie Ribbens5, Dirk Smeets5, Jonathan Rohrer2, and Sebastien Ourselin1,2

1Translational Imaging Group, UCL, London, United Kingdom, 2Dementia Research Centre, UCL, London, United Kingdom, 3MRI Unit, Epilepsy Society, Chalfont St Peter, United Kingdom, 4Wellcome EPSRC Centre for Interventional and Surgical Sciences (WEISS), UCL, London, United Kingdom, 5Icometrix, Leuven, Belgium

Thalamic changes have been reported in several neurological disorders, such as Alzheimer's disease and frontotemporal dementia (FTD). As pathologies affect different cortical and subcortical brain regions disproportionally, accurate segmentation of thalamic nuclei can provide relevant insights about brain function and neurological disorders mechanisms. Here, we used a previously developed thalamus parcellation strategy that relies on tractography and population-specific to infer any connectivity changes in presence of FTD. The obtained results were compared against to the ones derived with the commonly used probabilistic tractography pipeline available in FSL. 

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Kurtosis and IVIM measurements applied to ischemic stroke diagnosis: an initial experience.
Aude Pavilla1,2,3, Alessandro Arrigo4, Giulio Gambarota1,2, Mehdi Mejdoubi3, Régis Duvauferrier3, and Hervé Saint-Jalmes1,2,5

1INSERM, UMR 1099, Rennes, France, 2Université de Rennes 1, LTSI, Rennes, France, 3Department of Neuroradiology, Pierre-Zobda-Quitman Hospital, University Hospital of Martinique, Fort-de-France, Martinique, 4Radiology, CH La Palmosa, Menton, France, 5CRLCC, Centre Eugène Marquis, Rennes, France

Diffusional kurtosis imaging (DKI) enables the characterization of non-Gaussian diffusion providing an additional diffusion parameter, the kurtosis (K), that may reflect microstructure heterogeneity. The DKI-IVIM model that incorporates DKI into the IVIM model has been investigated here to assess the feasibility and the potential utility of the DKI-IVIM model for both enhanced diffusion characterization and perfusion measurements in ischemic stroke.

Five stroke patients were enrolled. DKI-IVIM imaging was performed using 8 b-values from 0 to 1500 s/mm2 with a 4 minutes scan duration. IVIM pseudo-diffusion coefficient D*, perfusion fraction f, blood flow-related parameter fD* in addition to the diffusion parameters D (diffusion coefficient) and K were determined in the ischemic lesion and contralateral normal tissue for the stroke patients. Diffusion and perfusion parametric maps were reconstructed.

A significant decrease for D (p<0.0001) and increase for K (p=0.0002) in the lesion was observed. The perfusion fraction exhibited a significant decrease in the ischemic regions (p=0.005). 

DKI-IVIM model enables for simultaneous cerebral perfusion and enhanced diffusion characterization in an acceptable clinically acquisition time that might improve ischemic stroke diagnosis.


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Interferon-alpha induced changes in NODDI predispose to the development of fatigue
Nicholas G Dowell1, Samira N Bouyagoub1, Mara Cercignani1, and Neil A Harrison1

1Neuroscience and imaging, Brighton and Sussex Medical School, Brighton, United Kingdom

Here we use NODDI modeling of multi-shell diffusion MRI to investigate whether changes in orientation-dispersion index (ODI) or intracellular volume fraction (Vic) can predict the later emergence of IFN-α-induced fatigue. Eighteen patients initiating IFN-α based treatment for hepatitis-C underwent diffusion MRI and blood sampling at baseline and 4 hours after their first IFN-α injection. They were then followed up with regular psychological assessments for 12 weeks of treatment. IFN-α injection stimulated an acute inflammatory cytokine response and evoked acute fatigue that peaked between 4 and 12 weeks of treatment. Within the brain, IFN-α induced an acute increase in intracellular volume fraction in patients that experienced a simultaneous increase in IFN-α induced fatigue but not patients that did not. Acute changes in striatal microstructure additionally predicted the continued development of fatigue but not mood symptoms 4 and 8 weeks later into treatment. Our findings highlight the value of NODDI as a potential in vivo biomarker of the central effects of peripheral inflammation. We highlight the exquisite sensitivity of the striatum to IFN-α and further implicate striatal perturbation in IFN-α-induced fatigue.

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Hippocampal Subfield-specific Tractography in Epilepsy Patients at 7 Tesla
John W Rutland1, Rebecca E Feldman1, Lara V Marcuse2, Madeline C Fields2, Bradley N Delman3, Prantik Kundu 1, Patrick R Hof4, and Priti Balchandani1

1Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 2Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 3Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 4Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States

This is the first investigation to use diffusion tensor imaging at 7 Tesla to quantify changes in the structural connectivity of individual hippocampal subfields in epilepsy patients. Diffusion imaging and automated hippocampal subfield segmentation were performed on 19 epilepsy patients and 10 healthy controls. We found that hippocampal volumes are reduced bilaterally in epilepsy patients compared with controls. Connectivity in the left fimbria and right hippocampal-amygdaloid transition area is significantly reduced in epilepsy patients compared with controls. These findings suggest that connectivity of hippocampal subfields are independently affected in epilepsy patients. 

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Positive DTI Findings After Recovery Following Youth Sport-Related Concussion May Be of Little Clinical Relevance
Najratun Nayem Pinky1, Carolyn Emery2,3,4, Chantel Debert5, and Bradley Goodyear1,6,7

1Biomedical Engineering Graduate Program, University of Calgary, Calgary, AB, Canada, 2Paediatrics, Faculty of Medicine, University of Calgary, Calgary, AB, Canada, 3Community Health Science, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada, 4Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada, 5Physicial Medicine & Rehabilitation, Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada, 6Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada, 7Clinical Neurosciences and Psychiatry, University of Calgary, Calgary, AB, Canada

Mild traumatic brain injury (mTBI), including sport-related concussion, is a major health issue. Diffusion Tensor Imaging (DTI) can be useful for identifying alterations in white matter tracts following sport-related concussion. We found that fractional anisotropy (FA) significantly differed between recovered and control youth within the right anterior thalamic radiation and the right inferior longitudinal fasciculus; however, the effect size (< 0.02 change in FA) suggests that the difference may be of little or no clinical relevance, given the recovered group exhibited no symptoms. Large cohort studies are needed before statistically significant MRI findings should be used to inform return-to-play policy

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Regional Brain Changes in Autonomic, Mood, and Cognitive Control Areas in Adolescents with Single Ventricle Heart Disease
Sadhana Singh1, Bhaswati Roy2, Nancy Halnon3, Alan Lewis4, Mary Woo2, Nancy Pike2, and Rajesh Kumar1,5,6,7

1Department of Anesthesiology, University of California Los Angeles, Los Angeles, CA, United States, 2UCLA School of Nursing, University of California Los Angeles, Los Angeles, CA, United States, 3Division of Pediatric Cardiology, University of California Los Angeles, Los Angeles, CA, United States, 4Division of Pediatric Cardiology, Children’s Hospital Los Angeles, Los Angeles, CA, United States, 5Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States, 6Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States, 7Brain Research Institute, University of California Los Angeles, Los Angeles, CA, United States

Adolescents with single ventricle heart disease (SVHD) show both white and gray matter injury in multiple brain areas that control autonomic, mood, and cognitive functions that are deficient in the condition. However, the nature and extent of brain injury in SVHD are unclear. Using diffusion tensor imaging based MD procedures, we showed wide-spread chronic tissue changes in SVHD subjects in areas involved in autonomic, mood, and cognitive regulatory functions. These findings may have resulted from hypoxia/ischemia- or developmental-induced processes accompanying the condition.

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Brain White Matter Microstructure Changes in Alzheimer disease with Type 2 diabetes:a DKI study
Junyi Dong1, Liang Han1, Xiaoxin Li1, and Yanwei Miao1

1Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China

In this study, the groups were respectively used as the people with Alzheimer disease with type 2 diabetes, Alzheimer disease without type 2 diabetes and healthy person, the effect of high blood glucose on the microstructure in patients with type 2 diabetes mellitus, and the changes on microstructure in patients with AD patients were studied used DKI study, and it was concluded that the high blood glucose level may have certain damage to the microstructure of the white matter. In conclusion, DKI study can evaluate secondary brain microstructure changes from hyperglycemia in T2DM patients.

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Brain Microstructure Changes of gray matter detected by DKI in Alzheimer disease with Type 2 diabetes patients
Junyi Dong1, Xiaoxin Li1, Liang Han1, and Yanwei Miao1

1Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China

In this paper, the experimental group and the control group were respectively used as the people with Alzheimer disease with type 2 diabetes and Alzheimer disease without type 2 diabetes, the effect of high blood glucose on the microstructure in patients with type 2 diabetes mellitus was studied used DKI study, and it is concluded that the high blood glucose level may have certain damage to the microstructure of the gray matter. In conclusion, DKI study can evaluate secondary brain microstructure changes from hyperglycemia in T2DM patients.

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Looking at the structural connectivity of the frontal inferior cortex to better decipher the inhibitory control mechanisms in Obsessive Compulsive Disorder
Ivy Uszynski1,2, Cyril Poupon2, Cédric Pichat3,4, Pauline Favre2, Benjamin Fredembach3, Hervé Mathieu1,5,6,7, Laurent Lamalle6,7, Alexandre Krainik1,6,7, Olivier David1,5, Emmanuel L. Barbier1,5, and Mircea Polosan1,5,8

1Grenoble Institut des Neurosciences, Université Grenoble Alpes, Grenoble, France, 2NeuroSpin, CEA Saclay, Gif-sur-Yvette, France, 3Department of Psychology, Université Grenoble Alpes, Grenoble, France, 4LPNC UMR 5105, CNRS, Grenoble, France, 5INSERM U1216, Grenoble, France, 6Unité Mixte de Service IRMaGe, CHU Grenoble Alpes, Grenoble, France, 7Unité Mixte de Service 3552, CNRS, Grenoble, France, 8Department of Psychiatry, CHU Grenoble Alpes, Grenoble, France

Obsessive-compulsive disorder (OCD) is a neuropsychiatric disease affecting 2.5-3% of the population and characterized by repetitive compulsive behaviours with severe complications such as depression, suicide and addiction. Diffusion MRI is a powerful non-invasive technique that evaluates the integrity of the white matter pathways such as those implicated in the impulse control, likely to be impaired in OCD. Here, we investigate the connectivity of the right posterior inferior frontal cortex and in particular to the presupplementary motor area (also involved in inhibition), to the striatum (involved in proactive and/or selective control) and to the primary motor cortex in the contralateral hemisphere.

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Predicting treatment outcome of schizophrenia based on white matter tract integrity using a support vector classifier
Wen-Bin Luo1, Jing-Ying Huang2,3, Yung-Chin Hsu2, and Wen-Yih Isaac Tseng2,4,5,6

1School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan, 2Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan, 3Department of Radiology, Wei Gong Memorial Hospital, Miaoli, Taiwan, 4Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan, 5Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan, 6Molecular Imaging Center, National Taiwan University, Taipei, Taiwan

Although white matter tract microstructure has been implicated in treatment outcome of schizophrenia, its predictive capability on first-episode patients remains unknown. In the study, diffusion spectrum imaging (DSI) data were acquired from both chronic and first-episode patients, reconstructed by mean apparent propagator (MAP) MRI and analyzed with tract-based automatic analysis (TBAA). Stepwise statistical analysis was then performed to identify specific segments of white matter tracts that were significantly different between remitted and non-remitted chronic patients. We built a support vector classifier on the preprocessed data matrix. The resulting model yielded fair validation and test accuracy on chronic and first-episode patients, respectively.

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Diffusion MRI as an imaging marker of depression from a large and homogenous population study
Julie Coloigner1, Jean-Marie Batail1,2,3, Isabelle Corouge1, Jean-Christophe Ferré1,4, Dominique Drapier2,5, and Christian Barillot1

1Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, VISAGES ERL U-1228, F-35000, Rennes, France, 2Academic Psychiatry Department, Centre Hospitalier Guillaume Régnier, Rennes, France, 3EA 4712 Behavior and Basal Ganglia, CHU Rennes, Rennes 1 University, Rennes, France, Metropolitan, 4Department of Neuroradiology, University Hospital of Rennes, Rennes, France, 52 EA 4712 Behavior and Basal Ganglia, CHU Rennes, Rennes, France

Despite the extensive therapy options available for depression, up to 80% of patients will suffer from a relapse. Consequently, understanding the neural correlates underlying the depression will optimize the diagnosis and treatment of individual depressed patients. The purpose of our study was to investigate alterations of white matter integrity in a large cohort of patients suffering from depression using diffusion tensor imaging. Our findings provide robust evidence that the reduction of white-matter integrity in the interhemispheric connections and fronto-limbic neuronal circuits may play an important role in depression pathogenesis.  

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Wired for music? – a diffusion MRI based study of normative music perception skills
Archith Rajan1, Jacob Antony Alappatt1, Apurva Shah2, Megha Sharda3, Jeffrey M Valla1, Madhura Ingalhalikar2, and Nandini C Singh1,4

1Language,Literacy and Music lab, National Brain Research Centre, Gurgaon, India, 2Department of Electronics and TeleCommunication, Symbiosis Institute of Technology, Symbiosis International University, Pune, India, 3International Laboratory for Brain, Music and Sound (BRAMS), University of Montreal, Montreal, QC, Canada, 4UNESCO Mahatma Gandhi Institute of Education for Peace and Sustainable Development (MGIEP), New Delhi, India

White matter micro-structural correlates of music perception skills have only been studied in expert musicians, although skills can be independent of musical training. We assessed normative variation of music perception skills in adult population by the PROMS-S musicality test. A tract based spatial statistic on high angular diffusion data revealed negative associations between Mode of Anisotropy and d’ measures of total scores, sub-scores of Accent, Embedded Rhythms and Tempo in the Corpus Callosum extending to Corona Radiata. Partial volumes of secondary fiber population also correlated positively to these scores, suggesting the recruitment of inter-hemispheric connections necessary for enhanced music perception.

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The neurosurgical implication of scanner, gradient performance and acquisition protocol on Meyer’s loop reconstruction
Maxime Chamberland1, Chantal M.W. Tax1, William Gray1, and Derek K. Jones1

1CUBRIC, Cardiff University, Cardiff, United Kingdom

The optic radiation (OR) is a key brain fiber bundle of the visual system which must be spared as much as possible during resection of the temporal lobe in epilepsy surgery to prevent visual field defects. Therefore, it is of utmost importance to avoid underestimating its anterior location (Meyer’s loop) with diffusion MRI tractography. For this reason, it is critical that this part of the OR is reconstructed as accurately as possible. In this abstract, we demonstrate that standard diffusion MRI acquisitions potentially underestimate the true location of Meyer’s loop, when compared to state-of-the-art protocols. 

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Retrospective Reduction of Systematic Differences Across Scanner Changes by Accounting for Noise Floor Effects in Diffusion Tensor Imaging
Ken Sakaie1, Xiaopeng Zhou2, Jian Lin1, Josef Debbins3, Mark Lowe1, and Robert Fox4

1Imaging Institute, The Cleveland Clinic, Cleveland, OH, United States, 2Life Science MRI Facility, Purdue University, West Lafayette, IN, United States, 3Keller Center for Imaging Innovation, Barrow Neurological Institute, Phoenix, AZ, United States, 4Neurological Institute, The Cleveland Clinic, Cleveland, OH, United States

Scanner upgrades are a persistent but important problem when conducting MRI research studies. Systematic differences introduced by a scanner upgrade can have undesirable effects on the conclusions of a study. Quantitative tissue microstructure measurements by diffuson tensor imaging (DTI) can be affected by systematic differences in noise floor effects. Noise floor effects are due to rectification of signal by magnitude reconstruction than can, in turn, bias microstructure measurements. A retrospective correction that accounts for noise statistics is proposed to limit systematic differences in DTI measurements across scanner upgrades. A practical measure, signal to noise floor ratio (SNFR) is proposed to determine the conditions under which the retrospective correction works effectively.

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Age-effects on cortical tissue diffusivity
Jordan A. Chad1,2, David H. Salat3, and J. Jean Chen1,2

1Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, 2Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 3MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States

Mean diffusivity (MD) is known to increase with age in the white matter (WM), serving as a measure of age-related WM degeneration. However, age-effects on MD with age have scarcely been studied in the gray matter. Here we examine age-effects on MD across the cerebral cortex. MD is shown to correlate more strongly with age than cortical thickness measurements derived from anatomical MRI. Cortical regions showing the largest MD age-effects include the insula and anterior cingulate, suggesting greatest neurodegeneration in these regions. This work suggests that MD may be used as a sensitive measure of aging in the cerebral cortex.

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Investigating the performance of Diffusional Kurtosis Imaging for group-wise analyses: A study from the Human Connectome Project
Hamed Y. Mesri1, Szabolcs David1, Max A. Viergever1, and Alexander A. Leemans1

1Image Sciences Institute, University Medical Center Utrecht and Utrecht University, Utrecht, Netherlands

Diffusional Kurtosis Imaging (DKI) is an extension to Diffusion Tensor Imaging (DTI), which allows the quantification of non-Gaussian water diffusion and the quantification of parameters related to microstructural changes. In this work, we used high-quality datasets from the Human Connectome Project and non-parametric statistical inference to evaluate the performance of the DKI measures for group-wise studies. To this end, we used the gender information to group the subjects and study the differences. Our results demonstrated that DKI metrics could reveal the differences more accurately compared to DTI metrics.

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IVIM values in healthy brain
Steren Chabert1, Jorge Verdu1,2, Gamaliel Huerta1, Cristian Montalba3, Pablo Cox4, Rodrigo Riveros4,5, Sergio Uribe3,6, Rodrigo Salas1, and Alejandro Veloz1,7

1Biomedical Engineering Department, Universidad de Valparaiso, Valparaiso, Chile, 2Universidad Politécnica de Valencia, Valencia, Spain, 3Center for Biomedical Imaging, Pontificia Universidad Católica de Chile, Santiago, Chile, 4Servicio de Imagenología, Hospital Carlos van Buren, Valparaiso, Chile, 5Facultad de Medicina, Universidad de Valparaiso, Valparaiso, Chile, 6Radiology Department, Pontificia Universidad Católica de Chile, Santiago, Chile, 7Informatics Department, Universidad Técnica Federico Santa María, Valparaíso, Chile

Even though there is much interest in brain IVIM imaging, it is difficult to get a clear view from literature on which values to expect. Our purpose is to obtain healthy brain D, D* and f, to add findings and get closer to reference values. Two distributions of 16 b-values were used to acquire data on 10 volunteers, at 1.5T: one commonly found in literature and the other considered as optimal. Values obtained from the “optimal distribution” were significantly different in all cases but D in white matter. This study emphasizes the dependence of IVIM results on the acquisition scheme applied.


Electronic Poster

Microstructure: Experiments & Applications

Exhibition Hall Monday 8:15 - 9:15

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Biomimetic numerical phantoms for white matter tissues characterization using a reduced number of design parameters
Kevin GINSBURGER1, Fabrice POUPON2, Felix MATUSCHKE3, Jean-François MANGIN2, Markus AXER3, and Cyril POUPON1

1UNIRS, CEA/ISVFJ/Neurospin, Gif-sur-Yvette, France, 2UNATI, CEA/ISVFJ/Neurospin, Gif-sur-Yvette, France, 3INM-1 Forschungszentrum Jülich, Jülich, Germany

We propose to extend the functionalities of the Diffusion Microscopist Simulator to design more realistic white matter phantoms without any input mesh and with few parameters. The biomimetic phantoms can represent crossing configurations with an arbitrary number of fiber populations, include a myelin sheath and Ranvier nodes and account for beading, tortuosity and angular dispersion of fibers.

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Analysis of the T2-Relaxation-Diffusion Correlation MRI in Glioblastoma
Yuan Li1,2, Michelle Kim3, Theodore Lawrence2, Parmar Hemant3, and Yue Cao1,2,3

1Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 2Radiation Oncology, University of Michigan, Ann Arbor, MI, United States, 3Radiology, University of Michigan, Ann Arbor, MI, United States

Analysis of the T2-relaxation-diffusion correlation is an emerging approach. It has the potential to reveal the biophysical behavior of tissue and tumor, which cannot be done by the analysis of T2-relaxation and diffusion MRI  separately.  This study applied this approach to glioblastoma (GBM) and revealed the different correlations between T2 and diffusion in tumor, normal tissue and edema.

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Bound Model for Extracting Small Airway Scales in Pediatric Asthma
Annie Malkus1, Robert V Cadman1, and Sean B Fain1,2,3

1Medical Physics, University of Wisconsin, Madison, WI, United States, 2Radiology, University of Wisconsin, Madison, WI, United States, 3Biomedical Engineering, University of Wisconsin, Madison, WI, United States

We evaluate a morphometric approach for measuring acinar airway and alveolar scales with diffusion weighted MRI of hyperpolarized helium in pediatric asthma subjects.

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In Vivo 3D Axonal Diameter Estimation in the Human Brain with 300 mT/m Gradient MRI
Alfred Anwander1, Thomas R. Knösche1, Thomas Witzel2, Assaf Horowitz3, and Yaniv Assaf3

1Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 3Tel Aviv University, Tel Aviv, Israel

The estimation of neural micro-structure in general and axon diameter in particular became feasible using advanced diffusion imaging frameworks such as CHARMED and AxCaliber. Recently, the AxCaliber model was extended to 3D enabling to capture the axonal properties of any fiber system in the brain. In this work we challenged the utility of using the CONNECTOM MRI, that provides a gradient strength of up to 300 mT/m, for axon diameter estimation. We found that the sensitivity of the model towards small diameter axons increases dramatically with the use of the strong gradient system increasing the validity and accuracy of AxCaliber3D.

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Estimation of Extracellular Matrix Diffusion Properties in Decellularized Porcine Myocardium from DTI
Noel Naughton1, Nicholas Gallo2, Marcella Viacik2, Aaron Anderson1, Bradley Sutton1, and John Georgiadis1,2

1Univeristy of Illinois at Urbana Champaign, Urbana, IL, United States, 2Illinois Institute of Technology, Chicago, IL, United States

We present a method to estimate microstructural parameters of a decellularized pig myocardium using a two-compartment exchange model. We also show that the estimated parameters are in good agreement with other values found in the literature. 

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MRI approaches to map focal cortical dysplasia in focal epilepsy using anomalous diffusion and magnetic susceptibility
Qiang Yu1, David Reutens1, Javier Urriola1, Surabhi Sood1, and Viktor Vegh1

1Centre for Advanced Imaging, University of Queensland, Brisbane, Australia

Focal cortical dysplasias (FCD) are developmental malformations of the cerebral cortex that are often highly epileptogenic. When medications fail to control seizures, surgical removal of dysplastic epileptogenic tissue may be curative. But, in 20-­40% of patients current MRI scans cannot identify FCD affected brain regions. Building on the anomalous nature of diffusion and magnetic susceptibility of tissue, we aimed to improve in vivo identification of FCD in the brain. We found the combination of anomalous diffusion model parameters and tissue magnetic susceptibility can be used to differentiate FCD from healthy tissue in the brain.

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A two-perfusion compartment model for human placenta.
Michele Guerreri1,2, Amanda Antonelli3, Silvia Bernardo3, Carlo Catalano3, Lucia Manganaro3, and Silvia Capuani2

1SAIMLAL department, Sapienza University, Rome, Italy, 2ISC, CNR, Rome, Italy, 3Department of Radiological, Oncological and Pathological Sciences, Rome, Italy

This work proposes the use of a two perfusion comparmtent model to fit diffusion MRI data of human placenta. The aim of the work is to characterize the parameters values and compare them with results obtained in animal models.

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Does the g-ratio influence resting-state functional connectivity? A group-level analysis
Matteo Mancini1, Charlotte Clarke2, Nick Dowell2, Neil Harrison2, and Mara Cercignani2,3

1Translational Imaging Group, University College London, London, United Kingdom, 2Brighton and Sussex Medical School, Department of Neuroscience, University of Sussex, Brighton, United Kingdom, 3Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy

Recent findings have shown specific relationships between the cortical myeloarchitecture of the brain and resting-state functional connectivity patterns, while little is known about the white matter myelin distribution. The aim of this work is to preliminary characterize how the g-ratio (i.e., the ratio of the inner and the outer diameters of myelinated axons) and functional connectivity are interrelated. We characterized at group level connectivity patterns using structural connectivity, functional connectivity and g-ratio. We then assessed potential differences between specific functional modules. We observed different distributions when comparing structure and function in terms of g-ratio, and reported significant differences.

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More certainty about your uncertainty in diffusion MRI microstructure estimates
Robbert Leonard Harms1 and Alard Roebroeck1

1Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands

Diffusion MRI microstructure approaches use point estimates ignoring the uncertainty in these estimates. In this work, we evaluate two general methods to quantify uncertainty and generate uncertainty maps for any microstructure model. We find that the Fisher Information Matrix method based in nonlinear optimization is fast and accurate for models with few parameters. The Markov Chain Monte Carlo (MCMC) based method takes more time, but provides robust uncertainty estimates even for sophisticated models with more parameters. Uncertainty estimates of microstructure measures can help power evaluations for group/population studies and assist in data quality control and analysis of microstructure model fit.

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Disentangling the Effects of Anisotropy and Orientation Dispersion Using Diffusion Spherical Mean Spectrum Imaging
Tiantian Xu1, Geng Chen1, Haiyong Wu1,2, Weili Lin1, Dinggang Shen1,3, and Pew-Thian Yap1

1University of North Carolina, Chapel Hill, NC, United States, 2Xiaozhuang University, Nanjing, China, 3Korea University, Seoul, Korea, Democratic People's Republic of

Diffusion fractional anisotropy (FA) measures voxel-level anisotropy, which mingles the effects of neurite microscopic-level anisotropy and orientation dispersion. We introduce a technique, called spherical mean spectrum imaging (SMSI), that can disentangle these two effects. We applied SMSI on baby brain diffusion MRI data collected during the first year of life and show that SMSI can extract microstructural information that is elusive to diffusion tensor imaging (DTI).  

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Quantification of white matter pathologies during multiple sclerosis disease development
Chunyu Song1, Peng Sun2, Anne H. Cross3, and Sheng-Kwei Song4

1Biomedical Engineering, Washington University in St. Louis, st louis, MO, United States, 2Radiology, Washington University in St. Louis, st louis, MO, United States, 3Neurology, Washington University in St. Louis, st louis, MO, United States, 4The Hope Center for Neurological Disorders, Washington University in St. Louis, St Louis, MO, United States

A new diffusion MRI histology (D-Histo) is proposed to model both intra and extra axonal diffusion, in addition to isotropic diffusion. It not only resolves crossing fibers but also quantitatively assess axonal injury, axon loss, demyelination, edema and inflammation. Through the multiple-tensor modelling of diffusion-weighted MRI signals, D-Histo has shown promise to monitor evolving pathologies in normal appearing corpus callosum in multiple sclerosis patient brain. 

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Determining how varying the number of gradient strengths and frequencies affects fitted mean axon diameters in the corpus callosum using oscillating spin echo gradients
Morgan Mercredi1, Sheryl L Herrera1, Richard Buist2, Kant Matsuda3, and Melanie Martin1,4

1Physics and Astronomy, University of Manitoba, Winnipeg, MB, Canada, 2Radiology, University of Manitoba, Winnipeg, MB, Canada, 3Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY, United States, 4Physics, University of Winnipeg, Winnipeg, MB, Canada

There is an increasing drive to use diffusion spectroscopy to infer the sizes of structures in samples. We present here the first use of the sine OGSE to infer the effective mean axon diameters in the human corpus callosum and study the effect on accuracy of reducing the number of images used in the inference.  Aiming to reduce imaging times, this study examines how the number of frequencies or number of gradients affects accuracy and precision. We found that collecting OGSE data with two gradients gives a difference in results of less than 5% compared to six gradients.

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Exchange arising from myelin water revealed from temperature-dependent multiexponential T2 mapping
Noam Shemesh1 and Mark D Does2

1Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal, 2Biomedical Engineering, Vanderbilt University, Nashville, TN, United States

The importance of myelin water exchange in relaxation and diffusion metrics extracted from tissues is still an open question. In particular, to what extent myelin water fraction (MWF) values derived from multiexponential T2 are due to exchange between myelin and intra/extra axonal spaces remains unclear. Here, fixed rat spinal cords were subject to temperature-dependent multiple spin echo experiments, aiming to probe how exchange modulates quantitative T2 maps in rat spinal cords. We find signatures for exchange from T2 shift patterns, which are tightly linked to the axon diameters in the spinal cord. 

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Fast and robust estimation of NODDI parameters using non-Gaussian noise models and spatial regularization
Erick Jorge Canales-Rodríguez1,2,3, Jean-Philippe Thiran1,2, and Alessandro Daducci1,2,4

1Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland, 2Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 3FIDMAG Germanes Hospitaláries, Barcelona, Spain, 4Computer Science Department, University of Verona, Verona, Italy

In this study we developed a robust inversion algorithm to estimate the Neurite Orientation Dispersion and Density Imaging (NODDI) model. It is based on the Accelerated Microstructure Imaging via Convex Optimization (AMICO) framework. However, in contrast to AMICO, the proposed method relies on realistic MRI noise models. Moreover, it allows to take into account the underlying spatial continuity of the brain image by including a total variation regularization term. In simulated data the new method was effective in reducing the outliers, producing results more close to the ground-truth and with lower variability. The method was also evaluated on real data.

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Diffusional changes of perivascular space in focused ultrasound induced Blood-Brain Barrier disruption in rat brain
Heajung Choi1, Huijin Song2, Kyung Eun Jang1, Hyunsil Cha1, Eunji Kim1, Mujin Yang1, Jiung Yang1, Hoesu Jung3, Mun Han4, Taekwan Lee3, Juyoung Park4, and Yongmin Chang1,5

1Department of Medical & Biological Engineering, Kyungpook National University, Daegu, Republic of Korea, 2Institute of Biomedical Engineering Research, Daegu, Republic of Korea, 3Laboratory Animal Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, Republic of Korea, 4Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, Republic of Korea, 5Department of Radiology, Kyungpook National University, Daegu, Republic of Korea

Focused ultrasound (FUS) induces microbubble oscillation, which loosens the tight junction of the endothelial cells in the brain and opens Blood-Brain Barrier (BBB). In this study, we opened the BBB of rat brain using the MRI guided FUS to investigate the changes of diffusivity in perivascular space using diffusion-weighted imaging (DWI). Our results showed that ADC of the perivascular space increased after sonication suggesting the increased water diffusion in perivascular space after BBB opening. Therefore, our study suggests that ADC change can be a possible imaging marker for opening of BBB.

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Feasibility of VERDICT-MRI for non-invasive characterisation of rectal cancer microstructure
Maira Tariq1, Christopher Liao2, Elisenda Bonet-Carne1,3, Andrew A Plumb2, Manuel Rodriguez-Justo4, Daniel C Alexander1, Manish Chand2, David Atkinson3, and Eleftheria Panagiotaki 1

1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 2University College London Hospital, London, United Kingdom, 3Centre for Medical Imaging, University College London, London, United Kingdom, 4Department of Pathology, University College London Hospital, London, United Kingdom

This work evaluates the feasibility of in-vivo microstructure imaging for rectal cancer using the VERDICT MRI framework. We perform a model comparison to find the form of VERDICT that can describe the rich DW-MRI data. Preliminary results from two subjects show promise for non-invasive clinical rectal cancer characterisation. We find that a multi-compartment VERDICT model that explicitly models restriction explains the signal in the rectal tissue better than the conventional cancer models and shows plausible estimates of microstructure in the rectal cancer tissue. Future work will compare these findings with corresponding histology.

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Towards the assessment of myelination using time-dependent diffusion MRI indices.
Abib O. Y. Alimi1, Alexandra Petiet2, Mathieu Santin2, Anne-Charlotte Philippe2, Stephane Lehericy2,3, Rachid Deriche1, and Demian Wassermann1,4

1Université Côte d'Azur, Inria, Valbonne, France, 2Institut du Cerveau et de la Moelle épinière – ICM, Centre de NeuroImagerie de Recherche – CENIR, Paris, France, 3Sorbonne Universités, UPMC Univ Paris 06, Inserm U1127, CNRS UMR 7225, Paris, France, 4Inria, CEA, Université Paris-Saclay, Paris, France

We study the sensitivity of time-dependent diffusion MRI indices or qτ-indices to demyelination in the mouse brain. For this, we acquire in vivo four-dimentional diffusion-weighted images -varying over gradient strength, direction and diffusion time-  and estimate the qτ-indices from the corpus callosum. First order Taylor approximation of each index gives fitting coefficients α and β whose variance we investigate. Results indicate that, cuprizone intoxication affects mainly index coefficient β by introducing inequality of variances between the two mice groups, most significantly in the splenium and that MSD increases and RTOP decreases over diffusion time τ.

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Towards Non-Invasive Characterization of Intravoxel Tumor Heterogeneity: Correlation between Non-Gaussian Diffusion MRI and Histology Using Machine Learning
Muge Karaman1, Lingdao Sha2, Tingqi Shi1, Weiguo Li3,4, Dan Schonfeld2,5,6, Tibor Valyi-Nagy7, and Xiaohong Joe Zhou1,6,8

1Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States, 2Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, IL, United States, 3Research Resource Center, University of Illinois at Chicago, Chicago, IL, United States, 4Department of Radiology, Northwestern University, Chicago, IL, United States, 5Department of Computer Science, University of Illinois at Chicago, Chicago, IL, United States, 6Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States, 7Department of Pathology, University of Illinois at Chicago, Chicago, IL, United States, 8Departments of Radiology, and Neurosurgery, University of Illinois at Chicago, Chicago, IL, United States

Tissue heterogeneity is an important consideration for diagnosing many diseases. Recently, a novel non-Gaussian diffusion model – continuous-time random-walk model (CTRW) – provided promising evidence indicating a possible link between voxel-level spatiotemporal diffusion heterogeneity and microscopic intravoxel tissue heterogeneity. Establishing a correlation between imaging-based and histology-based measurements, however, has been challenging because of the lack of efficient and subjective evaluation of tissue heterogeneity histologically.  In this study, we applied a machine-learning algorithm to quantitatively determine microscopic tissue heterogeneity, enabling a correlation between intravoxel diffusion heterogeneity based on CTRW parameters and structural heterogeneity from histopathology.

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Stromal collagen content correlates with fast diffusivity signal fraction in breast lesions
Liv Egnell1,2, Igor Vidić1, Dennis W. Adams, Jr.3, Neil P. Jerome2,4, Torill E. Sjøbakk4, Agnes Østlie2, Hans E. Fjøsne5,6, Rebecca Rakow-Penner7, Anders M. Dale7,8, Anna M. Bofin9, Tone F. Bathen4, and Pål Erik Goa1,2

1Department of Physics, NTNU – Norwegian University of Science and Technology, Trondheim, Norway, 2Clinic of Radiology and Nuclear Medicine, St. Olavs University Hospital, Trondheim, Norway, 3Department of Pathology, University of California San Diego School of Medicine, San Diego, CA, United States, 4Department of Circulation and Medical Imaging, NTNU – Norwegian University of Science and Technology, Trondheim, Norway, 5Department of Cancer Research and Molecular Medicine, NTNU – Norwegian University of Science and Technology, Trondheim, Norway, 6Department of Surgery, St. Olavs University Hospital, Trondheim, Norway, 7Department of Radiology, University of California, San Diego, La Jolla, CA, United States, 8Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States, 9Department of Clinical and Molecular Medicine, NTNU – Norwegian University of Science and Technology, Trondheim, Norway

The deviation from a monoexponential of the DW-signal decay towards higher b-values (>1000s/mm2) reflects the complex tissue microstructure. The biexponential decay model assumes that the signal is composed of two components with different diffusivity, possibly originating from two physically separated tissue components. In this study, we estimate the collagenous and non-collagenous extracellular contents in sixteen breast lesions using hematoxylin-eosin-saffron stained histological specimens and compare with pre-surgical in vivo DW-MRI data. Our results show that the signal fraction of the faster diffusivity component correlated significantly with collagen content, suggesting that collagen contributes to the DWI signal decay

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Multimodal microstructure imaging: joint T2-relaxometry and diffusometry to estimate myelin, intracellular, extracellular, and cerebrospinal fluid properties
Marco Pizzolato1, Erick Jorge Canales-Rodríguez1,2, Alessandro Daducci1,2,3, and Jean-Philippe Thiran1

1Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 2Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland, 3Computer Science Department, University of Verona, Verona, Italy

We propose a multimodal joint estimation that aims at exploiting the complementary information of diffusion and multi-echo spin echo data to disentangle the contributions and properties of the main tissue microstructure compartments. We recovered T2, diffusion coefficient, and volume fractions values of myelin, intracellular, extracellular, and cerebrospinal fluid compartments within an ex vivo spinal cord sample by means of diffusometry and relaxometry. A g-ratio map was also calculated.

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Prostate Cancer Classification Using Stretched Exponential Model Parameters of Diffusion Signal Decay
Meltem Uyanik1, Michael Abern2, Brandon Caldwell2, Muge Karaman3, Winnie Mar4, Virgilia Macias5, Xiaohong Joe Zhou1,3,4,6, and Richard Magin7

1Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States, 2Urology, University of Illinois at Chicago, Chicago, IL, United States, 3Center for Magnetic Resonance Research, College of Medicine, University of Illinois at Chicago, Chicago, IL, United States, 4Radiology, University of Illinois at Chicago, Chicago, IL, United States, 5Pathology, University of Illinois at Chicago, Cahicago, IL, United States, 6Neurosurgery, University of Illinois at Chicago, Chicago, IL, United States, 7Richard and Loan Hill Department of Bioengineering, University of Illinois, Chicago, IL, United States

Prostate cancer is a common malignancy among men. Using MRI to discriminating high-grade disease from benign and indolent cancer in the prostate is highly desirable for treatment planning. Single and multi- exponential models of diffusion signal decay in the prostate has proven useful for determining prostate cancer tissue structure. However, classification of cancer grade remains illusive. In this study, we investigate  the stretched exponential signal decay model using histology and ROC analysis to determine if it will more accurately characterize aggressive prostate cancer. 

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Pre-surgical high-resolution microstructural imaging in mesial temporal lobe epilepsy
Farshid Sepehrband1, Ryan P Cabeen1, Meng Law1,2, and Kristi A Clark1

1Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck school of medicine of USC, University of Southern California, Los Angeles, CA, United States, 2Department of Radiology, University of Southern California, Los Angeles, CA, United States

The gold standard for the treatment of medically refractory temporal lobe epilepsy continues to be surgical resection. This technique is not significantly different from when it was first popularized by Wilder Penfield in 1952. Significant advances in treatment are limited by our understanding of the structural abnormalities within the hippocampus prior to resection. In addition, pre-surgical planning for minimized resection demand accurate localization of hippocampal sclerosis (HS), which is limited by the achievable neuroimaging resolution. With advances in structural and diffusion MRI, microstructural imaging of brain tissue in high resolution is made possible, which can aid pre-surgical planning.

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Isotropic diffusion weighted 3D oscillating gradients at 7T
Ivan I Maximov1, Sebastian Vellmer2, Rüdiger Stirnberg3, and Tony Stöcker3

1Oslo University, Oslo, Norway, 2Berstein Center for Computational Neuroscience, Berlin, Germany, 3German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany

The diffusion MRI represents a signal obtained from the relatively large voxel size consisting of complex tissue microstructure. Modern diffusion MRI strategies typically work with one parametric dimension associated with either b-value or diffusion time. In turn, spatial anisotropy of biological tissue demands to take into account a high angular resolution. In order to simplify the interpretation of the diffusion signal, we introduce isotropic diffusion weightings. Essentially, we sample the diffusion signal by 3D oscillating gradient method. Novel biomarkers such as surface-to-volume ratio and mean neurite diameter are presented.

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Diffusion MRI in muscles at high b-values: towards a quantification of microscopic organelles
Nicolas Moutal1, Denis Grebenkov1, Sylvie Clerjon2, Guilhem Pages2, and Jean-Marie Bonny2

1PMC, CNRS – Ecole Polytechnique, F-91128, Palaiseau, France, 2AgroResonance - UR370 QuaPA, F-63122, Saint Genès Champanelle, France

We present an application of diffusion MRI at high b-values to a non-invasive quantification of micron-sized organelles such as mitochondria. The experiments were conducted ex vivo on pork muscle and analyzed with a bi-exponential tensorial model, which allows us to estimate the mitochondria content in the muscle. Even though a more systematic comparison between mesoscale diffusion and microscale histology is deserved, this work is a proof of concept and a prerequisite for developing in vivo methods for quantifying the content of various organelles in muscles, e.g. for studying mitochondrial dysfunction in aging.


Electronic Poster

Image Analysis for Neuroimaging

Exhibition Hall Monday 8:15 - 9:15

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Atlas-based brain extraction for bias field-affected structural imaging demonstrated using MPRAGE in marmoset
Isaac Huen1, Krishna Kanth Chitta1, Kuan Jin Lee2, Philip Lee3, Kheng Choon Lim4, Lisa F. P. Ng5, and Bhanu Prakash KN1

1Signal and Image Processing Group, Laboratory of Metabolic Imaging, Singapore Bioimaging Consortium, Singapore, Singapore, 2MR Methods Development Group, Laboratory of Metabolic Imaging, Singapore Bioimaging Consortium, Singapore, Singapore, 3Functional Metabolism Group, Laboratory of Metabolic Imaging, Singapore Bioimaging Consortium, Singapore, Singapore, 4Department of Diagnostic Radiology, Singapore General Hospital, Singapore, Singapore, 5Laboratory of Microbial Immunity, Singapore Immunology Network, Singapore, Singapore

Changes in volume and shape of structures under an intervention or disease state can be measured in many subjects by automatic segmentation of structural imaging. However, unwanted intensity variation (bias field artefact), such as observed using a surface coil, can compromise such segmentation. We investigated how this artefact could be resolved using post-processing, to yield accurate brain extraction from MPRAGE acquisition in a marmoset. This atlas-based method (ASM) significantly improved brain extraction, correcting multiple inaccuracies of the initial FSL-based method (FSM) such as exclusion of the olfactory bulb and inferior cerebellar structures, and is robust to bias field artefact.

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Fast and robust unsupervised identification of MS lesion change using statistical detection of changes (SDC) algorithm
Thanh D Nguyen1, Shun Zhang1, Ajay Gupta1, Susan A Gauthier1, and Yi Wang1

1Weill Cornell Medical College, New York, NY, United States

The objective of this study was to develop a robust automated lesion change detection algorithm for MS. Our preliminary results in 30 patients show that our SDC algorithm achieves much higher sensitivity and specificity (99%/76%) compared to that obtained with off-the-shelf LPA algorithm (76%/27%).

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Clinical feasibility of Quantitative Susceptibility Mapping with Automatic Uniform Cerebrospinal Fluid Zero Reference
Shun Zhang1,2, Zhe Liu2,3, Yihao Yao1, Thanh D. Nguyen2, Pascal Spincemaille2, and Yi Wang2,3

1Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 2Radiolgy, Weill Cornell Medical College, NewYork, NY, United States, 3Biomedical Engineerring, Cornell University, Ithaca, NY, United States

Longitudinal and cross-center studies using conventional quantitative susceptibility mapping (QSM) methods require the choice of a reference tissue, its manual segmentation and subtraction of its average. In this work, we report our initial clinical experience with a fully automated zero-referenced Morphology Enabled Dipole Inversion (MEDI+0) method that uses the ventricular cerebrospinal fluid (CSF) as zero reference in 393 consecutive patients. In 92.62% of cases, excellent agreement of image quality between MEDI+0 and MEDI was observed with high correlation of lesion susceptibility in a combined glioma, ischemic stroke and multiple sclerosis subset of patients. 

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Thalamus in schizophrenia revisited: a partial-volume estimation study
Philipp S. Baumann1,2, Elena Najdenovska3,4, Mário João Fartaria4,5, Alessandra Griffa3, Timo Roine2,3,4, Yasser Alemán-Gómez2,3,4, Emeline Mullier3, Philippe Golay1, Zita Rovo2, Patric Hagmann3, Kim Q. Do2, Philippe Conus1, Pascal Steullet2, and Meritxell Bach Cuadra3,4,6

1Service of General Psychiatry, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 2Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 3Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 4Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), Lausanne, Switzerland, 5Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 6Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

The thalamus has a central role in the pathophysiology of schizophrenia. Formed by several nuclei, it is mainly constituted by a mixture of grey and white matter and, thus, its MR signal is heavily affected by the partial volume (PV) effect. We hypothesize that tissue segmentation based on a PV model will better depict subtle changes in schizophrenia patients than total thalamus volume or local tissue volume measurements that do not consider PV. Results show statistically significant changes in gray matter and white matter average concentration from PV model within the thalamus in schizophrenia patients (SCHZ) compared to healthy controls (HC).

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Comparison study of Visualization of Low Intensity Spots between Susceptibility Weighted Imaging and Quantitative Susceptibility Mapping Created from the Same Raw Phase
Yasutaka Fushimi1, Tomohisa Okada2, Yuta Urushibata3, Takuya Hinoda1, Takayuki Yamamoto1, Hikaru Fukutomi1, Yusuke Yokota1, Sonoko Oshima1, Akira Yamamoto1, Tsutomu Okada1, and Kaori Togashi1

1Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan, 2Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan, 3Siemens Healthcare Japan K. K., Tokyo, Japan

This study was conducted to evaluate the contrast of microbleeds between SWI and QSM created from the identical raw phase of SWI. QSM was created by using STI Suite. The contrast between low intensity spot on SWI and the surrounding brain parenchyma was significantly higher in QSM than SWI.

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Regional Differences in Cortical Diffusion MRI Measurements Based on the HCP Dataset
Zifei Liang1, Di Wang1, Tanzil Arefin1, Yulin Ge1, and Jiangyang Zhang1

1Dept. of Radiology, New York University School of Medicine, NEW YORK, NY, United States

Diffusion MRI (dMRI) is widely used for investigation of microstructural properties of white matter structures, but its application in cortical gray matter structures has only emerged recently due to limited spatial resolution.  Little is known of the normal dMRI measurements among different cortical gray matter structures, their variations, and regional differences. In this work, we present the normative values of healthy volunteers for dMRI metrics across 74 parcellated cortical regions based on well-characterized high-resolution human connectome project (HCP) dataset. We found regional differences in several dMRI metrics among these cortical regions to be mainly in mean diffusivity and kurtosis.  

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PROBABILISTIC MODEL-BASED FUNCTIONAL PARCELLATION OF THE PRIMARY OLFACTORY CORTEX
Prasanna Karunanayaka1, Jiaming Lu2, Christopher Sica1, Bing Zhang2, Qing Yang1, Paul Eslinger3, and Ronald Janssen4

1Radiology, Center for NMR Research, Penn State University College of Medicine, Hershey, PA, United States, 2Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Nanjing, China, 3Neurology, Penn State University College of Medicine, Hershey, PA, United States, 4Radboud University Nijmegen, Donders Centre for Brain Cognition and Behaviour, Nijmegen, The Netherlands, Nijmegen, Netherlands

The primary olfactory cortex (POC) is the largest recipient of olfactory bulb projections. It has a functionally versatile organization with extensive reciprocal connections to several higher-order cortical regions likely resulting in specific brain signals. Here, we propose a Bayesian model-based clustering approach, applied solely to resting state functional MRI time courses, to identify intrinsic POC functional parcellations. Results of this study suggest that multiple regions within the POC, with clear inter-hemispheric correspondence and functional relevance, can be identified using resting state fMRI data.  

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A Deep Learning Approach to Synthesize FLAIR Image from T1WI and T2WI
Takashi Abe1 and Noriko Salamon1

1Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States

We synthewized FLAIR images of the brain from T1WI and T2WI by using autoencoder, which is one of the state of the art deep-learning technology.  Autoencoder compresses the input information and reproduces the information therefrom.  We used T1WI and T2WI as an input and synthewized FLAIR image with high accuracy.  This method could be applicable to other body part other than the brain and might synthewize of other MR imaging sequences.  This technology seems to be useful to improve clinical diagnosis and computer-aided diagnosis.

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Automatic quality assessment of high-resolution T2-weighted images used in hippocampus volumetry and functional studies – a tool developed as part of DZNE-DELCODE study.
Arturo Cardenas-Blanco1,2, Yi Chen3, Jose Pedro Valdes-Herrera4, Laura Dobisch1, Renat Yakupov1, Klaus Fliessbach5,6, Michael Wagner5,6, Annika Spottke6, Stefan Teipel7,8, Katharina Buerger9,10, Anja Schneider5,6, Oliver Peters11,12, Peter Nestor1, Josef Priller11,12, Jens Wiltfang13,14, Christoph Laske15,16, Frank Jessen6,17, and Emrah Duezel1,3,18

1German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany, 2IKND, Magdeburg, Germany, 3Institute of cognitive neurology and dementia research, Magdeburg, Germany, 4Aging & Cognition Research Group, German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany, 5Department of Psychiatry, University Hospital Bonn, Bonn, Germany, 6German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany, 7German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany, 8Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany, 9German Center for Neurodegenerative Diseases (DZNE), Munich, Germany, 10Institute for Stroke and Dementia Research, Ludwig-Maximillian-Universitaets, Munich, Germany, 11Department of Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany, 12German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany, 13Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Goettingen, Germany, 14German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany, 15Department of Psychiatry and Psychotherapy, Eberhard Karls University, Tuebingen, Germany, 16Aging & Cognition Research Group, German Center for Neurodegenerative Diseases (DZNE), Tuebingen, Germany, 17Department of Psychiatry, University of Cologne, Cologne, Germany, 18Institute of Cognitive Neuroscience, University College London, London, United Kingdom

This abstract presents a processing pipeline developed to automatically assess the quality of specific structural T2-weighted images typically acquired in the study of the hippocampus. By combining existing neuroimaging tools, the presented pipeline generates descriptive information about the signal properties in different tissue classes of the T2-weighted image. This information could subsequently be used to detect sub-optimal volumes due to noise or motion artifacts. Similarly as it measures the angulation of the T2-weighted slices with respect to the HC, it could also be used to automatically determine whether the field of view angulation follows protocol.

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Large Vessel Filtering of In Vivo High-Resolution Mouse CBV Map Using Expectation-Maximization Gaussian Mixture Model
Jia Guo1 and Scott A. Small2

1Department of Biomedical Engineering, Columbia University, New York, NY, United States, 2Departments of Neurology, Radiology or Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY, United States

When examining relative cerebral blood volume (rCBV) between mice, values from the unwanted large vessels should be excluded, otherwise, they may result in findings that are not associated with the basal metabolism mapped by microvascular blood volume. Our proposed method provides an automated and robust approach to estimate the rCBV distribution in large vessels with the maximum likelihood estimation using expectation-maximization Gaussian mixture model and to help filter out this unwanted confounding. In research related to rCBV analysis, we suggest applying this as one preprocessing step, which may help improve both sensitivity and specificity when comparing rCBV between subjects. 

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Regression of Quasi-Periodic patterns diminishes BOLD functional connectivity and reveals hidden dynamic correlations
Michaël Belloy1, Behnaz Yousefi2, Anzar Abbas2, Annemie van Der Linden1, Georgios A. Keliris1, Marleen Verhoye1, and Shella Keilholz2

1University of Antwerp, Antwerpen, Belgium, 2Emory university, Atlanta, GA, United States

Quasi-Periodic patterns (QPPs) represent large-scale recurring patterns in the brain, which appear as promising contributors to low frequency BOLD fluctuations. To assess the impact of QPPs on functional connectivity (FC), we used a general linear model approach to regress their contribution out of the functional images of a group of wild-type mice. We show that QPP regression diminished FC in co-active regions within the QPP, while anti-correlated regions became correlated. By calculating FC on QPP-scrubbed images, we highlight that these effects are not solely an artifact of regression. These results suggest that QPPs orchestrate dynamic correlations between resting state networks.

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Preliminary investigation of QSM stability across sites
Renat Yakupov1, Arturo Cardenas-Blanco1,2, Klaus Fliessbach3,4, Michael Wagner3,4, Annika Spottke4, Stefan Teipel5,6, Katharina Bürger7,8, Anja Schneider3,4, Oliver Peters9,10, Peter Nestor1, Josef Priller9,10, Jens Wiltfang11,12, Christoph Laske13,14, Frank Jessen3,15, Emrah Duezel1,2,16, and Julio Acosta-Cabronero1,17

1German Center for Neurodegenerative Diseases, Magdeburg, Germany, 2Institute for Cognitive Neurology and Dementia Research, Otto-von-Guericke University, Magdeburg, Germany, 3Department of Psychiatry, University Hospital Bonn, Bonn, Germany, 4German Center for Neurodegenerative Diseases, Bonn, Germany, 5Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany, 6German Center for Neurodegenerative Diseases, Rostock, Germany, 7Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität, Munich, Germany, 8German Center for Neurodegenerative Diseases, Munich, Germany, 9Department of Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany, 10German Center for Neurodegenerative Diseases, Berlin, Germany, 11Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany, 12German Center for Neurodegenerative Diseases, Göttingen, Germany, 13Department of Psychiatry and Psychotherapy, Eberhard Karls University, Tübingen, Germany, 14German Center for Neurodegenerative Diseases, Tübingen, Germany, 15Department of Psychiatry, University of Cologne, Cologne, Germany, 16Institute of Cognitive Neuroscience, University College London, London, United Kingdom, 17Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, United Kingdom

We compared quantitative susceptibility mapping (QSM) from two groups of subjects scanned at two different sites on different 3T Siemens MRI systems running different Syngo MR software versions. Qualitative whole-brain inspection of summary statistics and a statistical test comparing data from both sites revealed no major QSM offsets. The present results are only preliminary but they suggest QSM might be well suited for multi-site studies.

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Quantifying cortico-cerebellar structural covariance
Christopher J Steele1,2, Sejal Patel2, Jurgen Germann2, Gabriel Devenyi2, and Mallar Chakravarty2

1Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada

Invasive tract-tracing in primates has shown that cerebellar regions (lobules) are differentially connected to the cerebral cortex. As diffusion tractography to/from the cerebellum is problematic in living humans, we propose a simple non-invasive approach to identify the patterns of grey-matter structural covariance between cerebellar lobules and the cerebral cortex as a proxy for anatomical connectivity. We performed vertex-wise linear regressions between lobular volumes and cortical thickness/surface area. We then clustered lobule-wise correlations to identify similar spatial patterns of cortico-cerebellar covariance. We identified differential patterns that may reflect the underlying connectivity between the cerebellum and cortex.

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Carotid Artery Segmentation Based on Level Set Method in MR Images
Lian Luo1, Fei Shang1, Xinyu Tong1, Shuai Liu2, and Xihai Zhao2

1Department of Biomedical Engineering, Beijing Institute of Technology, Beijing, China, 2Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Beijing, China

Segmentation of blood vessels is the first step of visualization of vascular geometry and morphological analysis in cardiovascular diagnosis. However, the manual segmentation of blood vessels is time consuming. This study applied the level set method to automatic segmentation for carotid artery morphology on time-of-flight MR angiography images. The brightness weighting term is added to optimize the model, and the optimal setting of the parameters of the carotid artery images is discussed in detail.  The results showed that the model with the brightness weighting term was more stable, accurate and efficient, which might be used to automatic segmentation of carotid arteries.

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Spatio-temporal features of brain's iron accumulation across the life span.
Vyacheslav Karolis1,2, Thomas Hope3, Nikolaus Weiskopf4, Martina Callaghan3, Geraint Rees5, and Marinella Cappelletti5,6

1ICM - Institut du Cerveau et de la Moelle épinière, Hôpital de la Salpêtrière, Paris, France, 2Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom, 3Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom, 4Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 5Institute of Cognitive Neuroscience, University College London, London, United Kingdom, 6Psychology Department, Goldsmiths College, London, United Kingdom

In this study we characterised the spatiotemporal features of age-related iron accumulation marked by R2* maps in 97 participants distributed over the whole range of ages between 20 and 75 years old. The analyses showed a broad spectrum of linear and non-linear patterns of age-related differences in R2*. These were predominantly confined to striatum, motor, pre-motor and parietal regions of grey matter as well as subgyral pre- and postcentral regions of white matter. The spatial distribution of R2* changes seems to be related to a higher prevalence of long-distance white matter connections originating from a region. 

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Quantitative Assessment of the Intracranial Vasculature of an Elderly Population using the intraCranial Artery Feature Extraction (iCafe) Technique
Li Chen1, Quan Yuan2, Niranjan Balu3, Isabelle Yuan4, Daniel S Hippe 3, Jie Sun3, Xihai Zhao5, Rui Li5, Le He5, Jenq-Neng Hwang1, and Chun Yuan3

1Electrical Engineering, University of Washington, Seattle, WA, United States, 2Neurology, Xuanwu hospital, Capital Medical University, Beijing, China, 3Radiology, University of Washington, Seattle, WA, United States, 4Wellesley College, Wellesley, MA, United States, 5Biomedical Engineering, Tsinghua University, Beijing, China

iCafe is a novel technique which semi-automatically traces intracranial arteries from 3D magnetic resonance angiography (MRA) and computes corresponding quantitative morphometry and intensity features. MRA images of 100 healthy subjects (age 57-85) were processed and 8 representative features were extracted. We found significant decreases in total artery length (p=0.026), distal artery length (p=0.025), and number of branches (p=0.005) with increasing age using linear regression. These results suggest reduced vascularity with age, consistent with prior results showing cerebral blood flow with age. iCafe may be a useful tool to generalize systemic quantitative measurements of intracranial vascular structures.

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Prediction of Alzheimer’s disease by using deep learning 3D-Convolutional Neural Networks
Na Sang1, Francisco M. Garcia2, Wanshun Wei3, Huabing Li4, Tao Ma1, and Silun Wang1

1YIWEI Medical Inc, Shenzhen, China, 2University of Massachusetts - Amherst, Amherst, MA, United States, 3YIWEI Meidcal Inc, Shenzhen, China, 4ZhongNan University, ChangSha, China

We analyzed the T1 structural MRI by using deep learning 3D-CNN method.  The results indicate that deep learning models can accurately predict AD patients with diagnostic accuracy of 96%. This can be achieved using raw MRI data, with a minimum of processing necessary to generate an accurate AD prediction. Our model shows highly sensitivity and negative predictive value and thus appropriate for use for screening testing in population study. Currently model has the potential to be used as a screen biomarker to investigate the neurodegeneration, brain aging and associated brain diseases.

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Automated MR-based volumetry of basal ganglia and thalamus at the chronic phase of cortical stroke
Cindy Baudat1, Bénédicte Maréchal1,2,3, Ricardo Corredor-Jerez1,2,3, Patric Hagmann1, Philippe Maeder1, and Vincent Dunet1

1Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland, 2Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 3Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

We investigated the potential of automated T1-MPRAGE-based brain segmentation to assess individual basal ganglia and thalamus atrophy in nineteen patients with cortical stroke at the chronic phase. The basal ganglia and thalamus volumes z-scores were compared to the initial stroke ipsilateraly and contralateraly, and the relationship with the stroke volume was assessed. Except caudate nucleus, basal ganglia and thalamus, atrophy ipsilateraly to the stroke was observed and negatively correlated with the stroke volume in the territory of the middle cerebral artery. This suggests a potential role for automated MRI volumetry to assess brain plasticity after stroke at the individual level.

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Role of MRI Texture Analysis in Differentiating Post-treatment Changes from Tumour Recurrence in Patients with High Grade Glioma
Fahad Essbaiheem1, Rebecca Thornhill1, Gregory Cron1,2, John Woulfe1, Mario Kontolemos1, Beckie Manouchehri3, Nader Zakhari1, Andrew Boivin4, and Thanh Binh Nguyen1

1The Ottawa Hospital, Ottawa, ON, Canada, 2University of Ottawa, Ottawa, ON, Canada, 3Carleton University, Ottawa, ON, Canada, 4University of British Columbia, Kelowna, BC, Canada

In this prospective study, we have identified a combination of textural features from contrast-enhanced T1-weighted images which can help in differentiating tumour recurrence from post-treatment changes in patients with high grade gliomas.  The diagnostic accuracy of textural analysis was similar or slightly higher than that of two neuroradiologists who performed visual assessment.

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Deep Learning approach for Automatic Segmentation and characterization of Traumatic Brain Injury using Multi-parametric MRI
Krishna Kanth Chitta1, Abdalla Z Mohamed2, Fatima Nasrallah2, and Bhanu Prakash KN1

1Laboratory of Molecular Imaging, Singapore Bioimaging Consortium, Singapore, Singapore, 2Queensland Brain Institute, The University of Queensland, Brisbane, Australia

Automatic and accurate segmentation of Traumatic brain injury is vital to improve assessment of pathophysiology, plan treatment methods and enable large cohort studies. In this work we propose a framework based on 3D CNN and FCM to perform automatic segmentation of whole TBI volume and its sub-regions. The proposed framework utilizes multiple MRI contrasts and has shown high accuracy in delineating injury and sub-regions

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A Deep Learning Based Solution for Vertebrae Segmentation of Whole Spine MR Images: A Step Closer to Automated Whole Spine Labeling
Kavitha Manickam1, Jignesh Dholakia1, and Vignesh Singh1

1GE Healthcare, Bangalore, India

Any reporting on an MR spine scans involves labeling of the vertebrae. Hence, providing labeled spine images for reading can save significant time for radiologists. First step of an automated labeling is reliable segmentation of vertebral bodies. Most of the studies provide methods only for the segmentation and labeling of only a part of the spine.  Here, we have used a variant of U-Net based Deep Learning architecture for segmenting vertebrae of Whole Spine.  The network was trained with 165 datasets of whole spine images and tested with 8 datasets. We achieved average DICE score of 0.921.  

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Deciphering predictive models for differentiating vertebral lesions using multiparametric MRI
Durgesh Kumar Dwivedi1, Anit Parihar1, Rashi Rathore1, Neera Kohli1, Alok Kumar Dwivedi2, and Anil Chandra3

1Radiodiagnosis, King George's Medical University, Lucknow, India, 2Division of Biostatistics & Epidemiology, Biomedical Sciences, Texas Tech University Health Sciences Center, El Paso, TX, United States, 3Neurosurgery, King George's Medical University, Lucknow, India

Conventional MR imaging has high sensitivity but limited specificity in differentiating various vertebral lesions. We aimed to assess the ability of multiparametric MR imaging in differentiating spinal vertebral lesions and to develop statistical models for predicting the probability of malignant vertebral lesions. On the basis of the mean ADC and signal intensity ratio, we established automated statistical models that would be helpful in differentiating vertebral lesions. Our study shows that multiparametric MRI differentiates various vertebral lesions, and we established prediction models for the same.

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Evaluation of errors in image registration and diffusion measurement due to the cavum septum pellucidum
Chen-Hsiang Weng1, Yung-Chin Hsu1, and Wen-Yih Isaac Tseng1,2

1Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan, 2Molecular Imaging Center, National Taiwan University, Taipei, Taiwan, Taipei, Taiwan

To determine the registration errors caused by the cavum septum pellucidum (CSP), Dice coefficient and generalized fractional anisotropy (GFA) were assessed in brain using T1-weighted imaging and diffusion spectrum imaging (DSI), respectively. The subjects included 30 subjects with the CSP and 30 subjects without the CSP. Comparing with the subjects without the CSP, the subjects who had enlarged CSP showed significantly decreased Dice coefficient and significantly different GFA values in nine tracts. Our findings indicate that the existence of the CSP leads to errors in image registration and diffusion index calculation, and that the size of the CSP should be taken into consideration as a covariate in statistical analysis.

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Automated Segmentation and Volumetric Analysis of the Amygdala Nuclei in Epilepsy Patients at 7 Tesla
John W Rutland1, Rebecca E Feldman1, Lara V Marcuse2, Madeline C Fields2, Bradley N Delman3, Prantik Kundu 1, and Priti Balchandani1

1Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 2Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 3Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States

The present study employs ultra-high field MRI (7 Tesla) to perform structural imaging on a group of 19 epilepsy patients and 9 healthy controls. We use automated segmentation of the amygdala to derive volumes of constituent sub-nuclei. When comparing epilepsy patients and controls, we found that the volume of the right lateral nucleus was reduced compared with controls. We also found that the anterior-amygdaloid-area and the whole right amygdala approach significance for reduced volume. These are the first in vivo findings that indicate particular nuclei are affected in epilepsy patients.  


Electronic Poster

Emerging Methods

Exhibition Hall Monday 8:15 - 9:15

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Magnetic susceptibility in subcortical gray matter is associated with age-related neuropathologies: An ex-vivo QSM and pathology investigation in a community cohort of older adults
Arnold Evia1, Ashish Tamhane2, Aikaterini Kotrotsou1, Robert Dawe1,2,3, Sue Leurgans2,4, Julie Schneider2,4,5, David Bennett2,4, and Konstantinos Arfanakis1,2,3

1Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, United States, 2Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, United States, 3Department of Diagnostic Radiology, Rush University Medical Center, Chicago, IL, United States, 4Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States, 5Department of Pathology, Rush University Medical Center, Chicago, IL, United States

To understand the associations of quantitative susceptibility mapping with age-related neuropathologies, it is essential to combine QSM with direct assessments of age-related brain pathologies on the same individuals. Using ex-vivo QSM for this purpose may be more advantageous than in-vivo QSM, since ex-vivo QSM overcomes several of the obstacles that complicate MRI-pathology investigations and can provide magnetic susceptibility measurements that are linked to those collected in-vivo. Therefore, our goal was to investigate the associations of magnetic susceptibility with the pathology of multiple age-related diseases by combining ex-vivo QSM with histology.

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Imaging the effect of high-protein diet on the brain Glutaryl-CoA dehydrogenase deficient mice using GluCEST MRI
Puneet Bagga1, Damodara Reddy1, Delia Talos2, Kimberly Sansalone2, Leah Jacobs2, Gaurav Verma1, Hari Hariharan1, and Ravinder Reddy1

1Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States, 2Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States

Autosomal recessive inheritance of Glutaryl-CoA dehydrogenase (GCDH) deficiency or Glutaric Acidemia-1 is one of the common inherited metabolic disorders affecting many children worldwide. We applied GluCEST MRI to image the metabolic changes in the brain of GCDH-/- mice following the exposure to high-protein diet. GluCEST contrast was found to be significantly reduced in the striatum and cortex of the GCDH-/- mice following high-protein diet exposure. 1H MRS data corroborated with GluCEST results showing a significant reduction in the striatal glutamate level. GluCEST MRI may be used as an imaging biomarker for assessing the neurovascular damage caused by high-protein diet in GCDH-/- subjects.

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On Resonance Variable Delay Multiple Pulse (onVDMP) CEST MRI Detects Transient Lactate Depletion during Experimental Autoimmune Encephalomyelitis Progression
Aline Thomas1, Jiadi Xu2, Peter Calabresi3, Peter van Zijl2, and Jeff Bulte1

1Radiology, Johns Hopkins School of Medicine, Baltimore, MD, United States, 2Radiology, Kennedy Krieger Institute, Baltimore, MD, United States, 3Neurology, Johns Hopkins School of Medicine, Baltimore, MD, United States

On resonance variable delay multiple pulse CEST MRI detected a transient reduction in lactate levels in the cerebrospinal fluid during the disease course of a mouse model of multiple sclerosis, which was validated using magnetic resonance spectroscopy.

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On Resonance Variable Delay Multiple Pulse (onVDMP) CEST MRI for Monitoring Stem Cell Therapy in Experimental Autoimmune Encephalomyelitis
Aline Thomas1, Jiadi Xu2, Shen Li1, Piotr Walczak1, Peter Calabresi3, Peter van Zijl2, and Jeff Bulte1

1Radiology, Johns Hopkins School of Medicine, Baltimore, MD, United States, 2Radiology, Kennedy Krieger Institute, Baltimore, MD, United States, 3Neurology, Johns Hopkins School of Medicine, Baltimore, MD, United States

In mice with experimental autoimmune encephalomyelitis, spatiotemporal signal changes were detected with on resonance variable delay multiple pulse (onVDMP) CEST MRI for the brain and spinal cord. Transplantation of glial-restricted precursor cells resulted in normalization of those signal changes during the pre-onset stage of the disease.

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APT CEST in cerebrospinal fluid in patients with multiple sclerosis at 3T
Richard Dylan Lawless1,2, Quinn R Weinberg2, Bailey Box2, Samantha By3, Francesca Bagnato4, and Seth A Smith1,2,5

1Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 2Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States, 3Phillips Healthcare, Baltimore, MD, United States, 4Department of Neurology, Vanderbilt University, Nashville, TN, United States, 5Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States

There is currently no clinically available MRI method capable of monitoring chronic, systemic inflammation in the central nervous system as a confirmatory biomarker. Chemical exchange saturation transfer (CEST) is a novel MR technique sensitive to low concentration, exchangeable mobile solutes. Amide proton transfer (APT) CEST provides information about concentration of proteins/peptides with amide backbones. Our results show that APT CEST of CSF in the spinal cord demonstrates significant changes when compared between the control and MS cohort.

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MT and QSM of the Locus Coeruleus and Substantia Nigra on human healthy subjects
Catarina Rua1, Luca Passamonti2, Claire O’Callaghan3, James Rowe3,4,5, Adrian Carpenter1, and Guy Williams1

1Department of Clinical Neurosciences, University of Cambridge, Wolfson Brain Imaging Centre, Cambridge, United Kingdom, 2Department of Clinical Neurosciences, University of Cambridge, Cambridge Centre for Frontotemporal Dementia and related disorders, Cambridge, United Kingdom, 3University of Cambridge, Behavioural and Clinical Neuroscience Institute, Cambridge, United Kingdom, 4University of Cambridge, Department of Clinical Neurosciences, Cambridge, United Kingdom, 5Medical Research Council Cognition and Brain Sciences Unit, Cambridge, United Kingdom

The Locus Coeruleus (LC) and the Substantia Nigra (SN) are located in the mid-brain are known to show severe cell loss in several neurodegenerative diseases (e.g., Alzheimer’s disease). Developing new imaging techniques to quantify the signal changes in these regions is of high clinical relevance. In this pilot study of five healthy adults from different age groups, the LC and SN were evaluated for neuromelanin and iron content with an Magnetisation Transfer-weighted sequence and with Quantitative Susceptibility Mapping, respectively.

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Susceptibility weighted imaging with Compressed-SENSE: Quantitative and Clinical evaluation
Jaladhar Neelavalli1, Rakesh Kumar Gupta2, Jakob Meineke3, Rupsa Bhattacharjee4, Suthambhara Nagaraj1, Tejas Jatin Shah1, Ulrich Katscher3, and Indrajit Saha4

1Philips Innovation Campus, Philips India Limited, Bengaluru, India, 2Fortis Memorial Research Institute, Gurugram, India, 3Philips Research Europe, Hamburg, Germany, 4Philips India Limited, Gurugram, India

The current work evaluates the influence of a combined SENSE and compressed sensing algorithm, Compressed-SENSE, on the quantitative and qualitative aspects of SWI data. Quantitative evaluation is done using quantitative susceptibility maps. Clinical qualitative assessment is done in patients with cerebral glioma using ITSS score as the metric for image diagnostic quality.

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Functional MRI reveals resting state network alterations upon DREADD-induced silencing of the right dorsomedial prefrontal cortex in mice.
Lore Peeters1, Rukun Hinz1, Stephan Missault1, Marleen Verhoye1, Annemie Van der Linden1, and Georgios A. Keliris1

1Bio-Imaging Lab, University of Antwerp, Wilrijk, Belgium

Combining chemogenetics with non-invasive functional MRI (fMRI) allows establishing a link between the activity of selected populations of neurons with large-scale network activity. Here, we show that Kappa Opioid Receptor (KOR) DREADD-induced decreases in neural activity result in network alterations that can be picked up by pharmacological and resting state fMRI. In particular, inhibition of the right dorsomedial prefrontal cortex (dmPFC), a core region of the attention network in rodents, induces functional connectivity changes between other regions of the attentional network and between regions of distinct sensory networks (e.g. the visual network).

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Cross-Platform Comparison of Regional Brain Stiffness
Jun Chen1, Matthew Murphy1, Kevin Glaser1, Curtis Johnson2, Arvin Forghanian-Arani1, Yuan Le3, David Lake1, Roger Grimm1, John III Huston1, and Richard Ehman1

1200 1st St Sw, Mayo Clinic, Rochester, MN, United States, 2University of Delaware, Newark, DE, United States, 3200 1st St Sw, Mayo Clinic, Phoenix, AZ, United States

Brain MR Elastography (MRE) has been shown to add value to neurological imaging. Brain biomechanical properties are correlated with age, gender, exercise and memory in normal volunteers. In patients with neurological diseases, such as multiple sclerosis, dementia and intracranial tumors, global and regional brain mechanical properties may be sensitive biomarkers. Characterization of the cross-platform performance of regional stiffness measurements using 3D brain MRE is important for future multiplatform, multicenter brain MRE studies. The purpose of our study was to compare regional 3D brain MRE in normal volunteers using two vendor platforms.

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Magnetization Transfer Ratio based Metric for APTw or CESTw MRI Suppressing Signal from Fluid Compartments - Initial Application to Glioblastoma Assessment
Jochen Keupp1 and Osamu Togao2

1Philips Research, Hamburg, Germany, 2Kyushu University Hospital, Fukuoka, Japan

Amide proton transfer weighted (APTw) MRI has been shown to allow assessment of the tumor aggressiveness/tumor grade with high sensitivity and specificity. Compartments with significant fluid content, like cysts, haemorrhage or necrosis may complicate reading. A metric for APTw MRI is developed, applicable for chemical exchange saturation transfer (CEST) MRI in general, which suppresses fluids based on the spectral shape of the background magnetization transfer ratio (MTR). It is shown to essentially conserve numerical values of APTw MRI in solid tissues. Furthermore, no extra acquisition time is needed, because the metric can be computed from the minimum Z-spectral data also required for standard CEST MRI. The novel metric is explored in an intial study on N=12 gliobastoma cases.

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Longitudinal Change in the Developmental Rat Brain using in vivo Glutamate Chemical Exchange Saturation Transfer
Wooyul Paik1, Dong Cheol Woo2, and Ho Sung Kim3

1Graduate School, Ulsan University, Seoul, Republic of Korea, 2Department of Convergence Medicine, Asan Medical Center, Seoul, Republic of Korea, 3Department of Radiology, Asan Medical Center, Seoul, Republic of Korea

Our study results and analyses show the trend in glutamate concentration and the decreases in T2 and ADC values influenced by myelination, neuronal change, and the water and macromolecule content of the developing rat brain, and also provide evidence indicating the time point where a neurochemical balance is achieved. Our results demonstrating changes in glutamate concentration up to the eighth postnatal week should provide valuable reference data for other studies of the developing healthy rat brain, and should be useful for comparisons with diseased rat brain in further developmental studies.

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Optimizing Brain MR Elastography with Multiple Motion Encoding Gradient Cycles
Yuan Le1, Kevin Glaser2, Matthew Murphy2, Yuxiang Zhou3, Jun Chen2, William Pavlicek1, Joseph M. Hoxworth3, Bradley D. Bolster Jr.4, John Huston III.2, Joel P. Felmlee2, and Richard L. Ehman2

1Radiology, Mayo Clinic Arizona, Scottsdale, AZ, United States, 2Radiology, Mayo Clinic, Rochester, MN, United States, 3Radiology, Mayo Clinic Arizona, Phoenix, AZ, United States, 4Siemens Medical Solutions USA, Inc., Salt Lake City, UT, United States

A spin-echo EPI MR Elastography sequence was optimized so that multiple motion encoding gradient (MEG) cycles can be added to increase the motion sensitivity. Volunteer tests showed that comparing with the original one MEG version, optimized two or three MEG cycles provided higher Octahedral Shear Strain Signal-to-Noise Ratio (OSS-SNR), which means higher stiffness measurement precision. Global brain Images acquired with 2 and 3 MEG cycles are in most cases comparable in stiffness and OSS-SNR while images with 1 MEG tend to have a slightly lower OSS-SNR.

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Regional Changes in Brain Stiffness with Age Assessed with MR Elastography
Yu Sasaki1, Utaroh Motosugi1, Tomohiro Takamura2, Kevin J. Glaser3, Richard L. Ehman3, Hiroshi Kumagai1, Takashi Kakegawa1, and Hiroshi Onishi1

1Department of Radiology, University of Yamanashi, Yamanashi, Japan, 2Department of Radiology, Juntendo University, Tokyo, Japan, 3Department of Radiology, Mayo Clinic, Rochester, MN, United States

Various MR-assessed quantities change with age in the brain, including T2, diffusion, and fractional anisotropy. MR elastography (MRE) is a new technique that can measure the stiffness of tissue and is now widely used in the clinic for assessing hepatic fibrosis. Recently, it has become feasible to perform brain MRE as well. In this study, we showed that the stiffness of the brain, measured using MRE, decreased with age, especially in the parietal lobes and the sensory-motor area.

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The impact of age and sex on mouse brain stiffness measured with Magnetic Resonance Elastography
Katharina Schregel1,2,3, Miklos Palotai2,3, Navid Nazari4, Julie Priya Merchant5, Walter Monroe Taylor5, Charles Guttmann2,3, Ralph Sinkus6, Tracy Young-Pearse3,5, and Samuel Patz2,3

1Institute of Neuroradiology, University Medical Center Goettingen, Goettingen, Germany, 2Department of Radiology, Brigham and Women's Hospital, Boston, MA, United States, 3Harvard Medical School, Boston, MA, United States, 4Department of Biomedical Engineering, Boston University, Boston, MA, United States, 5Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Boston, MA, United States, 6Department of Radiological Imaging, Imaging Sciences & Biomedical Engineering Division, King's College London, London, United Kingdom

Aging is accompanied by neurodegeneration, which affects the cerebral biomechanical properties. We investigated the impact of age and sex on mouse brain stiffness using magnetic resonance elastography (MRE). Repeated MRI and MRE exams were performed on 5 male and 5 female healthy C57BL/6 mice over 14 months. A significant decrease of the viscoelastic modulus |G*| was observed, while the phase angle Y remained unaltered. Grey and white matter exhibited significant differences in |G*| and Y.  Sex differences were observed in the cortex at 11 months. This is relevant for future cerebral MRE studies on mice.

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Brain stiffness changes due to Alzheimer’s disease in cortical-centric regions
Matthew Christopher Murphy1, David T Jones1, Clifford C Jack1, Kevin C Glaser1, Matthew C Senjem1, Armando C Manduca1, Joel C Felmlee1, Richard C Ehman1, and John C Huston1

1Mayo Clinic, ROCHESTER, MN, United States

Brain stiffness is known to decrease in subjects with Alzheimer’s disease (AD). However, previously reported stiffness estimates were heavily weighted toward white matter. Here we investigate the sensitivity of cortical-centric stiffness measurements for detecting AD pathophysiology, given that the cortex is the primary site of pathology. Using a neural network-based inversion algorithm, cortical-centric measurements are highly repeatable with test-retest errors of less than 2% on average. With respect to AD, the medial temporal lobe region of interest is found to best discriminate those with dementia from cognitively normal subjects, and performs better than previously reported methods.

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Acute changes in rat brain metabolism after intravenous administration of alcohol, cocaine, and nicotine: A simultaneous PET/MR study with dynamic 1H-MRS and continuous infusion 18FDG.
Bart de Laat1,2, Akila Weerasekera1,3, Gwen Schroyen1,3, Cesar Molinos4, Uwe Himmelreich1,3, Cindy Casteels1,2, Koen Van Laere1,2, and Willy Gsell1,3

1KU Leuven – University of Leuven, MoSAIC, Molecular Small Animal Imaging Center, Leuven, Belgium., Leuven, Belgium, 2KU Leuven – University of Leuven/University Hospital Leuven, Division of Nuclear Medicine, Department of Imaging and Pathology, Leuven, Belgium., Leuven, Belgium, 3KU Leuven – University of Leuven, Biomedical MRI unit, Department of Imaging and Pathology, Leuven, Belgium, Leuven, Belgium, 4Bruker BioSpin, Preclinical Imaging NMI, Valencia, Spain

We have combined PET imaging with continuous 18F-deoxy-glucose PET and dynamic 1H-MRS focused on the prefrontal cortex in a rodent model of substance abuse. During imaging, animals received an intravenous injection of saline, alcohol, cocaine, or nicotine. Cocaine administration reduced the regional cerebral metabolic rate of glucose (rCMRGlu) as measured by PET, but increased prefrontal glucose and creatine levels as measured with dynamic MRS. Furthermore, alcohol administration significantly influenced the prefrontal concentration of ethanol, glucose, creatine, and glutamate. Finally, our data show that alcohol induces a transient decrease in prefrontal glutamate coinciding with the peak in ethanol concentration. 

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Assessment of cerebral infarction due to intracranial arterial stenosis in the human brain using hyperpolarized xenon-129 MRI
Madhwesha Rao1, Graham Norquay1, Neil J Stewart1, Nigel Hoggard1, Paul D Griffiths1, and Jim M Wild1

1University Of Sheffield, Sheffield, United Kingdom

In this pilot study we evaluate the feasibility of hyperpolarised 129Xe brain perfusion MR imaging to evaluate brain tissue perfusion patho-physiology in a subject with established intracranial arterial stenosis with collateralized blood flow. The 129Xe brain perfusion images from the patient exhibit regions of signal void which correspond to the infarcted region observed on T2 weighted MRI. Imaging hyperpolarized 129Xe dissolved in the brain tissue is a direct method of imaging perfusion of the tissue itself and we observe different patterns of cerebral perfusion than those measured with arterial spin labeling.

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Phase Laplacian Coil Combination
Rüdiger Stirnberg1, Lino Lemmer1, and Tony Stöcker1,2

1MR Physics, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany, 2Department of Physics and Astronomy, University of Bonn, Bonn, Germany

We propose a novel, computationally efficient coil combination technique for multi-channel phase data based on the Laplacian of single-channel phase images. This renders explicit knowledge or estimation of the receive sensitivities unnecessary. The combined phase Laplacian can be either be transformed back to unwrapped phase domain (Laplacian-based unwrapping) or directly utilized for further analyses based on the phase Laplacian, e.g. harmonic background-field removal. At 3T we demonstrate similar-to-improved phase reconstruction compared to the vendor-provided state-of-the-art coil combination, which uses the body-coil as a uniform reference, and successfully apply the technique at 7T.

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Resting-state fMRI study of brain activation using low-intensity repetitive transcranial magnetic stimulation in rats.
Bhedita J Seewoo1,2,3, Kirk W Feindel3, Sarah J Etherington2, and Jennifer Rodger1,4

1Experimental and Regenerative Neurosciences, School of Biological Sciences, The University of Western Australia, Crawley, Australia, 2School of Veterinary and Life Sciences, Murdoch University, Murdoch, Australia, 3Centre for Microscopy, Characterisation and Analysis, The University of Western Australia, Nedlands, Australia, 4Perron Institute for Neurological and Translational Research, Perth, Australia

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive neuromodulation technique used to treat many neuropsychiatric conditions. However, the mechanisms underlying its mode of action are still unclear. This is the first rodent study using resting-state fMRI to examine low-intensity (LI) rTMS effects, in an effort to provide a direct means of comparison between rodent and human studies. Our study shows that similar to human rTMS, 10 Hz LI- rTMS alters the resting brain activity of rats directly at the site of stimulation (e.g. cortex) as well as in remote but inter-connected brain regions (e.g. hippocampus).

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Imaging toxin-induced inflammation in the mouse brain with hyperpolarized 13C MRS
Lydia M Le Page1,2, Caroline Guglielmetti1,2, Brice Tiret1,2, and Myriam M Chaumeil1,2

1Department of Physical Therapy and Rehabilitation Science, University of California San Francisco, San Francisco, CA, United States, 2Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States

13C MRS of hyperpolarized (HP) [1-13C] pyruvate has recently shown promise in assessing neuroinflammation in mouse models of MS and TBI.  Here, we expanded on previous reports and evaluated whether HP 13C MRS could detect the effect of the inflammation-inducing toxin lipopolysaccharide (LPS), using mice injected intracranially with either LPS or saline. LPS-injected mice showed significantly elevated HP [1-13C] lactate:pyruvate ratios in the LPS-injected hemisphere compared to contralateral, in line with increased microglial number. In contrast, saline-injected mice showed no such changes. Our results further confirm the potential of hyperpolarized 13C MRS for non-invasive assessment of neuroinflammation in the brain.

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A real-time metabolic investigation of the effect of hypothermia on hypoxic ischemia during mouse brain development using hyperpolarized 13C
Yiran Chen1, Alkisti Mikrogeorgiou2, Robert Bok1, Subramaniam Sukumar1, R Ann Sheldon2,3, A James Barkovich1,3, Donna M Ferriero2,3, and Duan Xu1

1Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, 2Department of Neurology, University of California San Francisco, San Francisco, CA, United States, 3Department of Pediatrics, University of California San Francisco, San Francisco, CA, United States

In this study, we applied dynamic nuclear polarization (DNP) technique to investigate C1 labeled 13C pyruvate to lactate conversion to study the effect of hypothermia treatment on hypoxic ischemia (HI) injured neonatal mouse brains during development. Our results showed that lower pyruvate delivery to the injured hemisphere in comparison to the non-injured hemisphere at the day of injury (P10) for all subjects, and difference narrows as the brain matures. There were different individual responses to the lactate to pyruvate ratio between two hemispheres. With this technique, we are able to examine individual responses to treatment during brain development.  

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19F Signal Distribution in Pre-Symptomatic Experimental Autoimmune Encephalomyelitis
Paula Ramos Delgado1, Jason M. Millward1, Christian Prinz1, Ludger Starke1, Stefanie Münchberg1, Andreas Pohlmann1, Thoralf Niendorf1,2, and Sonia Waiczies1

1Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association(MDC), Berlin, Germany, Berlin, Germany, 2Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany, Berlin, Germany

Experimental autoimmune encephalomyelitis (EAE) is an animal model used to study the pathogenesis of autoimmune neuroinflammatory diseases, such as multiple sclerosis (MS). In MS, recruitment of immune cells into the central nervous system (CNS) occurs already at early stages of the disease. Magnetic resonance imaging (MRI) can be used as a non-invasive technique suited for tracking immune cell migration, following intravenous administration of fluorine (19F)-loaded nanoparticles which can then be followed using 19F MR techniques. The present study aims to investigate the distribution of immune cells during the pre-symptomatic disease phase in the EAE mouse model using 19F MR methods.

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Multi-contrast Brain MRI Image Super-resolution with Gradient-guided Edge Enhancement
Hong Zheng1, Kun Zeng1, Di Guo2, Jiaxi Ying1, Yu Yang1, Xi Peng3, Zhong Chen1, and Xiaobo Qu1

1Department of Electronic Science, Xiamen University, Xiamen, China, 2Xiamen University of Technology, Xiamen, China, 3Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

Since magnetic resonance imaging (MRI) can offer images of an object with different contrasts, e.g., T1-weighted or T2-weighted, the shared information between inter-contrast images can be used to benefit super-resolution. Multi-contrast images are assumed to possess the same gradient direction in a local pattern. We proposed to establish a relation model of gradient value between different contrast images, to restore a high-resolution image from its input low-resolution version. The similarity of image patches is employed to estimate intensity parameters, leading a more accurate reconstructed image. Then, iterative back-projection filter is applied to the reconstructed image to further increase image quality. The reconstructed edges are more consistent to the original high-resolution image, indicated with higher PSNR and SSIM than the compared methods.

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Novel Imaging Phantom for Accurate and Robust Measurement of Brain Atrophy Rates Using Clinical MRI
Houshang Amiri1, Iman Brouwer1, Joost P.A. Kuijer1, Jan C. de Munck1, Frederik Barkhof1,2, and Hugo Vrenken1

1Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands, 2Institutes of Neurology and Healthcare Engineering, UCL, London, United Kingdom

MR images are widely used to measure brain atrophy in neurodegenerative diseases. However, reliable evaluation of atrophy is hampered by scanner-induced systematic variability. Here, we developed an MR-compatible phantom and analysis software for robust and reliable evaluation of the brain volume loss. The phantom was made using 3D-printing and contains three inflatable brain structures equipped with a precise volume change system. The phantom was imaged at three different clinical 3T MR scanners and images were analyzed by our developed software. This phantom can accurately and robustly provide a selected volume change to mimic a certain disease.


Electronic Poster

Neuroimaging: Pulse Sequences & Reconstruction

Exhibition Hall Monday 8:15 - 9:15

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Brain Vessel Extraction without MRA / V using Deep Convolutional Neural Network
Hyungseob Shin1, Yohan Jun1,2, Taeseong Kim1, Taejoon Eo1, Sungsoo Ahn3, and Dosik Hwang1

1Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea, 2Philips Korea, Seoul, Republic of Korea, 3Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Republic of Korea

In this paper, we introduce a deep residual learning approach to extract brain vessels from contrast-enhanced(CE) magnetic resonance images. Our experiment results show that we can successfully achieve and visualize brain vessel information from CE MRI without magnetic resonance angiography and magnetic resonance venography(MRA/V) that are currently used for brain vessel extraction.

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High resolution atlasing of the venous brain vasculature from 7T quantitative susceptibility
Julia Huck1, Yvonne Wanner1,2, Audrey P. Fan3, Anna-Thekla Schmidt4, Sophia Grahl4, Uta Schneider4, Arno Villringer4, Christopher J. Steele4,5, Christine L. Tardif6,7, Pierre-Louis Bazin4,8,9, and Claudine J. Gauthier1

1Concordia University / PERFORM centre, Montreal, QC, Canada, 2Universität Stuttgart, Stuttgart, Germany, 3Stanford University, Stanford, CA, United States, 4Max Planck Institute for Human Cognitive and Brain Science, Leipzig, Germany, 5Douglas Mental Health University Institute, Montreal, QC, Canada, 6McGill University, Montreal, QC, Canada, 7Montreal Neurological Institute, Montreal, QC, Canada, 8Spinoza Centre for Neuroimaging, Amsterdam, Netherlands, 9Netherlands Institute for Neuroscience, Amsterdam, Netherlands

We present the first atlas of the venous vasculature using quantitative susceptibility maps (QSM) acquired at 7T with a 0.6mm isotropic resolution. The atlas was created from 16 datasets in young and healthy volunteers by using a three step registration method on the inflated skeletons of the venous vasculature. This cerebral vein atlas shows the average vessel location and diameter.

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High Resolution Black-blood T1-weighted Turbo Spin Echo with Variable Flip Angles for Visualization of Small Perforating Arteries at 3 and 7 Tesla
Samantha J Ma1, Lirong Yan1, Kay Jann1, and Danny JJ Wang1

1Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States

Cerebral small vessel disease frequently affects the small perforating arteries, resulting in silent strokes, which contribute to progressive cognitive impairment in elderly persons. Previous studies have demonstrated the ability of time-of-flight (TOF) MRA to non-invasively image these small arteries at 7T; In this study, we introduce and optimize a T1-weighted turbo spin echo sequence with variable flip angles (T1w-VFA-TSE) sequence for high resolution black blood MRI to delineate the lenticulostriate arteries (LSA) at 3T and 7T. Our results show T1w-VFA-TSE provides high contrast for visualizing LSAs and delineates small arteries better than TOF MRA at 7T.  

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Systematic comparison of DTI metrics as potential biomarkers  in cerebral small vessel disease
Ana Fouto1, Rita G. Nunes1, Joana Pinto1, Luísa Alves2, Sofia Calado2, Carina Gonçalves2, Pedro Vilela3, Miguel Viana Baptista2, and Patrícia Figueiredo1

1Department of Bioengineering, ISR-Lisboa/LARSyS, Instituto Superior Técnico - Universidade de Lisboa, Lisboa, Portugal, 2Department of Neurology, Hospital Egas Moniz, Lisbon, Portugal, 3Imaging Department, Hospital da Luz, Lisbon, Portugal

Cerebral small vessel disease (SVD) is the major cause of dementia among the elderly and sensitive biomarkers of disease progression are needed. Here, we investigated the potential of DWI to provide sensitive biomarkers of SVD, by evaluation multiple metrics extracted from DTI in terms of their predictive power of cognitive performance. We considered different white matter regions of interest to perform histogram analysis and extract multiple FA and MD metrics, and showed that specific DTI metrics were better than conventional structural MRI at explaining impairments in processing speed and execute function in a group of SVD patients.

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Feasibility and Evaluation of Multi-Delay Quantitative 3D GRASE pCASL MRI in Children at 3 Tesla
Houchun Harry Hu1, Ruiyue Peng2, Xingfeng Shao3, Mark Smith1, Jerome Rusin1, Ramkumar Krishnamurthy1, Bhavani Selvaraj1, and Danny JJ Wang3

1Radiology, Nationwide Children's Hospital, Columbus, OH, United States, 2Translational MRI, LLC, Los Angeles, CA, United States, 3Stevens Neuroimaging and Informatics Institute, Laboratory of FMRI Technology, University of Southern California, Los Angeles, CA, United States

Single post-labeling-delay (PLD) pCASL are commonly used to measure cerebral blood flow (CBF). A PLD of 1500-2000ms is commonly used in children and adults.  Multi-delay pCASL has been developed as an alternative approach to better account for prolonged arterial transit times (ATT) and to improve the accuracy of CBF perfusion quantification.  In this study, we evaluate the feasibility of multi-delay pCASL in children.  We compare two algorithms (weighted-delay linear mapping vs. nonlinear iterative curve fitting) for estimating ATT and CBF.  We further compare estimations of weighted-delay CBF derived from multi-delay pCASL data with those traditionally calculated from a single PLD measurement. 

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Imaging Ultrashort-T2* structures in the Eye with UTE MRI
Peder Eric Zufall Larson1, Peng Cao1, and Kevin C. Chan2

1Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, United States, 2Ophthalmology and Radiology, New York University, New York, NY, United States

Ultrashort echo time (UTE) MRI has the potential to image all structures in the eye, including the sclera, cornea and lens that have relatively short T2* relaxation times.   UTE MRI was used for motion-robust imaging of the eye in vivo, and multiple TE measurements were combined for 3D T2* mapping. We report measurements of in vivo T2* relaxation times in the range of several ms that suggest that UTE MRI can be used effectively to study ocular structures with short T2* in vivo. 

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Realistic dynamic speech numerical phantom for the evaluation of real-time MRI acquisition and reconstruction methods
Joseph Martin1,2, Redha Boubertakh1,3, Matthieu Ruthven1, and Marc E Miquel1,3

1Clinical Physics, Barts Health NHS Trust, London, United Kingdom, 2Medical Physics and Engineering, Kings College London, London, United Kingdom, 3William Harvey Research Institute, Queen Mary University of London, London, United Kingdom

Real time MRI (rtMRI) in human speech is an active field of research, with a particular clinical focus on the assessment of speech disorders.  In this work, a numerical phantom is developed to allow acquisition and reconstructions schemes for rtMRI to be compared to a ‘gold standard’. Previously acquired 2D rtMRI images of speech were used to create anatomical masks of various speech organs.  An interpolation method was then used to create a continuous time model of the moving structures, which forms the dynamic phantom. The model is then tested using different k-space sampling schemes (Cartesian, radial and spiral).

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Improved susceptibility-weighted imaging of the thalamic nuclei at 7T with enhanced contrast and venous vessel exclusion
João Jorge1,2, Elena Najdenovska2,3, Constantin Tuleasca4,5,6, José P. Marques7, Marc Levivier4,6, Philippe Maeder3, Rolf Gruetter1,3,8, and Meritxell Bach Cuadra2,3,5

1Laboratory for Functional and Metabolic Imaging (LIFMET), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 2Medical Image Analysis Laboratory (MIAL), Center for Biomedical Imaging (CIBM), Lausanne, Switzerland, 3Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 4Department of Clinical Neurosciences, Neurosurgery Service and Gamma Knife Center, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland, 5Signal Processing Laboratory, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 6Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland, 7Donders Center for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands, 8Department of Radiology, University of Geneva, Geneva, Switzerland

The thalamus plays a key role in neuronal signal transmission and modulation. While most of the current non-invasive imaging techniques fail to achieve substantial contrast between the thalamic nuclei, susceptibility-weighted imaging (SWI) has recently shown promising capabilities for their visualization at 7T, despite having been originally designed primarily for venous vessel imaging.

The aim of the present work was to optimize the SWI technique specifically for improved thalamic nuclei visualization, by jointly modifying the SWI combination and suppressing venous vessels. These modifications yielded substantially improved contrast and delineation of various thalamic nuclei, in good agreement with histological atlas information.


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$$$T_1$$$ dependency of magnetization transfer effect in human brain
Yuki Kanazawa1, Toshiaki Sasaki2, Hiroaki Hayashi1, Kotaro Baba3, Ikuho Kosaka3, Yuki Matsumoto4, Mitsuharu Miyoshi5, and Masafumi Harada1

1Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan, 2Department of Radiology, Uji Tokushukai Hospital, Uji, Japan, 3School of Health Sciences, Tokushima University, Tokushima, Japan, 4Graduate school of Health Science, Tokushima University, Tokushima, Japan, 5Global MR Applications and Workflow, GE Healthcare Japan, Hino, Japan

The purpose of this study is to develop a T1 mapping method derived from the variable flip angle with an MT pulse. T1 mapping of the brain with an MT pulse was performed in five healthy subjects. The mean T1_MT values were significantly decrease than the T1 in all regions (P < 0.05). The difference of T1 and T1_MT in deep gray matter (included caudate nucleus and putamen) were more decreased than those in white matter. In conclusion, determination of T1 with MT pulse makes it possible to obtain more detailed information of the macromolecular pool and the free water pool.

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Utility of real-time field control in subjects with mild cognitive impairment: T2* weighted imaging at 7T.
Laetitia Vionnet1, Jiri van Bergen2, Yolanda Duerst1, Rafael Meyer2, Nicole Fichtner1,3, Sonja Maria Kagerer2, Michael Wyss1, Paul Gerson Unschuld2, and Klaas Paul Pruessmann1

1ETH & University Zurich, Zurich, Switzerland, 2University of Zurich, Zurich, Switzerland, 3University of Bern, Bern, Switzerland

Subjects with Alzheimer disease or mild cognitive impairment are known to produce strong field perturbation by particular breathing pattern and limb motion. In this work we explore the feasibility and success of real-time field control in subjects with mild cognitive impairment and age-matched controls in the scenario of high resolution T2*-weighted imaging at 7T. Real-time field control shows to be feasible and yield greatly enhanced data quality in both type of subjects: mild cognitive impairment and cognitively normal.

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Multi-echo OxFlow for quantification of the cerebral metabolic rate of oxygen at 1.5T, 3T, and 7T
Erin K Englund1, Ana E Rodriguez-Soto1, and Felix W Wehrli1

1Radiology, University of Pennsylvania, Philadelphia, PA, United States

Fick’s principle can be used to quantify the cerebral metabolic rate of oxygen (CMRO2) as the product of oxygen extraction and blood flow. An interleaved dual-slice multi-echo GRE and phase contrast sequence, termed OxFlow, has previously been used for simultaneous measurement of SvO2 and blood flow. Here, we developed and evaluated an extended multi-echo OxFlow sequence designed for operation at multiple field strengths. The rate of phase accumulation, rather than the inter-echo phase difference, is used to compute SvO2. Results were obtained in 5 healthy subjects at 1.5T, 3T, and 7T, with agreement of the physiologic parameters between field strengths. 

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Comparing MEGA editing techniques for in-vivo measurement of 2-hydroxyglutarate
Ross Callaghan1, Bhavana Solanky2, Sotirios Bisdas1, Hui Zhang1, and Enrico De Vita1

1University College London, London, United Kingdom, 2Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom

MEGA-semiLASER is compared to a previously proposed MRS sequence for 2HG detection, MEGA-PRESS. The sequences are assessed using simulations of SNR with TE and the chemical shift displacement error (CSDE). Both sequences are shown to maximise 2HG SNR at TE of approximately 100ms. MEGA-semiLASER displays marginally higher SNR whilst reducing the CSDE of MEGA-PRESS. MEGA-semiLASER should offer a comparable reduction in CSDE to another proposed sequence, MEGA-LASER, whilst requiring fewer refocusing pulses and thus a lower SAR. 

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A novel minimally invasive, image-guided neurablation technique using MRI - MINIMA
Christopher Payne1, John J Connell1, Matin J Mohseni1, Stephen Patrick1, Yichao Yu1, Bernard Siow1, Quentin A Pankhurst2, and Mark F Lythgoe1

1Centre for Advanced Biomedical Imaging, UCL, London, United Kingdom, 2Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom

During tumour resection the goal is to remove a discrete region of cancerous tissue causing minimal damage to surrounding healthy tissue. Therefore, there is a demand for minimally invasive techniques, alongside MR imaging, for precise location of the tumour boundary. Presented here is the development of a minimally invasive, image-guided neurosurgery technique, whereby the position of an untethered surgical implant can be controlled and imaged in real time using an MRI scanner. We have demonstrated image-guided, precise movement of millimetre sized magnetic spheres inside ex vivo brain tissue by controlling the magnetic field gradients inside an MRI scanner.

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NODDI-DTI as proxy for Axonal Volume Fraction: Is g-ratio-weighted imaging feasible using single-shell DTI data?
Gergely David1, Maryam Seif1, and Patrick Freund1,2,3

1Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland, 2Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, United Kingdom, 3Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

G-ratio-weighted imaging is an active field of research with the goal of better characterizing white matter in both health and disease. However, clinical adoption is significantly hampered by the fact that most g-ratio protocols rely on time-intensive multi-shell diffusion data which is typically not available in clinical settings. In this study, we adopted the recently introduced NODDI-DTI in combination with magnetization transfer saturation to calculate g-ratio maps based on a single diffusion shell in healthy subjects. The so-acquired g-ratio maps greatly resembled maps from the literature and had high scan-rescan repeatability, which has great implications for clinical g-ratio-weighted imaging.

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MR Myelo-Neurography: Improved Visualization of MR Neurography in the Brachial Plexus using a Combination of SHINKEI and Phase-Cycling balanced SSFP
Hitoshi Tadenuma1, Kayoko Abe2, Masami Yoneyama3, Yasuhiro Goto1, Isao Shiina1, Mamoru Takeyama1, Isao Tanaka1, and Shuji Sakai2

1Department of Radiological services, Tokyo Women’s Medical University Hospital, Tokyo, Japan, 2Department of Diagnostic Imaging & Nuclear Medicine, Tokyo Women’s Medical University Hospital, Tokyo, Japan, 3Philips Electronics Japan, Tokyo, Japan

The brachial plexus could be involved in various kinds of diseases, which may lead to serious functional disorders. MR neurography is a useful technique for evaluating the abnormal state of the peripheral nerves, however, it is still difficult to visualize the entire brachial plexus, including nerve roots, using conventional MR neurography due to its complicated anatomical structure. In this study, we evaluated a new MR neurography using a combination of SHINKEI and Phase-Cycling balanced SSFP sequence to visualize the entire brachial plexus.

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Nonlocal multispectral image filtering to improve determination of cerebral blood flow from pseudo-continuous arterial spin labeling imaging
Mustapha Bouhrara1, Diana Y. Lee1, Abinand C. Rejimon1, and Richard G. Spencer1

1National Institute on Aging, National Institutes of Health, Baltimore, MD, United States

Changes in the cerebral blood flow (CBF), measured using arterial spin labeling (ASL), are an emerging biomarker for normal aging, Alzheimer's disease, and other neurodegenerative conditions. However, ASL signal-to-noise ratio (SNR) is inherently low, diminishing the quality of CBF determination. While attempts have been made to improve SNR in ASL images using post-processing filters, performance is limited and several user-defined parameters are required adding further complexity in implementation. Here, we introduce a simple, novel filtering algorithm and demonstrate its potential to enhance the quality of CBF mapping.

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Rapid Myelin Measurement: Comparison Between SyMRI (Simultaneous Tissue Relaxometry), Magnetization Transfer Saturation Index, and T1w/T2w Ratio Methods
Akifumi Hagiwara1,2, Masaaki Hori2, Koji Kamagata2, Misaki Nakazawa2, Christina Andica2, Tomoko Maekawa1,2, Saori Koshino1,2, Ryusuke Irie1,2, Lydia Chougar2,3, Osamu Abe1, and Shigeki Aoki2

1Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan, 2Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan, 3Hôpital Cochin, Paris, France

In 20 healthy adults, we examined the correlation between three rapid MR myelin measurement methods, including simultaneous tissue relaxometry of R1 and R2 relaxation rates and proton density (SyMRI), magnetization transfer saturation (MTsat) index, and the ratio of T1-weighted to T2-weighted images (T1w/T2w ratio). Even though SyMRI and MTsat showed strong correlation in the white matter, only weak to moderate correlation was found between T1w/T2w and SyMRI or MTsat. In conclusion, SyMRI and MTsat seem to be suitable for evaluating myelin in the white matter, but T1w/T2w ratio may be less optimal.

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Interleaved Multi-Slice Averaged Magnetization Inversion Recovery Acquisitions (imsAMIRA) for Fast Spinal Cord Imaging
Matthias Weigel1,2, Zarko Celicanin1,2, and Oliver Bieri1,2

1Division of Radiological Physics, Dept. of Radiology, University Hospital Basel, Basel, Switzerland, 2Dept. of Biomedical Engineering, University of Basel, Basel, Switzerland

To increase the acquisition efficiency for the averaged magnetization inversion recovery acquisitions (AMIRA) approach for spinal cord imaging, an interleaved multi-slice AMIRA implementation was developed. Utilizing a slice-selective adiabatic inversion pulse with optimized slice thickness, the interleaved multi-slice AMIRA sequence provides spinal cord imaging with the same high gray matter and white matter contrast and very similar image quality like the conventional AMIRA approach, however, in considerably reduced scan times per slice.

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Sampling order optimization preserves contrast and improves clinical diagnostic utility of accelerated prospective 3D brain MRI: a radiological assessment study on healthy volunteers
Arnold Julian Vinoj Benjamin1,2, Wajiha Bano1,2, Grant Mair2, Michael Davies1, and Ian Marshall2

1School of Engineering, Institute for Digital Communications, University of Edinburgh, Edinburgh, United Kingdom, 2Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom

This study shows the importance of sampling order optimization for the contrast preservation of accelerated prospective 3D MRI leading to the improvement in clinical diagnostic utility of accelerated scans using compressed sensing and parallel imaging reconstructions.

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Axial Gradient Echo Spiral MRI of the Pediatric Spine
Ryan Keith Robison1, Melvyn Ooi2, Amber Pokorney1, Zhiqiang Li3, Dinghui Wang3, James Grant Pipe3, and Jeffrey Miller1

1Phoenix Children's Hospital, Phoenix, AZ, United States, 2Philips Healthcare, Phoenix, AZ, United States, 3Barrow Neurological Institute, Phoenix, AZ, United States

MRI spine examinations are an important tool in pediatric care. Long acquisition times and artifacts related to motion and flow are a regular challenge in these examinations. Spiral MRI offers substantial potential benefits with regards to both acquisition time and artifact reduction. This work studies spiral MRI for gradient echo imaging of the pediatric spine and demonstrates promising results in preliminary patient data. The results from a contrast and SNR optimization study in a volunteer are also presented.

3191
Computer 117
Improved brain MR imaging from a compact, lightweight 3T scanner with high performance gradients.
Norbert Campeau1, Yunhong Shu1, Joshua D Trzasko1, Erin M Gray1, Thomas K.F. Foo2, Matt A Bernstein1, and John Huston1

1Mayo Clinic, Rochester, MN, United States, 2GE Global Research, Niskayuna, NY, United States

A compact, low-cryogen 3T MRI scanner with high-performance gradients capable of simultaneously achieving 80 mT/m and 700 T/m/s was compared to a 60-cm, whole body 3T system (50 mT/m, 200T/m/s) for 5 routine brain MR imaging sequences in 9 clinical patients, graded by two neuroradiologists. The compact 3T system performed equally well to a standard whole-body scanner in terms of motion artifacts, and performed better in terms of signal-to-noise ratio, lesion conspicuity, gray/white contrast, susceptibility artifacts and overall exam quality.


3192
Computer 118
Dynamic imaging of hyperpolarized xenon-129 uptake in the human brain with spiral MRI
Madhwesha Rao1, Guilhem Collier1, Rolf Schulte2, Graham Norquay1, and Jim Wild1

1University Of Sheffield, Sheffield, United Kingdom, 2GE Healthcare, Munich, Germany

In this study we explore the use of continuous 2D spiral k-space sampling to dynamically image the uptake of inhaled hyperpolarized 129Xe dissolved in human brain tissue. The sliding window reconstruction enables the monitoring of xenon uptake dynamics in the gray matter at high temporal resolution. Dynamic 129Xe brain MRI may be useful in pathologies related to cerebral perfusion and may provide insight in to blood brain barrier permeability.

3193
Computer 119
Comparison between 2D and 3D MEDIC in human cervical spinal cord at 3T
Abdullah Asiri1,2, Franky Dimpudus3, Aiman Alnajjar1, Katie McMahon1, and Nyoman kurniawan1

1Centre for Advanced Imaging, University of Queensland, Brisbane, Australia, 2Radiology department, College of applied medical sciences, Najran University, Najran, Saudi Arabia, 3Radiology Department, Ramsay Sime Darby Healthcare, Surabaya, Indonesia

High-resolution MRI of the cervical spinal cord is important to provide accurate diagnosis and pathological assessment of injuries. MEDIC (Multiple Echo Data Image Combination) sequence appears promising for use in clinical imaging, however the comparison in the performance of two-dimensional (2D) and three-dimensional (3D) MEDIC sequences for spinal cord imaging has not been reported. This study aims to compare axial 2D and 3D MEDIC sequence for the visualization of the grey matter (GM) and white matter (WM) of the human cervical spinal cord.

3194
Computer 120
Correcting a slice distortion artifact in the multiband diffusion images by postprocessing with the known diffusion gradients
Jiancheng Zhuang1

1University of Southern California, Los Angeles, CA, United States

The diffusion weighted images acquired with the multiband sequence or the Lifespan protocols shows a type of slice distortion artifact. This artifact is caused by the eddy currents, which can be induced by the diffusion gradient associated with either the current DW image or the previous DW images. The artifact can be corrected by a correction algorithm which includes the diffusion gradients from both the current and previous DW images.


Electronic Poster

Diffusion: In Vivo & Ex Vivo Applications: Body

Exhibition Hall Monday 9:15 - 10:15

3195
Computer 1
Atypical Imaging Features of Renal Pelvic Urothelial Carcinoma That Mimics Central Renal Cell Carcinoma:Utility of monoexponential, biexponential, and stretched exponential Diffusion-weighted imaging models
Haojie Li1

1Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wu Han, China

Multi-b values DWI are feasible and useful in the noninvasive tissue characterization of renal tumors. DDC and f may provide additional information and could lead to improved differentiation with better sensitivity and specificity between central renal cell carcinoma (RCC) from renal pelvic urothelial carcinoma compared with conventional diffusion parameters.

3196
Computer 2
A pilot study of the effect of high pressure renal pelvic perfusion on the renal microstructure and microcirculation using multiparametric magnetic resonance imaging (mpMRI)
Qiong Ye1, Zhixian Yu1, Honghui Zhu1, Zhao Zhang1, and Jiance Li1

1The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China

Multiparametric MRI is widely used for tissue characterization. High pressure perfusion is commonly used in endoscopic surgery. In this study we compared the quantitative change of renal microstructure and microcirculation using DTI and simplified intravoxel incoherent motion imaging (sIVIM) in an operation simulating high pressure renal pelvic perfusion in the process of endoscopic surgery. Additionally, we compared the cortical and medullar difference. The results of this pilot study showed the feasibility of mpMRI to characterize renal physiology and investigate its quantitative change, with the potential value in early detection of renal function. But further study with larger sample size is required to draw a clear conclusion.

3197
Computer 3
IVIM DWI in the assessment of renal diffusion and perfusion alternations in ischemic acute kidney injury (AKI) animals
Chengyan Wang1,2, Hanjing Kong2, Fei Gao3, Li Jiang4, Jue Zhang2,3, and Xiaoying Wang2,5

1Institute for Medical Imaging Technology, Shanghai Jiao Tong university, Shanghai, China, 2Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China, 3College of Engineering, Peking University, Beijing, China, 4Philips Healthcare, Suzhou, China, 5Department of Radiology, Peking University First Hospital, Beijing, China

Intravoxel incoherent motion (IVIM) DWI is able to simultaneously detect diffusion and perfusion characteristics of renal tissue, which provides more sensitive measurement of renal function than serum creatinine. This study investigates the feasibility of using IVIM DWI to evaluate renal diffusion and perfusion changes in ischemic AKI animals. IVIM DWI was performed on rabbits prior to (24 hours before surgery) and after the surgery (1 hour, 3 hours, 1 week and 2 weeks after surgery). After injection of 0.8 mg microspheres, a noticeable change of renal diffusion and perfusion can be seen in the cortex immediately after the surgery. Pathological results also confirmed the renal injury with findings of ischemic and wrinkled features with dilated change of Bowman’s capsule.

3198
Computer 4
Diffusion kurtosis imaging in the characterization of rectal cancer: Evaluation of segmentation strategies and repeatability
Yiqun Sun1, Qin Xiao2, Feixiang Hu2, Chao Xin2, Huixun Jia2, Sanjun Cai2, Robert Grimm3, Caixia Fu4, Xu Yan5, Weijun Peng2, Tong Tong1, and Yajia Gu1

1Department of Radiology;Department of Oncology, Fudan University Shanghai Cancer Center; Shanghai Medical College, Fudan University, Shanghai, China, 2Fudan University Shanghai Cancer Center; Shanghai Medical College, Fudan University, Shanghai, China, 3MR Application Predevelopment, Siemens Healthcare, Erlangen, Germany, 4Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China;, Shanghai, China, 5MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China;, Shanghai, China

The aim of this study was to evaluate the influence of different segmentation strategies on diffusion parameters and the performance of diffusion kurtosis imaging in predicting rectal cancer histopathological characteristics before a treatment decision is made. The results show that the whole-tumor-volume segmentation strategy could achieve the best inter- and intra-observer repeatability among the six different strategies, and DKI with this segmentation strategy performed accurately for differentiating between well-differentiated and poorly to moderately differentiated patients.

3199
Computer 5
Evaluation of cervical cancer staging using readout segmentation of long variable echo-trains and single-shot diffusion weighted echo-planar imaging: a comparison study
WeiLiang Qian1, Qian Chen1, Zhongshuai Zhang2, Hong Wang1, Jibin Zhang1, and Jianming Xu1

1Radiology, Suzhou Municipal Hospital, Nanjing Medical University, Suzhou, China, 2Diagnosis Imaging, Siemens Healthcare Ltd, Shanghai, China

Diffusion weighted imaging (DWI) sequence based on readout segmentation of long variable echo-trains (RESOLVE) is superior to that based on single-shot echo-planar imaging (SS-EPI) with respect to improved the image quality, which makes the images more valuable for clinical needs. In this study, we propose an idea to evaluate whether such differences in these images have an impact on  staging of cervical cancer. The results show that RESOLVE can improve the accuracy of staging of cervical cancer because of the reductions of image artifacts and geometric deformation.

3200
Computer 6
Predictive and prognostic value of intravoxel incoherent motion (IVIM) MR imaging in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy
Zhengyang Zhou1 and Weibo Chen2

1Department of Radiology, Drum Tower Hospital, School of Medicine, Nanjing University, Nanjing, China, 2Philips Healthcare, Shanghai, Shanghai, China

Pelvic IVIM MR imaging were performed on 30 women with advanced cervical cancers at three time points. The performance of tumour size and IVIM-derived parameters in predicting long-term prognosis was evaluated. After a median follow-up of 24 months, 83.33% patients were alive, 70.00% remained free of disease. A shrinkage rate of maximum diameter≥ 58.31% was useful in predicting a good long-term prognosis. The IVIM-derived ADCIVIM value at time point 2 and the ADCIVIM and f values at time point 3 also performed well in predicting a good prognosis. IVIM has great potential in predicting long-term prognosis in patients with advanced cervical.

3201
Computer 7
Whole-lesion apparent diffusion coefficient histogram analysis: significance in T and N staging of gastric cancers
Zhengyang Zhou1 and Weibo Chen2

1Department of Radiology, Drum Tower Hospital, School of Medicine, Nanjing University, Nanjing, China, 2Philips Healthcare, Shanghai, Shanghai, China

Eighty patients with pathologically confirmed gastric carcinomas underwent DWI-MR imaging before surgery prospectively. Whole-lesion ADC histogram analysis was performed. The differences of ADC histogram parameters among different T and N stages were compared with independent-samples Kruskal-Wallis test. ROC analysis was performed to evaluate the performance of ADC histogram parameters in differentiating particular T or N stages of gastric cancers.There were significant differences of all the ADC histogram parameters at different T (except ADCmin and ADCmax) and N (except ADCmax) stages. Whole-volume ADC histogram parameters held great potential in differentiating different T and N stages of gastric cancers preoperatively.

3202
Computer 8
Diffusional kurtosis imaging of parotid glands in Sjögren's syndrome: Initial findings
Zhengyang Zhou1 and Weibo Chen2

1Department of Radiology, Drum Tower Hospital, School of Medicine, Nanjing University, Nanjing, China, 2Philips Healthcare, Shanghai, Shanghai, China

A total of 40 patients with SS and 40 healthy volunteers underwent DKI-MR imaging, which generated ADC, D, and K values. The MR nodular grade was determined on the basis of MR morphological findings. The parotid ADC, D, and K values in patients with SS were significantly higher than those of healthy volunteers. The K values correlated positively with the MR nodular grade significantly in patients with SS.All parotid DKI parameters differed significantly among patients with SS at different MR nodular grades. Parotid DKI parameters hold great potential in diagnosing SS, especially in early-stage SS without MR morphological changes.

3203
Computer 9
Assessment of Liver Fibrosis: Comparison of Diffusion Kurtosis Imaging, Conventional DWI, Aspartate Aminotransferase-to-Platelet Ratio Index and Fibrosis-4
Li Yang1, Mengsu Zeng1, Shengxiang Rao1, Caizhong Chen1, Robert Grimm2, Caixia Fu3, and Xu Yan4

1Zhongshan Hospital, Fudan University, Shanghai, China, 2MR Application Predevelopment, Siemens Healthcare, Erlangen, Germany, 3Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China, 4MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China

Diffusion kurtosis imaging (DKI) is a recently developed diffusion model that measures the non-Gaussian diffusion of water molecules in biological tissue. Few studies reported the potential of DKI on assessing hepatic fibrosis. Aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 (FIB-4) are widely used non-invasive serum tests that estimate liver fibrosis. We compared the diagnostic performance of DKI, conventional DWI, APRI, and FIB-4 for evaluating the severity of liver fibrosis. Our results showed that diffusion-based measurements offer a similar diagnostic performance to the serum fibrosis biomarkers APRI and FIB-4 index for predicting liver fibrosis in patients with chronic liver disease.

3204
Computer 10
Postmortem MR diffusion-weighted imaging of the liver: Time behavior of the hepatic apparent diffusion coefficient in the early death interval
Jin Yamamura1, Tony Schmidt1, Anne Catherine Kim2, Roland Fischer3,4, Gerhard Adam1, and Sarah Keller1

1Diagnostic and Interevntional Radiology, University Medical Center Hamburg Eppendorf, Hamburg, Germany, 2Department Stroke and Neurovascular Imaging, The Permanente Medical Group, San Francisco, CA, United States, 3Department of Pediatric Hematology/Oncology, University Medical Center Hamburg Eppendorf, Hamburg, Germany, 4UCSF Benioff Children's Hospital Oakland, Oakland, CA, United States

Postmortem liver ADC values shows a characteristic change over time in the first 16 hours postmortem, which seemed to be influenced by the core body temperature. The postmortem time behavior of liver DWI values could be of interest for postmortem MRI in virtual autopsy. 

3205
Computer 11
Towards a definition of the biophysical bases of transient Anomalous Diffusion (tAD) parameters. Evaluation of tAD, DKI and DTI in normal and cancer prostate tissue with Magnetic Resonance micro-imaging at 9.4 Tesla
Maria Giovanna Di Trani1,2, Alessandra Caporale2, Marco Nezzo3, and Silvia Capuani2

1SAIMLAL Dept., Sapienza University of Rome, Rome, Italy, 2CNR-ISC Physics Dept., Sapienza University of Rome, Rome, Italy, 3Diagnostic and Interventional Radiology Dept., Tor Vergata University, Rome, Italy

Since DKI and transient anomalous diffusion imaging (tADI) are based on statistical models, they can be performed without the need of a-priori hypothesis on tissue micro-structures. However, the relation between tissue micro-structure DKI and tADI derived parameters have not been clearly established yet. In this work, we evaluated DKI, tAD and DTI diffusion parameters in normal and high-grade cancer prostate, by MR microimaging at 9.4T with a 70μmx70μm in plane resolution. As prostate tissue is a complex tissue, composed by several micro-compartments that exhibit different diffusion behaviors, it is an ideal tissue to investigate the biophysical features of diffusion parameters.

3206
Computer 12
Prostate Cancer: Influence of the Diffusion Time on Diffusion Kurtosis Imaging
Tristan Anselm Kuder1, Frederik Bernd Laun2, David Bonekamp3, and Matthias Carl Röthke3,4

1Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, 3Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 4Conradia, Hamburg, Germany

Diffusion MRI is routinely used in prostate cancer diagnosis. Diffusion kurtosis imaging allows measuring the kurtosis Kapp, related to deviations from free diffusion, additionally to the diffusion coefficient Dapp. Varying the diffusion time may yield additional information about the investigated tissue by probing the diffusion barriers at different length scales. Here, Dapp and Kapp were measured at three diffusion times in 27 patients with histologically confirmed prostate cancer. A reduction of Kapp was observed in tumor and normal control regions with increasing diffusion time, while a Dapp reduction was mostly seen in control regions.

3207
Computer 13
METastasis Reporting and Data System for Prostate Cancer (MET-RADS-P) for castration-resistant prostate cancer: prediction of clinical course, and identification of oligo-progressive lesions as targets for loco-regional ablative therapy.
Soichiro Yoshida1, Taro Takahara2,3, Chikako Ishii3, Thomas C Kwee4, Keiko Nakagawa5, Kazuma Toda5, Yuki Arita3, Toshiki Kijima1, Minato Yokoyama1, Junichiro Ishioka1, Yoh Matsuoka1, Kazutaka Saito1, Ryoichi Yoshimura5, Kazunori Kihara1, and Yasuhisa Fujii1

1Urology, Tokyo Medical and Dental University Graduate School, Tokyo, Japan, 2Biomedical Engineering, Tokai University School of Engineering, Kanagawa, Japan, 3Radiology, AIC Yaesu Clinic, Tokyo, Japan, 4Radiology, UMC Groningen, Groningen, Netherlands, 5Radiation Therapeutics and Oncology, Tokyo Medical and Dental University Graduate School, Tokyo, Japan

Whole-body diffusion-weighted MRI is a new-generation imaging tool for detecting prostate cancer. The extent of bone metastasis and the presence of visceral metastasis on whole-body diffusion-weighted MRI according to METastasis Reporting and Data System for Prostate Cancer (MET-RADS-P) were associated with a lower cancer-specific survival in castration-resistant prostate cancer. Furthermore, whole-body diffusion-weighted MRI facilitates identification of oligo-progressive lesions, which can be targets for loco-regional radiotherapy. MET-RADS-P score of whole-body diffusion-weighted MRI can be an imaging biomarker for castration-resistant prostate cancer in predicting clinical course, and identifying oligo-progressive lesions as targets for loco-regional ablative therapy.

3208
Computer 14
Acute Ankle Sprain: Demonstration of Reliability and Reproducibility of DTI in Imaging Peripheral Nerves
Natalia I Lopez1, Nadia Barakat1, Andrew M Youssef1, Katie E Silva1, Jürgen Finsterbusch2, Laura Simons1, and David Borsook1

1Boston Children's Hospital, Boston, MA, United States, 2University Medical Center Hamburg-Eppendorf, Hamburg, Germany

We investigated potential structural changes in peripheral nerves following ankle sprain injuries. Specifically, we assessed the integrity of the sciatic nerve and its major divisions: the tibial and peroneal nerves. Reduced field-of-view DTI was used, and the reproducibility of the DTI measures was examined. Our results revealed excellent reliability of DTI measures in injured versus control nerves across each parameter (FA, AD, RD, MD). A comparison of injured versus control nerves in the associated nerve branch indicated significant difference in AD. Given these results, DTI may have potential as a powerful tool to determine disease profile.

3209
Computer 15
Evaluation of two collagen conduits and autograft in sciatic nerve regeneration in a rabbit nerve gap model with DTI, histology and electrophysiology
Tina Jeon1, Emil S Vutescu2, Eliana B Saltzman2, Jordan C Villa2, Scott W Wolfe2, Steve K Lee2, Joseph H Feinberg3, Sarah L Pownder1, Jonathan P Dyke4, and Darryl B Sneag1

1Radiology and Imaging, Hospital for Special Surgery, New York, NY, United States, 2Department of Hand and Upper Extremity Service, Hospital for Special Surgery, New York, NY, United States, 3Department of Rehabilitation Medicine, Hospital for Special Surgery, New York, NY, United States, 4Citigroup Biomedical Imaging Center, Weill Cornell Medical College, New York, NY, United States

DTI has been used primarily to evaluate white matter tracks in the brain. More recent studies have applied DTI techniques to peripheral nerves, due to their anisotropic architecture. In this investigation, we evaluated peripheral nerve regeneration in a rabbit sciatic nerve gap model comparing two collagen conduits with nerve autograft using DTI and comparison with functional/physiologic testing and histology. We hypothesized that this study would allow us to reliably compare outcomes of nerve regeneration between collagen-based conduits and autograft nerve reconstructions and provide validation for the use of DTI techniques to non-invasively monitor nerve regeneration in-vivo.  

3210
Computer 16
Improvements in Whole Body Diffusion Weighted Imaging: Combination of Integrated Slice-Specific Dynamic Shimming and Readout-Segmented EPI
Wei Liu1, Alto Stemmer2, Elisabeth Weiland2, and Kun Zhou1

1Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China, 2Siemens Healthcare, Erlangen, Germany

Single-shot echo planar imaging (ss-EPI) is most frequently used for whole body diffusion weighted imaging (WB-DWI) because of short acquisition time and motion insensitivity. However, ss-EPI is vulnerable to the effects of the static field inhomogeneity and poses a challenge to perform ss-EPI based WB-DWI at 3 Tesla. Integrated slice-specific dynamic shimming (iShim) combined with ss-EPI has shown a remarkable improvement on the susceptibility related artifacts in WB-DWI. In this study, we demonstrate the application of rs-EPI using iShim to WB-DWI, which can provide higher quality WB-DWI, specifically less spatial distortions.

3211
Computer 17
The clinical value of DWIBS in the diagnosis of bone marrow involvement in lymphoma and hyperplastic hematopoietic bone marrow
Mengtian Sun1, Jingliang Cheng1, Yong Zhang1, and Zhizheng Zhuo2

1MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, 2Philips Healthcare, Beijing, China

This study aimed to investigate the clinical value of diffusion weighted imaging with background signal suppression(DWIBS) in differentiating bone marrow involvement(BMI) in lymphoma from hyperplastic hematopoietic bone marrow(HHBM). Eleven BMI patients, 19 HHBM patients and 20 normal controls underwent DWIBS before the bone marrow biopsy. The ADC value of the bone marrow within the biopsy regions in BMI group was lower than that of HHBM group and higher than that of normal controls. ADC values added relevant information in the potential clinical value of differentiating BMI and HHBM patients. 

3212
Computer 18
Development of Diffusion Tensor Imaging to Assess Traumatic Peripheral Nerve Injury and Recovery
Michael Pridmore1, Wesley P. Thayer2, Mark Does3, and Richard Dortch4

1Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States, 2Plastic Surgery, Vanderbilt University Medical Center, Nashville, TN, United States, 3Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 4Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States

Current clinical management following traumatic peripheral nerve injuries (TPNI) and repair require physicians to rely on qualitative measures from patient history/physical exam that can cause delay in patient care. Such delays can a negative impact on outcomes because the healing of nerves must occur in a timely fashion to avoid permanent loss of sensory and/or motor function. The current study aims to test the feasibility of performing DTI measurements in TPNI patients to better improve clinical outcomes.

3213
Computer 19
A Local Coregistration for Quantitative Evaluation of Distortion of Parotid Gland Tumors in Echo-Planar DWI and PROPELLER DWI
Kai-Min Chien1, Yi-Jui Liu2, Yi-Hsiung Lee 3,4, Hing-Chiu Chang 5, Hui-Chu Chiu 6, Ta-Wei Chiu 7, Kang Hsu 8, Hsian-He Hsu 4,9, Chun-Jung Juan4,9, Yu-Shu Fu10, and CHENG-YI JUAN11

1Master 's Program of Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung City 407, Taiwan, 2Department of Automatic Control Engineering, Feng Chia University, Taichung City 407, Taiwan, 3Ph. D. Program of Electrical and Communications Engineering, Feng Chia University, Taichung City 407, Taiwan, 4Department of Radiology, Tri-Service General Hospital, Taipei, Taiwan, 5Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong, 6Ph.D. program of Technology Management, Chung Hua University, Hsinchu, Taiwan, 7Department of Medicine, Taipei Medical University, Taipei, Taiwan, 8Department of Dentistry, National Defense Medical Center, Taipei, Taiwan, 9Department of Radiology, National Defense Medical Center, Taipei, Taiwan, 10Master 's Program of Biomedical Informatics and Biomedical Engineering, Feng Chia University, TAICHUNG, Taiwan, 11Institute of Automatic Control Engineering, Feng Chia University, TAICHUNG, Taiwan

The study is to quantitatively compare the morphology distortion in distinguishing parotid pleomorphic adenomas (PMA) between PROPELLER-DWI and EP-DWI. This retrospective study enrolled 14 PMAs. All participants underwent 1.5-T fat-saturated diffusion-weighted imaging with PROPELLER-DWI and EP-DWI. A local coregistration method to quantitatively evaluate the distortion of parotid gland tumors between single shot EP-DWI and PROPELLER DWI. Imaging distortion represented by Dice coefficient was quantitatively analyzed. Our results showed that PROPELLER-DWI allows distinguishing PMAs with less distortion than EP-DWI.

3214
Computer 20
Is ADC Affected by Distortion of EP-DWI for Distinguishing Parotid Gland Tumor- To Compare ADC of Parotid Gland in Echo-Planar DWI and PROPELLER DWI
Kai-Min Chien1, Yi-Jui Liu2, Yi-Hsiung Lee 3,4, Hing-Chiu Chang 5, Hui-Chu Chiu 6, Ta-Wei Chiu 7, Kang Hsu 8, Hsian-He Hsu 4,9, Chun-Jung Juan4,9, Yu-Shu Fu10, and CHENG-YI JUAN11

1Master 's Program of Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung City 407, Taiwan, 2Department of Automatic Control Engineering, Feng Chia University, Taichung City 407, Taiwan, 3Ph. D. Program of Electrical and Communications Engineering, Feng Chia University, Taichung City 407, Taiwan, 4Department of Radiology, Tri-Service General Hospital, Taipei, Taiwan, 5Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong, 6Ph.D. program of Technology Management, Chung Hua University, Hsinchu, Taiwan, 7Department of Medicine, Taipei Medical University, Taipei, Taiwan, 8Department of Dentistry, National Defense Medical Center, Taipei, Taiwan, 9Department of Radiology, National Defense Medical Center, Taipei, Taiwan, 10Master 's Program of Biomedical Informatics and Biomedical Engineering, Feng Chia University, TAICHUNG, Taiwan, 11Institute of Automatic Control Engineering, Feng Chia University, TAICHUNG, Taiwan

The study is to investigate if the perceptible geometric distortions could bias for parotid pleomorphic adenomas (PMA) by ADC measurements by comparing PROPELLER-DWI with EP-DWI. This retrospective study enrolled 14 PMAs. All participants underwent 1.5-T fat-saturated diffusion-weighted imaging with PROPELLER-DWI and EP-DWI. ADCs were measured on normal parotid gland and PMA for PROPELLER-DWI and EP-DWI. Our results showed that PMAs had significantly higher ADC than normal parotid glands no matter on PROPELLER-DWI or EP-DWI. The ADC measured by PROPELLER-DWI was significantly higher than by EP-DWI, but they were proportional to each other. EP-DWI allows distinguishing PMAs even under image distortion. 

3215
Computer 21
The value of DWI with Readout Segmentation of Long Variable Echo-trains in Differentiating Benign and Malignant Lesions of the Tongue
Baohong Wen1 and Jingliang Cheng1

1the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China

The purpose of this study was to assess the role of readout segmentation of long variable echo-trains(RESOLVE) DWI in differentiating benign and malignant lesions of the tongue. 120 patients with lingual lesions underwent preoperative RESOLVE DWI. The results demonstrated that the mean ADC values of benign lesions of the tongue were significantly higher than malignant lesions. Using an ADC value of 1.25×10-3 mm2/s as the threshold value, the sensitivity and specificity were 94.64%, 93.75% respectively. RESOLVE can offer high quality DWI of tongue. The ADC value can be applied in differential diagnosis between benign and malignant lesions of the tongue

3216
Computer 22
Diffusion kurtosis imaging in evaluating non-Hodgkin’s lymphoma: associations with tumor aggressiveness and proliferation
Jing Zhong1, Yunbin Chen1, Ying Chen1, Cuifang Chen1, and Weibo Chen2

1Radiology, Fujian Cancer Hospital, Fuzhou, China, 2Philips Healthcare, Shanghai, China

This study tries to evaluate the usefulness of diffusion kurtosis imaging (DKI) parameters in segregating the pathological subtypes of NHL lymphoma, and to explore its associations with aggressiveness and proliferative index. Significant differences were found among the WHO classified subgroups. Meanwhile, the stronger tumor aggressiveness (higher Ki67 percentage) was accompanied with more restricted water diffusivity (lower ADC and D values) and more complex cell micro-structural environment (higher K value). The DKI technique may help estimation of tumor proliferation in NHL lymphoma and DKI parameters can be used as imaging biomarker of the biological aggressiveness of the tumor.

3217
Computer 23
Assessment of the Specificity and Sensitivity of DTI Metrics for Evaluation and Diagnosis in Degenerative Cervical Myelopathy
Guangqi Li1, Xiaodong Ma1, JinChao Wang2, Donghang Li2, Xiao Han2, Wen Jiang3, Xiaoguang Cheng3, and Hua Guo1

1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Department of Spine Surgery, Beijing Jishuitan Hospital, Beijing, China, 3Department of Radiology, Beijing Jishuitan Hospital, Beijing, China

Diffusion Tensor Imaging (DTI) can detect diffusion information of water molecules, and is used to diagnose the severity of degenerative cervical myelopathy (DCM). However, the diagnostic capability of DTI metrics is not fully investigated. In this study, DTI metrics are employed to evaluate the spinal cord function in preoperative DCM patients and healthy volunteers. Nonparametric t-test results show that MD, FA and RD have significant differences between patients and healthy volunteers. In addition, ROC results indicate that FA has higher sensitivity, RD has higher specificity for evaluation and diagnosis in DCM. 

3218
Computer 24
L-spine Bone Marrow on Female: A Intravoxel Incoherent Motion MR Imaging Study
Teng Zhao1, Yunsong Zheng1, Hui Xu2, Yuanyuan Chen1, Yanbing Guo1, Dong Han1, and Nan Yu1

1Department of Medical Imaging, Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, Xianyang, China, 2Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

To our knowledge, no studies have employed IVIM diffusion-weighted MRI to explore the variation trend of bone marrow in female. Whether gender difference exists in marrow structure is not well investigated. Therefore, we explored the diagnostic utility of IVIM diffusion-weighted MRI parameters in this context. We found that D, D* and f value showed a decreased trend with age, and the D, D* value of bone marrow in female was significantly higher than that in male except the f value. IVIM diffusion-weighted MRI was useful in the evaluation of bone marrow.


Electronic Poster

Diffusion MRI: Validation

Exhibition Hall Monday 9:15 - 10:15

3219
Computer 25
How do current diffusion-based MR methods reflect hypomyelination – comparison of diffusion tensor, neurite orientation dispersion and density, and diffusion kurtosis imaging
Rakshit Dadarwal1, Amir Moussavi1, Wiebke Möbius2, and Susann Boretius1

1Functional Imaging Laboratory, German Primate Center, Göttingen, Germany, 2Department of Neurogenetics, Max Planck Institute for Experimental Medicine, Göttingen, Germany

Diffusion-based MRI comprises an exciting toolset to analyze tissue microstructures under normal and pathological conditions. Among numerous diffusion-based methods compared, all reflected the differences in myelination in a mouse model expressing only reduced levels of the myelin basic protein. However, diffusion tensor was more robust than diffusion kurtosis imaging. Intra-neurite volumes, as revealed by neurite orientation dispersion and density imaging or by the spherical mean technique, were not specific for the numbers of axons but were also affected by difference in myelination.

3220
Computer 26
Realistic 3D Fiber Crossing Phantom Models for Monte Carlo Diffusion Simulations
Jonathan Rafael-Patino1, Gabriel Girard1, David Romascano1, Muhamed Barakovic1, Gaëtan Rensonnet2,3, Jean-Philippe Thiran1,4, and Alessandro Daducci1,4,5

1Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 2ICTEAM Institute, Université catholique de Louvain., Louvain-la-Neuve, Belgium, 3Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, Lausanne, Switzerland, 4Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland, 5Computer Science Department, University of Verona, Verona, Italy

Monte-Carlo Diffusion Simulations has proved to be a powerful approach to study Diffusion-Weighted MRI; from generating ground-truth data, to study the diffusion process in complex media. However, a major problem with the current approaches is that they oversimplify the geometrical properties of the diffusion media. In this work we present a framework to create 3D meshes for realistic configurations that can be used for MCDS. The synthesized signals from this models can be used to study microstructure and tractography methods, which is of vital importance since novel methods require better ground-truth that mimics real tissue properties to avoid oversimplifications.

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Critical Choices in ROI Analysis of Diffusion MRI Data
Mohammad Alipoor1 and Stephan E Maier1,2

1Radiology, University of Gothenburg, Gothenburg, Sweden, 2Radiology, Brigham and Women's Hospital, Boston, MA, United States

Diffusion parameters such as diffusivity, compartment fractions and diffusion signal itself are informative bio-markers in understanding and analyzing pathological changes in biological tissue. One frequently needs to compute a representative value of a diffusion parameter in a homogeneous ROI. Here we compare and contrast 3 common choices that researcher would make in the course ROI analysis. Though ROI analysis is deemed to be a common practice, the critical choices of computational methods (depending on noise distribution and underlying model) can considerably affect its findings and conclusions.  

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Transient anomalous diffusion micro-MRI parameters reflect white matter morphology: comparison with histology of the mouse spinal cord.
Alessandra Caporale1, Giovanni Battista Bonomo2, Giulio Tani2, AdaMaria Tata3, Bice Avallone4, Felix Werner Wehrli5, and Silvia Capuani1

1Physics, CNR ISC, UOS Roma Sapienza, Sapienza University of Rome, Rome, Italy, 2Physics, Biophysics division, Sapienza University of Rome, Rome, Italy, 3Biology and Biotechnologies C. Darwin, Research Center of Neurobiology Daniel Bovet, Sapienza University of Rome, Rome, Italy, 4Biology, University of Naples Federico II, Naples, Italy, 5Radiology, Laboratory for Structural, Physiologic and Functional Imaging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States

Transient-anomalous diffusion (tAD) has previously been used for tumor delineation and human brain tissue characterization, however, comparison with histology is largely missing. This work aims to compare α and γ tAD parameters, DTI and q-space-imaging parameters obtained at 9.4T with micro-MRI, with the morphologic characteristics provided by optical microscopy of mouse spinal cord white matter (MSC-wm). We found that γ- and q-space-imaging are sensitive to axon diameter and effective local axon density, while α-imaging is sensitive to the heterogeneity or degree of disorder of the wm tracts. These techniques outperform DTI as a means to probe MSC-wm morphology.

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Developing 3D perfusion bioreactor for MRI and optical imaging
Slavka Carnicka1, Jeanne E. Barthold2, Kathryn E. Keenan1, Karl F. Stupic1, Corey P. Neu3, and Stephen E. Russek1

1NIST, Boulder, CO, United States, 2Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, United States, 3University of Colorado Boulder, Boulder, CO, United States

Whole-body medical imaging (such as MRI) can map many physical tissue parameters; however, there are currently many questions in the field regarding how changes in MRI are representative of changes in the underlying cells. To better understand these processes, we need to correlate MRI measurements with changes in microstructure. We created a living phantom for evaluation of techniques such as diffusion tensor imaging (DTI) that can be monitored and validated by optical techniques. Our future plan is to use MRI to study cell growth and monitor response to chemical and mechanical stimuli. 

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Test-retest reliability of graph theoretic metrics in adolescent brains
Justin P. Yuan1, Eva Henje Blom2, Trevor Flynn1, Yiran Chen1, Tiffany C. Ho3, Colm G. Connolly4, Rebecca A. Dumont Walter1, Tony T. Yang5, Duan Xu1, and Olga Tymofiyeva1

1Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, 2Department of Clinical Science Child and Adolescent Psychiatry, Umeå University, Umeå, Sweden, 3Department of Psychology, Stanford University, Stanford, CA, United States, 4Department of Biomedical Sciences, Florida State University, Tallahassee, FL, United States, 5Department of Psychiatry, University of California San Francisco, San Francisco, CA, United States

Graph theory analysis of structural brain networks derived from diffusion tensor imaging (DTI) has been utilized to study neurological and psychiatric disorders but its reliability remains understudied, especially in the still-developing brain. Repeated DTI scans of adolescents were acquired to assess the test-retest reliability of different weighting schemes of brain networks: fractional anisotropy (FA), streamline count (SC), and binary (B). The test-retest scans were performed at two time intervals: 12 weeks apart and within the same scan session, approximately 30 minutes apart. Results suggest that FA-weighting outperforms the other schemes.

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Design of multi-purpose and 3D-printed fibre phantoms for investigating complex tissue microstructures
Husan-Han Chiang1, Kuan-Hung Cho1, Ezequiel Farrher2, Johannes Lindemeyer2, Richard Buschbeck2, Ming-Jye Chen1, Farida Grinberg2,3, Nadim Jon Shah2,3, Chang-Hoon Choi2, and Li-Wei Kuo1

1Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan, 2Institute of Neuroscience and Medicine – 4, Forschungszentrum Juelich, Juelich, Germany, 3Department of Neurology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany

Investigating complex tissue microstructures has become of great interest during the past decade. One of the most promising MRI methods to map tissue microstructures is diffusion MRI. However, the validation of its accuracy in mapping fibre orientation and microstructural characteristics is still challenging. In this work, we have successfully designed and prototyped a fibre phantom using 3D printing and micro-scale fused silica capillaries. Our results show that susceptibility of the capillaries and/or the coating material is different from that of distilled water and suggest that our phantom design could provide detectable microstructures for further studies.

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Multisite Reproducibility of Radiomics and ADC Measurements for temperature-controlled phantom: Preliminary Results.
Michael A. Jacobs1, Dariya I. Malyarenko2, David C. Newitt3, Vishwa S. Parekh4, Nola M. Hylton3, and Thomas L. Chenevert2

1The Russell H. Morgan Dept of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2Radiology, University of Michigan, Ann Arbor, MI, United States, 3Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, 4Computer Science, The Johns Hopkins University, Baltimore, MD, United States

Radiomics is an emerging field which deals with high throughput extraction of quantitative features from radiological images. Radiomic features correspond to textural information that is otherwise not visually perceivable. To establish confidence intervals for extracted features the longitudinal reproducibility of the radiomic metrics should be assessed with the standard.  This work has demonstrated radiomic reproducibility for ADC mapping acquired for the ice-water phantom over several years on three independent systems at two different field strengths (1.5 and 3T).

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MR Characterization and Temperature Dependence of Aqueous Polyvinylpyrolidone (PVP) Solutions for use as MR Phantoms
Joelle E Sarlls1, Michal Komlosh2, Ferenc Horkay2, Uri Nevo3, Peter J Basser2, and Carlo Pierpaoli4

1NINDS/NMRF, National Institutes of Health, Bethesda, MD, United States, 2NICHD, National Institutes of Health, Bethesda, MD, United States, 3Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel, 4NIBIB, National Institutes of Health, Bethesda, MD, United States

Diffusion-weighted MRI methods often contain variability and bias in diffusion parameters that are measured between sites, scanners, and vendors. There is a clear need for a calibrated diffusion phantom to help identify and mitigate these differences.  Here we utilize a 7T spectrometer to characterize MR parameters of T1, T2, and the water self-diffusion coefficient in aqueous Polyvinylpyrolidone (PVP) solutions and their dependence on temperature and PVP concentration, without imaging confounds.  An empirical formula is presented for use wtih PVP aqueous solutions as a calibrated diffusion phantom.  Data show that aqueous PVP solutions are well suited as a MR phantom material.

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Does neurite density as measured by diffusion-weighted MR imaging relate to neuronal density as measured by MR spectroscopy?
Hamied A Haroon1, Ben R Dickie1, Faezeh Sanaei Nezhad1,2, Martyn McFarquhar1, Stephen R Williams1, Geoff JM Parker1,2, and Laura M Parkes1

1The University of Manchester, Manchester, United Kingdom, 2Bioxydyn Limited, Manchester, United Kingdom

Capturing the earliest signs of dementia with MR imaging relies on techniques that are sensitive to the subtle loss or disconnection of neurons before atrophy occurs. Models of multi-shell HARDI such as NODDI claim to quantify neurite density in vivo and non-invasively, but the specificity of these HARDI-based metrics remain unvalidated. This study aims to determine the sensitivity of NODDI’s neurite density and orientation dispersion index to regional variation of MRS markers of neuronal and glial cell density. We find that caution must be exercised when interpreting NODDI’s neurite density as related to neuronal density. Orientation dispersion instead appears to be a closer marker of neuronal density and may be a more sensitive marker of disease-related change.

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Free watER iNvariant Estimation of Tensor (FERNET): Addressing the Issue of Edema in Clinically Feasible Acquisitions
Abdol Aziz Ould Ismail1, Drew Parker1, Simon Alexander2, Emmanuel Caruyer3, Ofer Pasternak4, and Ragini Verma1

1Radiology, University of Pennsylvania, Philadelphia, PA, United States, 2Synaptive Medical Inc., Toronto, ON, Canada, 3IRISA, CNRS, Rennes, France, 4Psychiatry and Radiology, Harvard Medical School, Boston, MA, United States

Despite the growing research in free water elimination (FWE) methods with advanced diffusion acquisition protocols, the need for robust single-shell based FWE remains, as this is the standard acquisition protocol in the clinic. This is especially important in the characterization of peritumoral regions with infiltration. However, single-shell FWE is an ill-posed problem, dependent on parameter initialization, solutions to which often fail to obtain a balanced correction between healthy and abnormal tissue. We introduce FERNET, a robust FWE protocol for single-shell data with a comprehensive investigation of initialization parameters based on a software simulated phantom where the ground truth is known.

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Multi-shell multi-tissue fODF tractography improves V1-V2 macaque connectivity mapping
Guillaume Theaud1, Maxime Descoteaux1, Rémi Cossette-Roberge1, Jean-Christophe Houde1, Chuyang Ye2, Nathalie Richard3, Yujie Hou4, Loïc Magrou4, Kenneth Knoblauch4, Henry Kennedy4, and Bassem Hiba3

1Sherbrooke Connectivity Imaging Lab (SCIL), University of Sherbrooke, Sherbrooke, QC, Canada, 2Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China, 3Institut des Sciences Cognitives Marc Jeannerod, CNRS/université Lyon1 (UMR 5229), Bron, France, 4Inserm, Stem Cell and Brain Research Institute U1208, Université Claude Bernard Lyon 1, Bron, France

We show that multi-shell (multi b-value), multi-directional, and high spatial resolution (300 microns isotropic) diffusion MRI combined with multi-tissue fiber orientation distribution function (fODF) tractography increases by 6% the number of true positive connections and uniformly increases the cortical coverage by 3%, while preserving the same percentage of false positive connections, with respect to a more standard single-tissue single-shell tractography. As a result, it is possible to find all 5 ground truth V1-V2 bundles (true positives), while reconstructing only 4 invalid bundles (false positives) corresponding to 4 pairs of spatially neighboring regions.

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Apparent exchange rate mapping: relation to membrane permeability
Dominik Ludwig1, Frederik Bernd Laun2, Peter Bachert1, and Tristan Anselm Kuder1

1Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany

Apparent exchange rate (AXR) mapping might provide an insight into the exchange of water between intra- and extracellular space by using a double-diffusion encoded sequence with varying mixing time between the two gradient pairs. To investigate the connection between AXR and membrane permeability and to test the assumptions of the underlying theory, Monte Carlo simulations using simplified tissue models were performed. Simulations covered a broad range of membrane permeabilities to determine limits of the applicability of this technique. For the considered simplified tissue model, AXR-values could be reliably related to membrane permeabilities typically occurring in vivo.

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Characterization of Diffusion Metric Map Similarity in MRI Data from a Clinical PACS using the Histogram Distance
Graham C Warner1 and Karl G Helmer1,2

1Radiology, Massachusetts General Hospital, Boston, MA, United States, 2Radiology, Harvard Medical School, Boston, MA, United States

As data reuse becomes more popular, it is critical to develop methods that characterize the similarity of data.  Methods have been developed that characterize raw image files, but users often only have access to calculated parameter maps.  Here we describe a histogram-distance-based method applied to diffusion metric maps generated from MRI data extracted from a clinical data repository.  We find that metric maps from GE scanners are less similar than that from Siemens scanners.  We also find within vendor differences at any selection of the acquisition parameters considered here (field strength, number of gradient directions, b-value and vendor).

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Pre-treatment intra- and inter- voxel magnetic resonance diffusion heterogeneity correlates with chemoradiotherapy treatment outcome of patients with head and neck squamous cell carcinoma
Marianthi-Vasiliki Papoutsaki1, Harbir Singh Sidhu1, Nikolaos Dikaios2, David Atkinson1, Timothy Beale3, Simon Morley3, Martin Forster4, Dawn Carnell5, Ruheena Mendes5, and Shonit Punwani1

1Centre of Medical Imaging, Division of Medicine, University College of London, London, United Kingdom, 2Centre for Vision, Speech and Signal Processing, University of Surrey, London, United Kingdom, 3Department of Radiology, University College Hospital, London, United Kingdom, 4Research Department of Oncology, University College Hospital, London, United Kingdom, 5Radiotherapy Department, University College Hospital, London, United Kingdom

Heterogeneity assessment and diffusion weighted magnetic resonance imaging (DW-MRI) have been considered powerful diagnostic tools in predicting chemoradiotherapy treatment outcome in patients with cancer. In this study, pre-treatment microstructural heterogeneity derived by intra- and inter-voxel MR diffusion rates was assessed in patients with neck squamous cell carcinoma (HNSCC). A correlation was presented between the pre-treatment MR diffusion heterogeneity and the chemoradiotherapy treatment outcome of patients with HNSCC. Future work, to ascertain the mechanisms of these correlations would open the opportunity to tailor therapies to individuals in clinical practice.

3234
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Histological breast cancer stroma patterns correlate with diffusion MR signal
Sara Reis1, Colleen Bailey1, Thomy Mertzanidou1, Bernard Siow2, Eleftheria Panagiotaki1, John H. Hipwell1, Julie Owen3, Patrycja Gazinska3, Sarah E. Pinder3, Daniel C. Alexander1, and David J. Hawkes1

1Centre for Medical Image and Computing, University College London, London, United Kingdom, 2Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom, 3King's College London, London, United Kingdom

We report on the histological analysis of the stroma compartment of two formalin-fixed breast cancer ex-vivo samples that were scanned under a wide range of PGSE acquisitions. Our histological analysis of stroma approach shows that mature regions present higher ADC values compared to immature regions. Mature regions are mainly composed by highly organised fibres, normally following the same direction, which may facilitate directional movement of molecules. This increases the effective tortuosity in the tumour and its interstitial fluid pressure and osmotic pressure, which inhibits water diffusion and subsequently results in a lower ADC value.

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Investigating Diffusion-MRI based neurite density estimation model dependency: an in-vivo study on the HCP dataset
Mauro Zucchelli1, Maxime Descoteaux2, and Gloria Menegaz1

1University Of Verona, Verona, Italy, 2Université De Sherbrooke, Sherbrooke, QC, Canada

Diffusion MRI can be used to estimate the brain tissue neurite density from Multi-Compartment models. This index corresponds to the “stick” compartment volume fraction estimated in every voxel. In this work, we provide evidence that the distribution of stick volume fraction is characteristic of the brain tissue and is highly reproducible between subjects but strongly depends on the underlying multi-compartment model definition. In particular, in-vivo results on 10 subjects of the Human Connectome Project show that the neurite density distribution depends on both the stick parallel diffusivity and the extra-axonal compartment model.

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Time-dependent diffusion modeling using a hollow textile-based Phantom
Sudhir Kumar Pathak1, Vinod Jangir Kumar2, Catherine Fissell 3, Anthony Zuccolotto4, and Walter Schneider5

1Learning Research and Development Center, University Of Pittsburgh, Pittsburgh, PA, United States, 2Biological Cybernetics, Max Planck Institute, Tuebingen, Germany, 3Learning Research and Development center, University of Pittsburgh, Pittsburgh, PA, United States, 4Phantom Metrics division, Psychology Software Tools, Inc, Pittsburgh, PA, United States, 51Learning Research and Development center, University of Pittsburgh, Pittsburgh, PA, United States

A Textile Anisotropic Brain Imaging Phantom incorporating textile water filled hollow fibers (taxons with inner/outer diameter 12/34 micron) is used to examine time-dependent diffusion.  In this study, impermeable hollow tubes (taxons) with 12-micron diameter are used to test the relationship between axial and radial diffusivities with diffusion time (Δ) for a given taxon packing density. An inverse relationship of radial diffusivity with diffusion time (Δ) is established. A constant relationship of axial diffusivity with diffusion time is established. The dependence of these relationships on packing density is then tested and the radial diffusivity relationship is shown to vary with packing density.

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Investigation of Myocardial Fiber Crossings in the Human Heart Using Realistic HARDI Simulation Based on PLI
Lihui WANG1, Feng YANG2, Gabrielle Michalowicz3, Yves Usson3, Pierre-Simon Jouk3, Rongpin Wang4, and Yuemin Zhu5

1Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Compute Science and Technology, Guizhou University, Guiyang, China, 2School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China, 3Laboratoire TIMC-IMAG, UMR5525 CNRS, Université Grenoble Alpes, Grenoble, France, 4Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, China, 5Univ.Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, Lyon, France

We investigate fiber crossings in the myocardium of the human heart using realistic HARDI simulation based on polarized light imaging (PLI). The whole human heart was first imaged using PLI. Based on the fiber orientations measured by PLI, cardiac fiber structures were then modeled, and finally diffusion-weighted images were simulated at different scales using Monte Carlo method and the corresponding ODFs were calculated. The results show that fiber crossings clearly appeared in the myocardium with the increase of scale and that the accuracy of estimating the number of fiber  crossings degraded with variable false positive and/or false negative errors.

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Reliability of Neurite Orientation Dispersion and Density Imaging (NODDI) at 9.4 Tesla
Patrick McCunn1,2, Alex Li1, Peter Zeman1, Kyle Gilbert1, Ali Khan1,2, and Robert Bartha1,2

1CFMM, Robarts Research Institute, London, ON, Canada, 2Medical Biophysics, Western University, London, ON, Canada

Neurite Orientation Dispersion and Density Imaging (NODDI) is a rapidly emerging diffusion MRI (dMRI) technique used to characterize microstructural complexity through the compartmental modelling of neural water fractions into Intra-neurite, Extra-neurite and CSF volume fractions. This project aimed to further the ability of preclinical diffusion imaging through the application of NODDI to a rodent model with the objective to determine its utility, precision and reliability at 9.4 Tesla.

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Test-Retest and Between-Site Reliability in a Multisite Diffusion Tensor Imaging Study
Ikbeom Jang1, Sumra Bari1, Yukai Zou2,3, Nicole L. Vike3,4, Pratik Kashyap1, and Thomas M. Talavage1,2

1Electrical and Computer Engineering, Purdue University, West Lafayette, IN, United States, 2Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States, 3College of Veterinary Medicine, Purdue University, West Lafayette, IN, United States, 4Department of Basic Medical Sciences, Purdue University, West Lafayette, IN, United States

Diffusion tensor imaging (DTI) has been frequently employed in the identification of brain biomarkers for neurodevelopmental and neurodegenerative disorders due to its ability to measure spatial organization of brain tissue. Due to the need for larger sample size to address substantive questions of interest, many studies try to merge data from several scanners, and ideally, a reliability study should come first. In this study, we assess reliability of DTI measures across two systems using the intraclass correlation coefficient, such that we may pool data in future multi-site DTI studies.

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Optimal tissue preparation for ex vivo preclinical imaging
Rachel L. C. Barrett1,2, Diana Cash1, Camilla Simmons1, Tobias Wood1, Anthony C. Vernon3,4, Marco Catani1,2, and Flavio Dell'Acqua2

1Department of Neuroimaging, IOPPN, King's College London, London, United Kingdom, 2Natbrainlab, Department of Forensic and Neurodevelopmental Sciences, IOPPN, King's College London, London, United Kingdom, 3Department of Basic and Clinical Neuroscience, IOPPN, King's College London, London, United Kingdom, 4MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom

Ex vivo imaging is beneficial for studying rodent brain microstructure in healthy and pathological tissue at high resolution. There are challenges however associated with changes in tissue properties resulting from fixation. We present a tissue preparation protocol optimised for diffusion MRI in the rat brain by varying fixative concentration, gadolinium concentration and rehydration time. By altering T1 and T2 relaxivity, we show how these factors can be combined to maximise SNR efficiency. Improving SNR efficiency in ex vivo diffusion MRI will allow higher spatial and angular resolution for studying tissue microstructure in the rodent brain.

3241
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Oscillating gradient spin echo (OGSE) diffusion weighted imaging of the epidermoid cysts: simulation application
Saori Koshino1,2, Akiyuki Sakakibara3, Antoine Choppin3, Christina Andica1, Akifumi Hagiwara1,2, Tomoko Maekawa1,2, Mihiro Takemori1,4, Atsushi Arakawa5, Lydia Chougar1,6, Masaaki Hori1, and Shigeki Aoki1

1Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan, 2Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan, 3LPixel Inc., Tokyo, Japan, 4Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan, 5Department of Human Pathology, Juntendo University School of Medicine, Tokyo, Japan, 6Hôpital Cochin, Paris, France

Diffusion weighted imaging with shorter diffusion time using oscillating gradient spin echo (OGSE) may reveal microstructural features among brain disorders. Here we observed apparent diffusion coefficient (ADC) values in three patients with intracranial epidermoid cysts. ADC values measured by OGSE were higher than those measured by pulsed gradient spin echo (PGSE; used in conventional MRI), indicating restricted diffusion due to spatial restriction. The results of our diffusion simulation based on the pathological feature of epidermoid cysts suggest that spatial restriction of “Rugby Ball” regions formed by keratin layers should mainly affect the extent of restricted diffusion.  

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Correlation of baseline DSI based metrics with clinical motor outcomes at 6 weeks after acute ischemic stroke
Kyler K Hodgson1, Ganesh Adluru2, Lorie Richards3, Jennifer Majersik4, Nagesh Adluru5, and Edward DiBella2

1Bioengineering, University of Utah, Salt Lake City, UT, United States, 2Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States, 3Occupational Therapy, University of Utah, Salt Lake City, UT, United States, 4Neurology, University of Utah, Salt Lake City, UT, United States, 5Waisman Center, University of Wisconsin, Madison, WI, United States

The difference between the baseline ipsilesional and contralesional mean values in the internal capsule from Orientation Dispersion Index and Generalized Fractional Anisotropy correlate strongly with upper extremity clinical outcomes at 6 weeks. These models account for regions of crossing fibers and demonstrate improvements over DTI in using brain microstructure to make clinical judgments. 


Electronic Poster

Brain Morphometry

Exhibition Hall Monday 9:15 - 10:15

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Brain morphometry using diffusion MRI data (DTBM) reveals abnormalities in Down Syndrome that are not detected by conventional DTI analysis.
Carlo Pierpaoli1, Amritha Nayak1, Okan Irfanoglu1, Neda Sadeghi1, and Nancy Raitano-Lee2

1Quantitative Medical Imaging Section, NIBIB, NIH, Bethesda, MD, United States, 2Department of Psychology, Drexel University, Philadelphia, PA, PA, United States

We performed Tensor Brain Morphometry (TBM) as well as conventional FA analysis to compare the brains of subjects with Down Syndrome (DS) to typically developing Healthy Controls (HC). TBM deformation fields were computed from T1 weighted images (T1-TBM), as well as from diffusion data (D-TBM). D-TBM identifies differences between DS and HC brains that would have gone completely undetected by conventional TBSS analysis of FA results. 

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An Automatic Classification of Alzheimer’s Disease Based on Structural MRI Data Compared with Voxel-Based Morphometry Method
Xiangzhu Zeng1, Huishu Yuan1, Yan Liu2, Ling Wang3, Ying Liu1, Zheng Wang1, and Lizhi Xie4

1Department of Radiology, Peking University Third Hospital, Beijing, China, 2University of Chinese Academy of Sciences, Beijing, China, 3University of Electronic Science and Technology of China, Chengdu, China, 4MR Research, GE Healthcare, Beijing, China

In this study, a compartmental sparse feature selection method was used  with feature parameter identified, and compared with classical voxel-based morphometry method (VBM) for classification of Alzheimer ’s disease (AD) from the healthy subjects. Our method had high classification accuracy for AD diagnosis and a strong linear correlation between the extracted feature parameter and volume of hippocampus obtained by VBM.  The feature parameter of hippocampus had a higher linear correlation with mini-mental state examination  (MMSE) score than volume of hippocampus with MMSE. Hence, compartmental sparse feature selection is an effective computer-aided diagnosis method to help clinician identify AD.

3245
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Accuracy of Morphometry Measures from MPRAGE data with Prospective Motion Correction Based on an Optical Tracking System
Joelle E Sarlls1, Francois Lalonde2, J Andrew Derbyshire3, Sean Marrett3, Patrick Hucker4, Maxim Zaitsev4, and S Lalith Talagala1

1NINDS/NMRF, National Institutes of Health, Bethesda, MD, United States, 2NIMH/DNU, National Institutes of Health, Bethesda, MD, United States, 3NIMH/fMRIF, National Institutes of Health, Bethesda, MD, United States, 4MR Development and Application Center, University Medical Center Freiburg, Freiburg, Germany

Subject motion during MRI results in poor image quality and may cause bias in the morphormetric measures extracted from segmentation algorithms. Prospective motion correction (PMC) techniques can mitigate these effects by tracking brain motion and updating the scan parameters in realtime. Here, we compared the accuracy of cortical thickness and volume extracted from MPRAGE data of non-moving and intentionally moving subjects when using a PMC method based on a Moire phase tracking marker and an optical system. Data show that the PMC method used here can greatly reduce image artifacts and provide more accurate segmentation resuIts during intentional motion.

3246
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Brain volumetric and fractional anisotropy differences in mice selected for high and low empathy-like traits
Diana Cash1, Tobias Wood1, Francesca Zoratto2, Simone Macri2, Camilla Simmons1, Eugene Kim1, Steve Williams1, Jeffrey Glennon3, and Giovanni Laviola2

1Neuroimaging, King's College London, London, United Kingdom, 2Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità, Rome, Italy, 3Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, Netherlands

High resolution ex vivo imaging of mice with high and low empathy-like behavior revealed widespread volumetric and fractional anisotropy (FA) changes. Low empathy mice had decreased volumes of the dorsal and ventral hippocampi, periaqueductal grey and the cerebellar cortex, and increased volumes of the olfactory bulb and the hypothalamus compared to high empathy mice. FA was decreased in the low empathy group, specifically in the hippocampus and in the periaqueductal grey. Functional significance can be inferred as these affected brain circuits mediate olfactory cues-based communication of pain, predatory odor fear responses and autonomic stress responses. 


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Multicentric test-retest reproducibility of human hippocampal volumes: FreeSurfer 6.0 longitudinal stream applied to 3D T1, 3D FLAIR and high-resolution 2D T2 structural neuroimaging
Andrea Chiappiniello1, Roberto Tarducci2, Cristina Muscio3, Giovanni B. Frisoni4,5, Maria Grazia Bruzzone6, Marco Bozzali7, Daniela Perani8,9, Pietro Tiraboschi3, Anna Nigri6, Claudia Ambrosi10, Massimo Caulo11,12, Elena Chipi13, Stefano Chiti14, Enrico Fainardi15, Stefania Ferraro6, Cristina Festari4,16, Roberto Gasparotti17, Andrea Ginestroni15, Giovanni Giulietti7, Lorella Mascaro18, Riccardo Navarra11,12, Valentina Nicolosi4, Lucilla Parnetti13, Cristina Rosazza6, Laura Serra7, Fabrizio Tagliavini3,19, and Jorge Jovicich20

1Physics and Geology Department, University of Perugia, Perugia, Italy, 2Medical Physics Department, Santa Maria della Misericordia Hospital, Perugia, Italy, 3Division of Neurology V/Neuropathology, Fondazione IRCCS Istituto Neurologico "Carlo Besta", Milan, Italy, 4Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Fatebenefratelli, Brescia, Italy, 5Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland, 6Fondazione IRCCS Istituto Neurologico "Carlo Besta", Milan, Italy, 7Neuroimaging laboratory, IRCCS Santa Lucia Foundation, Rome, Italy, 8Vita-Salute San Raffaele University, Milan, Italy, 9Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy, 10University of Brescia, Brescia, Italy, 11Department of Neuroscience, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti, Chieti, Italy, 12Institute for Advanced Biomedical Technologies (ITAB), University “G. d’Annunzio” of Chieti, Chieti, Italy, 13Centre for Memory Disturbances, Lab of Clinical Neurochemistry, University of Perugia, Perugia, Italy, 14Department of Health Professions - U.O.c Research and Development, Careggi University Hospital, Florence, Italy, 15Department of Neuroradiology, Careggi University Hospital, Florence, Italy, 16Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy, 17Neuroradiology Unit, University of Brescia, Brescia, Italy, 18Medical Physics Unit, Spedali Civili di Brescia, Brescia, Italy, 19Scientific Direction, Fondazione IRCCS Istituto Neurologico "Carlo Besta", Milan, Italy, 20CIMEC - Center for Mind/Brain Sciences, University of Trento, Trento, Italy

This study evaluates across-session test-retest reproducibility of automatic hippocampus subfields segmentation. A customized acquisition protocol was designed to enhance segmentation reliability in FreeSurfer 6.0 longitudinal analysis stream. Images were processed performing a within-session T1 averaging, using FLAIR images for PIAL surface reconstruction and a high-resolution T2 for the hippocampal subfield segmentation. Results on 12 healthy subjects suggest high reproducibility for different hippocampal subfields and whole hippocampus, generally better than those achievable without T1 averaging and without using FLAIR and high-resolution T2 images.

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Regularized k-means clustering for segmentation of brain tissues using hemodynamic features in DSC-MRI
Jonathan Arvidsson1,2, Oscar Jalnefjord1,2, Fredrik Kahl3, Magnus Båth1,2, and Göran Starck1,2

1Department of Radiation Physics, University of Gothenburg, Gothenburg, Sweden, 2Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden, 3Department of Electical Engineering, Chalmers University of Technology, Gothenburg, Sweden

Inclusion of voxels containing CSF and/or blood vessels can bias ROI statistics used in DSC-MRI analysis. In order to address this problem we propose an automatic method for tissue segmentation based on hemodynamic features obtained from DSC-MRI data. Application of the method in test subjects shows promising results.

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Brain extraction and segmentation framework for bias field rich cranial MRI scans of rats
Jacob Daniel Kirstejn Hansen1, François Lauze1, Sune Darkner1, Kristian Nygaard Mortensen2, Simon Sanggaard2, Helene Benveniste3, and Maiken Nedergaard2,4

1Department of Computer Science, University of Copenhagen, Copenhagen, Denmark, 2Center for Translational Neuromedicine, University of Copenhagen, Copenhagen, Denmark, 3Anesthesiology, Yale School of Medicine, Yale University, New Haven, CT, United States, 4Center for Translational Neuromedicine, University of Rochester, Rochester, NY, United States

This abstract presents a framework to extract brain tissue and internal Cerebrospinal fluid in cranial magnetic resonance imaging of rats with strong bias fields. Desired segments are obtained through bias field correction and several passes of segmentation. A refinement procedure is proposed to remove brain surface CSF. Promising planar and 3D visualizations of results are presented and demonstrate the capabilities of the framework.

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A 3D-printed anatomical multimodal phantom for brain segmentation validation
Anna Altermatt1,2, Francesco Santini1,3, Xeni Deligianni1,3, Stefano Magon2,4, Till Sprenger5, Ludwig Kappos1,4, Philippe Cattin1, Jens Wuerfel1,2, and Laura Gaetano2,4

1Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland, 2Medical Image Analysis Center (MIAC) AG, Basel, Switzerland, 3Department of Radiology, University Hospital of Basel, Basel, Switzerland, 4Department of Neurology, University Hospital of Basel, Basel, Switzerland, 5DKD HELIOS Klinik, Wiesbaden, Germany

Brain tissue segmentation algorithms applied on magnetic resonance imaging (MRI) data lack a ground truth for evaluating their performance. For this purpose, an anatomical brain phantom prototype mimicking T1 relaxation times and the complex 3D geometry of the human brain was created for use with MRI and computed tomography (CT).  A scan-rescan experiment showed a low within-session variability of white matter (WM) and grey matter (GM) volumes when MRI images of the phantom were segmented with a commonly used software. Compared to the ground truth volumes derived from CT, the software overestimated the WM, while the GM was slightly underestimated.

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Multiparametric MRI characterization of microstructural substrate of literacy: Observations from a community cohort of literate and illiterate elderly in India
Kenchaiah Raghavendra1, Alladi Suvarna 1, Jala Sireesha2, Mekala Shailaja 3, and Bapi S Raju4

1Neurology, National Institute of Mental Health and Neurosciences, Bangalore, BANGALORE, India, 2Nizam's Institute of Medical Sciences Hyderabad, Hyderabad, India, 3Nizam's Institute of Medical Sciences, Hyderabad, Hyderabad, India, 4University of Hyderabad, Hyderabad, India

Few studies have evaluated neuroanatomical differences between illiterates and literates and majority have been unimodal investigations. We explore multiparametric, neuroanatomical substrates of literacy by studying grey and white matter microstructural neuroimaging biomarker differences between 61 literate and 15 illiterate elderly subjects with normal cognition. Univariate and multivariate methods for grey matter density, diffusion tensor parameters and cortical/subcortical morphometric measures were employed. Literacy provided an advantage through increase in grey matter density, white matter integrity, cortical thickness, area and volumes in brain areas related to reading, writing, language, Visuospatial and sensorimotor processes. Enhanced white matter integrity was the most discriminating factor on the machine learning.  

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Alterations in Cortical Thickness with Hydroxyurea Therapy in Children Treated for Sickle Cell Anemia
John O Glass1, Kathleen J Helton1, and Wilburn E Reddick1

1Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, TN, United States

Sickle cell anemia is a devastating hematological disease leading to brain injury and neurocognitive deficits. Twenty-five patients (16 Hydroxyurea treated; 9 not) were imaged twice one year apart. Cortical thickness was assessed using FreeSurfer and compared between groups. Treated patients had thicker cortex in frontal and bilateral parietal lobes and in superior temporal and bankssts regions. Preservation of cortex in these regions may have implications for neurocognitive functions supported by associated networks such as central executive, attention and memory networks. These findings should be further evaluated for their impact on neurocognitive performance and Diffusion Tensor Imaging.

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Alterations in cortical thickness and axonal density due to Experimental Autoimmune Encephalomyelitis in the Lewis Rat
J. Keiko McCreary1, Brietta Gerrard1, L. Sorina Truica1, and Gerlinde A.S. Metz1

1Neuroscience, Canadian Centre for Behavioural Neuroscience, Lethbridge, AB, Canada

The animal model of experimental autoimmune encephalomyelitis (EAE) is characterized by inflammatory lesions and demyelination which leads to axonal damage and subsequent neuronal death within the central nervous system. The effect is debilitating, resulting in loss of motor and sensory functions. Here, we investigated changes in cortical thickness using MRI, and axonal density in the corpus callosum using a neuronal tract tracer, biotinylated dextran amine, in Lewis rats induced with EAE. Our study found that EAE leads to a decrease in cortical thickness, particularly in the primary somatosensory trunk region, and axonal density in the corpus callosum.

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In-vivo probabilistic structural atlas of the inferior colliculus, superior colliculus, medial geniculate nucleus, and lateral geniculate nucleus based on 7 Tesla MRI
Christian Strong1, Nicola Toschi2,3, Bruce Rosen2, Lawrence L Wald2, and Marta Bianciardi2

1Department of Neurosurgery, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States, 2Department of Radiology, A.A. Martinos Center for Biomedical Imaging, MGH and Harvard Medical School, Boston, MA, United States, 3Medical Physics Section, Department of Biomedicine and Prevention, Faculty of Medicine, University of Rome “Tor Vergata”, Rome, Italy

Brainstem and thalamic nuclei such as the inferior-colliculus, superior-colliculus, lateral-geniculate-nucleus, and medial-geniculate-nucleus modulate visual/oculo-motor and auditory/auditory-motor functions. Dysfunction of these nuclei is implicated in disease states such as auditory-agnosia, pure-word deafness, eye-movement and visual-field deficits, Parkinson’s hallucinations, and glaucoma. However, a stereotaxic probabilistic atlas of these nuclei in humans does not exist. We used segmentation of 1.1mm-isotropic 7Tesla T2-weighted- and diffusion-fractional-anisotropy-images to generate and validate an in-vivo probabilistic neuroimaging-based structural atlas of these nuclei in stereotaxic-MNI space. We constructed this atlas to aid the localization of these nuclei in conventional images for future research and clinical investigations of visual/auditory functions.


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Dual Fully Convolutional Networks for Multiscale Context based Robust MRI Skull Stripping
Pascal Ceccaldi1, Benjamin Odry1, Boris Mailhe1, and Mariappan Nadar1

1Medical Imaging Technologies, Siemens Healthineers, Princeton, NJ, United States

Brain Segmentation is a standard preprocessing step for neuroimaging applications, but can however be subject to differences in MR acquisition that can lead to added noise, bias field and / or partial volume effect. To address those protocol differences, we therefore present a generic supervised framework, using consecutively two deep learning networks, to produce a fast and accurate brain extraction aimed at being robust across MR protocol variations. While we only trained our network on Human Connectome Project 3T dataset, we can still achieve state-of-the-art results on1.5T cases from LPBA dataset.

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Precision of Manual vs. Automated Corpus Callosum Atrophy Measurements in Multiple Sclerosis
Michael Platten1,2, Katarina Fink1,3, Juha Martola1, and Tobias Granberg1,2

1Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden, 2Department of Radiology, Division of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden, 3Department of Neurology, Karolinska University Hospital, Stockholm, Sweden

Corpus callosum atrophy is a favorable imaging biomarker in MS. Manual measurements of the corpus callosum are considered the best current standard, but their repeatability and reproducibility are uncertain. FreeSurfer is an automatic software that can volumetrically measure the corpus callosum. Using a representative cohort of 9 MS patients, scanned twice with repositioning on 3 different MRI scanners, we compared the manual and automatic measurements of corpus callosum. We found the longitudinal FreeSurfer method to be the most precise method. Thus, we recommend that this method be used in future studies of measuring corpus callosum atrophy in patients with MS. 

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Morphological Correlates of Objective and Subjective Cognitive Control in Healthy Adults
Adam Clemente1, Emma Lawrence1, Phoebe Imms1, Derek K Jones1,2, and Karen Caeyenberghs1

1School of Psychology, Australian Catholic University, Melbourne, Australia, 2School of Psychology, Cardiff University Brain Research Imaging Centre, Cardiff, United Kingdom

There is evidence showing the neural basis of cognitive control utilizing morphological measures of the brain in healthy adults. In the present study, we complement and extend on previous voxel-based morphometry based research by utilizing the more specific brain macrostructure metric of cortical thickness to investigate the differential morphological correlates of objective and subjective cognitive control. Here, we used a rigorous cognitive control test battery implemented on 25 healthy adults. Further research on morphological correlates of objective and subjective cognitive control in healthy populations is necessary to provide baseline data for future clinical populations.

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Hippocampal subfield analysis at 7 tesla in young adults with Down syndrome
Katherine A Koenig1, Sehong Oh1,2, Melissa R Stasko3, Emma Lissmore3, Elizabeth Roth3, Anne Birnbaum3, Thomas Scheidemantel4, Hudson Taylor4, Nancy Roizen4, Stephen Ruedrich4, Mark J Lowe1, and Alberto Costa3

1Imaging Sciences, The Cleveland Clinic, Cleveland, OH, United States, 2Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea, 3Case Western Reserve University, Cleveland, OH, United States, 4University Hospitals, Cleveland, OH, United States

This work uses ultra-high resolution at 7 tesla to assess hippocampal subfield volume in young adults with Down syndrome (DS). As compared to matched controls, individuals with DS show decreases in total hippocampal volume and in select regions, particularly on the left.

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Gray matter alterations in childhood obesity
Gergely Orsi1, Gabor Perlaki1, Gergely Darnai2, Denes Molnar3, Peter Bogner4, and Jozsef Janszky2

1MTA-PTE Clinical Neuroscience MR Research Group, Pecs, Hungary, 2Department of Neurology, University of Pécs, Pecs, Hungary, 3Department of Paediatrics, University of Pécs, Pecs, Hungary, 4Department of Radiology, University of Pécs, Pecs, Hungary

Childhood obesity a is major public health problem. 89 children were selected from a subsample of the I. Family study and investigated the volumes of predefined reward system structures -which are presumed to play crucial roles in body weight regulation- using MR volumetry and voxel-based morphometry. Statistical associations between obesity-related measures and MR based volumetric and morphometric parameters were assessed. Volumes of accumbens and amygdala showed significant positive correlations with obesity, while their gray matter density inversely related to obesity. Our results indicate that obesity is associated with enlarged brain volumes, but decreased gray matter density in the reward system.

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A 3D Convolutional Neural Network for Hippocampal Volume Estimation
Luca Jan Schmidtke1,2,3, Ricardo Corredor-Jerez1,2,3, Jonas Richiardi1,2,3, Bènèdicte Marèchal1,2,3, Alexis Roche1,2,3,4, and Tobias Kober1,2,3

1Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 2Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland, 3Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 4CoVii Ltd, Porto, Portugal

Accurate estimation of hippocampal volume is essential for exploiting its sensitivity to pathological changes caused by Alzheimer’s disease (AD) and other forms of dementia. We built and trained a 3D convolutional neural network for fast and accurate segmentation of the hippocampus in T1-weighted structural MR images of the brain. Compared to two software packages (MorphoBox prototype and FreeSurfer), we achieved good disease classification results based on estimated hippocampal volume in a significantly shorter amount of time.

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Bayesian Convolutional Neural Network Based Nonhuman Primate Brain Extraction in Fully Three-dimensional Context
Gengyan Zhao1, Fang Liu2, Jonathan A. Oler3, Mary E. Meyerand1,4, Ned H. Kalin3, and Rasmus M. Birn1,3

1Department of Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, 2Department of Radiology, University of Wisconsin - Madison, Madison, WI, United States, 3Department of Psychiatry, University of Wisconsin - Madison, Madison, WI, United States, 4Department of Biomedical Engineering, University of Wisconsin - Madison, Madison, WI, United States

Brain extraction of MR images is an essential step in neuroimaging, but current brain extraction methods are often far from satisfactory on nonhuman primates. To overcome this challenge, we propose a fully-automated brain extraction framework combining deep Bayesian convolutional neural network and fully connected three-dimensional conditional random field. It is not only able to perform accurate brain extraction in a fully three-dimensional context, but also capable of generating uncertainty on each prediction. The proposed method outperforms six popular methods on a 100-subject dataset, and a better performance was verified by different metrics and statistical tests (Bonferroni corrected p-values<10-4).

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Cerebrovascular Brain Aging Examined with Arterial Spin Labelling and Applied to Age Prediction
M. Ethan MacDonald1, Nils D. Forkert1, Yuhan Ma2, Rebecca J. Williams1, Alexandru Hanganu1, Hongfu Sun1, Randall Stafford1, Cheryl R. McCreary1, Richard Frayne1, and G. Bruce Pike1

1University of Calgary, Calgary, AB, Canada, 2McGill University, Montreal, QC, Canada

Changes in both cortical thickness and cerebral blood flow are observed with age. In this work, we look at how these parameters are modulated across the lifespan. T1-weighted and arterial spin labelling data from 146 subjects were analyzed, with 68 cortical regions selected in each subject to obtain mean cortical thickness and cerebral blood flow. We calculated rates of change, correlation, and laterality for both parameters. Finally, we explored predictive modeling using cortical thickness, CBF and a model combining the two. Predictive modelling was slightly improved when both measures were included. 

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Evaluation of tumor shape features for overall survival prognosis in glioblastoma multiforme patients
Parita Sanghani1, Ang Beng Ti2, Nicolas Kon Kam King2, and Hongliang Ren1

1Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore, 2Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore

We evaluated 13 shape features of glioblastoma multiforme (GBM) tumor for overall survival (OS) prognosis in 75 patients using univariate and multivariate Cox regression analysis. Age and Karnofsky performance scale were used as covariates for the multivariate analysis. Three shape features were found to be significant for OS prognosis in GBM patients. Kaplan-Merier survival curves were obtained for the significant features to illustrate their effectiveness. In future works, these shape features can be used along with volumetric and texture features derived from the tumor for OS prediction of GBM patients. 

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Investigation of Cerebral Structural Alterations of Patients with Mild Cognitive Impairment based on VBM and DBM Analysis
Zhe Ma1, Zhizheng Zhuo1, Lijiang Wei1, Bin Jing1, Haiyun Li1, and Yingjie Mei2

1Capital Medical University, Beijing, China, 2Clincial Science, Philips Healthcare, Guangzhou, China

Voxel-based morphometry (VBM) and deformation-based morphometry (DBM) are wildly-used automated analysis pipelines for neuro-structural images. This study aims to investigate gray matter abnormalities in mild cognitive impairment (MCI) patients. Some altered brain regions could be detected with VBM and DBM method for MCI patients compared to healthy controls. Besides, the features extracted from VBM and DBM could effectively identify the MCI from healthy controls. 

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Rostro-caudal architecture of the frontal lobes in humans
Michel Thiebaut de Schotten1, Marika Urbanski1, Leonardo Cerliani1, and Emmanuelle Volle1

1BCBlab, Institut du Cerveau et de la Moelle, Paris, France

Functional models of the frontal lobes suggest a rostro-caudal organization that is essential for goal-directed behaviour and cognitive control, in which higher processing-level anterior regions send control signals to lower processing-level posterior regions. Here we show that tractography can divide the frontal lobes into 12 regions organized in a rostro-caudal axis showing a gradient of cortical thickness, myelination and cell body density.

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Volume and surface-based structural analyses in active Crohn’s Disease Patients
Gita Thapaliya1, Sally Eldeghaidy2, Shellie Radford1, Gordon Moran1, and Susan Francis2

1National Institute for Health Research (NIHR) Biomedical Research Centre in Gastrointestinal and Liver disease at Nottingham University Hospitals NHS Trust, Queens Medical Centre Campus, University of Nottingham, Nottingham, United Kingdom, 2Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom

Structural brain changes in Crohn’s Disease (CD) have been studied in remission, however the data is inconsistent and not assessed in the active disease state. Grey matter volume (GMV) and cortical thickness (CT) were measured using VBM and CAT12/FreeSurfer in 25 active CD patients and age-matched healthy controls (HC). CD patients showed reduced CT and GMV in frontal and motor areas. Both CT and GMV were negatively correlated with proinflammatory markers, indicating these changes could be due to chronic inflammatory response. CAT and Freesurfer measures were highly comparable.


Electronic Poster

Functional & Structural Connectivity in the Brain

Exhibition Hall Monday 9:15 - 10:15

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Investigation of the default mode network in awake marmosets
Cirong Liu1, Cecil Chern-Chyi Yen1, Frank Ye2, David Leopold2, and Afonso C. Silva1

1National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States, 2National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States

We investigated the default mode network (DMN) in awake marmosets, by combining both resting-state and task-based fMRI, and by performing diffusion tractography and neuronal tract tracing. We found that dorsolateral (dlPFC) but NOT medial prefrontal cortex (mPFC) is a major region of the marmoset DMN. The dlPFC has direct anatomical connections and strong functional connectivity with the posterior DMN and also exists in macaques and humans, suggesting that it is more evolutionary conservative than the mPFC. However, its functions as a default mode are poorly understood and worth investigation.

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Resting state fMRI “Epilepsy networks”.
Rose Dawn Bharath1, Rajanikant Panda2, Jeetu Raj3, Sanjib Sinha4, Kenchaiah Raghavendra4, Ravindranadh Chowdary Mundlamuri4, Ganne Chaitanya5, Anita Mahadevan6, Arivazhagan Arimappamagan7, Malla Bhaskara Rao7, Kandavel Thennarasu8, Kaushik Majumdar9, Parthasarathy Satishchandra4, and Tapan Gandhi3

1Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India, 2Coma Science Group, Universitè de Liège, Liège, Belgium, 3Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India, 4Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, India, 5Department of Neurology, Thomas Jefferson University, Philadelphia, PA, United States, 6Department of Neuropathology, National Institute of Mental Health and Neurosciences, Bengaluru, India, 7Department of Neurosurgery, National Institute of Mental Health and Neurosciences, Bengaluru, India, 8Department of Biostatistics, National Institute of Mental Health and Neurosciences, Bengaluru, India, 9Systems Science and Informatics Unit, Indian Statistical Institute, Bengaluru, India

Resting state functional MRI (rsfMRI) research typically focuses on few well identified networks though many more networks (15-80) are often visualized, in the course of investigating functional networks. It is customary to discard these networks as they are presumed to have no functional relevance. We used machine learning methods to identify “epilepsy networks” in 45 individuals with TLE using FSL derived 88 independent components. In line with evidence from experimental models, the current results indicates that TLE is associated with disease specific “rsfMRI epilepsy networks” which can be visualised in-vivo at individual subject level.

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Effects of intraocular pressure elevation and oral citicoline treatment on resting state functional connectivity in the visual system
Yolandi van der Merwe1, Matthew C Murphy2, Leon C Ho3, Xiaoling Yang4, Yu Yu5, Ying Chau5, Christopher K Leung6, and Kevin C Chan7

1Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States, 2Department of Radiology, Mayo Clinic, Rochester, MN, United States, 3Department of Electrical Engineering, University of Hong Kong, Hong Kong, Hong Kong, 4Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA, United States, 5Department of Chemical and Biological Engineering, Hong Kong University of Science and Technology, Hong Kong, Hong Kong, 6Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, Hong Kong, 7Department of Radiology, New York University, New York, NY, United States

Glaucoma is a neurodegenerative disease that causes irreversible damage to the visual system. While elevated intraocular pressure (IOP) is a major risk factor, its neurobehavioral effects on the visual system remain unclear. Here we showed that increasing magnitude and duration of IOP elevation resulted in differential effects on the visuomotor behavior and resting-state functional connectivity between visual brain nuclei. In addition, under similar levels of chronic IOP elevation, oral citicoline treatment appeared to ameliorate visual behavioral deficits and functional connectivity decrease in some brain regions. These results suggest new potential mechanistic targets for treatment of glaucoma beyond IOP lowering.

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Construction of an MRI-Based Connectome for the Marmoset Brain: Methods and Initial Results
Cecil Chern-Chyi Yen1, Cirong Liu1, and Afonso C. Silva1

1National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States

The common marmoset, a small New World primate, is an excellent translational animal model due to the similarity between its brain network and humans. However, marmoset’s brain networks are not fully explored because of lacking a large group of resting-state functional MRI (rfMRI) data, like human connectome project. To facilitate collecting rfMRI in awake marmosets across multiple marmoset MRI sites, an MRI protocol was developed and optimized for ultra-high filed small animal MRI. Preliminary results show high data quality and robust detection of brain networks such as default mode network. More data are being acquired and collaboration is desired for the success of marmoset connectome database.

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Disrupted Nodal Organization of brain functional Network in Children with Type I Gaucher Disease
Miao Zhang1, Di Hu1, Shengpei Wang2, Huiying Kang1, and Yun Peng1

1Beijing Children's Hospital, Capital Medical University,National Center for Children's Health, China, Beijing, China, 2State Key Laboratory of Management and Control for ComplexSystems, Institute of Automation, Chinese Academy of Sciences, Beijing, China, Beijing, China

In our study, we utilize graph-based network analysis to investigate the topological properties of resting-state brain functional connectivity in children with type I GD. Sixteen children diagnosed as type I GD and sixteen age- and sex- matched healthy controls were recruited. No alterations were found at global level. Three nodes within the executive control network showed decreased nodal degree or efficiency. Our provide new insight to further understand the neurophysiological change of these patients.

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Altered Topological Properties of Brain Functional Networks in Type I GD Patients During a Near Five-year Follow-up
Di Hu1, Miao Zhang1, Shengpei Wang2, Huiying Kang1, and Yun Peng1

1Beijing Children's Hospital, Capital Medical University,National Center for Children's Health, China, Beijing, China, 2State Key Laboratory of Management and Control for ComplexSystems, Institute of Automation, Chinese Academy of Sciences, Beijing, China, Beijing, China

Our previous had shown altered nodal properties within the executive control network in children with type I GD. This time we further investigate the variation trend of brain topological properties in type I GD patients during a near five-year folloe-up under regular enzyme replacement. Results showed that the efficiency of functional segregation in brain network were increased and more nodes were involved and reorganized. The result may explain the improved mood and global functioning that have previous reported.

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Multimodal study of hyperbaric oxygenation effects on normal human brain metabolism and functional connectivity at 3 Tesla.
Andrei Valerievich Manzhurtsev1,2, Olga Vasiukova3, Dmitry Kupriyanov4, Victoria Sergeeva5, Tolib Akhadov2, Petr Menshchikov2,6, and Natalia Semenova1,2,6

10501, Emanuel Institute of Biochemical Physics of the Russian Academy of Sciences, Moscow, Russian Federation, 2Radiology, Clinical and Research Institute of Emergent Pediatric Surgery and Trauma, Moscow, Russian Federation, 3National Research Nuclear University MEPhI, Moscow, Russian Federation, 4Dmitry Rogachev National Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russian Federation, 5Hyperbaric Oxygen Dept., Clinical and Research Institute of Emergent Pediatric Surgery and Trauma, Moscow, Russian Federation, 6Semenov Institute of Chemical Physics of the Russian Academy of Sciences, Moscow, Russian Federation

This study is aimed to reveal the effects of hyperbaric oxygenation (HBO) on human brain metabolites using 1H and 31P MRS, and functional connectivity using resting-state fMRI. The MRS and rs-fMRI studies were performed twice: before and after one HBO session (p=1.2 atmosphere, 100% O2). The results demonstrate the positive effect of hyperbaric oxygenation on human brain metabolism and functioning.

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Brain structural plasticity associated with emotional processing in postpartum women: A longitudinal voxel-based morphometry study
Kaihua Zhang1,2, Mengxing Wang2, Xueyun Su3, Jilei Zhang2, Junyao Xie1, Haifeng Lu2, Zhong Chen*1, and Xiaoxia Du*2

1Department of Electronic Science, Xiamen University, Xiamen, China, 2Shanghai Key Laboratory of Magnetic Resonance and Department of Physics, School of Physics and Materials Science, East China Normal University, Shanghai, China, 3Department of Special Education, Faculty of Education, East China Normal University, Shanghai, China

Pregnancy constitutes a significant period in women’s lives, after which they often experience numerous physiological and psychological changes. However, structural changes in the brains of postpartum women remain unclear. To investigate these phenomena, we recruited forty-seven postpartum women to participate in a longitudinal magnetic resonance imaging study. Our results first suggest that brain structures in postpartum women show adaptive plasticity, especially regarding alterations in empathy-related regions, including grey matter volume, white matter volume, and cortical thickness, that can facilitate effective adaption and behavioural and emotional adjustments towards nurturing infants.

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Age related changes in topological properties of brain functional network and structural connectivity
Chandan Shah1, Jia Liu2, Peilin Lv2, Huaiqiang Sun2, Yuan Xiao2, Jieke Liu2, Youjin Zhao2, Wenjing Zhang2, Li Yao2, Qiyong Gong2, and Su Lui2

1Radiology, Sichuan University, Chengdu, China, 2Sichuan University, Chengdu, China

Title of the abstract was written. The body of the abstract was within word limits. Acknowledgements were mentioned. one figure was uploaded with figure caption. 

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Resting state functional networks longitudinally correlate with working memory in a transgenic rat model of Alzheimer’s disease
Raúl Tudela1, Emma Muñoz-Moreno2, Xavier López-Gil2, and Guadalupe Soria1,2

1Group of Biomedical Imaging of the University of Barcelona, CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona, Spain, 2Experimental MRI 7T Unit, IDIBAPS, Barcelona, Spain

The TgF344-AD rats represent the most suitable and promising animal model for Alzheimer’s disease (AD) research. Resting-state functional MRI was longitudinally acquired every 3 months in a cohort of transgenic Tg344-AD and control Fisher rats between 5 and 15 months of age, together with cognitive task evaluation. Independent component analysis was applied to rs-fMRI volumes and 10 networks were anatomically identified. Spearman correlation coefficients between functional and cognitive parameters were computed. Our results show that while no differences were observed in the cognitive task between both groups, significant differences were found in the functional networks.

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A meta-analysis of studies using graph theory in traumatic brain injury suggests inconclusive evidence for structural disconnectivity
Phoebe Elizabeth Imms1, Adam Clemente1, Derek K Jones1,2, and Karen Caeyenberghs1

1School of Psychology, Australian Catholic University, Melbourne, Australia, 2School of Psychology, Cardiff University Brain Research Imaging Centre, Cardiff, United Kingdom

The purpose of this meta-analysis is to investigate which graph metrics reliably represent changes to structural connectivity following Traumatic Brain Injury (TBI). Effect sizes were pooled for sixteen different graph metrics, from ten diffusion MRI articles that compared the structural connectome of TBI patients and healthy controls. Interestingly, no metric showed consistent differences across the studies. This analysis indicates that heterogeneity in samples are hindering progress towards clinically relevant disconnectivity biomarkers following brain trauma. 

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Structural and functional connectivity of the ipsilateral or nondecussating dentato-rubro-thalamic tract
Kalen Petersen1, Jacqueline Reid2, Srijata Chakravorti3, Meher Juttukonda4, Giulia Franco1, Paula Trujillo-Diaz1, Adam Stark1, Benoit Dawant3, Manus J. Donahue4, and Daniel O. Claassen1

1Neurology, Vanderbilt University, Nashville, TN, United States, 2Meharry Medical College, Nashville, TN, United States, 3Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 4Radiology, Vanderbilt University, Nashville, TN, United States

The dentato-rubro-thalamic tract (DRTT) is a cerebellar efferent pathway important to normal motor function and neurological disease. While the DRTT is described as a decussating (crossing) pathway, the existence of a nondecussating DRTT was recently demonstrated. We compared thalamic connectivity of decussating and nondecussating DRTT using both structural and functional MRI. Probabilistic tractography indicated that the two pathways contact distinct but partially overlapping sets of thalamic nuclei. These results were reinforced by significant correlations with functional connectivity. We conclude that the decussating and nondecussating DRTT exhibit different connectivity patterns, which suggests participation in divergent neural networks.

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A Preliminary MR g-Ratio–Based Connectome Analysis in Multiple Sclerosis
Koji Kamagata1, Andrew Zalesky2, Kazumasa Yokoyama3, Akifumi Hagiwara4, Kouhei Kamiya4, Maria Angelique Di Biase2, Yuki Takenaka1,5, Christina Andica1, Asami Saito1, Masaaki Hori1, Keigo Shimoji6, Ryusuke Irie1, Akihiko Wada1, Nobutaka Hattori3, and Shigeki Aoki1

1Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan, 2Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, Australia, 3Department of Neurology, Juntendo University Graduate School of Medicine, Tokyo, Japan, 4Department of Radiology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan, 5Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo, Japan, 6Department of Diagnostic Radiology, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system. We propose the use of g-ratio–based connectome for evaluating the network topology of MS since it is reported to be useful in the evaluation of demyelinating lesions in MS. Here, we evaluated the structural connectome of patients with MS, as mapped by MR g-ratio based connectome. The network-based statistic identified a subnetwork of reduced connectivity in patients with MS involving the limbic area. In conclusion, MR g-ratio–based connectome analysis can potentially detect changes in brain topology in MS with high sensitivity.

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Temporal evolution of functional connectivity of the intrinsic networks in mild traumatic brain injury
Zhuonan Wang1, Lijun Bai2, Qiuli Zhang1, Guanghui Bai3, Bo Yin4, Xuan Niu1, Yingxiang Sun1, and Ming Zhang1

1Department of Medical Imaging, First Affiliated Hospital of Xi’an Jiaotong University, XI AN, China, 2The Key Laboratory of Biomedical Information Engineering, Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi’ an Jiaotong University, XIAN, China, 3Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China, 4Neurosurgery, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China

Mild traumatic brain injury (mTBI) often leads to disconnection of the brain intrinsic networks. Our study was to investigate how SN interacts with CEN/DMN can be viewed from the observation of how network connectivity damage affects other networks as a function of time, as well as its impact on cognition and emotion. The results suggests that intrinsic brain networks in mTBI patients showed continued damage from acute to sub-acute phase after injury. Function connectivity of SN interacts with CEN/DMN are especially susceptible in mTBI patients and the damage for inter-network functional disconnection will lead to high level cognitive dysfunction.  

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A preliminary report: Confirmation of the relationship of episodic memory performance and frontoparietal functional connectivity in Multiple Sclerosis
Katherine A Koenig1, Jian Lin1, Daniel Ontaneda2, Kedar Mahajan2, Stephen M Rao3, Sanghoon Kim1, Stephen Jones1, and Mark J Lowe1

1Imaging Sciences, The Cleveland Clinic, Cleveland, OH, United States, 2Neurological Institute, The Cleveland Clinic, Cleveland, OH, United States, 3Schey Center for Cognitive Neuroimaging, The Cleveland Clinic, Cleveland, OH, United States

This work assesses the relationship of resting state fMRI (rs-fMRI) of the dorsal lateral prefrontal cortex to episodic memory in patients with multiple sclerosis (MS). We find that rs-fMRI in the frontoparietal network is related to performance on a verbal episodic memory measure. This finding confirms previous reports and suggests this measure is appropriate to investigate as a potential predictive marker of cognitive decline.

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Diffusion MR Imaging of Structural Connectivity and Therapeutic Potential of Deep Brain Stimulation in Alzheimer’s Disease Model
Ching-Wen Chang1, Yi-Chao Lee2, Ssu-Ju Li1, Ting-Chun Lin1, Yin-Chieh Liu1, You-Yin Chen1, and Yu-Chun Lo2

1Biomedical Engineering, National Yang Ming University, Taipei, Taiwan, 2The Ph.D. Program for Neural Regenerative Medicine, Taipei Medical Univeristy, Taipei, Taiwan

Alzheimer’s disease (AD) is one of the major causes of death that currently cannot be reversed or slowed. Fornix, a major output tract of the hippocampus, has been shown to be a promising target for DBS therapy in AD patients. In this study, triple-transgenic Alzheimer’s mice were used to investigate the changes of white matter integrity and the cognitive functions after the DBS-fornix therapy. We found improvement of the cognition and increased white matter integrity after that DBS-fornix therapy in AD mice. It suggested that the DBS-fornix therapy may be a potential therapeutic intervention of AD.

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Modulation of cortico-subcortical functional connectivity occurs after symptomatic treatment of fatigue in patients with multiple sclerosis
Paola Valsasina1, Bruno Colombo2, Paolo Preziosa1,2, Vittorio Martinelli2, Andrea Falini3, Giancarlo Comi2, Massimo Filippi1,2, and Maria A. Rocca1,2

1Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 2Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 3Department of Neuroradiology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy

In this study, 45 fatigued patients with multiple sclerosis (MS) were randomly assigned to undergo treatment with fampridine, amantadine or placebo and underwent clinical, neuropsychological and 3T resting state (RS) functional MRI at baseline and after four weeks of treatment. We found that treatment with fampridine (and, to a lesser extent, with amantadine) ameliorates fatigue in MS. Concomitant increase of RS functional connectivity (FC) in inferior frontal and parietal cortical regions, and decrease of abnormally high intra-thalamic FC were detected, suggesting an improved regulation of cortico-subcortical functional circuits.

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Relevance of functional connectivity abnormalities to cognitive impairment in neuromyelitis optica spectrum disoders
Paola Valsasina1, Maria A. Rocca1,2, Filippo Savoldi1, Gianna Carla Riccitelli1, Marta Radaelli2, Paolo Preziosa1,2, Giancarlo Comi2, Andrea Falini3, and Massimo Filippi1,2

1Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 2Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 3Department of Neuroradiology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy

In this study, we explored resting state (RS) functional connectivity (FC) abnormalities of the main cognitive networks of patients with neuromyelitis optica spectrum disorders (NMOSD) and their correlation with cognitive impairment (CI). We found increased RS FC in the default mode, salience and working memory networks in cognitively preserved NMOSD, and decreased RS FC in the default mode and working memory networks in CI NMOSD. Increased RS FC seems to contribute to a better cognitive performance, probably reflecting an adaptive mechanism. Conversely, reduced RS FC is likely to be a maladaptive mechanism associated with impaired cognitive functions.

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Longitudinal Evaluation of Post-Surgical Connectivity Changes of the Default Mode Network in Operated Glioma Patients
Domenico Zacà1, Silvio Sarubbo2, Monica Dalla Bona2, Umberto Rozzanigo3, Francesco Corsini2, Giovanna Faraca2, Franco Chioffi2, and Jorge Jovicich1

1Center for Mind/Brain Sciences-University of Trento, Trento, Italy, 2Department of Neurosciences, Division of Neurosurgery, “S. Chiara” Hospital, Trento APSS, Trento, Italy, 3Department of Radiology, “S. Chiara” Hospital, Trento APSS, Trento, Italy

In this study we evaluated the post-surgical changes in functional connectivity of the default mode network (DMN) in 6 operated glioma patients and assessed their relationship with pre-operative brain tumor size, a factor that pre-operatively has been negatively associated to cognitive performance. We found in all but one patient an increase in connectivity (average Z-score) of the DMN following brain tumor surgery. These changes were not associated with brain tumor volume, thus indicating that mechanisms other than reduction of mass effect may drive the post-surgical reorganization of the DMN.

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Short-term Visual Experience Increases Intrinsic Brain Connectivity Within Ventral Visual Pathway
Bingqiang Xu1, Hongmei Wang1, Jiayin Tong1, Xiaoyan Gao1, Chenwang Jin1, and Ming Zhang1

1Department of Medical Imaging, First Affiliated Hospital of Medical College, Xi’an Jiaotong University, Xi'an, China

Medical imaging interpretation fundamentally lies in radiologists’ exceptional visual recognition skill, which enables the identification of pathological regions to render diagnosis1. Such expertise is obtained through training across review hundreds of cases2, facilitated by the plastic changes in the central visual system3. Specifically, ventral visual pathway (VTP) is responsible for visual object recognition, i.e. the fine-grained visual information processing. Visual information processing in the adult human brain is highly malleable with neural processing adapting to incoming information4. The plastic changes in the VTP in response to visual recognition tasks are well studied5. While we propose that the information embedded in the intrinsic brain activity, as revealed in the resting data, is also important6. Therefore, in the current study, we investigate how visual experience, i.e. short-term radiological training, modulates brain activity in the VTP under task-free state in the resting brain using ICA.

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Individual patient-specific quantification of the network effects of lesions and diffuse disconnections with diffusion MRI
Christopher J Steele1,2, Yasser Iturria-Medina3, Pierre-Louis Bazin1,4, Bernhard Sehm1, and Arno Villringer1

1Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada, 3Montreal Neurological Institute, McGill University, Montreal, QC, Canada, 4Spinoza Centre for Neuroimaging. Netherlands Institute for Neuroscience, Amsterdam, Netherlands

Even with its crucial role as the backbone of communication within the brain and susceptibility to damage from diseases such as stroke and multiple sclerosis, the white-matter connectional architecture of the human brain has been largely ignored. To address this, we have developed a whole-brain model for the quantification of white-matter connectional anatomy – the Tractography-based Lesion Assessment Standard (TractLAS) – which provides a complete connectional network description of the human brain. It can be used to quantify the impact of lesions on the connectivity of the brain within individuals, providing clinically useful information for individualised care.

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Normal aging differences in static and dynamic functional connectivity between men and women studied by quantitative data-driven analysis of R-fMRI data
Ninni Persson1 and Tie-Qiang Li2

12Aging Research Center, Karolinska Institute, Stockholm, Sweden, 2Department of Medical Radiation and Nuclear Medicine, Karolinsak University Hospital, Stockholm, Sweden

A growing number of resting-state fMRI (R-fMRI) studies have reported a significant effect of normal aging in resting-state functional connectivity (RFC) of the default mode network (DMN). One of the more intriguing findings is that gender can interact with normal aging effect to influence the RFC changes over lifespan. This adds to our understanding of gender-related cognitive differences and gender-specific nature of aging-related brain disorders. However, the precise interaction effects between sex and age on RFC remain inconclusive. The aim of the study is to quantify the normal aging induced RFC reduction difference between man and women.

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Brain metabolic and connectivity changes associated to the progression of Alzheimer's disease in a transgenic rat model
Emma Muñoz-Moreno1, Rui Vasco Simoes2, Raúl Tudela1,3, and Guadalupe Soria1

1Experimental 7T MRI Unit, Institut d'Investigacions Biòmediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain, 2Champalimaud Foundation, Lisbon, Portugal, 3CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN) Group of Biomedical Imaging of the University of Barcelona, Barcelona, Spain

TgF344-AD is a transgenic rat model of Alzheimer’s disease (AD) that shows all its pathological hallmarks in a progressive way. A cohort of transgenic rats and their control littermates were scanned at different time-points from early adulthood to aged animals, including spectroscopy and diffusion-weighted MRI. Acquisitions were processed to obtain regional structural connectivity parameters and metabolite concentrations in hippocampus and striatum. Decrease in network metrics in both regions at different ages, and increases in glutamine and decreases in glutamate, NAA, NAAt and taurine were observed in the transgenic group. Thus, multimodal MRI can improve characterization of different AD stages.

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A novel method to detect fractional anisotropy differences in short association fibers discriminated by their functional connectivity between Multiple Sclerosis patients and healthy subjects
Cristian Montalba1, Mariana Zurita1,2, Tomas Labbe1,3, Pamela Guevara4, Claudia Carcamo3,5, Juan Pablo Cruz6, Carlos Sing-Long1,7, Marcelo Andia1,6, and Sergio Uribe1,6

1Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, 2Electrical Engieneering, Pontificia Universidad Católica de Chile, Santiago, Chile, 3Interdisciplinary Center of Neurosciences, Pontificia Universidad Católica de Chile, Santiago, Chile, 4Faculty of Engineering, Universidad de Concepción, Chile, Concepción, Chile, 5Neurology Department, Pontificia Universidad Católica de Chile, Santiago, Chile, 6Radiology Department, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile, 7Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile

We propose a novel method to evaluate fractional anisotropy (FA) differences in short association fibers (U-fibers) between patients with relapsing-remittent multiple sclerosis (RRMS) and healthy subjects by classifying each U-fiber in different groups according to their functional connectivity.


Electronic Poster

Neuroimaging at Ultra-High Fields

Exhibition Hall Monday 9:15 - 10:15

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Age-related changes in cortical thickness and R1 values measured at 7T
Koji Fujimoto1, Yuta Urushibata2, Hideto Kuribayashi2, Tobias Kober3,4,5, Tadashi Isa1, and Tomohisa Okada1

1Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan, 2Siemens Healthcare K.K., Tokyo, Japan, 3Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 4Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland, 5Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

Healthy volunteers at the age between 20-30 (N=22) and over 60 (N=8) were scanned using a 7T MRI and a 1ch-Tx/32ch-Rx coil with a MP2RAGE prototype sequence at 0.7mm isotropic resolution. Cerebral cortex was segmented based on the human connectome project pipelines with some modifications to obtain cortical thickness and R1 on the gray-ordinate space. Results showed that the average cortical thickness decreased from 2.58 to 2.34 (9%) between the age groups; average R1 increased from 0.542 to 0.552 (1.9%). R1 change seems to have spatial predominance, with the preference in the frontal area.

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Test-retest reproducibility of cortical thickness, B1+, and R1 in healthy young adults measured at 7T
Koji Fujimoto1, Yuta Urushibata2, Hideto Kuribayashi2, Tobias Kober3,4,5, Tadashi Isa1, and Tomohisa Okada1

1Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan, 2Siemens Healthcare K.K., Tokyo, Japan, 3Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 4Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland, 5Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

Twenty-two healthy volunteers were scanned at 7T using MP2RAGE (R1 mapping) and Sa2RAGE (B1 mapping) sequences. Applying a modified HCP pipeline, within-subject (test-retest) reproducibility and across-subject variability of cortical thickness, B1+, and R1 were analyzed. The mean absolute difference of cortical thickness was larger at the bilateral lower temporal lobes and insula. Intra-subject variation of B1+ was larger in the lower temporal lobe, whereas across-subject variation of B1+ seems to come from reference transmitter amplitude settings. Except for the lower temporal lobes, variation in the cerebral cortex R1 was very small for both intra-subject measurement (1.5%) and across-subject measurement (3%).

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In-Vivo Evaluation of MR Fingerprinting at 7T
Thai Akasaka1,2, Koji Fujimoto3, Martijn A. Cloos4, and Tomohisa Okada3

1Kyoto University Graduate School of Medicine, Kyoto, Japan, 2Osaka Red Cross Hospital, Osaka, Japan, 3Human Brain Research Center, Kyoto Univerisity Graduate School of Medicine, Kyoto, Japan, 4Department of Radiology, New York School of Medicine, Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, New York, NY, United States

At 7T RF wavelength effects create a highly heterogeneous B1+ field, which can lead to contrast artifacts and signal dropouts. Instead of attempting to mitigate the B1+ inhomogeneity, the Plug-and-Play MRF (PnP-MRF) method simultaneously encodes the B1+ produced by multiple transmit channels alongside desired tissue properties (PD,T1,T2) to extract B1+ bias free multi-parametric maps. Although this method was designed for use with multiple transmit-channels, a single transmit channel may suffice if B1+ voids can be avoided. In this work, we evaluate the performance of PnP-MRF for brain imaging at 7T in a single transmit configuration.

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Echo time dependence in temporal frequency shift curves at 3T and 7T
Surabhi Sood1, David C Reutens1, Shrinath Kadmangudi1, Markus Barth1, and Viktor Vegh1

1Centre for Advanced Imaging, Brisbane, Australia

Quantitative susceptibility mapping is an MRI tool for mapping anatomical variations. The region specific echo time dependence of frequency shift curves computed from gradient recalled echo MRI data are likely due to variations in tissue microstructure, arrangement and packing. However, the effect of field strength on frequency shift curves has not been established to date. We investigated how frequency shift curves vary with field strength (3T versus 7T) and assessed how changes in the quantitative susceptibility mapping pipeline change the result. 7T data leads to less variability in frequency shift curves and, non-linear trends are present irrespective of methodological differences.  

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Quantification of venous structures in the hippocampus using segment co-registered 7T susceptibility and structural images: First application to focal temporal lobe epilepsy
Rebecca Emily Feldman1, Alexandru L Rus2, Lara V Marcuse3, John W Rutland1, Madeline C Fields4, Bradley N Delman5, and Priti Balchandani5

1Radiology, Translational and Molecular Imaging Institute, New York, NY, United States, 2Icahn School of Medicine at Mount Sinai, New York, NY, United States, 3Neurology, Mount Sinai Hospital, New York, NY, United States, 4Mount Sinai Hospital, New York, NY, United States, 5Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States

Susceptibility-weighted imaging offers superior contrast between veins and surrounding tissue. Our technique to isolate and quantify vein-like objects on SWI, combined with hippocampal segmentation of T1-weighted images, permits characterization of vascular density in focal temporal lobe epilepsy.  We found difference in vascular density of both epilepsy patients (16%) and controls (30%), with diminished density on the left in both groups. 

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Imaging the perivascular spaces and lenticulostriate arteries at 3T and 7T to provide insight into the pathophysiology of neurodegenerative and neurovascular diseases
Giuseppe Barisano1, Samantha J. Ma2, Danny JJ. Wang2, Yonggang Shi2, Arthur Toga2, and Meng Law1,2

1Radiology, University of Southern California, Los Angeles, CA, United States, 2Stevens Institute of Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, United States

The CSF microcirculation in the brain is not well understood and the role of the perivascular spaces in the clearance of metabolic waste products (including amyloid beta and tau) is still debated. We hypothesize that the increased permeability of the BBB and the resulting passage of blood products into the perivascular spaces may be responsible for the obstruction of CSF-ISF flow. Using a novel T1-weighted 3D Turbo spin-echo with variable flip angles at 3T and 7T, we are able to demonstrate leakage of fibrin from the small lenticulostriate arteries into the perivascular spaces.

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Dissecting white-matter fiber pathways of the marmoset brain using ultra-high-resolution diffusion MRI at 7T and 14T
Cirong Liu1, John Newman2, Cecil Chern-Chyi Yen1, Frank Ye3, David Leopold3, and Afonso C. Silva1

1National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States, 2The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States, 3National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States

The common marmoset has received growing interests in neuroscience. The lissencephalic brain of the marmoset grants it experimental advantages for brain mapping and stimulation, but also brings challenges for dissecting white matter tracts, which is poorly depicted in existing marmoset brain atlases. Here, we collected ultra-high-resolution diffusion MRI datasets at 7T and 14T and performed probabilistic tractography and manual segmentation. The marmoset brain demonstrates a complex multi-layer white matter structure with many regions consist of multiple different fiber pathways. With the ultra-high-resolution data, we will provide the first comprehensive map (atlas) for the white matter of the marmoset brain.

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Age-related neurochemical changes in normal human brain: a proton MR spectroscopy study at 7T
Toru Ishii1, Koji Fujimoto1, Hideto Kuribayashi2, Yuta Urushibata2, Nouha Salibi3, Ravi Teja Seethamraju3, Sinyeob Ahn3, Tadashi Isa1, and Tomohisa Okada1

1Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan, 2Siemens Healthcare K.K., Japan, Tokyo, Japan, 3Siemens Healthcare, Charlestown, MA, United States

The purpose of this study was to quantify changes of neurochemical concentrations in human brain associated with normal aging with greater sensitivity and accuracy using ultra-high field 7T-MRI. 1H magnetic resonance spectra in the posterior cingulate cortex of 54 healthy adults were measured using a stimulated echo acquisition mode (STEAM) sequence with short echo time, and analysed with LCModel. In addition to the expected result of NAA decrease with aging, both Glutamate and GABA showed significant negative correlations with age. The results may provide significant insights in understanding alterations of human brain accompanying the normal aging. 

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Validation of a Radiological Definition for Central Vessel Sign using 7T FLAIR and SWI
Zahra Hosseini1,2, Jacob Matusinec3, David Rudko4, Junmin Liu1, Benjamin YinMing Kwan5, Fateme Salehi5, Manas Sharma5, Marcelo Kremenchutzky6, Ravi Menon1, and Maria Drangova1,2

1Robarts Research Institute, Western University, London, ON, Canada, 2Graduate Program in Biomedical Engineering, Western University, London, ON, Canada, 3Medicine, Western University, London, ON, Canada, 4Department of Neurology/Neurosurgery, McGill University, Montreal, QC, Canada, 5Radiology and Clinical Neurological Sciences, Western University, London, ON, Canada, 6Department of Clinical Neurological Sciences, Western University, London, ON, Canada

A number of recent clinical radiology studies support the central vessel sign (CVS) as a sensitive and specific means of differentiating MS white matter lesions (WML) from non-MS WML. However, these studies have employed varying practices for imaging veins and WMLs. This has led to an inconsistent radiological definition of CVS. Recently, the North American Imaging in Multiple Sclerosis publisheda set of guidelines, which provide grounds for derivation of a more robust radiological definition of CVS. Here we employ these guidelines, together with FLAIR and SWI at high field to arrive at a sensitive and specific radiological definition of CVS.

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Cortical T2* and QSM maps at 7T: test-retest reproducibility, similarity and differences.
Tomohisa Okada1, Koji Fujimoto1, Yuta Urushibata2, Hideto Kuribayashi2, Tobias Kober3,4,5, and Tadashi Isa1

1Human Brain Research Center, Kyoto University, Kyoto, Japan, 2Siemens Healthcare K.K., Tokyo, Japan, 3Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Swaziland, 4Department of Radiology, University Hospital (CHUV), Lausanne, Swaziland, 5LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

R2* and QSM measurement of the cortex is important to investigate human brain pathology. The 7T-MRI has a large potential to provide high-resolution information; however, measurement reliability has not been much investigated. This study investigated test-retest measurement reliability of cortical R2* and QSM values in 16 healthy subjects. High-resolution 3D multi-echo GRE imaging values were mapped onto the cortical surface extracted using 3D MP2RAGE images. Average maps show similar results for both R2* and QSM with larger variance at the frontotemporal base. Except these areas, measurement of cortical R2* and QSM values were found to be reliable at 7T.

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Localizing nociresponsive region within area 3a in human cortex using fMRI at 7T
Rosa M Sanchez Panchuelo1, Sally Eldeghaidy1, Francis McGlone2, Oleg Favorov3, and Susan Francis1

1Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom, 2Liverpool John Moores University, Liverpool, United Kingdom, 3University of North Carolina at Chapel Hill, Chapel Hill, NC, United States

A component of Brodmann area 3a has been shown to be highly responsive to thermonoxious skin stimulation in monkey studies. Here, we use BOLD fMRI at 7T to map on a fine scale the functional representation of a noxious heat stimulus in human primary somatosensory cortex (S1), and compare this to the hand representation identified from vibrotactile stimulation. Thermonoxious stimulation of both the palm and digits evoked a spatially distinct activation within S1, which extends beyond and partially overlaps with the anterior area responding to vibrotactile activation, consistent with the location of nociresponsive area 3a in monkeys. 

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Spinal Cord Gray Matter Myeloarchitecture Revealed by 7T Magnetization Transfer Imaging
Alan C Seifert1,2,3, Joo-won Kim1,2,3, and Junqian Xu1,2,3,4

1Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 2Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 3Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 4Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States

The human spinal cord gray matter contains multiple nuclei and laminae, which are not usually distinguishable in MRI at conventional field strengths.  The higher signal-to-noise ratio achievable at 7T provides the increased spatial resolution necessary to resolve these very small gray matter features.  Using a wrap-around brainstem/cervical spinal cord RF coil at 7T and a magnetization transfer-prepared multi-echo gradient echo pulse sequence, we resolved three differentially myelinated dorsal horn gray matter structures: the dorsolateral fasciculus, substantia gelatinosa, and nucleus proprius in a single subject at 150-µm in-plane resolution.

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Probing Activated Regions in Rat’s Olfactory System by Odor Stimulations through Manganese Enhanced MRI (MEMRI) at 7T
Bin Zhang1, Qunchen Yuan1, Zhen Qin1, Liujing Zhuang1, Ping Wang1,2, and Xiaotong Zhang1,2

1Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, 2Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China

In vivo bioelectronic nose utilizes mammalian olfactory system as a means of odor detection and discrimination. However, electrode localization during implantation relies on the researcher’s experiences, resulting in an unreliable success rate. The goal of this research is to determine the optimal electrode implantation positions for electrophysiological recordings by using the technique of manganese enhanced MRI (MEMRI) at 7T. A small dose of manganese ion was delivered into the rat’s right naris and an odor was delivered to its nose during MRI scanning. With the MRI data, the region activated by the specific odor can be identified in the OB.

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Concurrent changes in cerebral temperature, lactate and vasomotion in urethane anesthetized rats. Proton magnetic resonance study at 7T.
Devashish Das1,2, Aneurin James Kennerley1, Ben Babourina Brooks3, Samuel Harris1, Luke Boorman1, Paolo DiCarlo1, Christopher CJ Martin1, and Jason Berwick1

1Psychology, Sheffield University, Sheffield, United Kingdom, 2Biological Sciences, Sheffield University, Sheffield, United Kingdom, 3School of Cancer Sciences, University of Birmingham, Birmingham, United Kingdom

Cerebral vasomotion is frequently observed phenomenon that  accompanies hypotension (mean arterial blood pressure (MABP) 45-65mmHg) in anesthetised rat models(1,2). Although unclear, this mechanism appears to play, in part, a compensatory role in replenishing oxygen reserves in the anaerobic/hypoxic brain. Although the relationship between temperature and metabolism is always interactive. Brain cell metabolism is a major determinant of brain temperature, minor changes in brain temperature can result in significant changes in neural cell metabolism and therefore in brain function. During hypotension (MABP 45-65mmHg) analysis of  acquired 1H-spectra revealed thalamic temperature to be ~1.5-2 °C colder than that of the core body temperature (37±0.5)°C. Further analysis of the 1H-spectra revealed dynamic pool of the lactate in the thalamus during hypotension (MABP 45-65mmHg).

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Ultrafast 7T EEG-fMRI for epilepsy using 3D paradigm-free models
Stephen Jones1, Balu Krishnan2, Anna Crawford1, Wanyong Shin1, Sehong Oh1, Imad Najm2, César Caballero-Gaudes3, and Mark Lowe1

1Imaging Institute, Cleveland Clinic Foundation, Cleveland, OH, United States, 2Neurologic Institute, Cleveland Clinic Foundation, Cleveland, OH, United States, 33Basque Center of Cognition, Brain and Language, San Sabastian, Spain

There is enormous benefit for non-invasive MRI techniques guiding neurosurgeons to resect tissue causing epilepsy. We extend traditional EEG-fMRI methods in 3 ways: apply 7T to increase BOLD signal; use increased temporal resolution (TR 300ms) from multiband techniques to separate primary from secondary epileptogenic zones; and use paradigm-free mapping to identify interictal spikes obtained during long scans. We test this methodology using isolated finger taps as a surrogate for epileptogenic spikes. Close correspondence between conventional event analysis and paradigm free mapping suggests epileptogenic spikes can be reliably detected if their HRF is similar to a single finger tap.

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Evaluation of Diffusion-Weighted Imaging of the Macaque Brains Using Readout-Segmented EPI at 7T
Pinyi Wang1,2, Jialu Zhang1,2,3, Meizhen Qian1,4, Yi Sun5, Dingxin Wang3, and Xiaotong Zhang1,2,6

1Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China, 2College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, 3Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, 4School of Medicine, Zhejiang University, Hangzhou, China, 5MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China, 6Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China

Diffusion-weighted imaging (DWI) is an important tool for clinical diagnosis and neuroscience research. To evaluate DWI with higher spatial resolution and with reduced image distortion at higher field strengths, we conducted macaque brain imaging at 7T. Our results suggest that readout-segmented EPI (rsEPI) has reduced image distortion, high MR signal and image contrast. It is believed that the rsEPI can effectively benefit DWI for macaque brain researches at 7T.

3307
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In vivo characterization of cerebellar microglia activation in multiple sclerosis by combined 11C-PBR28 MR-PET and 7 Tesla MRI.
Valeria Teresa Barletta1,2, Elena Herranz1,2, Constantina Andrada Treaba1,2, Russell Ouellette1, Marco Loggia1,2, Ambica Mehndiratta1, Eric Klawiter2,3, Jacob Sloane2,4, and Caterina Mainero1,2

1Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Neurology, Massachusetts General Hospital, Boston, MA, United States, 4Neurology, Beth Israel Deaconess Medical Center, Boston, MA, United States

We assessed microglia activation in the cerebellum and its relationship to clinical parameters in 27 subjects with multiple sclerosis (MS) and 18 healthy controls by using integrated 3 Tesla magnetic resonance-positron emission tomography imaging with 11C-PBR28. 

The MS cohort showed increased cerebellar microglia activation in both lesioned and normal appearing cerebellum. The highest microglia activation was found in lesions, mainly concentrated in the cerebellar white matter in relapsing remitting patients, and extensively involving the cortical grey matter in progressive patients. In MS, the tracer uptake in the cerebellar white matter correlated with neurological disability and impaired cognitive performance.


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Comparison between 3D white-matter-suppressed MPRAGE and 3D SPACE FLAIR in the 7T MR imaging of tuberous sclerosis complex
Kaibao Sun1,2, Jianfei Cui3, Bo Wang1, Zhongwei Chen1, Yan Zhuo1,2, Rong Xue1,2, Shuli Liang3, and Lin Chen1,2

1State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China, 2University of Chinese Academy of Sciences, Beijing, China, 3Chinese PLA general hospital, Beijing, China

Tuberous sclerosis complex (TSC) is a multisystem, autosomal dominant disorder, which was characterized by tubers at the interface of gray and white matters. The 3D SPACE FLAIR sequence has previously been applied to detect the TSC lesions at 7T. The major limitations are its insensitivity to subtle lesions and long acquisition time. 3D white matter suppressed (WMS) MPRAGE was proposed in this study. T1-weighted 3D WMS MPRAGE suppressed the normal white matter signal selectively and made the lesions stand out. In comparison with 3D SPACE FLAIR, 3D WMS MPRAGE could detect more subtle tubers and details within reasonable time.

3309
Computer 115
MR spectroscopy of mouse spinal cord injury at 9.4 Tesla
Abdullah Ali Asiri1,2, Gary Cowin1, Marc Ruitenberg3, and Nyoman Kurniawan1

1Centre for Advanced Imaging, University of Queensland, Brisbane, Australia, 2Najran University, Najran, Saudi Arabia, 3School of Biomedical sciences, The University of Queensland, Brisbane, Australia

This study aims to measure metabolic changes in the acute and chronic stages of a mouse model of spinal cord injury (SCI) using MR spectroscopy. Animal groups consisted of sham, SCI, and SCI with an intravenous immunoglobulin (IVIG) treatment. This study showed that the NAA/Cho ratio can be used as a sensitive marker for chronic injury and testing the efficacy of IVIG to promote recovery. 

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MRI of whole brain formalin-fixed samples at 9.4T: influence of the fixation agent and its dielectric properties on image quality
Gisela E Hagberg1,2, Thomas Shiozawa-Bayer3, Christian Mirkes2, Jörn Engelmann2, Jonas Bause2, Bernhard Hirt3, and Klaus Scheffler1,2

1Biomedical Magnetic Resonnce, University Hospital Tübingen, Tübingen, Germany, 2High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 3Institute of Clinical Anatomy, University Hospital Tübingen, Tübingen, Germany

MRI of post mortem samples in formalin is an essential tool for validation purposes and comparison with clinical histology, since fixation preserve several microstructural tissue features. We found that the dielectric properties of the fixative influences image quality attained in whole brain post mortem samples at 9.4T. The standard fixative prevented high quality MRI across the entire sample. By using a high conductivity fixative with less field focussing, a more homogeneous excitation was achieved without any drop outs and T1 mapping could be performed using rapid inversion recovery techniques.

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High-resolution neurite orientation dispersion and density imaging of mouse brain using compressed sensing at 9.4T
Nian Wang1, Jieying Zhang2, Gary Cofer1, Robert J. Anderson1, Yi Qi1, and G. Allan Johnson1

1Center for In Vivo Microscopy, Department of Radiology, Duke University, Durham, NC, United States, 2Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China

To evaluate the potentials of compressed sensing (CS) in quantification of neurite orientation dispersion and density imaging (NODDI) index of ex vivo mouse brain at high resolution (45 µm3 isotropic). We were able to achieve compression factors of 4X through judicious choice of k-space sampling pattern. The strong heterogeneous microstructure of corpus callosum (CC) regions were illustrated using different diffusion metrics and NODDI index. 

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Comparison of high resolution ex vivo multi gradient echo sequences at 7T and 11.7T for amyloid load quantification in an Alzheimer's disease mouse model
Matthieu Gerstenmayer1, Francoise Geffroy1, Sébastien Mériaux1, and Benoit Larrat1

1CEA Saclay, Gis sur Yvette, France

The gold standard to quantify amyloid load in animal models of Alzheimer’s disease is histology. Despite being really reliable, this technique is destructive and still mainly 2D. Here we optimized a full 3D ex vivo protocol to image whole brain of Alzheimer’s disease mouse model. A high resolution Multi Gradient Echo sequence evidences the shortening of T2* caused by the iron content of amyloid plaques. Plaque detection capabilities were compared between 7T and 11.7T acquisitions for similar scan duration. Unlike the 7T protocol, the 11.7T setup clearly allows amyloid plaque detection and quantification.

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Resting state, gluCEST and anatomical MRI approaches at 11.7T for brain aging studies in a non-human primate
Clément Garin1, Nachiket Abhay Nadkarni1, Salma Bougacha1,2, Jeremy Pepin1, Julien Flament1, Jean-Luc Picq1,3, and Marc Dhenain1

1Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), Fontenay-aux-Roses, France, Fontenay aux roses, France, 23U1077, INSERM, Caen, France, 3Laboratoire de psychopathologie et de neuropsychologie, University of Paris 8, Paris, France

The gray mouse lemur (Microcebus murinus) is a small non-human primate with rapid maturity. This study focuses on the development of non-invasive MRI tools applied to neurodegenerative processes. We performed three different types of analysis: anatomical volumetric measures, neuronal network assessment with resting-state fMRI and brain glutamate distribution with gluCEST imaging. We found anatomical atrophy and functional deficiency mostly in cortical regions. To our knowledge, this study is the first to characterize the functional and anatomical brain aging process in a non-human primate. Furthermore, the mouse lemur functional and gluCEST maps have never been described before.

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Fluorine-19 Magnetic Resonance at 21.1 Tesla to Detect Brain Inflammation
Sonia Waiczies1, Jens T. Rosenberg2, Christian Prinz1, Ludger Starke1, Jason M. Millward1, Paula Ramos Delgado1, Andreas Pohlmann1, Andre Kuehne3, Helmar Waiczies3, and Thoralf Niendorf1,4

1Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrueck Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany, 2The National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, United States, 3MRI TOOLs GmbH, Berlin, Germany, 4Experimental and Clinical Research Center (ECRC), a joint cooperation between the Charité Medical Faculty and the Max Delbrueck Center, Berlin, Germany

Detection of brain inflammation by fluorine-19 (19F) MRI was studied for the first time at 21.1 T (NHMFL, Tallahassee, FL). Studies on phantoms showed an SNR gain of 2.1 at 21.1 T, when compared to 9.4 T. A dependency between 19F-MR relaxation and magnetic field strength (B0) was demonstrated. A T1 reduction and higher SNR per unit time counterbalanced the T2 shortening-induced loss in 19F MR signal when performing high spatially-resolved MRI of post mortem experimental autoimmune encephalomyelitis (EAE) mouse samples at 21.1 T. 19F-signals, not seen at 9.4 T, were revealed in both mouse brain and draining lymph nodes. 


Electronic Poster

Cardiac Function & Myocardial Perfusion

Exhibition Hall Monday 13:45 - 14:45

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Temporal changes in cardiac contractility, perfusion and infarct size after human cardiomyocyte transplantation to the infarcted heart of non-human primates.
Anna V Naumova1,2,3, William S Kerwin1, Yen-Wen Liu2,3,4,5, Billy Chen2,3,6, Xiulan Yang2,3,5, Hiroshi Tsuchida 2,3,5, R. Scott Thies2,3,5, and Charles E Murry2,3,5,6

1Radiology, University of Washington, Seattle, WA, United States, 2Center for Cardiovascular Biology, University of Washington, Seattle, WA, United States, 3Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, United States, 4Department of Internal Medicine, National Cheng Kung University, Tainan, Taiwan, 5Pathology, University of Washington, Seattle, WA, United States, 6Medicine/Cardiology, University of Washington, Seattle, WA, United States

This study demonstrates structural and functional benefits of human embryonic stem cell derived cardiomyocyte engraftment to the infarcted heart of nonhuman primates. Those benefits were manifested in improved global and regional left ventricle contractile function, improved myocardial perfusion, decrease in infarct size and partial regeneration of the scarred myocardium. The benefit from human cardiomyocyte therapy was durable with the potential for further improvement in function between 1 and 3 months. The functional recovery was larger than were observed previously on small animal models of myocardial infarction, which might be due to the greater physiological match between human and macaque species. 

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Feasibility of Multi-Thin-Slab Whole-Heart 3D Cine with Isotropic Resolution and High Contrast in Free Breathing
Peng Lai1, Haonan Wang2, Anja C.S Brau1, and Martin A Janich3

1Global MR Applications and Workflow, GE Healthcare, Menlo Park, CA, United States, 2Global MR Applications and Workflow, GE Healthcare, Waukesha, WI, United States, 3Global MR Applications and Workflow, GE Healthcare, Munich, Germany

Conventional 2D cine is hindered by its needs of repeated breathhold and imaging at each individual view, while breathheld 3D cine suffers from limited slice coverage and resolution. This work developed a new 3D cine sequence with free-breathing capability for whole-heart coverage and isotropic resolution and multi-thin-slab acquisition for high blood-to-myocardium contrast. 

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Evaluation of geometric models for estimating left ventricular (LV) mass in 980 children using cardiac cine magnetic resonance imaging
Jiming Zhang1, Carlo Uribe2, Benjamin Cheong1,2, Paolo Angelini2, and Raja Muthupillai1

1Diagnostic and Interventional Radiology, Baylor St Luke's Medical Center, Houston, TX, United States, 2Texas heart institute, Houston, TX, United States

LV mass computed from commonly used  bi-plane and tri-plane ellipsoidal models can deviate significantly when compared to LV mass estimated from a stack of short axis balanced SSFP cine MR images.  The results from the study show that by using different geometric assumptions for the shape of the endocardium (Cut-cone+cone) and epicardium (Cut-cone+parabola), it is possible to estimate LV mass with just two projections that is comparable to that obtained from a full stack of short axis slices. 

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Tissue Phase Mapping for Assessment of Biventricular Myocardial Motion in Pediatric Patients with Repaired Tetralogy of Fallot
Alexander Ruh1, Arleen Li2, Michael J Rose3, Haben Berhane3, Joshua D Robinson1,4,5, Michael Markl1,6, and Cynthia K Rigsby1,3,5

1Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States, 2Feinberg School of Medicine, Northwestern University, Chicago, IL, United States, 3Department of Medical Imaging, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, United States, 4Department of Pediatrics, Division of Pediatric Cardiology, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, United States, 5Department of Pediatrics, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States, 6Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Chicago, IL, United States

The purpose of this study was to assess regional biventricular myocardial function in pediatric patients with repaired tetralogy of Fallot (TOF) by tissue phase mapping (TPM). Segmental left (LV) and right ventricular (RV) peak velocities were calculated in systole and diastole based on an extended AHA 16+10-segment model. Inter-ventricular dyssynchrony was quantified from the correlation between global LV and RV radial, long-axis and circumferential velocity time courses. Compared to age-matched healthy controls, TOF patients exhibited reduced long-axis peak velocities in systole and diastole as well as increased inter-ventricular dyssynchrony for radial and circumferential myocardial motion.

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Volumetric Measurements with Real-Time Imaging for Cardiac Stress MRI
Shams Rashid1, Yang Cheng1, William Schapiro1, Kathleen Gliganic1, Ann-Marie Yamashita1, Marie Grgas1, Michelle Maragh1, Jie Jane Cao1,2, and Yu Yulee Li1,3

1Cardiac Imaging, St. Francis Hospital DeMatteis Center for Research and Education, Greenvale, NY, United States, 2Medicine, Stony Brook University (SUNY), Stony Brook, NY, United States, 3Radiology, Stony Brook University (SUNY), Stony Brook, NY, United States

Cardiac stress MRI is a valuable diagnostic tool for heart disease. However, volumetric measurements are challenging because stress introduces rapid heartbeats and body movements. Real-time MRI is advantageous for this application due to its robustness to motion and ability for ungated imaging during free breathing. Here, we demonstrate an undersampled radial balanced steady state free precession (bSSFP) sequence to acquire real-time cine images at high spatial (1.7 mm) and temporal (40 ms) resolutions, applied in cardiac stress MRI. We show that, compared to standard breath-held bSSFP cine MRI, our technique provides more robust and reliable volumetric measurements.

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Global left ventricular myocardial deformation measures by CMR tissue tracking in isolated diastolic dysfunction (DD) spontaneous T2DM rhesus monkeys: comparison with tagging
Tong Zhu1, Li Gong2, Yushu Chen1, Yu Zhang1, Wen Zeng2, Jie Zheng3, and Fabao Gao1,2

1Department of Radiology, Sichuan University, Chengdu, China, 2Sichuan Primed Biotech Group Co., LTD, Chengdu, China, 3Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States

In this study, the myocardial deformation characteristics of early diabetic cardiomyopathy were evaluated by using CMR strain imaging in a spontaneous non-human primate T2DM disease model. We found the early cardiac dysfunction characteristics of diabetic cardiomyopathy, and verified the effectiveness of CMR-tissue tracking in its early diagnosis.

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Whole heart First-pass spiral perfusion imaging with 1.25mm resolution at 3T
Yang Yang1, Christopher M Kramer1,2, and Michael Salerno1,2,3

1Medicine, University of Virginia, Charlottesville, VA, United States, 2Radiology, University of Virginia, Charlottesville, VA, United States, 3Biomedical Engineering, University of Virginia, Charlottesville, VA, United States

First-pass contrast-enhanced myocardial perfusion imaging is a useful noninvasive tool to evaluate patients with coronary artery disease, but current techniques are still limited in spatial-temporal resolution, and ventricular coverage which reduces the sensitivity to detect perfusion differences between the endocardium and epicardium and quantify ischemic burden. Outer-volume suppression (OVS) can achieve good signal suppression around the heart, but may have SAR limitations at 3T. In this study, we designed a spiral pulse sequence with slice-interleaved or simultaneous multi-slice (SMS) acquisition without OVS to achieve comparable high quality ultra-high 1.25mm resolution perfusion imaging. The sequences were tested in heathy volunteers and demonstrated high image quality.

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Impact of native T1 on pixel-wise myocardial blood flow quantification
Corina Kräuter1,2, Ursula Reiter1, Clemens Reiter1, Albrecht Schmidt3, Michael Fuchsjäger1, Rudolf Stollberger2, and Gert Reiter4

1Department of Radiology, Medical University of Graz, Graz, Austria, 2Institute of Medical Engineering, Graz University of Technology, Graz, Austria, 3Department of Internal Medicine, Medical University of Graz, Graz, Austria, 4Research and Development, Siemens Healthineers, Graz, Austria

Native myocardial T1 varies between subjects and between segments, yet its impact on pixel-wise quantification of myocardial blood flow (MBF) has not been studied. 15 patients with coronary heart disease underwent 3T cardiac magnetic resonance native myocardial T1 mapping and perfusion imaging at rest. Nonlinearity correction for MBF calculation was performed employing literature native T1 values and patient-specific global as well as local native T1, respectively. Since reference T1 revealed substantial individual MBF errors and application of patient-specific global T1 overestimated MBF in perfusion deficit regions compared to local T1, patient-specific local native T1 should be employed for MBF quantification.

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Accelerated Cardiac Perfusion MRI with Radial k-space Sampling, Compressed Sensing, and KWIC filtering to Enable Qualitative and Quantitative Analyses of Perfusion.
Nivedita K. Naresh1, Hassan Haji-Valizadeh2, Ali M. Serhal1, Pascale J. Aouad1, Daniel C. Lee1,3, and Daniel Kim1

1Radiology, Northwestern University, Chicago, IL, United States, 2Biomedical Engineering, Northwestern University, Chicago, IL, United States, 3Cardiology, Northwestern University, Chicago, IL, United States

First-pass cardiac perfusion MRI is widely used as an important diagnostic tool for cardiovascular disease and extensive efforts are focused on improving spatial coverage, minimizing dark rim artifacts and quantifying absolute myocardial blood flow. In this study, we used a combination of radial k-space sampling, compressed sensing, and KWIC filtering to address these issues. Compared to the conventional perfusion technique, the accelerated method improved spatial coverage, minimized dark rim artifact and enabled quantification of myocardial blood flow.

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Low-Rank plus Sparse Matrix Decomposition for Accelerated Radial MS-CAIPIRINHA in First-Pass Myocardial Perfusion Imaging
Tobias Wech1,2, Julius Heidenreich1,2, Daniel Gensler2,3, Tim Salinger2,3, Peter Nordbeck2,3, Daniel Stäb4, Peter Speier5, Thorsten Alexander Bley1, and Herbert Köstler1,2

1Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany, 2Comprehensive Heart Failure Centre, University Hospital Würzburg, Würzburg, Germany, 3Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany, 4The Centre for Advanced Imaging, The University of Queensland, Brisbane, Germany, 5Magnetic Resonance, Siemens Healthcare GmbH, Erlangen, Germany

The anatomical coverage in first-pass myocardial perfusion imaging was extended by applying undersampled radial MS-CAIPIRINHA and a model-based reconstruction exploiting low-rank plus sparse matrix decomposition.  The technique was tested in a patient with acute left ventricular myocardial infarction, yielding six short-axis slices from base to apex with a temporal resolution of one heartbeat. The reconstructed images exhibited a quality which is comparable to the conventional approach of acquiring only three slices per RR interval.

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Comparison of Dual- and Tri-band Excitation for MS-CAIPIRINHA-accelerated First-Pass Myocardial Perfusion Imaging
Tobias Wech1,2, Tina Urbanek1,3, Andreas Max Weng1, Daniel Stäb4, Peter Speier5, Thorsten Alexander Bley1, and Herbert Köstler1,2

1Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany, 2Comprehensive Heart Failure Centre, University Hospital Würzburg, Würzburg, Germany, 3Fakultät Ingenieurwissenschaften, Hochschule für Technik und Wirtschaft des Saarlandes, Saarbrücken, Germany, 4The Centre for Advanced Imaging, The University of Queensland, Brisbane, Germany, 5Magnetic Resonance, Siemens Healthcare GmbH, Erlangen, Germany

MS-CAIPIRINHA is a valuable technique to extend the anatomical coverage in myocardial first-pass perfusion imaging. In our previous studies, dual-band excitation was applied in conjunction with three SR-prepared acquisition blocks per RR interval to obtain six 2D-slices with a temporal resolution of one heartbeat. Especially in obese patients, however, the SNR occasionally turned out to be marginal, ultimately complicating the assessment of perfusion defects. In this work, an according approach using tri-band RF excitation was tested with respect to potential SNR benefits.

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Radial-CAIPI myocardial first-pass perfusion for high spatiotemporal resolution “iso-phase” multi-slice imaging at multiple cardiac phases per cycle
Merlin J Fair1,2, Peter D Gatehouse1,2, Ricardo Wage2, Aleksandra Radjenovic3, and David N Firmin1,2

1NHLI, Imperial College London, London, United Kingdom, 2CRC, Royal Brompton Hospital, London, United Kingdom, 3BHF Glasgow CRC, University of Glasgow, Glasgow, United Kingdom

A high-resolution myocardial perfusion sequence is implemented with radial-CAIPI to allow simultaneous acquisition of the conventional three myocardial slices, all at identical cardiac phase, which can be repeated for multiple phases of the cardiac cycle and throughout the first-pass. The synchronised cardiac phases and repeat acquisitions aim to enable improved specificity, through better artifact identification.

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Dynamic contrast-enhanced and phase contrast MRI of a novel 3D printed cardiac phantom mimicking transmural myocardial perfusion gradients
Xenios Milidonis1, Muhummad Sohaib Nazir1, Myles Capstick2, Sita Drost3, Gertjan Kok4, Nikola Pelevic4, Christian Poelma3, Tobias Schaeffter5, and Amedeo Chiribiri1

1School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2ZMT Zurich MedTech AG, Zurich, Switzerland, 3Laboratory for Aero- and Hydrodynamics, Technische Universiteit Delft, Delft, Netherlands, 4VSL B.V., Delft, Netherlands, 5Physikalisch-Technische Bundesanstalt, Berlin, Germany

In recognition of the lack of a physical standard for the assessment and validation of myocardial perfusion imaging methodologies, a phantom simulating first-pass perfusion has recently been developed. This study builds on this work by introducing a novel 3D printed myocardial compartment with a radial variation in flow that mimics physiological transmural perfusion gradients. Velocity and perfusion rate estimates using phase contrast and dynamic contrast-enhanced MRI of the myocardium, respectively, were found to be repeatable. The myocardium shows potential in multi-modality evaluation and validation of perfusion pulse sequences and quantification algorithms before their introduction into routine clinical use.

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MRI-derived myocardial strain in patients with mild cognitive impairment (MCI)
Heng Ma1, Jun Yang1, Haizhu Xie1, Fang Wang1, Xiao Xu1, Wei Bai1, Jing Liu1, James C. Carr2, and Kai Lin2

1Radiology, Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, China, 2Radiology, Northwestern University, Chicago, IL, United States

Our data show that patients with mild cognitive impairment (MCI) have a lower regional peak myocardial strain and peak systolic strain rate at left ventricle (LV) as compared with healthy controls. Patients with MCI seem to have a heavier burden of subclinical cardiovascular diseases (CVDs). 

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Fully automated spatio-temporal segmentation approach for myocardium ischemic lesions detection and tissue classification
Clément Daviller1, Thomas Grenier1, Shivraman Giri2, Pierre Croisille3, and Magalie Viallon3

1Univ Lyon, INSA‐Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, Villeurbanne, France, Villeurbanne, France, 2Siemens Medical Solutions USA, Inc. Boston, USA., Boston, MA, United States, 3Univ Lyon, INSA‐Lyon, UJM-Saint Etienne, Université Claude Bernard Lyon 1,CNRS, Inserm, CREATIS UMR 5220, U1206, F-42023, SAINT-ETIENNE, France, Saint-Etienne, France

CMR Perfusion Imaging proved its role in patient triage, identifying visually ischemia and its capability in quantifying heart perfusion1,2, but failed to transfer this technology to clinical routine and to show how this worth information could be used to improve tissue lesions comprehension. Deconvolution techniques are sensitive to noise present on time intensity curves S(t), when observation scale decreases. Automated segmentation prior modelling would be a powerful adjunct. Indeed, prior tissue classification would optimize perfusion quantification accuracy since enabling advanced modelling leading to additional markers while reducing processing time. Such automated method is proposed here.

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Rapid Motion Compensation Reconstruction for Dynamic MRI using Pixel Tracking Temporal Total Variation Constraint
Ye Tian1,2, Apoorva Pedgaonkar1, Jason Mendes1, Mark Ibrahim3, Brent Wilson3, Edward DiBella1, and Ganesh Adluru1

1UCAIR, University of Utah, Salt Lake City, UT, United States, 2Physics and Astronomy, University of Utah, Salt Lake City, UT, United States, 3Cardiology, University of Utah, Salt Lake City, UT, United States

We present a novel motion compensation reconstruction method based on spatiotemporal constrained reconstruction (STCR) by tracking the movements of every pixel in each time frame, and constrain the temporal total variation along the pixel tracks. The proposed method can handle both respiratory and cardiac motion, and has comparable reconstruction speed but offers better image quality compared with STCR.

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Myocardial microvascular dysfunction in patients with end-stage renal disease and the risk factors for the heart damage in hemodialysis
Rong Xu1, Yingkun Guo1, Zhigang Yang2, and Huayan Xu2

1West China Second University Hospital, Chengdu, China, 2West China Hospital, Sichuan University, Chengdu, China

Cardiovascular disease is the major cause of death in patients with chronic kidney disease, this study prospectively enrolled 67 patients with ESRD to quantify evaluate the difference in left ventricular (LV) regional myocardial microvascular function using cardiac magnetic resonance (CMR), and to discuss the factors that may affect myocardial damage in the clinical treatment. The results confirmed that the first-pass perfusion CMR can early defect the myocardial deformation and dysfunction in ESRD patients, and the treatment time may be a risk factor for the cardiovascular disease in the patients with CKD.

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Importance of Right Atrial Strain on Right Ventricular Dilation in Pediatric and Adult Patients with Repaired Tetralogy of Fallot: Fast CMR Feature Tracking Study
Shuang Leng1, Liwei Hu2, Xiaodan Zhao1, Ju Le Tan1,3, Wen Ruan1, Ru San Tan1,3, Yumin Zhong2, and Liang Zhong1,3

1National Heart Centre Singapore, Singapore, Singapore, 2Shanghai Children Medical Centre, Shanghai Jiaotong University, Shanghai, China, 3Duke-NUS Medical School Singapore, Singapore, Singapore

Right ventricular (RV) volume overload is common in patients after initial repair of tetralogy of Fallot (rTOF) and is associated with adverse long-term outcomes. We aimed to determine the effect of right atrial (RA) strain derived from feature tracking cardiovascular magnetic resonance (CMR) on the RV volume in both pediatric and adult rTOF patients. Results revealed that RA strain and strain rates were impaired in rTOF and RA reservoir strain impairment was significantly associated with RV dilatation. Hence, unloading of the RA and augmentation of RA function may be important future therapeutic targets in rTOF.

3333
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MR-compatible Echocardiography and Predictive Slice Tracking Towards Ultrasound-driven Cardiovascular MRI
Lindsey Alexandra Crowe1, Francesco Santini2, Laura Gui1, Pauline Guillemin1, Orane Lorton1, Pamina Bernou1, Myriam Roth1, Gibran Manasseh1, Oliver Bieri2, Jean-Paul Vallée1, and Rares Salomir1

1Division of Radiology, Geneva University Hospitals, Geneva, Switzerland, 2Radiology, Universitätsspital Basel, Basel, Switzerland

MR imaging of cardiac valves is challenging as out-of-plane motion limits the use of 2D cine acquisitions. Ultrasound is well accepted as the clinical tool for observing valve motion. Here we suggest a hybrid imaging technology using in-bore ultrasound for direct observation of the motion of interest and subsequent on-the-fly adaptation of the MR slice position. MR-compatibility and workflow of echocardiography in-situ was demonstrated on a volunteer. Dynamic correction of motion in MR images was quantified with a moving phantom. Future-predicting algorithms yielded a reduction of apparent motion amplitude by a factor of twenty and dramatically improved “cine” image sharpness versus uncorrected data. 

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Systolic and Diastolic Strain Abnormalities are Observed in Spontaneously Diabetic Non-Human Primates with Diastolic Dysfunction and Preserved Ejection Fraction.
Smita Sampath1, Li Gong2, Yushu Chen3, Chin Han Cheng1, Zhigang Liang2, Stephanie Seah1, Jie Zheng4, Sarayu Parimal1, Zhu Tong3, Zhang Yu3, Wei Chen3, Asad Abu Bakar Ali1, Jeffrey L Evelhoch5, Wen Zeng2, Chih-Liang Chin1, and Fabao Gao3

1Translational Biomarkers, MRL, MSD, Singapore, Singapore, 2Sichuan Primed Shines Bio-tech Co. Ltd., Chengdu, China, 3Department of Radiology, West China Hospital, Sichuan University, Chengdu, China, 4Department of Radiology, Washington University School of Medicine, St Louis, MO, United States, 5Translational Biomarkers, MRL, Merck & Co., Inc., West Point, PA, United States

Non-human primate (NHP) models of cardiovascular disease or metabolic disorder offer a unique framework to evaluate novel therapeutics. Herein, we perform cardiac strain MRI on a 3T MRI scanner to characterize systolic and diastolic function in naïve and spontaneously diabetic NHPs with diastolic dysfunction (T2DM-DD) and preserved ejection fraction (which may represent an early phenotype of HFpEF).  In addition, the naïve animals were imaged twice to perform test-retest analysis of the strain-based biomarkers.  Peak strains and peak diastolic strain-rates (both circumferential and longitudinal) are significantly impaired in the T2DM-DD monkeys compared to the naïve monkeys indicating impaired systolic and passive diastolic function.  In addition, peak untwist rate is also decreased depicting impairment in active diastolic function as well.  The test-retest results in the naïve animals show that all biomarkers, with the exception of peak longitudinal strain, are reproducible.

 



3335
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Cardiac MRI detects functional deterioration prior to apoptosis in a mouse model of doxorubicin-induced cardiotoxicity using tissue phase mapping
Bradley D Allen1, Nivedita K Naresh1, Alexander Ruh1, Sol Misener1, Zhuoli Zhang1, Daniele Procissi1, and James C Carr1

1Radiology, Northwestern University, Chicago, IL, United States

Doxorubicin-induced cardiotoxicity is an important limiting factor preventing dose-effective cancer treatment, and the associated cardiac sequelae appears to be mediated through cardiac myocyte apoptosis. Multiple studies have suggested there is potential for cardiovascular MRI (CMR) multiparametric analysis to detect doxorubicin-induced cardiotoxicity. In the current study, we performed multiparametric CMR including DENSE strain assessment and tissue phase mapping (TPM) for myocardial velocity measurement in a mouse model of doxorubicin-induced cardiotoxicity. Our results suggest that advanced CMR functional assessment shows promise in identifying treatment-related decrease in myocardial longitudinal systolic and diastolic velocity prior to the onset of cardiac myocyte apoptosis.

3336
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The assessment of global and regional strain in patients with preserved ejection fraction after Fontan operation using feature tracking technique as compared with healthy children
Li-wei Hu1, Rong-zhen Ouyang1, and Yu-min Zhong1

1Radiology, Shanghai Children's Medical Center, Shanghai, China

The quantification of myocardial deformation may allow detection of early abnormalities and provide independent prognostic information, as demonstrated in echocardiographic studies.Meanwhile, some studies have suggested that CMR-FT may be evaluated earlier than ejection fraction to detect early abnormalities of the ventricular myocardium in postoperative follow-up of CHD. But, there is still limited experience with cardiac magnetic resonance feature tracking strain analysis in child patients. To the best of our knowledge, the significance of quantifying ventricular myocardial deformation in post-Fontan patients with pEF using CMR-FT has not been investigated. Therefore, the aim of this study was to evaluate the myocardial strain in children with pEF after the Fontan operation using feature tracking technique  compared to healthy children.

3337
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Hypertrophic Cardiomyopathy: The Potential Value of Tissue-Tracking Strain Analysis
Lindsay M Griffin1, Emily L Ferris1, Scott K Nagle1, and Christopher J Francois1

1Radiology, University of Wisconsin, Madison, WI, United States

In hypertrophic cardiomyopathy (HCM), myocardium is disorganized, causing contraction abnormalities, perhaps before wall motion abnormalities are visually apparent. Tissue-tracking, a post-processing technique using routinely-acquired cine images, can assess strain, a multidimensional measure of contraction. We assess strain in 19 HCM cases. Global circumferential strain (GCS) and radial strain (GRS) correlated well (r > -0.85, p < 0.0001) and were worse in those with late gadolinium enhancement (p < 0.05). GCS modestly correlated with segment thickness (r = 0.46, p < 0.05). These data suggest strain may add value as a diagnostic/prognostic tool in assessment of HCM, available without additional imaging time.   

3338
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Subtle differences in left ventricular cardiotoxicity remodeling between risk groups of cancer survivors based on strain analysis from cine-DENSE MRI
Delphine Perie-Curnier1, Denis Corbin1, Frederik Epstein2, Daniel Auger2, Tarik Hafyane3, and Daniel Curnier4

1Mechanical Engineering, Polytechnique Montreal, Montreal, QC, Canada, 2Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, 3Research Center, Montreal Heart Institute, Montreal, QC, Canada, 4Kinesiology, University of Montreal, Montreal, QC, Canada

The aim of this study was to evaluate a reliable clinical tool to assess subtle differences in left ventricular cardiotoxicity remodeling in acute lymphoblastic leukemia survivors. Cine-DENSE MRI provided accurate evaluation of heart’s functionality of young cancer survivors in the short-axis view. Significant strain differences between groups were mostly observed in basal septal and apical septal segments while most of the other segments did not show significant differences. The next step of this study will be to include a control group of healthy volunteers.


Electronic Poster

Vascular

Exhibition Hall Monday 13:45 - 14:45

3339
Computer 25
Three-dimensional MRA Demonstrates Eccentric Enlargement of the Non-Conjoined Cusp-Sinus in Bicuspid Aortic Valve Patients
Pascale Aouad1, Hector I Michelina2, Ian Murphy3, James Carr1, Jeremy Collins1, and Alex J Barker1

1Northwestern University, chicago, IL, United States, 2Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Rochester, MN, United States, 3AMNCH Tallaght Hospital, Dublin, Ireland

Bicuspid aortic valve is associated with ascending aortic dilatation, including the aortic root. The etiology of this aortopathy is controversial, with contributions proposed to come from both genetic and hemodynamic origins. While the pattern of aortic dilatation has been loosely associated with cusp fusion patterns and valve function, no study has investigated if eccentric sinus dilation is present and whether it varies in relation to the BAV phenotype. Thus, this study uses b-SSFP cine imaging and gated CE-MRA or 3D IR SSFP to assess the structure of the bicuspid aortic valve and identify the presence of a dominant sinus.

3340
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MR Venography with Ferumoxytol in Central Venous Occlusion
Puja Shahrouki1,2, John Moriarty1,2, Biraj Bista1,2, Sarah Khan1,2, Stephen Kee1, Brian DeRubertis3, Takegawa Yoshida1,2, Kim-Lien Nguyen2,4, and J. Paul Finn1,2

1Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, 2Diagnostic Cardiovascular Imaging Laboratory, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, 3Department of Cardiothoracic Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, 4Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States

Treatment of central venous occlusion is guided largely by anatomic considerations determined by pre-procedural imaging. Current approaches to imaging such as ultrasound and conventional cross-sectional imaging of central veins face many technical challenges and may be contraindicated in patients with renal impairment. We demonstrated that ferumoxytol-enhanced MR venography (FE-MRV) is a safe and highly accurate diagnostic tool that can be used as a reliable pre-interventional vascular map.

3341
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Whole Body Vascular MR Imaging in Five Minutes for Patients With Claustrophobia
Puja Shahrouki1,2, John Moriarty1,2, Biraj Bista1,2, Sarah Khan1,2, Stephen Kee1, Brian DeRubertis3, Takegawa Yoshida1,2, Kim-Lien Nguyen2,4, and J. Paul Finn1,2

1Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, 2Diagnostic Cardiovascular Imaging Laboratory, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, 3Department of Cardiothoracic Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, 4Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States

Patients with claustrophobia represent a significant proportion of patients who would otherwise be suitable candidates for MR angiography.  With conventional acquisition techniques, examination times for MRA typically exceed 30 minutes and claustrophobic patients are often unwilling or unable to undergo the study.  We implemented a new approach to minimize time in the magnet bore for patients with claustrophobia, acquiring comprehensive vascular evaluation of the thorax, abdomen and pelvis in as little as 5 minutes.

3342
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Feasibility and Optimization of Ultra-Short Echo Time MRI for Improved Imaging of IVC Filters
Gesine Knobloch1, Scott Nagle1,2,3, Timothy Colgan1, Tilman Schubert1, Kevin M. Johnson1,2, Peter Bannas1, Nathan Artz1, Christopher François1, Mark Schiebler1, James Holmes1, and Scott Reeder1,2,4,5,6

1Department of Radiology, University of Wisconsin – School of Medicine and Public Health, Madison, WI, United States, 2Department of Medical Physics, University of Wisconsin – School of Medicine and Public Health, Madison, WI, United States, 3Department of Pediatrics, University of Wisconsin – School of Medicine and Public Health, Madison, WI, United States, 4Department of Biomedical Engineering, University of Wisconsin – School of Medicine and Public Health, Madison, WI, United States, 5Department of Medicine, University of Wisconsin – School of Medicine and Public Health, Madison, WI, United States, 6Department of Emergency Medicine, University of Wisconsin – School of Medicine and Public Health, Madison, WI, United States

Monitoring of inferior vena cava (IVC) filters for complications is commonly performed using CTA. It would be desirable to evaluate IVC-filters using MRA to avoid the need for ionizing radiation and to exploit the superior soft tissue contrast of MRA. Unfortunately, conventional contrast enhanced MRA (cMRA) techniques are limited by distortion and signal voids arising from metal in the IVC-filter. In this pilot study, we evaluated the feasibility of ultra-short echo time (UTE) MRA at 3.0T in nine patients with IVC-filters. Results demonstrate feasibility of free-breathing UTE-MRA for the assessment of IVC-filters with comparable IVC-depiction compared to cMRA.

3343
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MR time optimization: 2-year institutional experience in clinically applied high-resolution intracranial vessel wall imaging
Laura Eisenmenger1, Lizhen Cao1, Chengcheng Zhu1, Christopher Hess1, and David Saloner1

1Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States

High-resolution intracranial vessel wall imaging (VWI) can provide valuable information not only regarding vascular morphology but also about the presence or absence of vessel wall enhancement; however, VWI acquisition times are often long, limiting routine use in clinical practice. We sought to investigate the use of the VWI in routine clinical practice to evaluate its application within our institution as well as optimize the imaging protocol to meet clinical needs. Our study found post-contrast VWI better demonstrated the vascular pathology compared to pre-contrast VWI. We also found only one case that may have benefited from the addition of pre-contrast VWI; however, the addition of pre-contrast VWI in this case would not have changed clinical management. Our findings suggest that the routine use pre-contrast VWI may not be needed to obtain the imaging necessary for clinical diagnosis and patient management. 


3344
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MRI and Non-Contrast CT Image Fusion to Guide Vascular Intervention: Feasibility Using Ferumoxytol in Patients with Renal Failure
Takegawa Yoshida1,2, Puja Shahrouki1,2, Kim-Lien Nguyen1,3, John M. Moriarty1,2, Stephen Kee2, and J Paul Finn1,2

1Diagnostic Cardiovascular Imaging Laboratory, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, 2Department of Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States, 3Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States

Accurate pre-procedural vascular mapping may be crucial to guide successful intervention.  Whereas MRA provides excellent definition of the perfused vascular lumen, it is insensitive to vascular calcification and may fail to image indwelling devices. CTA can address the latter limitations, but may be contraindicated in patients with renal impairment, as is the case for gadolinium based contrast agents (GBCA).  Our early results suggest that, in patients with renal failure, 3D fusion of non-contrast CT and ferumoxytol-enhanced MR images leverages the complementary strengths of both modalities while avoiding both iodinated contrast agents and GBCA.

3345
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Monitoring intraluminal thrombus (ILT) progression in abdominal aortic aneurysm (AAA) using 3D black blood MRI: a longitudinal analysis
Chengcheng Zhu1, Lizhen Cao1,2, Zhaoying Wen1,3, David Saloner1, and Michael D Hope1

1Radiology, University of California, San Francisco, San Francisco, CA, United States, 2Radiology, Xuanwu Hospital, Beijing, China, 3Radiology, Anzhen Hospital, Beijing, China

The composition of intraluminal thrombus (ILT) is uniquely identified by MRI and has been suggested as a marker of abdominal aortic aneurysm (AAA) growth. However, the natural history of ILT progression is still unknown. This study followed 25 AAA patients over 19±9 months using repeated high resolution black-blood MRI. We found baseline ILT types did not predict AAA growth, however, AAAs with new ILT formation or fresher ILT during follow-up grew 3 times faster than AAAs without ILT change or older ILT (4.0±2.3mm/year vs. 1.3±2.5 mm/year, p=0.009). Monitoring ILT change provides new insights into the AAA risk assessment. 

3346
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Particle swarm optimization (PSO) and comparison of a water selective T2 preparation module for simultaneous robust fat suppression and tissue contrast enhancement at 3T
Lionel Arn1, Ruud B van Heeswijk1, Andrew J Coristine1, Matthias Stuber1, and Jessica AM Bastiaansen1

1Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland

Gradient echo based pulse sequences at 3T may lack the required contrast to distinguish blood from muscle. To overcome this, T2 preparation (T2-prep) modules are used in cardiac imaging to distinguish the blood pool from the myocardium. To suppress unwanted fat signals, we exploited the additional degrees of freedom that offer the multiple radiofrequency pulses of an adiabatic T2-prep and we used particle swarm optimization (PSO) to develop a T2-prep with robust fat suppression capabilities that works in the presence of flow. Its robustness against B1 and B0 inhomogeneities were predicted by the Bloch simulations for a range of fatty tissue frequencies, and could be confirmed experimentally both in phantoms and in volunteers.

3347
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Rapid, non-contrast thoracic MRA using a combination of stack-of-star k-space sampling, compressed sensing, and self-navigation of respiratory motion
Hassan Haji-valizadeh1, Nivedita K. Naresh2, Jeremy D. Collins2, Joshua D. Robinson3,4, Pascale J. Aouad2, Ali M. Serhal2, James C. Carr2, Cynthia K. Rigsby4,5, and Daniel Kim2

1Biomedical Engineering, Northwestern University, Evanston, IL, United States, 2Radiology, Northwestern University, Chicago, IL, United States, 3Division of Pediatric Cardiology, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, United States, 4Department of Medical Imaging, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, United States, 5Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States

We sought to highly accelerate high resolution (1.5 mm x 1.5 mm x 1.5 mm) non-contrast thoracic MRA using a combination of compressed sensing, stack-of-stars k-space sampling with variable density, and self-navigation , and we compared its performance against clinical contrast-enhanced MRA in patients with suspected aortic disease.

3348
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Application of non-contrast-enhanced MR angiography in hepatic arteriography
Xianlun Zou1, Di Zhu1, Hao Tang1, Yaqi Shen1, Zhen Li1, and Daoyu Hu1

1Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

Accurate evaluation of hepatic arterial anatomy and variants is essential for preoperative planning of hepatic resection, transarterial chemoembolization and liver transplantation. In the present study, we try to explore the value of non-contrast-enhanced MR angiography using spatial labeling with multiple inversion pulses (SLEEK-MRA) in hepatic arteriography, and to compare the results with CT angiography (CTA). Although SLEEK-MRA was inferior to CTA in depicting small branches, it was comparable to CTA for depiction of the common hepatic artery, proper hepatic artery, left hepatic artery and right hepatic artery. As a noninvasive angiography method, SLEEK-MRA is valuable in hepatic arteriography.

3349
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Simultaneous acquisition of motion-corrected coronary MRA and respiratory-resolved attenuation maps for whole-heart PET-MR imaging
Camila Munoz1, Radhouene Neji2, Gastao Cruz1, René M Botnar1, and Claudia Prieto1

1School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2MR Research Collaborations, Siemens Healthcare, Frimley, United Kingdom

Motion-compensated attenuation correction is fundamental for accurate quantification in cardiac PET imaging. Here we propose a dual-echo water/fat coronary MR angiography acquisition with a motion-corrected reconstruction framework that simultaneously allows visualisation of the coronary anatomy and produces respiratory-resolved high-resolution attenuation maps. Results from healthy subjects show that the motion correction approach improves vessel contrast and sharpness compared to uncorrected water/fat images. Additionally, respiratory-resolved attenuation maps were obtained from motion fields and water/fat images with good tissue contrast. The proposed scheme can potentially be used for accurate and highly efficient whole-heart motion-corrected cardiac PET-MR imaging ensuring alignment between emission PET, attenuation maps and diagnostic MR data.

3350
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Combined Assessment of Peripheral Artery Disease by MRI-based Vascular Calcification Visualization and Quiescent Interval Single-Shot (QISS) MRA
Akos Varga-Szemes1, Taylor M. Duguay1, Thomas M. Todoran2, Megha Penmetsa1, Stephen R. Fuller1, Carlo N. De Cecco1, Pal Suranyi1, Robert R. Edelman3, Ioannis Koktzoglou3, and U. Joseph Schoepf1

1Department of Radiology, Medical University of South Carolina, Charleston, SC, United States, 2Department of Medicine, Medical University of South Carolina, Charleston, SC, United States, 3NorthShore University, Evanston, IL, United States

The diagnostic accuracy of quiescent-interval single-shot (QISS) MRA to detect peripheral artery disease (PAD) has been shown to be similar to that of CTA. Unlike CTA, standard MR techniques are limited in the detection of vascular calcification. However, proton density-weighted, in-phase 3D stack-of-stars gradient-echo (PDIP-GRE) prototype pulse sequence has been shown to accurately depict calcifications in PAD. In our study, PDIP-GRE MRI provided comparable assessment to CTA. The MRI visualization of lower extremity vascular calcification improved readers’ confidence and the diagnostic accuracy of QISS-MRA in detecting significant vascular stenoses. Quantification of vascular calcium with MRI showed good agreement with CTA.

3351
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Improved Golden Ratio Radial Arterial Spin Labeling Angiography Reconstruction using k-t Sparsity Constraints
Mark Chiew1 and Thomas W Okell1

1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

Dynamic arterial spin labeling angiography enables non-invasive visualization of arterial flow patterns, but is often time-consuming to perform.  Undersampled radial trajectories help reduce acquisition time, but can result in noise-like aliasing artefacts and reduced spatial fidelity, particularly for a combined angiographic and perfusion golden ratio imaging technique, CAPRIA.  An image reconstruction framework leveraging coil information and sparsity in the spatial and temporal frequency domains is presented which reduces aliasing and improves image sharpness in both 2D and 3D data.  In addition, scan time reductions up to 10x are shown to be feasible whilst maintaining spatial and temporal information.

3352
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Accelerated Non-Rigid Respiratory Motion Corrected Simultaneous Bright- and Black-Blood 3D Whole-Heart Coronary MR Angiography
Giulia Ginami1, Aurelien Bustin1, Gastao Cruz1, Radhouene Neji1,2, René M Botnar1, and Claudia Prieto1

1School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom

A novel 3D whole-heart sequence for simultaneous bright- and black-blood coronary angiography (named BOOST) was recently introduced. BOOST alternates the acquisition of two differently magnetization-prepared bright-blood volumes for coronary lumen visualization and from which respiratory motion information can be independently extracted. These datasets are subsequently combined in a PSIR-like reconstruction to obtain a complementary co-registered black-blood volume for thrombus/haemorrhage visualization. BOOST acquisitions, however, require prolonged acquisition times. Here, we accelerate BOOST acquisition by exploiting a variable density Cartesian trajectory that generates incoherent undersampling artefacts. Furthermore, non-rigid respiratory motion correction incorporated in the undersampled reconstruction is exploited for improved sharpness.

3353
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Contrast-enhanced magnetic resonance angiography (MRA) in pre-surgical planning of deep inferior epigastric artery perforator flaps: comparison with surgical outcomes
Sze Yiun Teo1, Christopher Au1, and Evan Woo2

1Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore, Singapore, 2Department of Plastic, Reconstructive and Aesthetic Surgery, KK Women's and Children's Hospital, Singapore, Singapore

Deep inferior epigastric perforator (DIEP) flap reconstruction is an excellent choice because only the subcutaneous fat is used. DIEP flap reconstruction requires selection of a suitable perforator vessel, which can be highly variable in size and location. Pre-operative imaging can identify these vessels. Doppler sonography is the standard imaging modality, but has mixed results. CT angiography is accurate, but involves ionising radiation. MR angiography is less commonly used, but obviates any radiation exposure. This study shows that MR angiography is an accurate imaging modality to detect the size and location of suitable perforator vessels. Pre-operative knowledge of these vessels allows for optimal surgical planning, reduced area of surgical dissection and shortened dissection times.

3354
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Pulmonary venous and coronary artery visualization from isotropic whole-heart kt-accelerated 3D cardiac CINE MRI
Raluca Gabriela Chelu1, Hye-Jeong Lee2, Tara Retson3, and Albert Hsiao3

1Erasmus MC, Rotterdam, Netherlands, 2Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea, 3Altman CTRI, San Diego, CA, United States

Isotropically-acquired 3D cine cardiac MRI has potential for quantification of cardiac size and function, which has been previously studied. We observed that pulmonary veins and coronary artery origins can be seen with this technique, and sought to further evaluate diagnostic visualization of these vessels. Two observers scored the coronary artery origins and pulmonary veins using a 5-point Likert score. Pulmonary veins were more readily visualized than coronary arteries. Isotropically-acquired 3D cine cardiac MRI enables depiction of vascular anatomy, and potentially may be used for pulmonary venous mapping and depicting coronary anomalies.

3355
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Comparison of SPGR Phase-Sensitive Inversion-Recovery and FIESTA Phase-Sensitive Inversion-Recovery MRI at 3.0T for the assessment of Late Gadolinium Enhancement in Patients with Hypertrophic Cardiomyopathy
Huimin Yin1, Ying Wang1, and Lizhi Xie2

1Radiology Department, Peking University Third Hospital, Beijing, China, 2GE Healthcare, China, Beijing, China

Cardiovascular magnetic resonance(CMR) imaging is now accepted as a valuable tool for the evaluation of many cardiac disease. It is particularly useful for the assessment of cardiomyopathies because it can depict different myocardial enhancement patterns on inversion-recovery(IR) late gadolinium-enhanced(LGE) images. This study would like to compare breath-holding SPGR PSIR with free-breathing FIESTA PSIR sequences and evaluate the feasibility of FIESTA for the assessment of LGE in patients with hypertrophic cardiomyopathy.

3356
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Highly Accelerated 3D MR Angiography Using Multi-Channel Blind Deconvolution
Peizhou Huang1, Jingyuan Lyu2, Hongyu Li3, Yongsheng Chen4,5, Saifeng Liu4, Chaoyi Zhang3, Ukash Nakarmi3, E. Mark Haacke4,5, and Leslie Ying1,3

1Biomedical Engineering, State University of New York at Buffalo, Buffalo, NY, United States, 2United-Imaging Healthcare America, Houston, TX, United States, 3Electrical Engineering, State University of New York at Buffalo, Buffalo, NY, United States, 4The MRI Institute for Biomedical Research, Detroit, MI, United States, 5Department of Radiology, Wayne State University, Detroit, MI, United States

In many clinical applications, the three dimensional (3D) MRA plays an important role because that the 3D MRA can provide plenty of details for more compact anatomic regions with various flow directions. However, the speed limitation of the 3D MRA reconstruction is still an unignorable problem due to the size of the dataset, especially when the dataset has multi channels. With our proposed method, the Multi-Channel Blind Deconvolution (MalBEC), the experiment demonstrate that this method can provide high quality reconstruction image with high acceleration factors using much less time. 

3357
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Comparison of Time-Resolved 3D Contrast-Enhanced MR Angiography on a Compact 3T Scanner with a Whole-Body 3T Scanner
Eric G. Stinson1, Joshua D. Trzasko1, Erin M. Gray1, Eric A. Borisch1, Jeffrey L. Gunter1, Norbert G. Campeau1, Matt A. Bernstein1, John Huston III1, and Stephen J. Riederer1

1Radiology, Mayo Clinic, Rochester, MN, United States

High spatiotemporal resolution contrast-enhanced MR angiography of the whole brain was performed on a compact 3T system with a 32 channel RF coil and compared to a spatial-resolution-matched study on a 60 cm bore whole-body 3T scanner. The quality of images from both scanners was excellent. Higher temporal resolution (4.18 s vs 5.75 s) on the compact 3T scanner was enabled by high performance gradients and increased PNS limits compared to the whole-body scanner. 

3358
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Efficacy of Gadoterate Meglumine enhanced MRA in evaluating thoracic aortic aneurysm and comparison with Gadobutrol enhanced MRA
Kaitlin Crawford1, Ali Serhal2, Olivia D. Reese2, Pascale Aouad2, Matthew Barrett2, Monica Korell2, Amir Rahsepar2, Monda Shehata2, Ahmadreza Ghasemiesfe2, Jeremy Collins2, and James Carr2,3

1University of Notre Dame, South Bend, IN, United States, 2Northwestern University, Chicago, IL, United States, 3Knight Family Professor of Cardiac Imaging, Chicago, IL, United States

Contrast enhanced Magnetic resonance imaging plays an important role in the diagnosis and follow-up of patients with thoracic aortic aneurysm (TAA). Gadoterate Meglumine, which has recently become available in the US, is considered one of the safer gadolinium contrast agents with respect to tissue deposition and NSF, due its macrocyclic structure. In this study, we compare the qualitative image quality and quantitative aortic dimensions of Gadoterate Meglumine enhanced MRA and compare it to Gadobutrol enhanced MRA for evaluation of thoracic aortic disease. These preliminary results showed that Gadoterate Meglumine enhanced MRA has comparable image quality to Gadobutrol enhanced MRA and excellent correlation with respect to aortic diameter measurements.

3359
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Truncation Artifact in Pulmonary Magnetic Resonance Angiography
Timothy J Colgan1,2, Scott K Nagle1, and Scott B Reeder1,2,3,4,5

1Radiology, University of Wisconsin - Madison, Madison, WI, United States, 2Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, 3Medicine, University of Wisconsin - Madison, Madison, WI, United States, 4Biomedical Engineering, University of Wisconsin - Madison, Madison, WI, United States, 5Emergency Medicine, University of Wisconsin - Madison, Madison, WI, United States

Pulmonary magnetic resonance angiography is a promising technique for the detection of pulmonary embolism but suffers from central vessel dropout (truncation artifact) that can mimics emboli in medium-sized vessels. Corner-cutting k-space acquisition strategies are suspected to exacerbate this artifact. Simulations and in vivo experiments were used to investigate the relationship between corner-cutting and truncation artifact. Our simulations suggest that eliminating corner-cutting reduces the symmetry and magnitude of the ringing with this artifact but we observed only minor differences in volunteers. We conclude that corner-cutting, which can be used to shorten scan times and/or improve spatial resolution, does not exacerbate the central vessel dropout artifact.

3360
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Multiparametric MRI Reveals Blood-Flow Dependent Spatial and Temporal Variations in Murine Venous Thrombosis
Olivia R Palmer1, Jie Ma2, Jose A Diaz3, and Joan M Greve1

1Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 2Biomedical Engineering and Biostatistics, University of Michigan, Ann Arbor, MI, United States, 3Surgery, Vascular Surgery, University of Michigan, Ann Arbor, MI, United States

There is a critical need for a noninvasive method to determine the optimal treatment for patients with deep vein thrombosis (DVT), the 3rd most common cardiovascular disease. We have implemented multiparametric MRI to evaluate spatial and temporal changes in thrombus composition using two murine models of DVT. We show that T2- and T2*-weighted MRI detects blood-flow dependent variations in thrombus composition. Classification in fully occlusive thrombi indicated an increased inflammatory response and more rapid thrombus organization when compared to thrombi developed in the presence of blood flow. This work provides foundational methodology that could eventually inform optimal DVT treatment planning.

3361
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Quantification heterogeneous wall displacement and circumferential strain in the thoracic and abdominal aorta by spiral cine DENSE MRI
John Wilson1, Xiaodong Zhong1,2, and John Oshinski1

1Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States, 2Research and Development, Siemens Healthineers, Atlanta, GA, United States

We used spiral cine DENSE (Displacement Encoding with Stimulated Echoes) MRI in the aortic wall to examine the heterogeneity of displacement and strain at three axial locations along the aorta. The major findings of this study were that spiral cine DENSE MRI is a viable technique for assessing patient-specific aortic wall kinematics in-vivo, that regional displacement and circumferential strain are heterogeneous and vary depending on aortic location, and neither mean nor maximum displacement co-localized with sections of peak circumferential strain.


Electronic Poster

Machine Learning for Image Reconstruction

Exhibition Hall Monday 13:45 - 14:45

3362
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A Recurrent Inference Machine for accelerated MRI reconstruction at 7T
Kai Lønning1, Patrick Putzky1, Max Welling1, and Matthan W.A. Caan2,3

1Institute for Informatics, University of Amsterdam, Amsterdam, Netherlands, 2Radiology, Academic Medical Center, Amsterdam, Netherlands, 3Spinoza Centre for Neuroimaging, Amsterdam, Netherlands

Accelerating high resolution brain imaging at 7T is needed to reach clinically feasible scanning times. Deep learning applies multi-layered neural networks as universal function approximators and is able to find its own compression implicitly. We propose a Recurrent Inference Machine (RIM) that is designed to be a general inverse problem solver. Its recurrent architecture can acquire great network depth, while still retaining a low number of parameters. The RIM outperforms compressed sensing in reconstructing 0.7mm brain data. On the reconstructed phase images, Quantitative Susceptibility Mapping can be performed.

3363
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Densely Connected Iterative Network for Sparse MRI Reconstruction
Itzik Malkiel1, Sangtae Ahn2, Zac Slavens3, Valentina Taviani4, and Christopher J Hardy2

1GE Global Research, Herzliya, Israel, 2GE Global Research, Niskayuna, NY, United States, 3GE Healthcare, Waukesha, WI, United States, 4GE Healthcare, Menlo Park, CA, United States

We propose a densely connected deep convolutional network for reconstruction of highly undersampled MR images. Eight-channel 2D brain data with fourfold undersampling were used as inputs, and the corresponding fully-sampled reconstructed images as references for training. The algorithm produced notably higher-quality images than state-of-the-art parallel imaging and compressed sensing methods, both in terms of reconstruction error and perceptual quality. The dense architecture was found to significantly outperform a similar network without dense connections.

3364
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Reconstruction of synthetic T1 MPRAGE via Deep Neural Network from Multi Echo Gradient Echo images.
Kanghyun Ryu1, Yoonho Nam2, Na-young Shin2, Jinhee Jang2, Jiyong Park1, and Dong-Hyun Kim1

1Yonsei University, Seoul, Republic of Korea, 2Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea

We propose to use deep learning to reconstruct synthetic T1-weighted Magnetization prepared rapid gradient echo (MPRAGE) image from multi echo gradient echo (mGRE) images. With our method, high tissue contrast can be achieved without actual MPRAGE scan, which could be utilized for post processing methods, such as tissue segmentation or volumetric quantification. We validated our method’s accuracy by comparing the result of synthetic images with the true image via segmentation and volumetry. Additionally, we tested our method on clinical images containing pathologies not seen in the training set.

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Fast and Realistic Super-Resolution in Brain Magnetic Resonance Imaging using 3D Deep Generative Adversarial Networks
Yuhua Chen1,2, Feng Shi2, Yibin Xie2, Zhengwei Zhou2, Anthony Christodoulou2, and Debiao Li2

1Department of Bioengineering, UCLA, Los Angeles, CA, United States, 2Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States

High-resolution magnetic resonance image (MRI)  are favorable by clinical application thanks to its detailed anatomical information. However, high spatial resolution typically comes at the expense of longer scan time, less spatial coverage, and lower signal to noise ratio (SNR). Single Image Super-Resolution (SISR), a technique aimed to restore high-resolution (HR) details from one single low-resolution (LR) input image, has been improved dramatically by the recent invention of deep Generative Adversarial Networks(GAN). In this paper, we introduce a new neural networks structure, 3D Densely Connected Super-Resolution GAN (DSRGAN) to realistic restore HR features of structural brain MR images. Through experiments on a dataset with 1,113 subjects, we demonstrate that our network outperforms bicubic interpolation in restoring 4x resolution-reduced images.

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MR Image Generation with Deep Learning Incorporating Anatomical Prior Knowledge
Ki Hwan Kim1, Won-Joon Do1, and Sung-Hong Park1

1Department of Bio and Brain Engineering, Korea Advanced Institute of Science & Technology (KAIST), Daejeon, Republic of Korea

We proposed a new convolutional neural network (CNN) to generate high resolution (HR) MR images from highly down-sampled MR images, incorporating HR images in another contrast. Anatomical information from another HR images and adversarial loss functions allowed the proposed model to restore details and edges clearly from the down-sampled images, proved in normal and brain tumor regions. Pre-training with a public database improved performance in real human applications. The proposed methods outperformed several CS algorithms in both pseudo-k-spaces from public data and real k-spaces from human brain data. CNNs can be a good alternative for accelerating routine MRI scanning.

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Image Reconstruction of Accelerated Dynamic MRI using Spatiotemporal Dictionaries with Global Sparsity Regularization
Valery Vishnevskiy1 and Sebastian Kozerke1

1Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland

Adaptive spatiotemporal dictionaries offer improved reconstruction accuracy for dynamic cardiac MRI. However, most modern methods perform local encoding of image patches treating them independently. In order to increase reconstruction quality, we present a convex model that allows global control of encoding sparsity. The proposed method has a single tunable parameter and delivers 9% peak signal-to-noise ratio improvement of reconstruction compared to the state-of-the-art dictionary-based approach. Moreover, the implemented numerical scheme allowed 3-fold reconstruction time reduction.

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Parallel Imaging Reconstruction with a Conditional Generative Adversarial Network
Pengyue Zhang1,2, Fusheng Wang1, and Yu Li2,3

1Department of Computer Science, Stony Brook University, Stony Brook, NY, United States, 2Department of Cardiac Imaging, St.Francis Hospital, Greenvale, NY, United States, 3Department of Radiology, Stony Brook University, Stony Brook, NY, United States

This work presents a parallel imaging reconstruction framework based on deep neural networks. A conditional generative adversarial network (conditional GAN) is used to learn how to recover anatomical image structure from undersampled data for imaging acceleration.  The new approach is shown to be suitable for image reconstruction with high undersampling factors when conventional parallel imaging suffers from  a g-factor increase. 

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Highly-Scalable Image Reconstruction using Deep Neural Networks with Bandpass Filtering
Joseph Yitan Cheng1, Feiyu Chen2, Marcus T. Alley1, John M. Pauly2, and Shreyas S. Vasanawala1

1Radiology, Stanford University, Stanford, CA, United States, 2Electrical Engineering, Stanford University, Stanford, CA, United States

To increase the flexibility and scalability of deep convolution neural networks in the context of MRI reconstruction, a framework is proposed using bandpass filtering. The introduction of bandpass filtering enables us to leverage imaging physics while ensuring that the final reconstruction is consistent with known measurements to maintain diagnostic accuracy. We demonstrate this architecture for reconstructing subsampled datasets of contrast-enhanced T1-weighted volumetric scans of the abdomen. Additionally, we demonstrate the generality of the framework through the reconstruction of wave-encoded 2D single-shot fast-spin-echo scans of the abdomen. The proposed technique performs comparably with state-of-the-art techniques while offering the ability for simple parallelization and increase computational speed.

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Compressed Sensing MRI Reconstruction using Generative Adversarial Networks with Cyclic Loss.
Tran Minh Quan1, Thanh Nguyen-Duc1, and Won-Ki Jeong1

1School of Electrical Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea

Compressed Sensing MRI (CS-MRI) has provided theoretical foundations upon which the time-consuming MRI acquisition process can be accelerated. However, it primarily relies on iterative numerical solvers which still hinders their adaptation in time-critical applications. In addition, recent advances in deep neural networks have shown their potential in computer vision and image processing, but their adaptation to MRI reconstruction is still at an early stage. Therefore, we propose a novel compressed sensing MRI reconstruction algorithm based on a deep generative adversarial neural network with cyclic data consistency constraint. The proposed method is fast and outperforms the state-of-the-art CS-MRI methods by a large margin in running times and image quality, which is demonstrated via evaluation using several open-source MRI databases.

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A Learning-based Metal Artifacts Correction Method using Dual-Polarity Readout Gradients
Kinam Kwon1, Jaejin Cho1, Seohee So1, Byungjai Kim1, Namho Jeong1, and HyunWook Park1

1KAIST, Daejeon, Republic of Korea

 Metallic implants induce large field perturbations, which generate various types of artifacts according to the spatial encoding mechanisms in MRI. Especially, a frequency encoding dimension is influenced by bulk displacements with off-resonance frequencies and the pixel sizes are distorted in the frequency encoding dimension. In the abstract, a new learning-based method is proposed to map two metal-induced-artifacts images with positive and negative-polarity readout gradients into a metal-induced-artifacts-free image. Simulated data was utilized for training the network instead of real MR data that requires many resources to be collected.

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DL-POCS: Deep Learning Augmented POCS Reconstruction for Vastly Undersampled MR Data
Fang Liu1, Julia Velikina1, Richard Kijowski1, and Alexey Samsonov1

1Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States

We introduced a novel reconstruction framework by combining deep learning (DL) neural network with the Projections Onto Convex Sets (POCS) algorithm, termed DL-POCS. The image restoration from undersampled images was first performed by a convolutional encoder-decoder network. Then the output from deep learning was used as initialization and extra constraints were imposed to promote the POCS reconstruction. We evaluated this approach on vastly undersampled knee MR data and found that this combined approach is superior to each of individual components alone. Our study suggests that deep learning regularized image reconstruction will have a substantial impact on data-driven accelerated MR imaging.

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Parallel Imaging and Convolutional Neural Network Combined Fast Image Reconstruction for Low Latency Accelerated 2D Real-Time Imaging
Ziwu Zhou1, Fei Han1, Vahid Ghodrati1, Yu Gao1, Yingli Yang2, and Peng Hu1

1Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States, 2Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, United States

Real-time imaging is a powerful technique to exam multiple physiological motions are the same time. Previous literature has described methods to accelerate the real-time imaging acquisition down to 20ms with the help of compressed sensing. However, reconstruction time remains relatively long, preventing its wide clinical use. Recent developments in deep learning have shown great potential in reconstructing high-quality MR images with low-latency reconstruction. In this work, we proposed a framework that combines the parallel imaging, which is a unique feature in MR imaging, with convolution neural network to reconstruct 2D real-time images with low-latency and high-quality.

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Combining MR-Physics and Machine Learning to Address Intractable Reconstruction Problems
Berkin Bilgic1, Stephen F Cauley1, Itthi Chatnuntawech2, Mary Kate Manhard1, Fuyixue Wang1, Melissa Haskell1, Congyu Liao1, Lawrence L Wald1, and Kawin Setsompop1

1Martinos Center for Biomedical Imaging, Charlestown, MA, United States, 2National Nanotechnology Center, Pathum Thani, Thailand

We are combining Machine Learning (ML) with MR-physics based image reconstruction to tackle intractable problems. We address open problems that are either too stochastic to be modeled (e.g. shot-to-shot phase variations in multi-shot EPI due to physiological noise), or that admit a computationally prohibitive model (e.g. motion correction with simultaneous estimation of motion parameters and image content). Using ML to jumpstart physics-based non-convex reconstructions dramatically improve their efficiency and helps avoid local minima. In return, MR-physics reconstruction keeps ML in check, and avoids using it as a blackbox. Such synergistic combination also provides >2x reduction in RMSE over conventional reconstruction.  

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MultiNet PyGRAPPA: A Novel Method for Highly Accelerated Metabolite Mapping
Sahar Nassirpour1,2, Paul Chang1,2, and Anke Henning1,3

1Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, 2IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Tuebingen, Germany, 3Institute of Physics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany

In this work, a novel acceleration method (MultiNet PyGrappa) is introduced which enables high in-plane acceleration factors for non-lipid suppressed 1H MRSI data. By using a variable density undersampling scheme and reconstructing the missing data points with multiple neural networks, this method enables a more robust reconstruction of highly undersampled data. High resolution metabolite maps acquired at 9.4T in the human brain using the proposed method are presented.

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Assessment of the generalization of learned image reconstruction and the potential for transfer learning
Florian Knoll1,2, Kerstin Hammernik1,2,3, Thomas Pock3, Daniel K Sodickson1,2, and Michael P Recht1,2

1Center for Biomedical Imaging, New York University School of Medicine, New York, NY, United States, 2Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, United States, 3Institute of Computer Graphics and Vision, Graz University of Technology, Graz, Austria

The goal of this study is to assess the influence of image contrast, SNR and image content on the generalization of machine learning in MR image reconstruction. Experiments are performed with patient data from clinical knee MR exams as well as synthetic data created from a public image database. It shows that while SNR is a critical parameter, trainings can be generalized towards a range of SNR values. It also demonstrates that transfer learning can be used successfully to fine-tune trainings from synthetic data to a particular target application using only a very small number of training cases.

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Characterization of Sparsely Trained Deep Learning Reconstruction of Noisy MR Fingerprinting Data
Ouri Cohen1,2, Bo Zhu1,2, and Matthew S. Rosen1,2

1Radiology, MGH Athinoula A. Martinos Center/Harvard Medical School, Charlestown, MA, United States, 2Physics, Harvard University, Cambridge, MA, United States

MR Fingerprinting offers the ability to obtain simultaneous tissue (T1,T2…) and hardware (B1, B0…) parameter maps in a fast acquisition time but is limited by the size of the reconstruction dictionary. In previous work we demonstrated that these issues can be overcome by reconstructing the data using a properly trained neural network. Here we characterize the accuracy of a neural network trained on sparse dictionaries for reconstruction of noisy data.


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k-space Aware Convolutional Sparse Coding: Learning from Undersampled k-space Datasets for Reconstruction
Frank Ong1 and Michael Lustig1

1University of California, Berkeley, Berkeley, CA, United States

Learning from existing datasets has the potential to improve reconstruction quality. However, deep learning based methods typically require many clean fully-sampled datasets as ground truths. Such datasets can be hard to come by, especially in applications where rapid scans are desired. Here, we propose a method based on convolutional sparse coding that can learn a convolutional dictionary from under-sampled datasets for sparse reconstruction. Recent works have shown close connections between deep learning and convolutional sparse coding. The benefit of convolutional sparse coding is that it has a well-defined forward model, and can be easily extended to incorporate physical models during training. We extend convolutional sparse coding to incorporate the under-sampling forward model. We show that the dictionary learned from under-sampled datasets is similar to the dictionary learned from fully-sampled datasets, and improves upon wavelet transform for l1 regularized reconstruction in terms of mean-squared error.

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Constrained Image Reconstruction Using a Kernel+Sparse Model
Yudu Li1,2 and Zhi-Pei Liang1,2

1Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States

Constrained image reconstruction incorporating prior information has been widely used to overcome the ill-posedness of reconstruction problems. In this work, we propose a novel "kernel+sparse" model for constrained image reconstruction. This model represents the desired image as a function of features "learned" from prior images plus a sparse component that captures localized novel features. The proposed method has been validated using multiple MR applications as example. It may prove useful for solving a range of image reconstruction problems in various MR applications where both prior information and localized novel features exist.

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Quantification of relaxation times in MR Fingerprinting using deep learning
Zhenghan Fang1, Yong Chen1, Weili Lin1, and Dinggang Shen1

1University of North Carolina at Chapel Hill, Chapel Hill, NC, United States

MRF is a new quantitative MR imaging technique, which can provide rapid and simultaneous measurement of multiple tissue properties. Compared to the fast speed for data acquisition, the post-processing to extract tissue properties with MRF is relatively slow and often requires a large memory for the storage of both image dataset and MRF dictionary. In this study, a convolutional neural network was developed, which can provide rapid estimation of multiple tissue properties in 0.1 sec. The T1 and T2 values obtained in white matter and gray matter are also in a good agreement with the results from pattern matching.

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High efficient reconstruction of overlapping-echo detachment (OLED) planar imaging based on deep residual network
Congbo Cai1, Chao Wang2, Xinghao Ding2, Shuhui Cai2, Zhong Chen2, and Jianhui Zhong3

1Xiamen University, Xiamen, China, 2Xiamen University, xiamen, China, 3University of Rochester, Rochester, NY, United States

Overlapping-echo detachment (OLED) planar imaging sequence can provide reliable T2 mapping within milliseconds even under continuous object motion. A detachment algorithm based on the sparsity and structure similarity constraints has been used to separate the echo signals to form T2 map. However, the effectiveness of separation is limited and the reconstruction is time consuming. Here, an end-to-end deep convolutional network based on deep residual network was introduced. The results of simulation and in vivo human brain show that it can reconstruct T2 mapping efficiently and reduce the reconstruction time from minutes to milliseconds after deep residual network is trained.

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Optimal Regularization Parameter Selection for Constrained Reconstruction Using Deep Learning
Xi Peng1,2, Fan Lam1, Yudu Li1,3, Bryan Clifford1,3, Brad Sutton1,4, and Zhi-Pei Liang1,3

1Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Shenzhen, China, 3Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 4Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States

Regularization is widely used for solving ill-posed image reconstruction problems and an appropriate selection of the regularization parameter is critical in ensuring high-quality reconstructions. While many methods have been proposed to address this problem, selecting a regularization parameter for optimal performance (under a specific metric) in a computationally efficient manner is still an open problem. We propose here a novel deep learning based method for regularization parameter selection. Specifically, a convolutional neural network is designed to predict the optimal parameter from an “arbitrary” initial parameter choice. The proposed method has been evaluated using experimental data, demonstrating its capability to learn the optimal parameter for two different L1-regularized reconstruction problems.

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A Machine Learning Approach for Mitigating Artifacts in Fetal Imaging due to an Undersampled HASTE Sequence
Sayeri Lala1, Borjan Gagoski2, Jeffrey N. Stout3, Bo Zhao4, Berkin Bilgic4, Ellen P. Grant2, Polina Golland5, and Elfar Adalsteinsson6

1Electrical Engineering and Computer Science, MIT, Cambridge, MA, United States, 2Boston Children’s Hospital, Boston, MA, United States, 3IMES, MIT, Harvard-MIT Health Sciences and Technology, Cambridge, MA, United States, 4Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital, Boston, MA, United States, 5Electrical Engineering and Computer Science, MIT CSAIL, Cambridge, MA, United States, 6Electrical Engineering and Computer Science, Institute for Medical Engineering and Science, MIT, Cambridge, MA, United States

This work investigates using deep learning to mitigate artifacts in fetal images resulting from accelerated acquisitions. We applied an existing deep learning framework to reconstruct undersampled HASTE images of the fetus. The deep learning architecture is a cascade of two convolutional neural networks combined with data consistency layers. Training and evaluation were performed on coil-combined and reconstructed HASTE images with retrospective undersampling. The datasets derived from imaging of ten pregnant subjects, GA 19-37 weeks, yielding 3994 HASTE slices. This approach mitigates artifacts from incoherent aliasing with residual reconstruction errors in high spatial frequency features in the phase encoding direction.

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Single Point Dixon Reconstruction of Whole-Body Scans Using a Convolutional Neural Network
Jonathan Andersson1, Håkan Ahlström1,2, and Joel Kullberg1,2

1Department of Radiology, Uppsala University, Uppsala, Sweden, 2Antaros Medical, BioVenture Hub, Mölndal, Sweden

Reconstructions of water and fat images are clinically useful for removing obscuring fat signal. It can also be useful in for example obesity related research, measuring for example different adipose depot volumes. Normally reconstructions would be performed using at least two echos, which requires about twice as much time as collecting a single echo. Therefore, using only a single echo would reduce the required scan time drastically. In this abstract a method for reconstruction of water and fat images from a single echo is introduced, using a convolutional neural network. We conclude from visual evaluation that the results are promising. 

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Artificial Neural Network for Suppression of Metal Artifacts with Slice Encoding for Metal Artifact Correction (SEMAC) MRI
Sunghun Seo1, Ki Hwan Kim1, Seung Hong Choi2, and Sung-Hong Park1

1Magnetic Resonance Imaging Laboratory, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea, 2Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea

We present a new method of artificial neural network (ANN) to suppress metal artifacts in MR Imaging with Slice Encoding for Metal Artifact Correction (SEMAC). Seven titanium‑embedded phantoms were imaged using different SEMAC factors. The acquired data with low and high SEMAC factors were separated into input and label images, respectively, for training. The trained model was tested on separate phantoms. Metal artifacts in low SEMAC factors could be further suppressed visually and quantitatively using the implemented ANN, with the performance being comparable to that of label images. The proposed method reduces scan time necessary for high‑quality SEMAC imaging.


Electronic Poster

RF Pulses & Sequences

Exhibition Hall Monday 13:45 - 14:45

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Cardiac B1+ Shimming using ZTE Transmit Phase Mapping
Rolf F Schulte1, Haonan Wang2, Anja CS Brau3, and Martin A Janich1

1GE Healthcare, Munich, Germany, 2GE Healthcare, Milwaukee, WI, United States, 3GE Healthcare, Menlo Park, CA, United States

Two different transmit B1+ mapping techniques were implemented and investigated for cardiac B1+ shimming at 3T: (1) 2D cardiac-triggered spiral-Bloch-Siegert B1+ mapping; (2) 3D Zero-Echo-Time (ZTE) B1+ phase mapping. B1+ homogeneity was optimised and performance assessed by evaluating the cardiac black-blood fast spin-echo sequence performance in healthy volunteers.

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Parcellated shimming for brain imaging with 3D EPI at 7T
Christopher Mirfin1, Simon Shah1, Paul Glover1, and Richard Bowtell1

1Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom

A novel acquisition strategy to improve the overall B0 field homogeneity by utilising 2D RF selection with acceleration via parallel transmission in conjunction with parcellated sub-volume shimming is proposed. The method has been demonstrated for brain imaging using a 3D EPI sequence at 7T.

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Optimisation of parallel transmission radiofrequency pulses using neural networks
Christopher Mirfin1, Paul Glover1, and Richard Bowtell1

1Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom

Developing fast accurate large-tip-angle radiofrequency pulses and gradient trajectories suitable for ‘online’ use is a challenging problem. In this work we propose a novel method for the sub-second design of RF pulses and gradient trajectories through use of a suitably trained artificial neural network which attempts to learn the required pulse and gradient spoke parameters from B1+ field spatial variations. A method for synthesising a large training database is also described. Our initial results highlight some of the challenges of this approach but suggest areas for future development.  

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Empirical Sequence Design for Combined T2-Preparation and Outer Volume Suppression Preparation Sequence
David Y Zeng1, Mario O Malavé1, Corey A Baron1,2, Adam B Kerr1, Phillip C Yang3, Bob S Hu1,4, and Dwight G Nishimura1

1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Medical Biophysics, Robarts Research Institute, London, ON, Canada, 3Cardiovascular Medicine, Stanford University, Stanford, CA, United States, 4Cardiology, Palo Alto Medical Foundation, Palo Alto, CA, United States

A new combined T2-prepared, multidimensional OVS pulse sequence was designed by an empirically-driven method. We defined a T2-prepared OVS module as a tip-down pulse, refocusing sequence, and a selective tip-up pulse. Candidate pulses were proposed for each portion of the module and all possible modules were evaluated by a metric based on Bloch simulations. Multidimensional OVS was achieved by concatenation of modules. The proposed sequence had the lowest metric and was compared against an existing T2-prepared OVS sequence for in vivo (n=5) coronary imaging. The proposed sequence had superior vessel sharpness, SNR, OVS, and qualitative reader scores.

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Contrast Preparation Pulses Robust to B1 and B0 Inhomogeneities: an Optimal Control Approach
Eric Van Reeth1, Hélène Ratiney1, Kevin Tse Ve Koon1, Michael Tesch2, Denis Grenier1, Olivier Beuf1, Steffen J Glaser2, and Dominique Sugny3,4

1CREATIS, Villeurbanne, France, 2Department of Chemistry, TUM, Munich, Germany, 3ICB, Dijon, France, 4TUM, Institute for Advanced Study, Munich, Germany

This abstract proposes an optimal control strategy for the computation of contrast preparation pulses robust to B1 (+/- 35%) and B0 (+/- 400Hz) inhomogeneities. The problem formulation allows to optimize the compromise between contrast performance and preparation time. An in vitro short-T2 enhancing contrast experiment validates the robustness superiority of the proposed preparation compared to a block pulse-based scheme, and shows a good match with simulations.


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A Simplified Framework for Contrast Optimization in MRI
Eric Van Reeth1, Hélène Ratiney1, Kevin Tse Ve Koon1, Michael Tesch2, Denis Grenier1, Olivier Beuf1, Steffen J Glaser2, and Dominique Sugny3,4

1CREATIS, Villeurbanne, France, 2Department of Chemistry, TUM, Munich, Germany, 3ICB, Dijon, France, 4TUM, Institute for Advanced Study, Munich, Germany

This abstract details the implementation and interest of an adapted parameterization for the computation of contrast preparation schemes in an optimal control framework. It optimally balances the effect of T1 and T2 relaxation, penalizes long preparation sequences in order to improve the compromise between contrast performance and preparation time, and significantly reduces the computation time. As an example, an in vitro experiment validates the contrast benefit over an inversion-recovery scheme. Finally, it offers a huge flexibility in terms of achievable contrasts, which is demonstrated in vivo by a white-matter enhancement experiment on a rat brain.

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Near real-time parallel-transmit pulse design
Emre Kopanoglu1

1School of Psychology / CUBRIC, Cardiff University, Cardiff, United Kingdom

With many MRI scans lasting several minutes, patient motion is a common problem, especially with uncooperative subjects such as paediatric patients or patients with dementia or Parkinson’s. Realizing the finer-resolution that higher field strengths offer through the availability of increased SNR necessitates even longer scans, exacerbating this problem. While prospective motion correction techniques can compensate for motion at lower field strengths, such techniques are not directly applicable at higher field strengths, when more complicated parallel-transmit pulses are used. This study proposes a pulse design technique that can design multi-spoke and simultaneous multi-slice parallel-transmit pulses in less than one second, while adhering to peak-voltage limits, local and global SAR. 

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16-channel pTx body MRI for reduced field of view lumbar spine and kidney imaging at 7 Tesla
Sascha Brunheim1,2, Stephan Orzada1, Sören Johst1, Marcel Gratz1,2, Jessica Kohl3, Mark E Ladd1,4, and Harald H Quick1,2

1Erwin L. Hahn Institute for MRI, University of Duisburg-Essen, Essen, Germany, 2High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany, 3University of Applied Science Ruhr West, Mülheim an der Ruhr, Germany, 4Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany

In this work we present in-vivo pTx excitation results in the low flip angle regime with a 16-channel transceiver body array at 7 Tesla. The pTx pulse calculation was based on a jointly fast acquired B0 and single-channel B1+ dataset (B01TIAMO) of the central abdomen. The pTx pulse enabled us to acquire high-resolution reduced field of view images of the distal spinal cord and the unilateral left kidney. The results of the established workflow for abdominal pTx provide promising perspectives, especially for neuroradiological spine imaging.

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pTx-PINS pulses for simultaneous multislice excitation using 32 ch Tx array and insertable head gradient
Mihir Pendse1, Riccardo Stara1, Joshua deBever1, and Brian K Rutt1

1Stanford University, Stanford, CA, United States

We describe a method for combining the PINS method for SMS excitation with pTx to design pulses that achieve both good B1+ uniformity (15% inhomogeneity over whole volume) and significant multiband factors (MB = 16) at ultra high field strengths (7T, 10.5T). This is enabled by the use of advanced hardware including a 6-row 32 channel parallel transmit array and a high performance head gradient (130 mT/m strength, 1500 T/m/s slew rate). We optimized RF shimming over the whole volume and applied the optimized shim weights at each point in the PINS trajectory. We satisfied very demanding pulse requirements (0.4 mm slice thickness, MB=16, total flip angle inhomogeneity = 15%) with a practical pulse duration (<12 ms) which is >2 times shorter compared to using conventional hardware

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Universal Parallel Transmit Pulse Design for Local Excitation
Ole Geldschläger1, Tingting Shao1, and Anke Henning1,2

1Max-Planck-Institut, Tübingen, Germany, 2Ernst-Moritz-Arndt-Universität Greifswald, Greifswald, Germany

This study investigates different parallel transmission (PTx) pulse design methods to find a universal PTx-pulse that excites the same local pattern with a 90 degree flip-angle across different heads. Thus, it abandons prospective the need for time-consuming subject specific B1+ mapping and PTx-pulse calculation, during the scan session. The best results were achieved by solving a minimax optimization problem were the maximum normalized root mean square error (NRMSE) over all subjects was minimized. The resulting pulse created magnetization profiles with a maximum NRMSE of around 0.049 across all volunteers.

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k-Space Domain Parallel Transmit Pulse Design
William A Grissom1

1Biomedical Engineering, Vanderbilt University, Nashville, TN, United States

Current parallel transmit pulse design methods are based on a spatial domain formulation that has prohibitive memory and computational requirements when the number of coils or the number of dimensions is large. We describe a k-space domain parallel transmit pulse design method that directly solves for the columns of a sparse design matrix with a much smaller memory footprint than existing methods, and is highly parallelizable. The method is validated with phantom and in vivo 7T 8-channel spiral excitations.

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Optimal control based design of parallel transmission RF pulses with minimum local SAR
Armin Rund1, Christoph Stefan Aigner2, Lena Nohava3, Roberta Frass-Kriegl3, Elmar Laistler3, Karl Kunisch1,4, and Rudolf Stollberger2

1Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria, 2Institute of Medical Engineering, Graz University of Technology, Graz, Austria, 3Division MR Physics, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria, 4Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, Linz, Austria

An optimal control framework for designing parallel transmission RF pulses and gradient shapes is introduced. The optimal control model includes technical constraints and a local SAR model based on the Q-matrix formalism. Second-order optimization methods give RF pulses with enhanced homogeneity of the excitation pattern and/or decreased local SAR. The optimized results are tested in numerical experiments and validated with numerical electromagnetic simulations.

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Z-segmentation of a transmit array head coil improves RF ramp pulse design for TOF MRA at 7T
Gaël Saïb1, Raphaël Tomi-Tricot1, Franck Mauconduit2, Vincent Gras1, Nicolas Boulant1, Alexandre Vignaud1, Edouard Chazel1, Eric Giacomini1, Guillaume Ferrand3, Michel Luong3, Denis Le Bihan1, Laurent Le Brusquet4, and Alexis Amadon1

1CEA/DRF/Joliot/NeuroSpin/UNIRS, Gif-sur-Yvette, France, 2Siemens Healthineers France, Saint-Denis, France, 3CEA/DRF/IRFU/DACM, Gif-sur-Yvette, France, 4Laboratoire des Signaux et Systèmes, Université Paris-Saclay/CentraleSupélec/CNRS, Gif-sur-Yvette, France

In Time-Of-Flight sequences, ramp pulses such as TONE are frequently used to compensate for thru-slab blood saturation in cerebral MRA. At Ultra High Field, parallel transmit fast-kz spokes can be used to greatly mitigate B1+ heterogeneities in the slab selection process. Here we use this technique to design TONE pulses with improved flip angle ramp fidelity and compare the performance achieved with a homemade z-segmented head coil versus a non-segmented commercial array. 

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Improving arterial spin labelling at ultra-high field using parallel transmission: a simulation study
Yan Tong1, Peter Jezzard1, Thomas Okell1, and William T Clarke1

1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

Implementing ASL at ultra-high field is challenging due to increased B1+ and B0 inhomogeneity. Parallel transmission (pTx) provides additional degrees of freedom to mitigate B1+ inhomogeneity. Among various pTx strategies, RF shimming is a simple formulation that modulates the complex weights of each RF channel. RF shimming is particularly robust for applications involving small regions-of-interest. In this study, we explored the possibility of using RF shimming for ASL via simulation, and RF shimming is shown to achieve improved lower NRSME and improved labeling homogeneity over CP mode through simulation. 

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Investigating the effect of B1 map inaccuracies on advanced pulse design
Marjolein Piek1, Nam Gyun Lee1, Anouk Marsman1, Vincent O Boer1, and Esben Thade Petersen1,2

1Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 2Center for Magnetic Resonance, Department of Electrical Engineering, Technical University of Denmark, Lyngby, Denmark

B1 inhomogeneities at high field lead to undesired variation of contrast over the images. With advanced RF pulse design, the effect of B1 inhomogeneities on the excitation pattern can be restored. Bloch simulations in combination with advanced pulse design were performed to study the B1 mapping robustness. The results show that there is relatively high variation between four well established B1 mapping methods. From the results it is clear that next to acquisition speed and SNR, the robustness of B1 estimation is also an important factor if the B1 mapping is to be used for advanced RF pulse design.

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2D selective excitation with UNFOLD for 4D Flow Imaging
Clarissa Wink1, Jean Pierre Bassenge1, Giulio Ferrazzi1, and Sebastian Schmitter1

1Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany

4D flow MRI allows to quantify the velocity vector field non-invasively in-vivo. However, it still suffers from long acquisition times and low temporal and spatial resolution. Here, we accelerate acquisition time and increase temporal resolution without loss of spatial resolution by combining 2D selective excitation and UNFOLD. 2D selective excitation allows to limit the field-of-view in phase encoding direction and thus acquisition time, whereas UNFOLD grants to increase temporal resolution.

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Extending the small tip angle approximation to the non-equilibrium initial condition
Bahman Tahayori1,2,3, Zhaolin Chen2, Gary Egan2, and N. Jon Shah 4

1Electrical and Computer Systems Engineering, Monash University, Clayton, Australia, 2Monash Biomedical Imaging, Monash University, Clayton, Australia, 3Medical Physics and Biomedical Engineering Department, Shiraz University of Medical Sciences, Shiraz, Iran (Islamic Republic of), 4Department of Neurology, JARA, RWTH Aachen University, Aachen, Germany

We have applied Volterra series expansion to the Bloch equation and have calculated the kernels for an arbitrary initial condition. We have shown that small tip angle approximation can be extended to the non-equilibrium initial condition.  Simulation results illustrated the validity of the extended small tip angle approximation. 

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Minimum-TR pulse design for rapid gradient echo sequences
Samy Abo Seada1, Arian Beqiri1, Anthony Price1, Jo Hajnal1, and Shaihan Malik1

1School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom

Use of Multiband and high-TBW RF pulses in SSFP sequences is limited due to their long pulse duration and high RF energy. These two properties are not independent of each other, as shorter RF pulses lead to higher RF energy and often violate SAR limitations when using short repetition times (TR). We show how Time-optimal VERSE can be used to produce pulses that are optimized for minimum TR performance with both single and multi-band examples.

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Translating the Human Connectome Project to Marmoset Imaging: 16-Channel Multi-Array Coil and HCP-Style MRI Protocols and Preprocessing
Yuki Hori1, Joonas Autio1, Masahiro Ohno1, Yoshihiko Kawabata2, Yuta Urushibata3, Katsutoshi Murata3, Masataka Yamaguchi1, Akihiro Kawasaki1, Chiho Takeda1, Chihiro Yokoyama1, Matthew F Glasser4,5, and Takuya Hayashi1

1Center for Life Science Technologies, RIKEN, Kobe, Japan, 2Takashima Seisakusho Co. Ltd., Hino, Kiribati, 3Siemens Healthcare Japan, Tokyo, Japan, 4Department of Anatomy and Neurobiology, Washington University in St. Louis, St. Louis, MO, United States, 5St. Luke's Hospital, St. Louis, MO, United States

The common marmoset is increasingly used as a non-human primate model to understand the organization of the brain. Better cross species comparisons can be achieved by adapting methods from the Human Connectome Project. Here, we show a customized 16-channel receiver coil designed for the marmoset brain and present the initial imaging results on a 3T MRI scanner with powerful gradients. The coil had high signal-to-noise ratio and B1 transmit homogeneity. In-vivo marmoset data, acquired and preprocessed using HCP-style methods, provided high-resolution images, allowing cortical mapping of myelin, thickness, and structural and functional connectivity, enabling high quality cross-species comparisons.

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Development of a 24-Channel 3T Multi-Array Coil for functional MRI in awake monkeys
Atsushi Yoshida1, Yoki Hori1, Kantaro Nishigori1,2, Masahiro Ohno1, Yoshihiko Kawabata3, Yuta Urushibata4, Katsutoshi Murata4, Masataka Yamaguchi1, Joonas Autio1, Matthew F Glasser5,6, and Takuya Hayashi1

1Center for Life Science Technologies, RIKEN, Kobe, Japan, 2Sumitomo Dainippon Pharma Co. Ltd, Osaka, Japan, 3Takashima Seisakusho Co. Ltd., Tokyo, Japan, 4Siemens Healthcare Japan, Tokyo, Japan, 5Department of Anatomy and Neurobiology, Washington University Medical School, St. Louis, MO, United States, 6St. Luke's Hospital, St. Louis, MO, United States

High-resolution fMRI in awake macaques may address compelling questions for how the brain is dynamically organized to create behaviors. Here, we developed a 24-channel multi-array receive coil for awake macaques and a 3T MRI scanner. High performance of the coil was confirmed by assessing noise correlation, B0/B1 field and SNR. Preliminary resting-state fMRI data, preprocessed with the Human Connectome Project pipeline, revealed a number of functional network components, some of which replicated previous findings. Our system may be useful for multi-modal cortical mapping of task-dependent and resting functional activity.

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Accelerated spin-echo fMRI using generalized SLIce Dithered Enhanced Resolution Simultaneous MultiSlice (gSlider-SMS) with 'complex-basis' RF-encoding
SoHyun Han1, Congyu Liao1,2, Mary Kate Manhard1, Berkin Bilgic1,3, Fuyixue Wang1,4, Anna I. Blazejewska1,3, Maaike van den Boomen1, William A. Grissom5, Jonathan R. Polimeni1,3,6, and Kawin Setsompop1,3,6

1Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, 2Department of Biomedical Engineering, Zhejiang Uninversity, Hangzhou, Zhejiang, China, 3Department of Radiology, Harvard Medical School, Boston, MA, United States, 4Medical Engineering & Medical Physics, Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States, 5Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States, 6Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States

High spatiotemporal resolution spin-echo (SE) fMRI acquisition is challenging due to the longer repetition times (TR) compared to conventional gradient-echo (GE) fMRI. In this study, we developed a new method, dubbed ‘complex-basis’ gSlider, which utilizes the spatiotemporal phase-smoothness of SE-fMRI time frames to accelerate the slice coverage of SE-fMRI acquisitions. We further combined ‘complex-basis’ gSlider with conventional SMS to boost the slice-acceleration as well. The proposed method showed comparable tSNR and a two-fold increase in slice-acceleration when compared with standard SE-SMS-EPI. This method would be beneficial for applications requiring high resolution SE-fMRI with whole-brain coverage


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A Bootstrap Analysis of Diffusion MRI Parameters Derived from Simultaneous Multislice Diffusion MRI
Adam Scott Bernstein1,2, Loi V Do2, Nan-kuei Chen2, and Theodore P Trouard2

1NICHD, National Institutes of Health, Rockville, MD, United States, 2Biomedical Engineering, University of Arizona, Tucson, AZ, United States

In this study, we design a unique bootstrapping method to approximate the distributions of diffusion MRI parameters derived from scans that utilize simultaneous multislice techniques compared to the distribution of parameters fit from a single slice EPI sequence. While there are no statistically significant differences between accelerated and non-accelerated datasets, there are some subtle differences that may warrant closer inspection.

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Sharing Radial GRAPPA Weight Sets Across k-Space to Decrease Memory Requirements for Real-Time Imaging
Evan Cummings1, Dominique Franson1, Jesse Hamilton1, and Nicole Seiberlich1

1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States

This study examines the feasibility of reconstructing multiple neighboring k-space points from a single non-Cartesian GRAPPA weight set. This approach reduces both the time to calibrate the GRAPPA weights and the memory needed to store the weights with minimal loss of image quality in the reconstructed images.


Electronic Poster

Image Analysis

Exhibition Hall Monday 13:45 - 14:45

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The average sheep: multi-modal population atlases and variability maps
Stephen John Sawiak1, Nicholas Perentos1, Lucy Johnson1, and A Jennifer Morton1

1University of Cambridge, Cambridge, United Kingdom

We present a sheep atlas from 160 subjects from high-resolution MRI images. Aided by histology, cortical and subcortical regions were labelled for surgical planning and anatomical localisation. Templates for voxel-based morphometry were produced for SPM/DARTEL approaches. To demonstrate the use of the atlas and software, we analysed post mortem volumetric changes in repeatedly scanned brains from in vivo to 12 weeks post mortem. 


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Assessing the Relation between Image Quality Metrics and Brain Volume in a Scan-Rescan Dataset
Ricardo A. Corredor-Jerez1,2,3, Jonas Richiardi1,2,3, Mário João Fartaria1,2,3, Bénédicte Maréchal1,2,3, Adrian Tsang4, Robert Bermel5, Stephen E. Jones5, Izlem Izbudak6, Ellen M Mowry6, Yvonne W. Lui7, Lauren Krupp7, Elizabeth Fisher4, and Tobias Kober1,2,3

1Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 2Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland, 3Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 4Biogen, Cambridge, MA, United States, 5Cleveland Clinic, Cleveland, OH, United States, 6Johns Hopkins University, Baltimore, MD, United States, 7New York University, New York, NY, United States

Satisfactory image quality is essential to accurately assess brain volume using automated methods for evaluating neurodegenerative diseases. Variations in image quality may cause volume estimation errors hard to distinguish from disease-induced changes. We studied the relationship between brain volume estimations and image quality metrics in a scan-rescan study. Two segmentation methods were used to quantify brain volume in FLAIR and MPRAGE images. Volume estimations on MPRAGE varied less with hardware, compared to the estimations on FLAIR. We found a significant correlation between hardware and several image quality metrics, suggesting that these can be used to render volume estimations more hardware-independent.

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Multi-atlas based Detection and Localization (MADL) of White Matter Hyperintensities: Relationship with Amyloid Accumulation and Vascular Risks
Dan Wu1, Kenichi Oishi1, Anja Soldan2, Corinne Pettigrew2, Chenfei Ye1, Michael I Miller3, Marilyn Albert2, and Susumu Mori1

1Radiology, Johns Hopkins University School of Medicine, BALTIMORE, MD, United States, 2Neurology, Johns Hopkins University School of Medicine, BALTIMORE, MD, United States, 3Biomedical Engineering, Johns Hopkins University School of Medicine, BALTIMORE, MD, United States

Recent findings suggest white matter hyperintensities (WMH) that appear on FLAIR images may play a role in the evolution of Alzheimer’s disease (AD). Here, we developed a novel algorithm that simultaneously detects and locates WMH, based on a FLAIR atlas database and a multi-atlas fusion algorithm. The method showed a respectful WMH detection accuracy. We also investigated region-specific WMH load in participants for whom amyloid imaging and vascular data were available. The results suggested that posterior WMH is related to amyloid deposition; whereas anterior and parietal WMH is associated with vascular risk factors.

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Surface Uniform Random Partition for Atlas-free Brain Network Analysis
Teng Zhang1, Pan Sun2, Lin Shi1, Queenie Chan3, and Defeng Wang4

1Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong, 2Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong, 3Philips Healthcare, Hong Kong, Hong Kong, 4Research Center for Medical Image Computing, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong

Random partition is the cornerstone of atlas-free brain network analysis which can be used for multiscale analysis and comparison of cohorts with different brain sizes. The random parcels should be uniform to avoid additional variability from different parcel areas. In this study a uniform random partition of meshed surface is proposed considering geodesic distances and parcel areas. The partition results showed that proposed method can partition surface into any given number of parcels with similar areas. With repeating network analysis using proposed uniform parcels, results showed low intra-subject variations of global network measures.

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Can brain MRI skull-stripping methods be further improved using manual segmentation as ground-truth for validation?
Roberto Souza1, Oeslle Lucena2, Letícia Rittner2, Roberto Lotufo2, and Richard Frayne1

1Seaman Family Magnetic Resonance Research Centre, Calgary, AB, Canada, 2Medical Image Computing Lab, Campinas, Brazil

Automatic skull-stripping (SS) methods have reached a high level of accuracy compared to expert manual segmentation (typically defined as the “ground-truth”), but SS is still an active research area with many methods being proposed every year. In this work, we use twelve T1-weighted brain magnetic resonance (MR) images with each image having two different manual segmentations performed by experts, and four state-of-the-art SS methods to assess if it is possible to evaluate further accuracy improvements to SS. Our results indicate that at the current level of SS accuracy, this is not possible using single expert manual segmentation.

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Lifespan study by cross-sectional case-control comparisons in sliding age windows: test of ASD heterogeneity with One-Class Classifiers
Piernicola Oliva1, Alessia Giuliano2, Paolo Bosco2, Elisa Ferrari3, Michela Tosetti4, Filippo Muratori4, Calderoni Sara4, and Alessandra Retico2

1University of Sassari and National Institute for Nuclear Physics, Cagliari, Italy, 2National Institute for Nuclear Physics, Pisa, Italy, 3University of Pisa, Physics Department and National Institute for Nuclear Physics, Pisa, Italy, 4IRCCS Stella Maris Foundation, Pisa, Italy

Cross-sectional studies reported inconsistent findings on distinctive neuroanatomical characteristics of Autism Spectrum Disorders (ASD). We set up a lifespan study through a series of machine-learning-based case-control comparisons made on sub-cohorts obtained by partitioning a large structural MRI data sample (age range: 2-25 years) in subsamples with partially-overlapping narrower age ranges (3-4 years). We implemented One-Class Support Vector Machines on these sub-cohorts, obtaining the temporal evolution of the case-control separation ability, which is related to the detectability of neuroimaging-based biomarkers. Distinctive common features characterize children with ASD under 5 years of age; the heterogeneity of the ASD condition dominates from adolescence.

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An image-based method for undistorted image estimation from distorted brain EPI image with field inhomogeneity
Seiji Kumazawa1, Takashi Yoshiura2, Takumi Tanikawa1, and Yuji Yaegashi1

1Hokkaido University of Science, Sapporo, Japan, 2Kagoshima University, Kagoshima, Japan

Our purpose was to develop an image-based method for undistorted image estimation from the distorted EPI image using T1 weighted image. Our basic idea to estimate the field inhomogeneity map is to reproduce the distorted EPI image, and estimates the undistorted image using the estimated field inhomogeneity map based on the signal equation in a single-shot EPI k-space trajectory. The value of the NRMSE between the measured EPI and synthesized EPI was 0.017, and both images were in good agreement. Results demonstrate that our proposed method was able to perform a reasonable estimation of the field inhomogeneity map and undistorted EPI image.

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MRIQC Web-API: Crowdsourcing image quality metrics and expert quality ratings of structural and functional MRI
Oscar Esteban1, Ross W Blair1, Dylan M Nielson2, Jan C Varada3, Sean Marrett3, Adam G Thomas2, Russell A Poldrack1, and Krzysztof J Gorgolewski1

1Dept. of Psychology, Stanford University, Stanford, CA, United States, 2Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, United States, 3Functional Magnetic Resonance Imaging Facility, National Institute of Mental Health, Bethesda, MD, United States

The MRIQC Web-API is a resource for scientists to train new automatic quality classifiers. The MRIQC Web-API has collected more than 30K sets of image quality measures automatically extracted from BOLD and T1-weighted scans using MRIQC. MRIQC is an automated MRI Quality Control tool, and here we present an extension to crowdsource these quality metrics along with anonymized metadata and manual quality ratings. This new resource will allow a better understanding of  the normative values and distributions of these quality metrics, help determine  the relationships between image quality and metadata such as acquisition parameters and finally, provide a cost-effective, easy way to annotate the quality of a large number of cross-site MR scans.

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Collaborative volumetric magnetic resonance image rendering on consumer-grade devices
Andrew Dupuis1,2, Dominique Franson1, Yun Jiang3, Jeff Mlakar2, Henry Eastman2, Vikas Gulani3, Nicole Seiberlich1, and Mark A. Griswold1,2,3

1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 2Interactive Commons, Case Western Reserve University, Cleveland, OH, United States, 3Department of Radiology, School of Medicine, Case Western Reserve University, Cleveland, OH, United States

We present a system for intra- or post-acquisition 3D rendering of volumetric MRI datasets for independent or collaborative use on AR/VR and mobile platforms. Consumer-grade head mounted displays, phones, and computers are used to provide 3D visualizations. Datasets can be windowed and leveled in the same manner as classic visualizations, and arbitrary slices can be selected and viewed in real time in the context of the whole volume. Real world dimensionality and spatialization is retained. Using this system, multiple users can interact with a dataset collaboratively using current AR/VR platforms or any modern cellphone, tablet, or laptop. 

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Quantification of Morphometry and Intensity Features of Intracranial Arteries from 3D TOF MRA: A Reproducibility Study
Li Chen1, Mahmud Mossa-Basha 2, Daniel S Hippe 2, Jie Sun2, Niranjan Balu2, Kristi D. Pimentel2, Thomas S Hatsukami3, Jenq-Neng Hwang1, and Chun Yuan2

1Electrical Engineering, University of Washington, Seattle, WA, United States, 2Radiology, University of Washington, Seattle, WA, United States, 3Surgery, University of Washington, Seattle, WA, United States

The aim is to evaluate the reproducibility of intracranial artery feature extraction (iCafe) technique for quantitative analysis of intracranial arteries from 3D time-of-flight (TOF) magnetic resonance angiography (MRA). Twenty-four patients with known intracranial artery stenosis were recruited and underwent two separate MRA scans within 2 weeks. Each dataset was processed blindly using iCafe. Eight morphometry and intensity features were acquired from each artery. The inter-scan reproducibility of iCafe was excellent with intra-class correlation coefficients between 0.92-0.98 and within-subject coefficients of variation between 3.2-8.6% across all features, showing iCafe is a reliable technique for intracranial artery feature quantification from TOF MRA.

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An automatic system for asymmetry vein analysis in patients with acute ischemic stroke
Hanjing Kong1, Wenjian Huang1, Mei Yang1, Weihai Xu2, Yining Huang3, and Jue Zhang1,4

1Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China, 2Department of Neurology, Peking Union Medical College Hospital, Beijing, China, 3Department of Neurology, Peking University First Hospital, Beijing, China, 4College of Engineering, Peking University, Beijing, China

Asymmetry veins in patients with acute ischemic stroke are associated with infarct growth and clinical outcome. However, due to the lack of effective segmentation and quantification methods, these studies focus only on medullary or cortical veins. In this study, an automatic image processing system was developed for asymmetry analysis in medullary and cortical veins using the magnitude data of SWI.

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Quantitative Micro-Vasculature Volume Assessment of Intra Tumoral Susceptibility Signal (ITSS) in differentiating Grade-III from IV glioma
Rupsa Bhattacharjee1,2, Prashant Budania1, Pradeep Kumar Gupta3, Rakesh Kumar Gupta3, Sunita Ahlawat4, and Anup Singh1,5

1Centre for Biomedical Engineering, Indian Institute of Technology, Delhi, New Delhi, India, 2Philips Health Systems, Philips India Limited, Gurgaon, India, 3Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurgaon, India, 4SRL Diagnostics, Fortis Memorial Research Institute, Gurgaon, India, 5Biomedical Engineering, AIIMS, New Delhi, Delhi, India

Angiogenesis transforms gliomas from low-to-high-grade. Vasculature-properties are of essential prognostic-value within grade-III and IV glioma as compared to grade-II. High-resolution susceptibility-weighted imaging (SWI) improves the diagnostic accuracy1. Existing Semi-quantitative methods are user-dependent which manually counts intra-tumoral-susceptibility-signal-intensities (ITSS); a combination of haemorrhage and vasculature. Haemorrhage contributes to false ITSS-count and subsequently to misclassification of tumor-grading. We propose a non-invasive segmentation-based-quantitative approach that calculates the R2-Star relaxivity maps of ITSS, automatically removes haemorrhages from ITSS based on high-R2-Star relaxivity of haemorrhage and finally calculate microvasculature volume within glioma. The proposed-method scores over the existing semi-quantitative method in-terms-of ITSS-estimation and grading-accuracy. 

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SeedNet: a sliding-window convolutional neural network for radioactive seed detection and localization in MRI
Jeremiah Sanders1, Steven Frank2, and Jingfei Ma1

1Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States, 2Radiation Oncology, MD Anderson Cancer Center, Houston, TX, United States

Radioactive seed localization is an essential step in quantifying the dose delivered to the prostate and surrounding anatomy after low-dose-rate prostate cancer brachytherapy. Currently, dosimetrists spend hours manually localizing the radioactive seeds in postoperative images. In this work, we investigated a novel sliding-window convolutional neural network approach for automatically identifying and localizing the seeds in MR images. The method doesn’t rely on prior knowledge of the number of seeds implanted, strand placements, or needle-loading configurations. In initial testing, the proposed approach achieved a recall of 100%, precision of 97%, and processing time of ~0.5-1.5 minutes per patient.

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An improved automatic localization method for abnormal lumbar vertebrae using MR Images
Fei Gao1, Shui Liu2, Xiaodong Zhang2, Jue Zhang1,3, Xiaoying Wang2,3, and Jing Fang1,3

1College of Engineering, Peking University, Beijing, China, 2Department of Radiology, Peking University First Hospital, Beijing, China, 3Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China

In this study, we provide an automatic lumbar localization method efficient for abnormal vertebrae based on the local context information of lumbar MR images. The localization results indicate the efficiency of the proposed method for lumbar vertebrae with various abnormalities.

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An objective tool for diagnosing Prostate Cancer and Benign Prostatic Hyperplasia: Radiomics Featuresextracted from Diffusion-weighted Imaging
Lihua Chen1, Ailian Liu1, Yan Guo2, Xin Li3, and Dan Guo1

1The First Affiliated Hospital of DaLian Medical University, Dalian, China, 2GE Healthcare, China, ShenYang, China, 3GE Healthcare, China, GuangZhou, China

Prostate cancer is the second most common cancer for men, and it has high leading cause of cancer death among men. The term radiomics has attracted increased attention in recent years, and it is the process of the conversion of medical images into high-dimensional, mineable data via high-throughput extraction of quantitative features, followed by subsequent data analysis for decision support.The aim of this study was to evaluate radiomics as a tool to distinguish PCa from BPH based on diffusion-weighted imaging (DWI) sequence without subjective factors.

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User-defined, scanner-integrated, and real-time MRI image analysis in a cloud-based computing environment
Refaat E Gabr1, William J Allen2, Getaneh B Tefera1, Xiaojun Sun1, Renjie He1, Manickam Kumaravel1, Matthew W Vaughn2, and Ponnada A Narayana1

1Diagnostic and Interventional Imaging, University of Texas Health Science Center at Houston, Houston, TX, United States, 2Texas Advacnced Computing Center, University of Texas at Austin, Austin, TX, United States

To enhance the utility of quantitative MRI, we propose a flexible platform for high-performance cloud computing integrated with the MRI scanner. Jetstream, an NSF-sponsored open science platform for high-performance computing resources, was integrated into a clinical 3.0T MRI system for executing user-defined image analysis using the graphical pipeline environment (GRAPE) tool. Integration was achieved through the Agave platform. This framework was used for real-time quantitative T1 mapping for cartilage tissue assessment. Seamless scanner integration enabled immediate access to the results to the interpreting clinician, providing valuable quantitative information which can be incorporated in clinical practice.

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mridata.org: An Open Archive for Sharing MRI Raw Data
Frank Ong1, Shahab Amin1, Shreyas Vasanawala2, and Michael Lustig1

1University of California, Berkeley, Berkeley, CA, United States, 2Radiology Department, Stanford University, Stanford, CA, United States

Current machine learning techniques for image reconstruction require large number of datasets for training, yet the number of public MRI raw datasets is limited. We present mridata.org as an open archive for researchers to share their MRI raw data. The website is designed to facilitate sharing MRI datasets, with features including automatic ISMRMRD conversion from uploaded vendor specific files. We hope that with contributions from many researchers, this website can provide more datasets to train and validate machine learning models for MRI reconstruction.

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qMapIt, a multi-parametric analysis platform for ImageJ
Michael Gerhard Kaul1 and Gerhard Adam1

1Department for Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

Workstations are expensive and the access is often limited. We developed several ImageJ-plugins to build the basis for a multi-parametric imaging platform for ImageJ. ImageJ is a flexible and extendable image processing software that runs with Windows, MacOS and Linux. With qMapIt the researcher has a graphical user interface to selectively import DICOM files and to perform multi-core supported data analysis. Whether relaxation time analysis for T1, T2, T2*, T1ρ, or various diffusion models, or velocity mapping, or vessel size imaging, or pharmacokinetic modelling you name it. Every step can also be addressed in a macro script to automate the workflow. To reduce programming overhead and to speed up the plugin development a fitting and visualisation framework is embedded.

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Pipeline for Registering Histological Sections to MRI Volumes
Istvan N. Huszar1, Karla L. Miller1, Menuka Pallebage-Gamarallage2, Olaf Ansorge2, Christopher Mirfin3, Mattias P. Heinrich4, and Mark Jenkinson1

1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 2Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 3Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom, 4Insitute of Medical Informatics, Universität Lübeck, Lübeck, Germany

Post-mortem MRI–histology comparisons provide great potential to advance our understanding of disease, and validating the source of MRI signals, that is necessary for the development of novel imaging methods to study neurodegeneration. A semi-automated prototype of a registration pipeline is reported, that was designed for conventional sparse histological sampling. Use of the pipeline is demonstrated by inserting individual 25 x 25 mm histological sections to their respective locations in whole-brain MRI data. The registration accuracy is approximately 1 mm.

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Automated breast segmentation with high reproducibility of MR-based breast density measurement
Jie Ding1, Arjun Anilkumar2, Patricia A Thompson3,4, Maria I Altbach5,6, Jean-Philippe Galons5,6, Cynthia A Thomson5, Alison T Stopeck4,7, and Chuan Huang1,2,8,9

1Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States, 2Radiology, Stony Brook Medicine, Stony Brook, NY, United States, 3Pathology, Stony Brook Medicine, Stony Brook, NY, United States, 4Stony Brook University Cancer Center, Stony Brook, NY, United States, 5University of Arizona Cancer Center, Tucson, AZ, United States, 6Medical Imaging, University of Arizona, Tucson, AZ, United States, 7Hematology and Oncology, Stony Brook Medicine, Stony Brook, NY, United States, 8Computer Science, Stony Brook University, Stony Brook, NY, United States, 9Psychiatry, Stony Brook Medicine, Stony Brook, NY, United States

Breast density(BD) is a significant risk factor for breast cancer and serves as a biomarker of risk in clinical trials. Breast segmentation is the first and an important step for accurate and reproducible BD estimation. However, the conventional manual segmentation is labor-intensive and bias-prone. Based on fat-water decomposition MRI, we developed an automated breast segmentation method and validated it against manual segmentation using 50 test-retest scans. The BD measures using our automated segmentation were very comparable to results from manual segmentation, and exhibited extremely high test-retest reproducibility. Our automated segmentation yielded more reproducible BD measures than the manual segmentation method.

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Feature Extraction and Analysis for Characterization of Breast Lesion Type using Multi-parametric MRI
Snekha Thakran1, Subhajit Chatterjee1,2,3, Rakesh Kumar Gupta4, and Anup Singh1,5

1Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, 2C-DOT India, New Delhi, India, 3Computer Science and Engineering, Indian Institute of Technology Delhi, New Delhi, India, 4Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurgaon, India, New Delhi, India, 5Department of Biomedical Engineering, All India Institute of Medical Sciences Delhi, New Delhi, India

Quantitative analysis of T1-perfusion data provides estimation of hemodynamic and physiological parameters of tissue. Texture analysis uses mathematical approach to distinguish the spatial distribution of signal intensity variations. In this study, we computed different texture and quantitative parameters in terms of characterizing histological types (lobular and ductal) of invasive breast cancer. Experimental results revealed that combination of texture and quantitative features provided highest sensitivity and specificity to differentiate IDC and ILC breast lesions.

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Detection of Liver Fibrosis using Strain-Encoding MRI and Support Vector Machine
Inas A Yassine1,2, Mai Wael1, Mohamed Elmahdy2, Tamer Basha2, Ahmed S Fahmy1,2, Ralph Sinkus3, Theo Heller4, Ahmed M Gharib5, and Khaled Z Abd-Elmoniem5

1School of communication and Information Technology, Nile University, Cairo, Egypt, 2Systems and Biomedical Engineering Department, Cairo University, Cairo, Egypt, 3Biomedical Engineering Department, King’s College, London, United Kingdom, 4Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, United States, 5Biomedical and Metabolic Imaging Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, United States

This study proposes a device-free semi-automatic liver fibrosis identification system based on Strain Encoded (SENC) MRI. SENC-MRI was applied to quantify liver deformation induced by the heart motion over the cardiac cycle. Twenty-two patients with different stages of biopsy proven liver fibrosis and ten healthy subjects were imaged using SENC-MRI. A Support Vector Machine (SVM) classification system was used to classify the strain and strain rate for both the patients and healthy subjects. Based on leave-one-out cross validation. Strain and strain rate were more robust than the peak-to-peak value based classification, which has bias towards the sensitivity. The proposed method showed classification accuracy of 87.5% with sensitivity and specificity of 90.0% and 90%, respectively.

3431
Computer 119
A Methodology Towards Registering Prostate Histology and Radiologic Imaging to Validate Prostate Cancer Detection in 2D
Brandon Caldwell1,2, Meltem Uyanik2, Michael Abern1, Virgilia Macias3, Cristian Luciano2, and Richard Magin2

1Urology, University of Illinois at Chicago College of Medicine, Chicago, IL, United States, 2Bioengineering, University of Illinois at Chicago, Chicago, IL, United States, 3Pathology, University of Illinois at Chicago College of Medicine, Chicago, IL, United States

In-vivo radiological imaging is used globally to detect possible cancers and inform treatment decisions, but difficulties arise when attempting to compare radiological findings to the gold-standard of diagnosis, histopathology. Standard imaging protocols have documented success but to determine the reliability of new imaging sequences and modalities, correlation to histopathology must be made. Several methods have been proposed for registration in both 2D and 3D, but these have shown limited effectiveness and often require unique equipment or proprietary algorithms. In this study, we attempt to complete an accurate registration in 2D in order to validate different imaging modalities.

3432
Computer 120
Combined Visual Analysis of Myocardial Strain and Intra-Ventricular Blood Flow
Chitiboi Teodora1, Anja Hennemuth2, Lennart Tautz3, and Leon Axel1

1New York University School of Medicine, New York, NY, United States, 2Charité Universitätsmedizin Berlin, Berlin, Germany, 3Fraunhofer MEVIS, Bremen, Germany

Intra-ventricular blood flow dynamics are closely related to both ventricle and valve geometry and to the contraction pattern of the myocardial wall.  The interaction mechanisms between contraction forces inside the myocardium and hydrodynamic forces are highly complex and have not yet been fully understood, especially in the presence of pathology. We propose a visual analysis framework for the integrated assessment of ventricle and valve morphology, blood flow and local myocardial function. This is a first step to enable better understanding of the different mechanical factors involved in hypertrophic cardiomyopathy (HCM) and their combined contributions to the formation of obstructive HCM.


Electronic Poster

Velocity & Flow

Exhibition Hall Monday 14:45 - 15:45

3433
Computer 1
Quantification of 3D aortic wall shear stress using k-t accelerated 4D flow MRI in under 2 minutes: a two center study
Emilie Bollache1, Kristopher Knott2, Redha Boubertakh2, Ryan Scott Dolan1, Claudia Camaioni2, Saadullah Ahmed-Villiers2, Thomas Treibel2, James C Carr1, Pim van Ooij3, Jeremy D Collins1, Julia Geiger4, James Moon2, Alex J Barker1, Steffen E Petersen2, and Michael Markl1,5

1Department of Radiology, Northwestern University, Chicago, IL, United States, 2Barts Heart Centre, London, United Kingdom, 3Department of Radiology, Academic Medical Center, Amsterdam, Netherlands, 4University Children's Hospital, Zurich, Switzerland, 5Department of Biomedical Engineering, Northwestern University, Chicago, IL, United States

Our aims were to study the feasibility at two centers of a newly developed k-t accelerated non-navigator gated 2-minute aortic 4D flow MRI sequence and to evaluate its wall shear stress (WSS) estimates. Eleven and 14 healthy volunteers, as well as 10 and 6 patients were scanned at Northwestern University and Barts Heart Centre, respectively. Despite an underestimation of distal aortic WSS in patients when compared to conventional 4D flow, our measurements were sensitive to expected aging and disease-related variations. We confirmed that aortic 4D flow MRI in 2 minutes is feasible and provides consistent WSS measurements.

3434
Computer 2
Quantitative evaluation of compressed sensing reconstruction in mouse phase contrast 4D-flow Magnetic Resonance Imaging
Moritz Braig1, Marius Menza1, Jochen Leupold1, Li Feng2, Pierre LeVan1, Juergen Hennig1, Axel J Krafft1, and Dominik von Elverfeldt1

1Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany, 2Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, United States

Preclinical 4D-flow measurements remain challenging due to long acquisition times. This study presents a retrospective analysis of 4D-flow measurements with a radial 3D phase contrast sequence in combination with an advanced compressed sensing reconstruction. We evaluate the impact of different undersampling factors regarding peak velocities, flow, wall shear stress values and streamline analysis. We could show that high acceleration factors for preclinical phase contrast imaging can be used without substantially degrading the quantitative results. Our findings might enable high resolution 4D-flow acquisitions in less than one hour.

3435
Computer 3
Exploring vessel inward normal computation for 4D flow based wall shear stress estimation in complex vessel geometries.
Judith Zimmermann1,2, Daniel Demedts3, Michael Markl4, Christian Meierhofer2, Heiko Stern2, and Anja Hennemuth3,5

1Department of Computer Science, Technical University of Munich, Munich, Germany, 2Department of Pediatric Cardiology and Congenital Heart Defects, German Heart Center Munich, Munich, Germany, 3Fraunhofer MEVIS Institute for Medical Image Computing, Bremen, Germany, 4Departments of Radiology and Biomedical Engineering, Northwestern University Feinberg School of Medicine, Chicago, IL, United States, 5Institute for Computational and Imaging Science in Cardiovascular Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany

Wall shear stress (WSS) is a hemodynamic parameter which can be estimated from 4D flow MRI. The aim of this work was to advance the surface inward normal computation for complex (i.e. cone-shaped) vessel geometries and thus to improve the accuracy of wall shear stress estimates. We propose a Gauss gradient field approach to adapt to complex vessel courses and evaluate our method using synthetic flow data and selected patient data. Results show that correct inward normal definition is crucial for reliable WSS estimates, in particular in cases where complex vessel geometries are present.  

3436
Computer 4
On the Influence of Intravoxel Velocity Distributions on the Noise of Phase Contrast Velocimetry
Simon Schmidt1, Sebastian Flassbeck1, Mark E. Ladd1, and Sebastian Schmitter1,2

1Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany

In this work we investigate the influence of intravoxel velocity distributions on the velocity noise in phase contrast velocimetry. Intravoxel velocity distributions are directly measured via Fourier velocity encoding and subsequently fitted by Gaussian distributions. Taking intravoxel dephasing due to a finite distribution width into account, a noise-optimized VENC is calculated for phantom flow measurements and in-vivo data at 7 Tesla.

3437
Computer 5
Whole-heart 4D phase-contrast MRI for clinical cardiovascular flow analysis: a comparison and validation on an imaging pulse sequence aspect
Shuo Zhang1,2, Jun-Mei Zhang1,3, Jennifer Ann Bryant1, Bao Ru Leong1, Pankaj Garg4, Rob van der Geest5, Ru San Tan1,3, and Liang Zhong1,3

1National Heart Centre Singapore, Singapore, Singapore, 2Philips Healthcare Singapore, Singapore, Singapore, 3Duke-NUS Medical School Singapore, Singapore, Singapore, 4Division of Biomedical Imaging, University of Leeds, Leeds, United Kingdom, 5Department of Radiology, Leiden University Medical Center, Leiden, Netherlands

Whole-heart 4D phase-contrast magnetic resonance imaging (4D PC-MRI) provides qualitative and quantitative cardiovascular flow information. Recent technological advances in acquisition have rendered its clinical adoption without breath hold or respiratory gating. However, with different acquisition methods available their accuracy and influence in flow measurement are not well studied. We report our result in comparison of different commercially available imaging pulse sequences with validation to conventional 2D PC-MRI in healthy volunteers and patients with congenital heart disease.

3438
Computer 6
Feasibility of 4D phase-contrast MRI for the assessment of blood flow in the fetal aorta using Doppler ultrasound gating: preliminary results
Fabian Kording1, Bjoern P Schoennagel1, Christian Ruprecht1, Daniel Giese2, Einar Heiberg 3, Manuela Tavares4, and Jin Yamamura1

1Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 2Department of Radiology, University Hospital Cologne, Cologne, Germany, 3Lund University, Lund, Sweden, 4University Medical Center Hamburg-Eppendorf, Hamburg, Germany

Fetal magnetic resonance imaging (MRI) is increasingly used as a second-line imaging tool for prenatal evaluation. The recet Doppler ultrasound trigger method enables the use of cardiovascular imaging techniques which may be usefull  to improve prenatal cardiovascular imaging.  This work investigates the use of 4D phase contrast measurements for the visualisation and quantification of fetal blood flow in the great vessels. In a small study group (n=2) it was shown for the first time that 4D flow measurements are feasible in the fetal vessels which may be beneficial for visualization and quantification of complex congenital cardiovascular malformations.


3439
Computer 7
Magnetic Particle Imaging based 4D flow analysis technique using regional MRI data evaluation – initial in vivo results of a beating rodent heart
Jochen Franke1,2, Heinrich Lehr1, and Volkmar Schulz2

1Preclinical Imaging, Bruker BioSpin MRI GmbH, Ettlingen, Germany, 2Physics of Molecular Imaging Systems, University RWTH Aachen, Aachen, Germany

A dual-modal cardiovascular in vivo assessment in rodents was performed using a highly integrated Magnetic Particle Imaging – Magnetic Resonance Imaging hybrid system. 4D velocity flow field estimation of a beating rodent heart was extracted from the pulsed tracer information within the MPI dataset of a non-toxic tracer bolus. By means of co-registered morphological MRI data acquired at 0.5 T, an anatomical regional velocity flow field evaluation was performed for the four heart chambers individually.

3440
Computer 8
Dual-venc and single-venc 4D Flow MRI in cerebral aneurysms in comparison to image-based CFD modeling
Joseph Christopher Muskat1, Sean Rothenberger1, Ahmadreza Baghaie1, Sameer A Ansari2, Craig Goergen1, Susanne Schnell3, Michael Markl3,4, and Vitaliy Rayz1

1Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States, 2Radiology, Neurological Surgery and Neurology, Northwestern University, Chicago, IL, United States, 3Radiology, Northwestern University, Chicago, IL, United States, 4Biomedical Engineering, Northwestern University, Evanston, IL, United States

Blood flow in two cerebral aneurysms was measured with 4D Flow MRI and simulated with image-based Computational Fluid Dynamics (CFD). A dual-venc 4D Flow MRI sequence with a shared reference scan was used in addition to a standard, single-venc 4D Flow acquisition in order to improve the dynamic range of measured velocities. Comparison of the MRI-measured and CFD-simulated flow fields showed that the 4D Flow and CFD methods can complement each other by eliminating modeling errors and augmenting imaging resolution. The dual-venc 4D Flow MRI provided valuable information on recirculating flow patterns that was not available from the single-venc data.

3441
Computer 9
Modeling Physiological Flow Variation in Total Cavopulmonary Connection with Physical Model Experiments and 4D Flow MRI
David R Rutkowski1,2, Ryan Valk3, Christopher J François2, and Alejandro Roldán-Alzate1,2,4

1Mechanical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 2Radiology, University of Wisconsin-Madison, Madison, WI, United States, 3Medicine, University of Wisconsin-Madison, Madison, WI, United States, 4Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States

The total cavopulmonary connection (TCPC) is a successful treatment for single ventricle defect, however, long term complications, such as exercise intolerance still occur.  To examine the effects of exercise conditions on TCPC fluid dynamics, in vitro experiments using 4D Flow MRI were conducted at high and low flow conditions.  Significant difference in pulmonary flow distribution between conditions was found, and flow patterns and structures were characterized. After further development these models may provide a useful tool for analyzing and predicting changes in a variety of patient specific TCPC anatomy.

3442
Computer 10
Blood Velocity Measurement by RF Phase Gradient Differences between Receiver Coils: Initial Work towards Stenotic Jet Velocity
Jonathan Wagner1, Peter David Gatehouse2, and David Nigel Firmin2

1Imperial College, London, United Kingdom, 2Cardiac MRI, Royal Brompton Hospital, London, United Kingdom

Fluid velocity was measured in vitro using the difference between spatial phase responses of array coils in 1993 by Famili, Wright and Porter. Aiming at application to cardiovascular stenotic jets, this abstract re-investigates their method with newer coil arrays and adds a multi-echo approach enabling aortic velocity measurement in normal subjects, with moderate results.

3443
Computer 11
Self-Gated Golden-Angle Spiral 4D Flow MRI
Rene Bastkowski1, Kilian Weiss1,2, David Maintz1, and Daniel Giese1

1Radiology, University Hospital of Cologne, Cologne, Germany, 2Philips GmbH Healthcare, Hamburg, Germany

A time efficient fully self-gated 4D flow sequence is presented that operates at predictable scan times and allows for a retrospective binning into an arbitrary number of cardiac and/or respiratory states. The acquisition time is fixed independently of the subjects’ physiology. Data is reconstructed using conjugate-gradient-SENSE. Feasibility is shown in 10 healthy volunteers and results are compared to a standard Cartesian 4D flow sequence.

3444
Computer 12
Evaluation of aortic viscous energy loss, kinetic energy and association with pumping function in congenital patients with transposition of great arteries using time-varying aortic geometry: Volumetric 4D Flow MRI Analysis
Covadonga Terol Espinosa de los Monteros1, Roel L.F. Van der Palen1, Arno A.W. Roest1, Pieter J. Van den Boogaard2, Lucia J.M. Kroft2, Westenberg J.M. Jos2, and Mohammed S.M. Elbaz2

1Pediatric Cardiology, Leiden University Madical Ceneter, Leiden, Netherlands, 2Radiology, Leiden Univeristy Medical Center, Leiden, Netherlands

Aortic hemodynamic energetics including kinetic energy (KE) and non-turbulent viscous energy loss (EL) and the association with cardiac function were evaluated in 8 TGA patients after arterial switch operation (ASO) and in 8 healthy individuals by 4D flow MRI. EL was significantly increased in TGA compared to healthy volunteers and aortic regions of highest levels indicate influence of complex ASO-related aortic geometry on blood flow efficiency. Significant positive correlation between aortic EL and cardiac index was found. Understanding the impact of ASO on aortic blood flow efficiency might enable insights on ways to improve operative procedure for TGA in future.

3445
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CArtesian sampling with Variable density and Adjustable temporal resolution (CAVA)
Adam Rich1, Ning Jin2, Yingmin Liu3, Lee C. Potter4, Orlando P. Simonetti3,5,6, and Rizwan Ahmad1,3

1Department of Biomedical Engineering, The Ohio State University, Columbus, OH, United States, 2Siemens Medical Solutions, Columbus, OH, United States, 3Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, United States, 4Electrical and Computer Engineering, The Ohio State University, Columbus, OH, United States, 5Division of Cardiovascular Medicine, Department of Internal Medicine, The Ohio State University, Columbus, OH, United States, 6Department of Radiology, The Ohio State University, Columbus, OH, United States

We present a variable density Cartesian sampling method that allows retrospective adjustment of temporal resolution, providing added flexibility for real-time applications where optimal temporal resolution may not be known in advance. This method, called CArtesian sampling with Variable density and Adjustable temporal resolution (CAVA), is validated using real-time, free-breathing phase-contrast MRI data from four volunteers. Diagnostic quality images were successfully recovered at different temporal resolutions. Also, flow quantification based on CAVA was in good agreement with the breath-held segmented acquisition. In summary, CAVA provides a Cartesian alternative to Golden Angle-based radial sampling and can benefit a wide range of 2D real-time applications.

3446
Computer 14
4D Flow MRI velocity encoding effects on in vitro aortic dissection false lumen velocity distribution
Sylvana García-Rodríguez1, Philip Corrado2, Jon Wrobel3, Timothy Aaron Ruesink4, Alejandro Roldán-Alzate1,4, and Christopher Jean François1

1Department of Radiology, University of Wisconsin - Madison, Madison, WI, United States, 2Department of Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, 3School of Medicine, University of Wisconsin - Madison, Madison, WI, United States, 4Department of Mechanical Engineering, University of Wisconsin - Madison, Madison, WI, United States

Selecting the appropriate velocity sensitivity is critical in assessing flow within the false lumen of aortic dissections, where low velocities are dominant. This study compares effects of two VENC settings on velocity distribution within the false lumen of 3D printed aortic dissection models. We observed significant changes in velocity distributions depending on the VENC selected for the 4D Flow MRI acquisition. This difference tends to be accentuated at lower flow rates and would have important implications on calculations of other hemodynamic parameters, including wall shear stress, kinetic energy and vorticity, which may be predictors of outcomes in aortic dissection patients.

3447
Computer 15
Rapid, real-time phase-contrast MRI using a combination of radial k-space sampling and compressed sensing with spatially varying regularization weights
Hassan Haji-valizadeh1, Bradley D. Allen2, Roberto Sarnari3, Matthew Barrett4, and Daniel Kim2

1Biomedical Engineering, Northwestern University, Evanston, IL, United States, 2Radiology, Northwestern University, Chicago, IL, United States, 3Radiolgy, Northwestern University, Chicago, IL, United States, 4Cardiology, Northwestern University, Chicago, IL, United States

We sought to develop a compressed sensing reconstruction method for radial k-space derived real-time phase contrast that uses spatially varying regularization to reduce flickering artifacts without significant loss in quantified flow accuracy, and evaluate its performance with respect to clinical breath-hold phase contrast in patients undergoing aortic valve evaluation with cardiovascular MRI.

3448
Computer 16
Pseudo Spiral Compressed Sensing for Aortic 4D flow MRI: a Comparison with k-t Principal Component Analysis
Lukas M. Gottwald1, Eva S. Peper1, Qinwei Zhang1, Bram F. Coolen2, Gustav J. Strijkers2, R. Nils Planken1, Aart J. Nederveen1, and Pim van Ooij1

1Radiology, Academic Medical Center, Amsterdam, Netherlands, 2Biomedical Engineering & Physics, Academic Medical Center, Amsterdam, Netherlands

In this study, 8-fold pseudo spiral compressed sensing (CS) accelerated aortic 4D flow MRI was compared with 8-fold k-t principal component analysis (k-t PCA) acceleration. Scan times were approximately 7 minutes at 50% respiratory navigator efficiency. Image quality of the peak systolic phase contrast magnitude images was scored slightly higher for CS than for k-t PCA and time-resolved velocity pathline trajectories were similar. Quantitative hemodynamic differences in velocity and wall shear stress were found but these were small and can be attributed to a combination of acquisition strategy and physiological variation. CS can be used to accelerate 4D flow MRI.

3449
Computer 17
Vortex Flow in Left Ventricle Interrupts Efficient Ejection: Demonstration by Vortex Flow Map of Cardiac Cine Magnetic Resonance Imaging
Masateru Kawakubo1, Kenji Fukushima2, Risako Nakao3, Eri Watanabe3, Yamato Shimomiya4, Yasuhiro Goto5, Hitoshi Tadenuma5, Masami Yoneyama6, and Michinobu Nagao2

1Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, Fukuoka, Japan, 2Department of Diagnostic Imaging & Nuclear Medicine, Tokyo Women’s Medical University, Tokyo, Japan, 3Department of Cardiology, The Heart Institute of Japan, Tokyo Women’s Medical University, Tokyo, Japan, 4Clinical Application Development Marketing Division, Ziosoft Inc., Tokyo, Japan, 5Department of Radiological Service, Tokyo Women’s Medical University, Tokyo, Japan, 6Philips Electronics Japan, Ltd., Tokyo, Japan

Quantitative characterization of vortex flow might be a novel objective tool for evaluating left ventricular (LV) function. We developed the novel technique of vortex flow map (VFM). The VFM based on MR feature tracking can calculate the temporal displacement of the pixels on standard cine MRI. In this study, we analyzed the association with the VFM in LV and ejection fraction. As a result, it is indicated that the strong 3-dimensional vortex flow appears and impairs efficient LV ejection in severe heart failure. And the VFM is a useful tool for the evaluation of the efficiency of LV ejection.

3450
Computer 18
A dedicated MRI flow laboratory for quantitative flow measurements and method development
Martin Bruschewski1 and Sven Grundmann1

1Institute of Fluid Mechanics, University of Rostock, Rostock, Germany

A unique MRI flow laboratory is currently being commissioned at the University of Rostock. The laboratory is specifically designed for quantitative measurements in technical flows. The MRI system, a whole-body Magnetom Trio (Siemens, Erlangen, Germany), will be integrated into various flow circuits with water and other fluids. This MRI system is not intended for clinical trials. Instead, the research focuses on the development and validation of flow quantification methods for medical and technical applications. The long-term aim is to make MRI more available to the field of fluid mechanics research and flow engineering.

3451
Computer 19
Assessment of Pulmonary Artery Mean Pressure with MRI and 4D Flow Vortex Assessment.
Lindsey Alexandra Crowe1, Anne-Lise Hachulla1, Gabriel Guglielmi1, Maurice Beghetti2, Frederic Lador3, and Jean-Paul Vallée1

1Division of Radiology, Geneva University Hospitals, Geneva, Switzerland, 2Division of Pediatric Cardiology, Geneva University Hospitals, Geneva, Switzerland, 3Division of Pneumology, Geneva University Hospitals, Geneva, Switzerland

Flow vortices have been observed in patients with elevated pulmonary artery pressure.  We investigated 4D flow MRI and software packages to quantify vortex duration.  This parameter was assessed compared to other MRI derived measurements to provide a potential non-invasive alternative to right heart catheterization.

3452
Computer 20
Effect of gravity on inferior vena cava and abdominal aortic flow: evaluation using multi-posture MRI
Yoshisuke Kadoya1, Tosiaki Miyati1, Naoki Ohno1, Satoshi Kobayashi1, and Toshifumi Gabata1

1Kanazawa University Graduate School of Medical Sciences, Kanazawa, Japan

Inferior vena cava flow (IVCF) and abdominal aortic flow (AAF) are seems to be affected by gravity, ie., it depends on the body posture. We validated the effect of gravity on IVCF and AAF in supine and upright positions using an original multi-posture MRI. IVCF/AAF mean velocity, IVCF/AAF maximum velocity, mean IVCF/AAF, maximum IVCF/AAF in the upright position were significantly lower than those in the supine position. The cross-sectional area of IVC was significantly lower than those in the supine position, but that of AA was not significantly changed. Both IVCF and AAF decrease in the upright position.

3453
Computer 21
Experimental Validation of 4D Flow MRI for the Assessment of Recirculation and Acceleration using Tomographic Particle Image Velocimetry
Rafael Medero1 and Alejandro Roldán-Alzate1,2,3

1Mechanical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 2Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 3Radiology, University of Wisconsin-Madison, Madison, WI, United States

4D flow MRI has shown to be a feasible tool for the assessment of hemodynamics in different vascular territories, however reliable validation using gold standard fluid dynamics experiments is needed for improvement of its accuracy and precision. Particle image velocimetry (PIV) is an experimental technique widely used in engineering analysis of fluids. PIV measures flow velocity by optically tracking the movement of laser-illuminated particles. The purpose of this study was to validate 4D Flow MRI for the assessment of flow recirculation and acceleration using tomographic PIV.

3454
Computer 22
4D flow MRI: Preliminary in vivo results comparing two commercially available analysis software platforms
Christopher J François1, Lindsay M Griffin1, Niti R Aggarwal2, and Mark L Schiebler1

1Radiology, University of Wisconsin-Madison, Madison, WI, United States, 2Cardiovascular Medicine, University of Wisconsin-Madison, Madison, WI, United States

Main pulmonary artery (MPA) and ascending aorta flow was quantified from 4D flow MRI using two commercially available software programs. Flow measurements made in three locations in each of these vessels were internally consistent with negligible bias for both programs. Furthermore, differences in mean MPA and aorta flow between programs were also negligible. These preliminary results are encouraging in affirming the reproducibility and reliability of flow measurements from clinical 4D flow MRI acquisitions.

3455
Computer 23
4D Flow MRI assessment of hypertrophic cardiomyopathy –the comparison with pressure gradient measured by Doppler ultrasound-
Kotomi Iwata1, Tetsuro Sekine1, Masaki Tachi1, Yoichi Imori2, Minako Takeda1, Yasuo Amano3, Makoto Obara4, Yoshio Matsumura1, and Shin-ichiro Kumita1

1Radiolody, Nippon Medical School, Tokyo, Japan, 2Cardiology, Nippon Medical School, Tokyo, Japan, 3Radiology, Nihon University, Tokyo, Japan, 4Philips Electronics Japan Ltd., Tokyo, Japan

The purpose of this study was to compare the flow abnormality based on 4D Flow MRI data with the PG measured by Doppler ultrasound. we enrolled 9 patients who underwent echocardiography followed by 4D Flow MRI. Helical grade of HOCM group was higher than that of HNCM group (2.33±0.47 vs. 1.33±0.47, p=0.032). There was no significant difference between HG and each characteristic of HCM (PG, septal thickness, septum/free wall ratio and the presence of SAM). 4D Flow MRI can visualize abnormal helical flow of ascending aorta in patients with hypertrophic obstructive cardiomyopathy.

3456
Computer 24
Regional distribution of Local 3D Pulse Wave Velocity with and without Aortic Arch Replacement in Pediatric Patients with Single Ventricle
Amol S. Pednekar1, Matthew Goette1, Prakash Masand1, and Cory Noel2

1Radiology, Texas Children's Hospital, Houston, TX, United States, 2Cardiology, Texas Children's Hospital, Houston, TX, United States

PC-CMR permits precise discrete 3D aortic pulse wave velocity (PWV) measurements as a surrogate for changes in vascular stiffness and ventricular-vascular interaction. In this preliminary study, global PWVs are 50% higher in 3 single ventricle (SV) patients with reconstructed arch (RA) than 3 patients with native arch (NA). Furthermore, the regional distribution of PWVs in SV-RA indicates rapid deceleration (50-70%) from proximal to distal aorta that is absent in SV-NA. The abnormal shape, large caliber change, and prosthetic material of reconstructed aortas may be additional explanatory variables. Regional distribution of local PWVs could potentially predict development of abnormal ventricular-vascular interaction.


Electronic Poster

Atherosclerosis & Vessel-Wall Imaging

Exhibition Hall Monday 14:45 - 15:45

3457
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High Spatiotemporal Resolution Dynamic Contrast Enhanced (DCE) For Assessing Vascular Inflammation: Initial Clinical Experience
Nan Wang1,2, Anthony Christodoulou1, Yibin Xie1, Zixin Deng1,2, Bill Zhou1,3, Zhaoyang Fan1,3, Wei Yu4, and Debiao Li1,2

1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 2Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, 3Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States, 4Department of Radiology, Anzhen Hospital, Beijing, China

Dynamic contrast enhanced (DCE) MRI is a promising technique for quantitatively assessing the inflammation of atherosclerosis. However, current applications are facing demanding sampling challenges, and compromises have to be made among spatial resolution, coverage and temporal resolution. We recently proposed a 3D DCE protocol based on Low Rank Tensor (LRT) framework to achieve high spatiotemporal resolution, adequate anatomical coverage and dynamic T1 mapping. In this work, we demonstrated the in vivo feasibility on both healthy subjects and patients with known atherosclerosis. 

3458
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An inverse association between microvasculature and intraplaque hemorrhage in atherosclerotic carotid lesions: an MR imaging study
Geneviève Crombag1,2, Raf van Hoof1, Floris Schreuder3, Martine Truijman4, Sylvia Heeneman5, Paul Nederkoorn6, Werner Mess2,7, Robert van Oostenbrugge2,4, Jan-Willem Daemen8, Mat Daemen9, Joachim Wildberger1,2, and Eline Kooi1,2

1Radiology & Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands, 2Cardiovascular Research Institute Maastricht, Maastricht, Netherlands, 3Department of Neurology & Donders Institute for Brain Cognition & Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands, 4Neurology, Maastricht University Medical Center, Maastricht, Netherlands, 5Pathology, Maastricht University Medical Center, MAastricht, Netherlands, 6Neurology, Amsterdam Medical Center, Amsterdam, Netherlands, 7Clinical Neurophysiology, Maastricht University Medical Center, Maastricht, Netherlands, 8Surgery, Maastricht University Medical Center, Maastricht, Netherlands, 9Pathology, Amsterdam Medical Center, Amsterdam, Netherlands

The presence of intraplaque haemorrhage (IPH) has been related to plaque rupture, plaque progression, and predicts cerebrovascular events. However, the mechanisms leading to IPH are not fully understood. The dominant view is that IPH is caused by leakage of erythrocytes from immature microvessels. 101 patients underwent MRI of the symptomatic carotid plaque for detection of IPH and dynamic contrast-enhanced MRI for assessment of plaque microvasculature. A decreased vessel wall Ktrans was found for IPH positive patients. No difference in adventitial Ktrans was found in patients with and without IPH. Not only leaky plaque microvessels, but additional factors may contribute to IPH development.

3459
Computer 27
Decreased plaque microvasculature in symptomatic carotid plaques: a DCE-MRI study
Geneviève Crombag1,2, Raf van Hoof1, Floris Schreuder3, Martine Truijman4, Tobien Schreuder5, Narender van Orshoven6, Werner Mess2,7, Paul Hofman1, Robert van Oostenbrugge2,4, Joachim Wildberger1,2, and Eline Kooi1,2

1Radiology & Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands, 2Cardiovascular Research Institute Maastricht, Maastricht, Netherlands, 3Department of Neurology & Donders Institute for Brain Cognition & Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands, 4Neurology, Maastricht University Medical Center, Maastricht, Netherlands, 5Neurology, Zuyderland Medical Center, Sittard, Netherlands, 6Zuyderland Medical Center, Sittard, Netherlands, 7Clinical Neurophysiology, Maastricht University Medical Center, Maastricht, Netherlands

Rupture of a vulnerable atherosclerotic plaque can lead to thrombus formation and, subsequently, to ischemic events. Intraplaque microvessels are thought to play an important role in atherogenesis, since they may facilitate entrance of red blood cells and inflammatory cells into the plaque tissue due to increased endothelial permeability. Symptomatic patients underwent DCE-MRI to assess plaque microvasculature. A significantly lower vessel wall Ktrans was found in the symptomatic carotid plaque compared to the contralateral asymptomatic side. The decrease in vasa vasorum in the symptomatic plaques might be due to a higher amount of necrotic tissue on this side.

3460
Computer 28
Feature Extraction using Convolutional Networks for Identifying Carotid Artery Atherosclerosis Patients in a Heterogeneous Brain MR Dataset
Mariana Bento1, Luis A. Souto Maior Neto2, Marina Salluzzi3, Yunyan Zhang1, and Richard Frayne1

1Departments of Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada, 2Biomedical Engineering, University of Calgary, Calgary, AB, Canada, 3Calgary Image Processing and Analysis Centre, Foothills Medical Centre, Calgary, AB, Canada

Analysis of pathology in patients from heterogeneous datasets using machine learning techniques provide valuable information for identifying patients with carotid artery atherosclerosis disease. We propose and evaluate a method to automatically identify these patients based only on MR brain imaging findings in a dataset also containing multiple sclerosis patients and healthy control subjects. The features extracted using convolutional networks were discriminative, showing high accuracy rates (>96%) to distinguish between the three classes: atherosclerosis patients, multiple sclerosis patients or healthy controls. The method may help specialists in the diagnosis (specially in critical cases), and evaluation of disease activity.  

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Investigating the estimated intracranial wall thickness on MRI vessel wall images: what voxel size do we need?
Kees M. van Hespen1, Jaco J.M. Zwanenburg2, Anita A. Harteveld2, Peter R. Luijten2, Jeroen Hendrikse2, and Hugo J. Kuijf3

1Center for Image Sciences, UMC Utrecht, Utrecht, Netherlands, 2Department of Radiology, UMC Utrecht, Utrecht, Netherlands, 3Image Sciences Institute, UMC Utrecht, Utrecht, Netherlands

We investigated the influence of voxel size on the accuracy and precision of intracranial vessel wall thickness measurements on MR images. Circle of Willis specimens were scanned at ultra-high resolution (0.11mm). Downsampling these images showed that distinguishing thin (0.35-0.45mm), medium (0.65-0.75mm) and thick (0.95-1.05mm) vessel walls requires voxel sizes below 0.55-0.66mm, although thickness measurements showed considerable bias at those resolutions. Unbiased measurements required a voxel size of 0.2mm or less. A clinically used MRI protocol (0.8mm), could only correctly measure vessel walls thicker than 0.9mm. In summary, current intracranial vessel wall MRI protocols provide limited quantification of vessel wall thickness.

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Precision and Accuracy of Coronary Cross-Sectional Area MRI Measurements Used to Measure Coronary Endothelial Function
Michael Schär1, Sahar Soleimanifard1, Gabriele Bonanno1,2, Jérôme Yerly3,4, Allison G Hays2, and Robert G Weiss1,2

1Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 3Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 4Center for Biomedical Imaging (CIBM), Lausanne, Switzerland

Coronary endothelial function (CEF) can be measured noninvasively with MRI by quantifying changes in coronary artery cross-sectional area in response to isometric handgrip exercise. Those area changes are only a few imaging pixels because of MRI’s limited spatial resolution. Here we show with both numerical simulations and phantom measurements that 8-fold Fourier interpolation enables sub-pixel area measurement precision. Second, area measurement precision and accuracy can be further improved with smaller acquisition voxels as long as the signal-to-noise ratio remains above 30. Third, the currently used CEF-MRI protocol distinguishes area-changes of less than 5%  at SNR measured in vivo.

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3D dual-contrast vessel wall imaging of the aortic arch
Zhaoyang Fan1,2, Qi Yang1,3, Guoxi Xie4, Xiaoming Bi5, Shlee Song1, Marcel Maya1, and Debiao Li1,2

1Cedars-Sinai Medical Center, Los Angeles, CA, United States, 2University of California, Los Angeles, CA, United States, 3Xuanwu Hospital, Beijing, China, 4Guangzhou Medical University, Guangzhou, China, 5Siemens Healthineers, Los Angeles, CA, United States

Atherosclerotic disease of the aortic arch has been considered a potential cause of cryptogenic stroke. Vessel wall MR imaging can directly probe atherosclerotic lesions to provide assessment of plaque burden and instability. However, its clinical adoption for the aortic arch is hindered primarily by long imaging time that is associated with the needs for large spatial coverage, high spatial resolution, compensation of motion, and multiple image contrasts. In this work, we proposed a fast 3D dual-contrast vessel wall MR technique that is potentially useful for detecting intraplaque hemorrhage and calcification as well as measuring plaque burden at the aortic arch.             

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Quantitatively monitoring therapeutic response in  patients with symptomatic intracranial atherosclerotic disease using 3D MR plaque imaging
Zhaoyang Fan1,2, Qi Yang1,3, Feng Shi1, Shlee Song1, Konrad Schlick1, Mercel Maya1, Nestor Gonzalez1, and Debiao Li1

1Cedars-Sinai Medical Center, Los Angeles, CA, United States, 2University of California, Los Angeles, CA, United States, 3Xuanwu Hospital, Beijing, China

Intracranial atherosclerotic disease (ICAD) is one of the most common causes of ischemic stroke worldwide. Despite intensive medical management, which is the current standard of care, the rate of recurrent stroke is 13% in the first year and as high as 35% in certain populations by 2 years. Initial and follow-up evaluations of these patients rely exclusively on assessments of clinical risk factors and, in some circumstances, the degree of luminal stenosis on imaging, which may overlook subtle non-luminal changes within ICAD lesions. In the present work, we sought to assess the feasibility of quantitatively monitoring regression or progression of intracranial atherosclerotic plaques using 3D VWI.

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Quantitative and Noninvasive MRI of the Endothelial Permeability and Function in Carotid Atherosclerosis
Alkystis Phinikaridou1, Justinas Silickas2, Begoña Lavin1, Marcelo Andia3, Alberto Smith2, Prakash Saha2, and René Botnar2

1Biomedical Engineering, King's College London, London, United Kingdom, 2King's College London, London, United Kingdom, 3Pontificia Universidad Católica de Chile, Santiago, Chile

Over the past two decades, the central role of the endothelium in the initiation, progression, and clinical sequelae of atherosclerosis has been recognized. Increased endothelial permeability and impaired function precedes and portends the development of atherosclerotic lesions and their clinical manifestations. We have previously shown that quantitative assessment of albumin leakage into the vessel wall, using a clinically approved albumin-binding contrast agent, and endothelial-dependent dysfunction associated with lesion progression and instability in animal models. Here, we translated this technique in man to test whether endothelial permeability and dysfunction associate with carotid atherosclerosis risk in patients undergoing endarterectomy.

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Automatic segmentation of the aortic arterial wall in a pre-clinical rabbit model of atherosclerosis: preliminary experience with a convolutional neural network
Daniel Samber1, Claudia Calcagno1, Edmund Wong1, Venkatesh Mani1, Cheuk Tang1, and Zahi A. Fayad1

1Icahn School of Medicine at Mount Sinai, New York, NY, United States

The task of manually evaluating medical images can be onerous, plagued by subjective bias, and subject to human error. In this study we apply a convolutional neural network (CNN) for automated image segmentation of the atherosclerotic vessel wall, a notoriously challenging and time consuming segmentation task. Our CNN shows a classification accuracy of 90% on testing data, and a intersection over union (IoU) weighted by the number of pixels in each class of 86%, indicating excellent segmentation. Our results suggest that, if appropriately optimized this method has the potential deliver faithful and automatic segmentation of the arterial vessel wall. 

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Head and Neck Vascular Calcification Imaging using Zero Echo Time
Jianmin Yuan1, Florian Wiesinger2, Pascal Ruetten1, Ilse Patterson3, Martin Janich2, Ana Beatriz Solana2, Gaspar Delso4, Scott Reid5, Jonathan Gillard1, and Martin Graves1,3

1Department of Radiology, University of Cambridge, Cambridge, United Kingdom, 2ASL Europe, GE Healthcare, Munich, Germany, 3Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom, 4ASL Europe, GE Healthcare, Cambridge, United Kingdom, 5ASL Europe, GE Healthcare, Pollards Wood, United Kingdom

Calcification is an important factor in carotid plaque development and rupture. Current standard method for detecting plaque calcification is CT angiography (CTA). The purpose of this study is to introduce a new MRI method using zero echo time sequence for detection of carotid vessel wall calcification with high sensitivity. The protocol was optimized in volunteers and then applied to patient scan. The results demonstrate that carotid plaque calcification can be detected with high accuracy using proposed protocol compared with contrast-weighed images. 

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Quantitative Assessment of Carotid Artery Atherosclerosis by Three-Dimensional Magnetic Resonance Imaging and 2D Ultrasound: A Comparison Study
Huiyu Qiao1, Ying Cai2, Qiang Zhang1, Lingyun Huang3, Manwei Huang4, Chun Yuan1,5, and Xihai Zhao1

1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China, 2Department of Radiology, Taizhou People's Hospital, Taizhou, China, 3Clinical Sites Research Program, Philips Research China, Shanghai, China, 4Department of Ultrasound, China Meitan General Hospital, Beijing, China, 5Department of Radiology, University of Washington, Seattle, WA, United States

The size of carotid atherosclerotic plaques is associated with ischemic cerebrovascular events. Both 3D MR vessel wall imaging and 2D ultrasound can measure carotid plaques. To improve the work flow of screening for subclinical carotid atherosclerosis, this study sought to compare the quantitative measurements of carotid plaque between 3D MR and 2D ultrasound imaging. Excellent agreement was found between MR and ultrasound imaging in measuring carotid artery maximum wall thickness. Although there was moderate to strong correlation between MR and ultrasound imaging, the plaque area measured by MR imaging was more than two folds than that measured by ultrasound imaging.

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PD-T2-Shuffled Volumetric ISotropic Turbo spin echo Acquisition (VISTA) for 3D Simultaneous Multi-contrast Intracranial Vessel Wall Imaging
Shuo Chen1, Zechen Zhou2, Haikun Qi1, Chun Yuan1,3, and Rui Li1

1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China, 2Philips Research North America, Cambridge, MA, United States, 3Vascular Imaging Lab, Department of Radiology, University of Washington, Seattle, WA, United States

The aim of this study was to develop a PD-T2-shuffled VISTA technique, which can provide co-registered 3D high multi-contrast intracranial vessel wall images with high scan efficiency. Phantom study and healthy volunteers study were performed to validate the feasibility of the proposed method. The results showed that middle cerebral artery vessel wall was clearly depicted on different weighed images of PD-T2-shuffled VISTA.

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Imaging uptake of plasma macromolecules in the arterial wall
Marta Dazzi1, René Botnar2, and Peter Weinberg1

1Department of Bioengineering, Imperial College London, London, United Kingdom, 2Biomedical Engineering, King's College London, London, United Kingdom

Elevated endothelial permeability is a precursor to atherosclerosis. Imaging macromolecule uptake in the artery wall can be used to detect and investigate early structural and functional endothelial dysfunction. Current techniques make use of destructive post-mortem analysis of tissue, limiting studies to animal models only. MR imaging of the transport of an albumin-binding contrast agent (Gadofosveset) could be used instead. We employed a mathematical model to differentiate between the bound and unbound fraction of the contrast agent thus making this method a promising non-invasive technique to measure permeability in humans for the first time.

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Quantification of Wall Shear Stress in the Carotid Arteries of Naïve and Dyslipidemic Non-Human Primates
Smita Sampath1, Weiwei Luo2, Ying-Hua Chu3, Fa-Hsuan Lin3, Michael Klimas4, Elaine Manigbas5, Willy Gsell5,6, Kirsten Jacobsen7, Eric Gifford2, Asad Abu Bakar Ali1, Jeffrey L Evelhoch4, and Chih-Liang Chin1

1Translational Biomarkers, MRL, MSD, Singapore, Singapore, 2Bioinformatics, MRL IT, MSD, Singapore, Singapore, 3National Taiwan University, Taipei, Taiwan, 4Translational Biomarkers, MRL, Merck & Co., Inc., West Point, PA, United States, 5Imaging, Maccine Pte. Ltd., Singapore, Singapore, 6MoSAIC, Biomedical MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium, 7Early Discovery Pharmacology, MRL, MSD, Singapore, Singapore

Herein, we quantified regional carotid wall shear stress (WSS) in 9 naïve NHPs on a normal diet and 4 dyslipidemic NHPs on a high fat diet.  A custom-built carotid coil was used to achieve high-resolution imaging.  Image analysis was performed including 3D structural and velocity interpolation, contour extraction and through-plane velocity projection. Velocity gradients at the contours were computed to quantify WSS.  Animals on high fat diet showed enlarged common carotid arteries (diameter: 2.717 ± 0.195 mm) and lower WSS (0.1478 ± 0.0522 N/m2) compared to animals on a normal diet (diameter: 2.132 ± 0.203 mm, 0.2209 ± 0.0817 N/m2). 

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A Phantom Study to Compare the Theoretical Accuracy and Precision of CT Angiography versus Radial MRI for the Assessment of Coronary Endothelial Function
Jerome Yerly1,2, Fabio Becce1, Danilo Gubian3, Ruud van Heeswijk1,2, Francis R Verdun4, Reto Meuli1, and Matthias Stuber1,2

1Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV and UNIL), Lausanne, Switzerland, 2Center for Biomedical Imaging (CIBM), Lausanne, Switzerland, 3Direction des Constructions, Ingénierie, Technique et Sécurité (CIT-S), Lausanne University Hospital (CHUV and UNIL), Lausanne, Switzerland, 4Institute of Radiation Physics, Lausanne University Hospital (CHUV and UNIL), Lausanne, Switzerland

CT angiography (CTA) and MRI are non-invasive imaging modalities to assess coronary endothelial function (CEF). However, the performance of these techniques has yet to be quantitatively compared. Images of an in vitro phantom that simulates a physiological range of coronary artery cross-sectional areas (CSAs) were acquired using both CTA and MRI. CSAs were automatically measured and compared to the known nominal values. Statistical analysis suggests that MRI is capable of detecting significantly smaller CSA differences than CTA (2.25±0.80% vs. 7.42±0.63% for a 3-mm baseline diameter; p<0.0001), which is well within the range of physiological vasomotor responses of proximal coronary arteries.

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Does the amount of signal change depend on calcium concentration in lipid-rich core plaque?
Yuki Kanazawa1, Kotaro Baba2, Tosiaki Miyati3, Masafumi Harada1, Hiroaki Hayashi1, Ikuho Kosaka2, Mitsuharu Miyoshi4, Michael Carl5, and Yuki Matsumoto6

1Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan, 2School of Health Sciences, Tokushima University, Tokushima, Japan, 3Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan, 4Global MR Applications and Workflow, GE Healthcare Japan, Hino, Japan, 5GE Healthcare, San Diego, CA, United States, 6Graduate school of Health Science, Tokushima University, Tokushima, Japan

The purpose of this study was to quantitatively detect calcification in LRNC plaques using multi-component analysis with UTE imaging. A phantom experiment was performed using a four echo-UTE sequence. The phantom consists of six different concentrations of hydroxyapatite (as calcification) and mayonnaise (as a lipid). The bi-exponential analysis with UTE enabled a split into two components of short- and long T2*successfully. R2* derived from each dataset increased with increasing concentrations of hydroxyapatite. In conclusion, multi-component T2* analysis with UTE makes it possible to evaluate calcification in atherosclerotic plaques.

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Dynamic MRI of Nitroxide Radical for TEMPOL kinetics and Redox State Assessment in Porcine Aortic Wall
Maxim Terekhov1, Mihaela Pali1, Christian Wittke1, David Lohr1, Anja Schroeder2, Sueleyman Erguen3, Alma Zernecke-Madsen4, Heike Walles2, and Laura Maria Schreiber1

1Chair of Cellular and Molecular Imaging, Comprehensive Heart Failure Center, University Hospital Wuerzburg, Wuerzburg, Germany, 2Translational Center Regenerative Therapies, Fraunhofer Institute for Silicate Research, Wuerzburg, Wuerzburg, Germany, 3Institute of Anatomy and Cell Biology, University Wuerzburg, Wuerzburg, Germany, 4Institute for Experimental Biomedicine II, University Hospital Wuerzburg, Wuerzburg, Germany

Reactive oxygen species (ROS) plays a key role in vascular disease. The physiological mechanisms regulating vascular local oxidative stress (LOS) are not completely understood. Nitroxide radicals like TEMPOL have been used in basic science NMR studies of ROS and LOS. Therefore, we developed a technique for dynamic imaging of nitroxide radicals to assess their kinetics and redox state of tissue.

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Quantification of endothelial permeability in the mouse aortic root with 3D self-gated T1 mapping: disease progression and treatment with statins
Raphael Soler1, Zahi Fayad1, Christopher Faries1, Gustav Strijkers1,2, and Claudia Calcagno1

1Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 2Biomedical Engineering and Physics, Academic Medical Center, Amsterdam, Netherlands

Quantification of endothelial permeability in the mouse aortic root with 3D self-gated T1 mapping: disease progression and treatment with statins

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Feasibility of coronary artery wall imaging using 3D turbo spin-echo (black blood -T1-VISTA) in children with Kawasaki disease
Koji Matsumoto1,2, Hajime Yokota3, Hiroki Mukai3, Naoki Saito4, Yoshitada Masuda1, Takashi Uno3, and Tosiaki Miyati2

1Department of Radiology, Chiba University Hospital, Chiba, Japan, 2Division of Health Sciences, Graduate School of Medial Science, Kanazawa University, Kanazawa, Japan, 3Diagnostic Radiology and Radiation Oncology, Graduate School of Medicine, Chiba University, Chiba, Japan, 4Department of Pediatrics, Chiba University Hospital, Chiba, Japan

We evaluate feasibility of three-dimensional turbo spin echo imaging (BB-T1-VISTA) as coronary artery wall imaging for Kawasaki disease. BB-T1-VISTA could visualize the proximal regions of the coronary artery appropriately. BB-T1-VISTA with axial orientation produced the highest reproducibility to magnetic resonance coronary angiography (MRCA). Although BB-T1-VISTA showed significantly smaller diameter than MRCA, the limits of agreement were small in the proximal regions with normal diameter. By contrast, the larger aneurysms were, the larger bias became between MRCA and BB-T1-VISTA. BB-T1-VISTA has a potential to evaluate wide range of the coronary artery at once and was feasible in regions with small diameter.

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Infarct Pattern and Large Artery Atherosclerosis Features Revealed by Combined Intra- and Extra-cranial Vessel Wall Imaging in Patients with Non-cardiac Acute and Sub-acute Ischemic Stroke
Na Zhang1, Jinhao Lyu2, Lei Zhang1, Lin Jia3, Wenxiao Jia3, Hairong Zheng1, and Xin Liu1

1Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 2Department of Radiology, Chinese PLA General Hospital, Beijing, China, 3XinJiang Medical University, Urumchi, China

Infarct pattern referring single or multiple infarction lesions of patients with ischemic stroke is a feasible imaging marker to predict future stroke recurrence. The aim of this study was to detect large artery atherosclerosis features resulting in single or multiple infarction lesions in patients with non-cardiac acute and sub-acute ischemic stroke using the combined intra- and extra-cranial vessel wall MR imaging method. The results demonstrated that in large artery atherosclerosis, infarct pattern may be associated with the vulnerability of atherosclerotic plaques, and this combined imaging method can be used to explore the vascular pathology and predict recurrence of ischemic stroke.

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DCE-MRI of Intracranial Artery Athoersclerosis: Quantitative Change After 6-month Statin Therapy.
Huijun Chen1, Jiaqi Dou1, Le He1, Chunyao Wang1, Haikun Qi1, Qiang Zhang1, and Xihai Zhao1

1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua university, Beijing, China

Dynamic contrast-enhanced MRI (DCE-MRI) has been proven to be able to quantify the inflammation and neovasculature in the atherosclerotic plaque of carotid artery. However, few studies has focus on the DCE-MRI of intracranial artery atherosclerosis, which is another major cause of cerebral ischemic events. This study found that the Ktrans of intracranial artery calculated from DCE-MRI was significantly lower at follow-up comparing with baseline after 6-month statin therapy, suggesting DCE-MRI a good tool for therapeutic response evaluation for intracranial artery atherosclerosis

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“3D-Stars” Cine MRI for the Coronary Arteries: Initial Steps towards Volumetric Endothelial Function Assessment
Gabriele Bonanno1,2, Davide Piccini3,4, Jérôme Yerly4,5, Sahar Soleimanifard1,2, Li Pan6, Xiaoming Bi7, Allison G Hays1, Matthias Stuber4,5, Robert G Weiss1,2, and Michael Schär2

1Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 3Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 4Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 5Center for Biomedical Imaging (CIBM), Lausanne, Switzerland, 6Siemens Healthineers, Baltimore, MD, United States, 7Siemens Healthineers, Los Angeles, CA, United States

Recently, 2D coronary cine MRI has been shown to noninvasively assess coronary endothelial dysfunction, which is an early manifestation of atherosclerosis and a predictor of future acute events. However, atherosclerosis is a diffuse process, whereas this 2D approach provides local functional measures. Here, we present a free-breathing golden-angle 3D stack-of-stars cine sequence with isotropic spatial resolution combined with respiratory self-gating and 5D-GRASP reconstruction to image the proximal and mid segments of the right coronary artery. We call this new method “3D-Stars” and show feasibility to obtain volumetric cross-sectional area measures that can be used in future endothelial function studies.

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Influence of Field Strength on the Appearance of Peripheral Vascular Calcifications using Magnetic Resonance Imaging
Ali Serhal1, Ioannis Koktzoglou2,3, Pascale Aouad1, James Carr1, Shivraman Giri4, Omar Morcos5, and Robert R Edelman1,2

1Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States, 2Radiology, NorthShore University HealthSystem, Evanston, IL, United States, 3Radiology, Prtizker School of Medicine, University of Chicago, Chicago, IL, United States, 4Siemens Healthineers, Chicago, IL, United States, 5Surgery, NorthShore University HealthSystem, Evanston, IL, United States

A major deficiency of MR angiography compared with CT angiography (CTA) has been its inability to detect and characterize peripheral vascular calcifications. Recently, MRI using a proton density-weighted, in-phase stack of stars technique proved capable of identifying these calcifications.  However, the diamagnetic susceptibility and short T2* of calcifications have the potential to cause clinically relevant, field strength-dependent changes in lesion appearance with MRI.  Since the impact of field strength on the appearance of vascular calcifications is unknown, we performed a two-center clinical study which demonstrated that MRI accurately depicts peripheral vascular calcifications at both 1.5 Tesla and 3.0 Tesla.  


Electronic Poster

Machine Learning for Image Analysis

Exhibition Hall Monday 14:45 - 15:45

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AUTO-DCE-MRI: A Deep-Learning Augmented Liver Imaging Framework for Fully-Automated Multiphase Assessment and Perfusion Mapping
Li Feng1, Fang Liu2, Henry Rusinek1, Bari Dane1, Henry Brody1, Teodora Chitiboi1, Daniel K Sodickson1, Ricardo Otazo1, and Hersh Chandarana1

1Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States, 2Department of Radiology, University of Wisconsin School of Medicine, Madsion, WI, United States

This work proposes and tests a novel dynamic contrast-enhanced liver MRI framework called AUTO-DCE-MRI, which allows for simultaneous multiphase assessment and automated perfusion mapping from a single continuous free-breathing data acquisition. A deep convolutional neural network is trained to automatically select the abdominal aorta and the main portal vein. For low temporal-resolution multiphase assessment, the contrast bolus information is extracted from the aorta to guide image reconstruction of desired contrast phases. For high temporal-resolution perfusion analysis, the arterial/venous input functions are generated from the automatically selected regions in the aorta and main portal vein for pharmacokinetic modeling. 

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Supervised Machine Learning with Blind Source Separation (BSS) reveals distinct networks of pathological changes in brain magnetic susceptibility (QSM): Application to multiple sclerosis.
Ferdinand Schweser1,2, Juliane Damm1, Niels P Bergsland1,3, Michael G Dwyer1, Akshay V Dhamankar1, Bianca Weinstock-Guttman4, and Robert Zivadinov1,2

1Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States, 2Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, United States, 3MR Research Laboratory, IRCCS, Don Gnocchi Foundation ONLUS, Milan, Italy, 4BairdMS Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States

Conventional region-of-interest (ROI) or voxel-based analyses of quantitative susceptibility maps (QSM) do not provide insights on the mechanistic and temporal independence of tissue alterations between subjects. In this study, we combined Blind Source Separation (BSS) with a Machine Learning strategy to reveal specific, independent disease-related networks of tissue alterations. Our analysis identified anatomically localized independent networks of pathological susceptibility alterations in multiple sclerosis (MS) without a priori information on age, sex, disease, or anatomy. 


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Machine learning for prostate cancer Gleason score prediction using radiomics of T2-weighted imaging, diffusion weighted imaging and T2-mapping
Jussi Toivonen1,2, Ileana Montoya Perez1,2, Parisa Movahedi1,2, Harri Merisaari1,2, Janne Verho2, Pekka Taimen3, Peter J Boström4, Tapio Pahikkala1, Hannu J Aronen2, and Ivan Jambor1,2

1Department of Future Technologies, University of Turku, Turku, Finland, 2Department of Diagnostic Radiology, University of Turku, Turku, Finland, 3Department of Pathology, University of Turku, Turku, Finland, 4Department of Urology, Turku University Hospital, Turku, Finland

We extensively evaluated large number radiomics of prostate T2-weighted imaging, diffusion weighted imaging and T2-mapping. The highest overall performance estimate (AUC = 0.88) we obtained for the model utilizing a small subset of texture features from the ADCm, K, and T2w parameters. These features included texture descriptors based on gray-level co-occurrence matrix, Gabor transform, and the Zernike and Hu moments.

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An integrative deep learning model to distinguish between normal and atherosclerotic carotid arteries on black-blood vessel wall MRI
Jiayi Wu1,2, Jingmin Xin1, Jie Sun2, Zechen Zhou3, Baocheng Chu2, Dongxiang Xu2, and Chun Yuan2

1Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi'an, China, 2Department of Radiology, University of Washington, Seattle, WA, United States, 3Philips Research North America, Cambridge, Cambridge, MA, United States

Vessel wall (VW) MRI has been used to characterize atherosclerotic plaques but the review process is complex. To facilitate the translation of VWMRI into clinical application, we utilized deep convolutional neural networks (CNN) to distinguish between normal and atherosclerotic carotid arteries automatically in black-blood (BB) VWMRI. Trained with a dataset that contains both normal and diseased carotid arteries with expert labeling, an integrative deep CNN model was developed and yielded better automatic diagnosis accuracy of carotid atherosclerosis (85.18%) compared with other existing methods. This model may be used as an initial screening to separate normal from diseased arteries.

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Deep learning analysis of cardiac MRI for unsupervised classification of heart disease
Carlo Biffi1,2, Ozan Oktay1, Wenjia Bai1, Giacomo Tarroni1, Antonio De Marvao2, Martin Rajchl1, Stuart Cook2,3, Declan O'Regan2, and Daniel Rueckert1

1Department of Computing, Imperial College London, London, United Kingdom, 2Cardiovascular Magnetic Resonance Imaging and Genetics, MRC London Institute of Medical Sciences, London, United Kingdom, 3Graduate Medical School, Duke-National University of Singapore, Singapore, Singapore

Magnetic resonance imaging provides detailed assessment of cardiac structure and function. However, conventional manual phenotyping reduces the rich biological information to few global metrics. A learning-based approach providing more complex phenotypic features could offer an objective data-driven means of disease classification. In this work, we exploit a convolutional variational autoencoder model to learn low-dimensional representations of cardiac remodelling which are easily visualisable on a template shape and readily applicable in classification models. This approach yielded 91,7% accuracy in the discrimination among healthy, hypertrophic and dilated cardiomyopathy subjects, and shows promise for unsupervised classification of pathologies associated with ventricular remodelling.

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Automated segmentation of abdominal organs in T1-weighted MR images using a deep learning approach: application on a large epidemiological MR study
Thomas Küstner1,2, Marc Fischer1, Sarah Müller2, Daniel Guttmann1, Konstantin Nikolaou1, Fabian Bamberg1, Bin Yang2, Fritz Schick1, and Sergios Gatidis1

1University of Tübingen, Tübingen, Germany, 2University of Stuttgart, Stuttgart, Germany

In this study we implemented and validated an automated method for segmentation of T1-weighted MR images using a deep learning approach. We applied the algorithm two 80 training and 20 validation data sets drawn from an epidemiological MR study and observed high accuracy compared to manual tumor segmentation. This approach can potentially contribute to efficient analysis of large epidemiological MR studies in the future.


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Fully Automatic Proximal Femur Segmentation in MR Images using 3D Convolutional Neural Networks
Siyuan Xiang1, Gregory Chang2, Stephen Honig3, Kyunghyun Cho4, and Cem M. Deniz5,6

1Center for Data Science, New York University, New York, NY, United States, 2Department of Radiology, Center for Musculoskeletal Care, New York University Langone Medical Center, New York, NY, United States, 3Osteoporosis Center, Hospital for Joint Diseases, New York University Langone Medical Center, New York, NY, United States, 4Courant Institute of Mathematical Science & Center for Data Science, New York University, New York, NY, United States, 5Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, New York University Langone Medical Center, New York, NY, United States, 6The Sackler Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, United States

MRI has been successfully used in structural imaging of trabecular bone micro architecture in vivo. In this project, we develop supervised convolutional neural network for automatically segmental proximal femur from structural MR images. We found that the proposed method provides accurate segmentation without any post-processing, bringing trabecular bone micro architecture analysis closer to clinical practice.

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Explanatory Auxiliary Generative Adversarial Network for Prostate Cancer Lesion Awareness with Very-Weak Supervision
Ruiming Cao1,2, Xinran Zhong1, and Kyunghyun Sung1

1Radiology Department, University of California, Los Angeles, Los Angeles, CA, United States, 2Computer Science, University of California, Los Angeles, Los Angeles, CA, United States

Although supervised deep convolutional neural network has shown good performance regarding lesion detection and classification using multi-parametric MRI, it is still limited by high data label requirement. In this work, we proposed a model called explanatory auxiliary generative adversarial network (ExpA-GAN), which generates heatmap for object detection under very-weak supervision (no ground truth location). The model was trained and evaluated in a public TCIA prostate dataset. Among 50 testing slices enclosing the whole prostate, the proposed model achieves 0.169 normalized distance for lesion detection, showing the potential to improve lesion detection using limited labeled data.  

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Cascaded 3D fully convolutional neural network for segmenting amygdala and its subnuclei
Yilin Liu1, Brendon Nacewicz1, Gregory Kirk1, Andrew Alexander1, and Nagesh Adluru1

1University of Wisconsin Madison, Madison, WI, United States

We address the problem of segmenting subcortical brain structures that have small spatial extent but are associated with many neuropsychiatric disorders and neurodegenerative diseases. Specifically, we focused on the segmentation of amygdala and its subnuclei. Most existing methods including deep learning based focus on segmenting larger structures and the existing architectures do not perform well on smaller structures. Hence we designed a new cascaded fully convolutional neural network with architecture that can perform well even on small structures with limited training data. Several key characteristics of our architecture: (1) 3D convolutions (2) deep network with small kernels (3) no pooling layers.

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MR Image Synthesis Using A Deep Learning Based Data-Driven Approach
Fang Liu1 and Alan McMillan1

1Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States

In this study, we demonstrate MR image synthesis using deep learning networks to generate six image contrasts (T1- and T2-weighted, T1 and T2 FLAIR, STIR, and PD) from a single multiple-dynamic multiple-echo (MDME) sequence. A convolutional encoder-decoder (CED) network was used to map axial slices of the MDME acquisition to the six different image contrasts. The synthesized images provide highly similar contrast and quality in comparison to the real acquired images for a variety of brain and non-brain tissues and demonstrate the robustness and potential of the data-driven deep learning approach.

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Arterial spin labeling (ASL)-based radiomics features for predicting perfusion territory changes after carotid endarterectomy: a pilot study
Tianye Lin1, Chencui Huang2, Jianxun Qu3, Bing Wu3, Panli Zuo2, Xiangfei Chai2, and Feng Feng4

1Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China, 2. Huiying Medical Technology Co., Ltd, Beijing, China, 3GE Healthcare, MR Research China, Beijing, China, 4Peking Union Medical College Hospital, Beijing, China

To investigate whether radiomics can be apply to cerebrovascular disease and to develop features based on ASL for predicting perfusion territory change after carotid endarterectomy (CEA). A total of 1029 features were derived from ASL images, and 14 features were selected when comparing the differences between the two groups (select K best P<0.05). The selected features in difference are in agreement with visual inspection of collateral flow based on arterial transit artifact (ATA) on ASL.

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Perfusion MRI in stroke as a regional spatio-temporal texture
Noëlie Debs1, Mathilde Giacalone1, Pejman Rasti2, Tae-Hee Cho1, Carole Frindel1, and David Rousseau2

1CREATIS UMR 5220, U1206, University of Lyon, Lyon, France, 2LARIS, UMR INRA IRHS, Université d'Angers, Angers, France

We tackle the clinical issue of predicting the final lesion in stroke from early perfusion magnetic resonance imaging. We demonstrate here the value of exploiting directly the raw perfusion data by encoding the local environment of each voxel as a spatio-temporal texture. As an illustration for this approach, the textures are characterized with Haralick coefficients computed on co-occurrence matrices and a standard support vector machine classifier is used for the classification. This simple machine learning classification scheme demonstrates good results while working on raw perfusion data.

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Predicting Contrast Agent Enhancement with Deep Convolution Networks
Thomas Christen1, Enhao Gong1, Jia Guo1, Michael M. Moseley1, and Greg Zaharchuk1

1Radiology, Stanford University, Stanford, CA, United States

In this study, we tested whether deep convolutional neural networks (CNNs) could predict what an image would look like if a contrast agent was injected in the body. We trained a network to use information contained in a non-contrast MR brain exam and create a synthetic T1w image acquired after gadolinium injection. Multiple datasets including patients with tumors were used for training. Great similarities were found between the predicted and the actual images acquired after contrast agent injection. If further validated, this approach could have great clinical utility in patients who cannot receive contrast.

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Automatic Segmentation of Carotid Vessel Wall Using Convolutional Neural Network
Li Chen1, Jie Sun2, Wei Zhang3, Thomas S Hatsukami4, Jianrong Xu3, Jenq-Neng Hwang1, and Chun Yuan2

1Electrical Engineering, University of Washington, Seattle, WA, United States, 2Radiology, University of Washington, Seattle, WA, United States, 3Radiology, Renji Hospital, Shanghai, China, 4Surgery, University of Washington, Seattle, WA, United States

Accurate vessel wall segmentation on black-blood MRI is an important but difficult task. Using previously annotated carotid vessel wall contours by human reviewers, a convolutional neural network (CNN) was trained to predict vessel wall region from the combination of T1-weighted and time-of-flight images. Compared with human segmentation results, the CNN-based model achieved a Dice similarity coefficient of 0.86±0.06 and a correlation coefficient of 0.96 (0.94, 0.97) in measuring vessel wall area. Fast and accurate vessel wall segmentation may help fully realize the potential of vessel wall MRI in monitoring atherosclerosis progression or regression in serial studies and clinical trials.

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3D Texture Analysis on fMRI to Detect Alterations in the Striatal Network of an Alcohol-Preferring Rat Model
Silvia Ruiz-España1, Rafael Ortiz-Ramón1, Úrsula Pérez-Ramírez1, Antonio Díaz-Parra1, Roberto Ciccocioppo2, Santiago Canals3, and David Moratal1

1Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain, 2School of Pharmacy, University of Camerino, Camerino, Italy, 3Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas - Universidad Miguel Hernández, Sant Joan d' Alacant, Spain

We propose an approach that uses 3D texture features extracted from fMRI to detect changes in the striatal network induced by alcohol drinking. Scans of eighteen alcohol-preferring rats before and after 30 days of alcohol consumption were analyzed. Data were preprocessed and a group independent component analysis was performed to identify striatal network; in total 36 volumes of interest were studied. Texture analysis was performed using 43 texture features and six predictive models. An AUC of 0.927±0.089 (sensitivity=84.25%, specificity=81.75%) was obtained for the best model (random forests). The proposed method was able to accurately identify subjects with alcohol use disorders.

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Estimating Inclusion Stiffness with Artificial Neural Networks in Magnetic Resonance Elastography
Jonathan M. Scott1, Matthew C. Murphy1, Arvin Arani1, Christopher G. Schwarz1, Armando Manduca1, John Huston III1, and Richard L. Ehman1

1Radiology, Mayo Clinic, Rochester, MN, United States

Magnetic Resonance Elastography stiffness estimates in intracranial tumors correlate with intraoperative assessment of tumor consistency, but the spatial kernel-based stiffness calculation of Direct Inversion (DI) creates challenges for small or heterogeneous tumors. The objective of this study is to evaluate an artificial neural network based inversion technique (NNI) in the assessment of small stiff inclusions in a brain phantom. This study shows that NNI can resolve inclusions as small as 1.75cm in diameter with a contrast to noise ratio higher than that of DI. Furthermore, preliminary clinical results show agreement with intraoperative findings.

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Classification of Adipose Tissues using Machine Learning
Brandon Campbell1,2, Gregory Simchick1,2, Hang Yin3, and Qun Zhao1,2

1Physics and Astronomy, University of Georgia, Athens, GA, United States, 2Bio-Imaging Research Center, University of Georgia, Athens, GA, United States, 3Biochemistry and Molecular Biology, University of Georgia, Athens, GA, United States

Previous classification techniques for determining the quantification of white adipose tissue and brown adipose tissue have relied on using fat fraction and proton relaxation times using fixed peak spectroscopic models. Machine learning algorithms have proven to be highly accurate for image segmentation but their accuracies rely heavily on input datasets. By using the recently proposed Multi-Varying MR Spectroscopy model an increase in dataset specificity can be applied to each voxel by addition of varying fat peak intensity values. Using this new dataset, four machine learning models were compared.

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Automated Zonal Prostate Segmentation with 2.5D Convolutional Neural Networks
Alex Bratt1, Kevin Seals2, and Daniel Margolis3

1Department of Radiology, Weill Cornell Medicine/New York Presbyterian Hospital, New York, NY, United States, 2Department of Radiology, University of California, Los Angeles, Los Angeles, CA, United States, 3Department of Radiology, Weill Cornell Medicine, New York, NY, United States

Accurate delineation of anatomical boundaries on prostate MR is crucial for cancer staging and standardized assessment. Unfortunately, manual prostate segmentation is time consuming and prone to inter-rater variability while existing automated segmentation software is expensive and inaccurate. We demonstrate a novel fully-automated zonal prostate segmentation method that is fast and accurate using a convolutional neural network. The network is trained using a dataset of 149 T2-weighted prostate MR volumes that were manually annotated by radiologists. Our method improves upon prior related work, achieving a full-gland Dice score of 0.92 and zonal Dice score of 0.88.

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MR Intensity Normalization: Influence on Supervised Machine Learning Algorithms using Textural and Convolutional Features
Mariana Bento1, Marina Salluzzi2, Leticia Rittner3, and Richard Frayne1

1Departments of Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada, 2Calgary Image Processing and Analysis Centre, Foothills Medical Centre, Calgary, AB, Canada, 3School of Electrical and Computer Engineering, University of Campinas, Campinas, Brazil

Supervised machine learning techniques have been used in medical imaging and aim to reduce subjectivity and improve quantitative results. When handling heterogeneous MR datasets, most algorithms require pre-processing, such as intensity normalization. Here, the influence of MR normalization techniques on supervised classification is evaluated using handcrafted textural and convolutional features. These features combined can differentiate control subjects from atherosclerosis patients using only imaging scans. Non-significant statistical difference in classification was found across intensity normalization methods, demonstrating little influence of this pre-processing step on the supervised classification outcome.

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How easily can an existing stroke outcome deep learning model become attuned to new acquisition protocols and patient cohorts?
Anne Nielsen1,2, Mikkel Bo Hansen1, Soren Christensen3, Maarten Lansberg3, Greg Zaharchuk4, and Kim Mouridsen1

1Center of Functionally Integrative Neuroscience and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark, 2Cercare Medical, Aarhus, Denmark, 3Department of Neurology, Stanford University, Stanford, CA, United States, 4Department of Radiology, Stanford University, Stanford, CA, United States

Acute ischemic stroke is a major disease and one of the leading causes of adult death and disability. Final outcome prediction is hampered by the heterogeneity and physiological complexity of stroke progression. Convolutional neural networks have shown promising results in final outcome predictions. However, less attention has been paid to the generalizability of the results across patient cohorts. We test the applicability of an existing neural network trained on two clinical studies to completely independent cohort from the DEFUSE 2 trial. We examine how a few additional patients can be used to obtain performance comparable to the original studies.

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Bi-exponential modeling of prostate diffusion weighted MR imaging acquired using high b values: clinical evaluations of advanced post-processing methods
Parisa Movahedi1,2, Harri Merisaari1,3, Ileana Montoya Perez1,2, Jussi Toivonen1,2, Pekka Taimen4, Peter J. Boström5, Janne Verho1, Hannu J. Aronen1,6, Tapio Pahikkala2, and Ivan Jambor1,6

1Department of Diagnostic Radiology, University of Turku, Turku, Finland, 2Department of Future Technologies, University of Turku, Turku, Finland, 3Turku PET Center, University of Turku, Turku, Finland, 4Department of Pathology, Turku University Hospital, Turku, Finland, 5Department of Urology, Turku University Hospital, Turku, Finland, 6Medical Imaging Center of Southwest Finland, Turku University Hospital, Turku, Finland

The aim of this study was to evaluate various mathematical methods for enhanced parameter estimation of bi-exponential DWI (12 b values 0-2000 s/mm2) of prostate cancer. Least Squares (LSQ), Bayesian Shrinkage (BS) and Maximum Penalized Likelihood Estimation (MPLE) fitting methods were evaluated in the terms of Coefficients of Variation (CV), Contrast to Noise Ratio (CNR) and the Area under the curve (AUC) between tumor and non-tumor prostate tissue. BS and MPLE methods improved AUC and CNR values of bi-exponential model parameters and also decreased CV values in comparison with the commonly used LSQ fitting method.

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Pelvic Organ Segmentation with Sample Attention based Stochastic Connection Networks
Dong Nie1,2, Li Wang2, Jun Lian3, and Dinggang Shen2

1Department of Computer Science, UNC-Chapel Hill, Chapel Hill, NC, United States, 2Department of Radiology and BRIC, UNC-Chapel Hill, Chapel Hill, NC, United States, 3Department of Radiation Oncology, UNC-Chapel Hill, Chapel Hill, NC, United States

Accurate segmentation of pelvic organs is important for prostate radiation therapy. Modern radiation therapy starts to use magnetic resonance image (MRI) as an alternative to CT image, because of the superior soft tissue contrast of MRI and also no risk of radiation exposure. In this abstract, we propose a novel deep network architecture, called “Sample Attention based Stochastic Connection Networks” (SASCNet), to delineate pelvic organs from MRI in an end-to-end fashion. Our proposed network has two main contributions: 1) We propose a novel randomized connection module and adopt it as a basic unit to combine the shallower and deeper layers in the fully convolutional networks (FCN); 2) We propose a novel adversarial attention mechanism to automatically dispatch sample importance so that we can avoid the domination of easy samples in training the network. Experimental results show that our SASCNet achieves competitive segmentation accuracy. 

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Fully Convolutional Networks for Automated Segmentation of Abdominal Adipose Tissue Depots in Water-Fat MRI
Taro Langner1, Anders Hedström2, Håkan Ahlström1,2, and Joel Kullberg1,2

1Department of Radiology, Uppsala University, Uppsala, Sweden, 2BioVenture Hub, Antaros Medical, Mölndal, Sweden

The segmentation and quantification of human adipose tissue depots offers new insights into the development of metabolic and cardiovascular disease but is often hindered by the need for time-consuming and subjective manual input. We propose an automatic method that uses a convolutional neural network for the segmentation of both visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). The network was applied to two-dimensional slices of 90 water-fat MRI scans of the abdomen. In a 10-fold cross-validation it reached average dice scores of 0.979 (VAT) and 0.987 (SAT), with average absolute quantification errors of 0.8% (VAT) and 0.5% (SAT).

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Analysis of longitudinal MRI changes using mixed effects models on deformation tensors
Nagesh Adluru1, Hyunwoo J Kim1, Molly Prigge2, Nicholas T Lange3, Erin D Bigler4, Janet E Lainhart1, Andrew L Alexander1, and Vikas Singh1

1University of Wisconsin Madison, Madison, WI, United States, 2University of Utah, Salt Lake City, UT, United States, 3Harvard Medical School, Cambridge, MA, United States, 4Brigham Young University, Provo, UT, United States

Mixed effects models that include fixed and factor-specific (also known as random) effects offer a natural framework for studying longitudinal MRI data. This work extends mixed effects models to the setting where the responses lie on curved spaces such as the manifold of symmetric positive definite matrices. By treating the subject-wise diffeomorphic deformations between consecutive time points as a field of Cauchy deformation tensors, our framework can facilitate longitudinal analysis that respects the geometry of such data. While the existing body of work dealing with regression models on manifold-valued data is inherently restricted to cross-sectional studies, the proposed mixed effects formulation significantly expands the operating range of longitudinal analyses.


Electronic Poster

Image Reconstruction Potpourri

Exhibition Hall Monday 14:45 - 15:45

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Improving Parallel Imaging by Jointly Reconstructing Multi-Contrast Data
Berkin Bilgic1, Tae Hyung Kim2, Congyu Liao1, Mary Kate Manhard1, Lawrence L Wald1, Justin P Haldar2, and Kawin Setsompop1

1Martinos Center for Biomedical Imaging, Charlestown, MA, United States, 2Department of Electrical Engineering, University of Southern California, Los Angeles, CA, United States

We propose a general joint reconstruction framework to accelerate multi-contrast acquisitions further than currently possible with conventional parallel imaging. Our joint parallel imaging techniques simultaneously exploit similarities between echoes/phase-cycles/contrasts, virtual coil concept, partial Fourier acquisition, complementary sampling across images along with limited support and smooth phase constraints. These permit highly accelerated 2D, Simultaneous MultiSlice and 3D acquisitions as well as improved calibrationless parallel imaging from multiple contrasts. Our algorithms, JVC-GRAPPA and J-LORAKS, provide over 2-fold improvement in reconstruction error compared to conventional GRAPPA, with improved mitigation of artifacts and noise amplification.

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Parameter Optimization of Wave-CAIPI Based on Theoretical Analysis
Zhilang Qiu1, Haifeng Wang1, Leslie Ying2, Xin Liu1, and Dong Liang1

1Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 2Department of Biomedical Engineering and Department of Electrical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, United States

Wave-CAIPI is an novel 3D imaging technique with corkscrew trajectory in k-space to reduce g-factor penalty and speed up MRI acquisitions. The sinusoidal gradient parameters of Wave-CAIPI, amplitude and cycles, play an important role since they determine the point spread function of the trajectory and thus the final reconstruction. However, how to choose the optimal sinusoidal gradient parameters which leads to the minimal g-factor has not been exploited. In this work, we theoretically analyzed the influence of the sinusoidal gradient parameters on g-factor. An optimization algorithm which can be automatically conducted is then proposed to optimize these parameters for achieving minimal g-factor penalty. The simulations show that using the optimized sinusoidal gradient parameters can achieve lower g-factor penalty in Wave-CAIPI reconstructions.


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Nonlinear GRAPPA Reconstruction with Virtual Coil Conception
Haifeng Wang1, Yuchou Chang2, Leslie Ying3, Xin Liu1, and Dong Liang1

1Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 2Department of Computer Science and Technology Engineering, University of Houston-Downtown, Houston, TX, United States, 3Department of Biomedical Engineering and Department of Electrical Engineering, The State University of New York, Buffalo, NY, United States

Nonlinear GRAPPA is a kernel-based approach for improving parallel imaging reconstruction, by reducing noise-induced error. Virtual coil conception has been applied into the reconstruction process for parallel acquisitions, by generating virtual coils containing conjugate symmetric k-space signals from actual multiple-channel coils. In this work, we proposed a hybrid method to combine nonlinear GRAPPA and virtual coil conception for incorporating additional image- and coil-phase information into the reconstruction process. The experiments of in vivo human brain data show that the proposed method can reduce more noise and artifacts than the traditional GRAPPA and original Nonlinear GRAPPA methods.

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A Method for Automatically Determining an Optimal Kernel Size in ESPIRiT Reconstruction
Jong Bum Son1, Colleen Costelloe2, Tao Zhang1,3, and Jingfei Ma1

1Imaging Physics Department, The University of Texas MD Anderson Cancer Center, Houston, TX, United States, 2Diagnostic Radiology Department, The University of Texas MD Anderson Cancer Center, Houston, TX, United States, 3GE Healthcare Technologies, Waukesha, WI, United States

ESPIRiT is a hybrid-domain parallel imaging method which can estimate the coil-sensitivity information from the k-space calibration matrix. In ESPIRiT, the calibration matrix is constructed by sliding a window through the fully sampled data region of auto-calibrating signals. Presently, the kernel size of the sliding window determining the performance of ESPIRiT reconstruction is empirically chosen, even though an optimal value may vary depending on a combination of scan parameters and scan configurations. In this work, we developed an automatic data-driven method for determining an optimal kernel size in ESPIRiT to reduce the performance variation of ESPIRiT reconstructions.

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Improved Parallel Imaging Reconstruction of EPI using Inversely Distortion Corrected FLASH as Calibration Data
Mengye Lyu1,2, Yilong Liu1,2, and Ed X. Wu1,2

1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China, 2Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China

For parallel imaging reconstruction of EPI, EPI based calibration scan may suffer from ghost artifacts, whereas non-EPI based calibration scan such as FLASH cannot provide consistent geometric distortion. In this study, we propose to employ dual-echo FLASH as the calibration scan, such that B0 field maps can be derived to match FLASH images to EPI images and the reconstruction artifact related to inconsistent distortion can be minimized.

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Accelerated reconstruction for calibrationless parallel imaging using grouped joint nonlinear inversion and its application in myelin water imaging
Zhe Wu1, Hongjian He1, Yi Sun2, and Jianhui Zhong1,3

1Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China, 2MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China, 3Department of Imaging Sciences, University of Rochester, Rochester, NY, United States

The simultaneous estimation of images and coil sensitivities using joint nonlinear inversion (JNLINV) has been shown to be effective for calibrationless parallel imaging for multi-echo data. However, the number of unknowns grows with increasing number of echoes, so the reconstruction procedure could be lengthy. This study proposes an improved method called grouped JNLINV (gJNLINV) to enhance the reconstruction efficiency. Its reconstruction time is ~1/3 of that with JNLINV while preserving a similar root-mean-square error (RMSE) and increasing the fidelity of the coil sensitivities. We further demonstrate the application of gJNLINV on a 32-echo GRE data set for myelin water imaging.

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In-Plane Signal Leakage (L-factor) Maps from TGRAPPA
R. Allen Waggoner1, Kenichi Ueno2, Hideto Kuribayashi3, and Keiji Tanaka1,2

1Laboratory for Cognitive Brain Mapping, RIKEN-Brain Science Institute, Wako-shi, Japan, 2Support Unit for Functional Magnetic Resonance Imaging, RIKEN-Brain Science Institute, Wako-shi, Japan, 3Siemens Healthcare KK, Tokyo, Japan

Residual aliasing is a well-documented problem for multiband reconstructions, but it can be an important issue with in-plane acceleration methods as well.  With GRAPPA in particular, the residually aliased signal can be distributed fairy randomly, making it appear as g-factor noise.  We demonstrate that the use of TGAPPA permits not only the elimination of the residually aliased signal but also the determination of L-factor maps, which can be a potentially useful tool in understanding how to minimize residual aliasing.

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Parallel Imaging Reconstruction Algorithm Mitigating SNR Loss Using Phase Distribution for Fast Spin Echo Sequence
Kosuke Ito1 and Masahiro Takizawa1

1Hitachi, Ltd. Healthcare Business Unit, Tokyo, Japan

Parallel imaging is widely used in clinical routine practice. However, SNR degradation occurs due to undersampling and higher g-factor in higher acceleration factor. In this study, a new algorithm of parallel imaging reconstruction mitigating noise enhancement for fast spin echo sequence was proposed. The algorithm uses information of phase distribution of unaliased image, aliasing image, and folded image. SNR was compared in vivo T2 weighted image between full sampling, conventional parallel imaging, and proposed method. And higher SNR was demonstrated.

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Whole-Volume, High-Resolution, In-Vivo Signal-to-Noise Ratio and G-factor Superiority, and Structural Similarity Index Differences, of Compressed Sensing SPACE and CAIPIRINHA SPACE over GRAPPA SPACE
Neil Kumar1, Sheil Kumar2, and Jan Fritz3

1Radiology, Johns Hopkins Hospital, Baltimore, MD, United States, 2Microsoft Corporation, Redmond, WA, United States, 3Johns Hopkins Hospital, Baltimore, MD, United States

Compressed Sensing, CAIPIRINHA, and GRAPPA techniques reduce MRI acquisition times. We used a 3-dimensional sliding region-of-interest analysis tool to perform parameter-controlled, whole-volume average signal-to-noise ratio and g-factor comparison, and g-factor structural similarity index measurements (SSIM) of the above techniques in the setting of 3 Tesla knee MRI. We demonstrate g-factor superiority of CS SPACE over CAIPIRINHA SPACE and g-factor superiority of CAIPIRINHA SPACE over GRAPPA SPACE in living subjects. Post-processing, including pre-scan normalize and distortion correction, improves g-factors and causes variation in the g-factor SSIM results between the techniques.

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Reduced-FOV k-space Variant Radial Parallel Imaging Reconstruction for Real-time Cardiac MR
Yu Yulee Li1,2, Shams Rashid1, Yang Cheng1, William Schapiro1, Kathleen Gliganic1, Ann-Marie Yamashita1, Marie Grgas1, Michelle Maragh1, and Jie Jane Cao1,3

1Cardiac Imaging, St. Francis Hospital DeMatteis Center for Cardiac Research and Education, Greenville, NY, United States, 2Radiology, Stony Brook University (SUNY), Stony Brook, NY, United States, 3Medicine, Stony Brook University (SUNY), Stony Brook, NY, United States

Radial imaging is k-space variant, but mostly uses k-space invariant methods in image reconstruction. This permits reconstructing images with lower computation complexity at a cost of performance. Here a k-space variant parallel imaging reconstruction technique is developed to reconstruct Cartesian data directly from multi-channel radial samples with affordable computation. It is demonstrated that this technique offers the ability to collect real-time images with a temporal resolution of 40ms and a spatial resolution of 1.7mm. The new technique outperforms those gridding-based methods with k-space invariant algorithms in a stress cardiac test.

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Radial acquisition and PFT reconstruction allow for retrospective selection of spatial resolution in fMRI studies
Banfshe Shafiei Zargar1 and Abbas Nasiraei Moghaddam1,2

1Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran (Islamic Republic of), 2School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran (Islamic Republic of)

Aiming for fine resolution is always a challenging compromise between various parameters. We have investigated a method for retrospective adjustment of resolution in reconstruction step. Our study of fMRI data indicates that an adjustable pixel size is obtainable in a selected central region during the PFT (Polar Fourier Transform) reconstruction of a radially acquired K-space. Preserving the functional sensitivity, this improvement of resolution results in finer activation detection and higher functional CNR.

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Comparison of leading reconstruction techniques for real-time speech MRI
Weiyi Chen1, Yongwan Lim1, Yannick Bliesener1, Shrikanth S. Narayanan1, and Krishna S. Nayak1

1Electrical Engineering, University of Southern California, Los Angeles, CA, United States

Real-time MRI (RT-MRI) has revolutionized the study of human speech production. Two state-of-the-art reconstruction techniques have been adopted by different groups to accelerate real time imaging, constrained SENSE, and regularized nonlinear inversion. In this study, we describe our best performing implementations of both classes of reconstructions, and compare performance on common data from spiral RT-MRI of human speech at 1.5T. 

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Partial Fourier Acquisitions in Myocardial First Pass Perfusion Revisited
Tobias J Hoh1, Jonas Walheim1, Mareike Gastl1,2, Alexander Gotschy1,2, and Sebastian Kozerke1

1Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland, 2Department of Cardiology, University Hospital Zurich, Zurich, Switzerland

The inflow of a paramagnetic contrast agent (CA) in cardiac dynamic contrast-enhanced (DCE) MRI effects the local phase of magnetization. In this work the impact of phase variations on Partial Fourier (PF) reconstruction is simulated for k-space zero filling, homodyne (HR) and projections onto convex sets (POCS) reconstruction and consequently assessed in in-vivo first-pass perfusion. CA induced phase variations in DCE MRI are seen to compromise HR and POCS reconstruction of PF data to an extent where they do not convey any benefit over simple zero-filling reconstruction.

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Optimization-Based Simultaneous Combination and Unwrapping for MR Phase Imaging
John S H Baxter1,2, Zahra Hosseini1,2, Olivia W Stanley1,3, Ravi S Menon1,3, Maria Drangova1,2,3, and Terry M Peters1,2,3

1Imaging Research Laboratories, Robarts Research Institute, London, ON, Canada, 2Graduate Program in Biomedical Engineering, Western University, London, ON, Canada, 3Medical Biophysics, Western University, London, ON, Canada

MRI phase allows for the extraction of inherent tissue contrasts arising from differences in magnetic susceptibility. However, in order to enhance signal-to-noise ratio and accelerate acquisition, modern MRI uses multiple receiver coils. Extracting susceptibility information relies on combining phase information from these multiple channels. Once combined, phase unwrapping beyond the [$$$-\pi$$$, $$$\pi$$$] range allows for further processing and visualization. These processes can be sensitive to noise and errors which are compounded during serial processing, motivating more robust integrated algorithms. This paper introduces simultaneous combination and unwrapping (SCAU) that simultaneously estimates channel phase offset images and a combined unwrapped image. 

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Reconstruction of Accelerated DCE-MRI Guided by Image Quality Metrics
James A Rioux1,2,3, Nathan Murtha4, Chris V Bowen1,2,3,5, Sharon E Clarke1,2,3, and Steven D Beyea1,2,3,5

1Biomedical Translational Imaging Centre, Nova Scotia Health Authority, Halifax, NS, Canada, 2Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada, 3Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada, 4Physics, Carleton University, Ottawa, ON, Canada, 5Biomedical Engineering, Dalhousie University, Halifax, NS, Canada

Golden-angle sampling allows arbitrary retrospective selection of temporal resolution in dynamic MRI scans.  To select the fastest temporal resolution that preserves time course fidelity, we propose the use of image quality metrics (IQMs).  We demonstrate multiple IQMs that correlate strongly with the accuracy of fitted pharmacokinetic parameters up to at least an acceleration factor of R=12.  For a fixed undersampling factor, these metrics can also inform the selection of reconstruction parameters such as regularization weights for compressed sensing. This approach may enable rational, individual-level tuning of temporal resolution following a prospectively accelerated DCE-MRI scan.

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PEC-GRAPPA Reconstruction of Simultaneous Multislice EPI with Slice-Dependent 2D Nyquist Ghost Correction
Zheyuan Yi1,2, Yilong Liu1,2, Mengye Lyu1,2, and Ed X. Wu1,2

1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China, 2Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China

Nyquist ghost correction is challenging for simultaneous multislice (SMS) EPI due to the slice-dependent 2D phase error between positive and negative echoes. For this problem, phase error correction SENSE (PEC-SENSE) has been proposed recently, which incorporates slice-dependent 2D phase error maps into coil sensitivity maps. In this study, we extend the concept of PEC-SENSE to k-space based implementation termed as PEC-GRAPPA. It outperforms 1D LPC based GRAPPA reconstruction and requires less tuning than PEC-SENSE such as excluding background areas.

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Optimal Partial Fourier MRI reconstruction: Homodyne vs POCS
Venkata Suryanarayana kadimesetty1 and Harsh kumar Agarwal 1

1Health and Medical Equipment, Samsung R&D Institute India Bangalore Pvt. Ltd., Bangalore, India

Partial Fourier MRI (PF-MRI) is a common fast MRI technique to reduce the scan time. While POCS PF-MRI is known to produce MRI images with least amount of RMSE error, homodyne PF-MRI is popularly used in clinical practice. In this abstract we did digital phantom experiments to show that for smoothly varying phase, such as for FSE, POCS localises the error while an over-/under-estimation in image intensity is observed for Homodyne PF-MRI technique. However for fast varying phase such as for GRE, error is localised for Homodyne compared to POCS PF-MRI technique. 

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Easy-to-Implement and Rapid Image Reconstruction of Accelerated Cine and 4D Flow MRI Using TensorFlow
Valery Vishnevskiy1, Jonas Walheim1, Hannes Dillinger1, and Sebastian Kozerke1

1Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland

Many MR image reconstruction algorithms can be formulated as optimization problems and solved with gradient-based optimization methods of choice. In this work, we present and analyze the performance of the TensorFlow framework for modeling and solving MR image reconstruction problems. We test our approach on undersampled cine cardiac and 4D flow datasets. It is demonstrated that MR image reconstruction is easy to implement in TensorFlow, TensorFlow performs comparably to sophisticated optimization algorithms with theoretical convergence guarantees, and that TensorFlow is as fast as or faster compared to standard MR reconstruction toolboxes.

3523
Computer 91
A Python-based MRI Reconstruction Toolbox, “MRIPY”, for Compressed Sensing, Parallel Imaging and Machine Learning
Peng Cao1, Xucheng Zhu1, Jing Liu1, Yan Wang1, and Peder Larson1

1Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA, United States

A python-based open-source package, “MRIPY” combines the existing MRI reconstruction methods, i.e. compressed sensing and parallel imaging, with deep neural networks that are implemented in the Tensorflow software. 

3524
Computer 92
Uniform Combined Reconstruction (UNICORN) of Multi-channel Surface-coil Data at 7T without use of a Reference Scan
Venkata Veerendranadh Chebrolu1, Peter Kollasch1, Vibhas Deshpande2, John Grinstead3, Thomas Benner4, Robin Heidemann4, Daniel Spence5, Joel Felmlee5, Matthew Frick5, and Kimberly K Amrami5

1Siemens Healthineers, Rochester, MN, United States, 2Siemens Healthineers, Austin, TX, United States, 3Siemens Healthineers, Portland, OR, United States, 4Siemens Healthineers, Erlangen, Germany, 5Mayo Clinic, Rochester, MN, United States

An algorithm for correcting the intensity non-uniformity in MR images without the use of a calibration/reference scan was proposed and its efficacy was demonstrated at ultra-high-field in musculoskeletal MRI. The algorithm was shown to provide better sensitivity in the inferior/superior regions of the knee compared to state-of-the-art inhomogeneity correction filters. Without the use of a reference scan, the algorithm was also shown to provide image uniformity equivalent to calibration based methods.

3525
Computer 93
MR Fingerprinting using a Gadgetron-based reconstruction
Wei-Ching Lo1, Yun Jiang2, Dominique Franson1, Mark Griswold1,2, Vikas Gulani1,2, and Nicole Seiberlich1,2

1Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 2Department of Radiology, University Hospitals Cleveland Medical Center at Case Western Reserve University, Cleveland, OH, United States

Gadgetron-based online MRF reconstruction enables rapid generation of quantitative tissue property maps directly at the scanner before completing acquisition of the following slice. This technique can facilitate multicenter clinical studies and facilitate easier and direct comparisons of quantitative maps from different scanners.

3526
Computer 94
Sparsely Sampled Cardiac Diffusion Tensor Imaging Using Phase-Corrected Joint Low-Rank and Sparsity Constraints
Sen Ma1,2, Christopher T Nguyen2,3, Anthony G Christodoulou2, Sang-Eun Lee2,4,5,6, Hyuk-Jae Chang4,5,6, and Debiao Li1,2

1Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, 2Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 3Cardiovascular Research Center, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States, 4Severance Cardiovascular Hospital, Seoul, Republic of Korea, 5Yonsei-Cedars-Sinai Integrative Cardiovascular Imaging Research Center, Yonsei University, Seoul, Republic of Korea, 6College of Medicine, Yonsei University, Seoul, Republic of Korea

We propose to sparsely sample in vivo cardiac diffusion tensor imaging (CDTI) by combining a phase-corrected low-rank model and sparsity constraint. The proposed method was evaluated on 7 hypertrophic cardiomyopathy patients. Helix angle and mean diffusivity maps were compared against employing single constraint, and changes in helix angle transmurality and mean diffusivity were evaluated using Wilcoxon signed rank test to statistically determine the highest achievable acceleration factors preserving CDTI measurements with no significant difference. Our framework shows promise in accelerating acquisition window while preserving myofiber architecture features, and may allow higher spatial resolution or shorter temporal footprint in the future.

3527
Computer 95
Minimum-variance weighted image reconstruction and the application to MRI
Jyh-Miin Lin1 and Philippe Ciuciu2

1Department of Radiology, University of Cambridge, Cambridge, United Kingdom, 2Neurospin, CEA Saclay, Paris, France

Non-stationary MRI noise occurs in sparse and non-uniform k-space. Weighted least squares regression has been used to handle data with non-stationary noise. A minimum-variance weighting function may reduce the variance (image noise) of the image, and it may also relax the regularization needed for MRI reconstruction. To obtain the optimal weighting in non-uniform MRI reconstruction, this study uses the Monte Carlo method to determine the minimum-variance weighting function in Shepp-Logan phantom and breast MRI. The parameter $$$\alpha=-0.5$$$ provides a weighting function with the minimum-variance in the reconstructed images.

3528
Computer 96
Deep-SENSE: Learning Coil Sensitivity Functions for SENSE Reconstruction Using Deep Learning
Xi Peng1,2, Kevin Perkins1,3, Bryan Clifford1,3, Brad Sutton1,4, and Zhi-Pei Liang1,3

1Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Shenzhen, China, 3Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 4Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States

Parallel imaging is an essential tool for accelerating image acquisition by exploiting the spatial encoding effects of RF receiver coil sensitivity functions. In practice, the coil sensitivity functions are often estimated from low-resolution auto-calibration signals (ACS) which limits estimation accuracy and in turn results in aliasing artifacts in the final reconstructions. This paper presents a novel deep learning based method for coil sensitivity estimation which exploits empirical and physics-based prior information to produce high-accuracy estimates of coil sensitivity functions from low-resolution ACS. Results are given which demonstrate the proposed method provides a significant reduction in aliasing over standard methods.


Electronic Poster

Compressive MRI

Exhibition Hall Monday 14:45 - 15:45

3529
Computer 97
Joint Reconstruction of Images with Different Temporal Basis in Carotid Vessel Wall Imaging
Nan Wang1,2, Anthony Christodoulou1, Yibin Xie1, Zixin Deng1,2, Zhaoyang Fan1,3, and Debiao Li1,2

1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 2Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, 3Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States

We recently proposed two techniques, qMATCH and DCE, based on Low Rank Tensor (LRT) framework. qMATCH is a single 8-min scan for carotid T1 T2 mapping and LRT DCE is a 10-min scan evaluating inflammatory status of carotid atherosclerosis. The LRT DCE has many advantages over conventional DCE protocols, but has a scan time longer than typical 5-6 minutes. In this work, we proposed a new protocol combining qMATCH and 5-min DCE. In vivo studies have demonstrated the feasibility of the joint reconstruction. Results of joint reconstruction showed improved image quality with shortened scan time. 

3530
Computer 98
Accelerated Localized Correlated Spectroscopy with Compressed Sensing Reconstruction Using Joint Hankel Low Rank Regularization and Group Sparsity
Andres Saucedo1, Manoj K. Sarma1, and M. Albert Thomas1

1Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States

Compressed sensing (CS) combined with non-uniform undersampling, such as the low-rank Hankel matrix completion method, have accelerated the acquisition time of 2D magnetic resonance spectroscopy (MRS).  This technique relies on reconstructing the vector of all t1 points separately for each F2 point. We introduce a CS-based method that implements joint Hankel low rank regularization, which enforces the low-rankness of all Hankel matrices formed from the entire F2-t1 data simultaneously.  We compare this method with group sparsity CS reconstruction of retrospectively undersampled localized correlated spectroscopy (COSY) acquisitions in a brain phantom and calf muscle. 

3531
Computer 99
Patch-Tensor Low-n-Rank Reconstruction for Oscillating Steady State fMRI Acceleration
Shouchang Guo1 and Douglas C. Noll2

1Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, United States, 2Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States

Oscillating steady-state imaging is a new acquisition method for T2*-weighted functional MRI that offers very high SNR, but longer acquisition times.  The oscillations are highly reproducible, which make low-rank models suitable.  In this work, a sparse sampling scheme combined with a patch-based low-rank tensor reconstruction is introduced to speed the image acquisitions.  The low-n-rank algorithm was applied to oscillating steady state data to demonstrate the utility of this approach for functional MRI, demonstrating a 17-fold speed up with error levels less than 3%.

3532
Computer 100
Gini reweighted ℓ1 minimization for rapid MRI
Carlos Castillo-Passi1,2, Claudia Prieto1,2,3, Gabriel Varela-Mattatall1,2, Carlos Sing-Long2,4,5, and Pablo Irarrazaval1,2,5

1Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, 2Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, 3Division of Imaging Sciences and Biomedical Engineering, King’s College London, London, United Kingdom, 4Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, United States, 5Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

Under-sampling acquisition is oftenly used to reduce the scan time. Compressed Sensing allows the reconstruction of these data by solving a convex optimization problem. This is done to exploit the sparsity of the signals using the ℓ1-norm. We propose to use the Gini Index as a sparsity measure. In this work we demonstrate that this index allow to further increase the under-sampling factor. Interestingly this non-linear index can be computed by solving iteratively reweighted ℓ1 problems, without excessive computational load.

3533
Computer 101
Robust Autocalibrated LORAKS for Improved EPI Ghost Correction with Structured Low-Rank Matrix Models
Rodrigo A Lobos1, Ahsan Javed1, Krishna S Nayak1, W Scott Hoge2,3, and Justin P Haldar1

1Electrical Engineering, University of Southern California, Los Angeles, CA, United States, 2Radiology, Brigham and Women's Hospital, Boston, MA, United States, 3Radiology, Harvard Medical School, Boston, MA, United States

The presence of ghost artifacts is a recurrent problem in EPI images, which has been recently addressed using structured low-rank matrix (SLM) methods. In this work we propose a new SLM ghost correction method called Robust Autocalibrated LORAKS (RAC-LORAKS). RAC-LORAKS considers autocalibrated k-space constraints (similar to GRAPPA) to deal with the ill-posedness of existing SLM EPI ghost correction methods. RAC-LORAKS additionally adapts these constraints to enable robustness to possible imperfections in the autocalibration data.  We illustrate the capabilities of RAC-LORAKS in two challenging scenarios: highly accelerated EPI of the brain, and cardiac EPI with double-oblique slice orientation. 

3534
Computer 102
Compressive Sensing Reconstruction for Multi-Contrast Data with Unequal Acceleration Rates
Emre Kopanoglu1,2, Alper Güngör1, Toygan Kilic3,4, Emine Ulku Saritas3,4,5, Tolga Çukur3, and H. Emre Guven1

1Department of Advanced Sensing Research Programs, ASELSAN Research Center, Ankara, Turkey, 2School of Psychology / CUBRIC, Cardiff University, Cardiff, United Kingdom, 3Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey, 4National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey, 5Neuroscience Program, Bilkent University, Ankara, Turkey

In multi-contrast acquisitions, a critical concern is whether to distribute undersampling uniformly or unequally across contrasts, as scan times and SNR typically vary among sequences. This study investigates a compressive sensing framework in jointly reconstructing multi-contrast data with unequal acceleration rates. Using in-vivo and numerical datasets, the total scan time was fixed and acceleration factors were varied between protocols. The results suggest using lower acceleration rates for protocols with higher-SNR and shorter duration, and higher rates for protocols with lower-SNR and longer duration improves image quality, even in the highly accelerated contrast. The method was also compared to seven state-of-the-art methods from the literature. 

3535
Computer 103
Joint Sparse Reconstruction of Multi-contrast MRI Images with Graph Wavelets
Zongying Lai1, Xinlin Zhang1, Di Guo2, Xiaofeng Du2, Zhong Chen1, and Xiaobo Qu1

1Department of Electronic Science, Xiamen University, Xiamen, China, 2School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China

Multi-contrast images in magnetic resonance imaging (MRI) are widely applied in clinical applications, since an abundant contrast information reflects the characteristics of the internal tissue of human body, providing an effective reference for clinical diagnosis. However, long acquisition time limits the application of magnetic resonance multi contrast imaging. Under-sampling the k-space data and reconstructing images with sparsity constraint is one efficient way to accelerate magnetic resonance imaging sampling. In this work, multi-contrast undersampled MRI images are jointly reconstructed under the sparse representation using graph wavelets. Experiment results demonstrate that the proposed method outperforms the compared state-of-the-art methods.

3536
Computer 104
Feasibility of High Spatial and Temporal Resolution Breast DCE-MRI using Radial Acquisition with Data-Driven Model Consistency Condition Reconstruction
Pingni Wang1, Roberta M Strigel1,2,3, Julia V Velikina1, Alexey A Samsonov2, Leah C Henze Bancroft2, Kang Wang4, Ty A Cashen4, Kevin M Johnson1, and James H Holmes2

1Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 2Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States, 3Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI, United States, 4Global MR Applications & Workflow, GE Healthcare, Madison, WI, United States

Dynamic contrast-enhanced (DCE) MRI using conventional Cartesian sampling is used in routine clinical practice due to its high sensitivity for breast cancer. However, ghosting artifacts caused by cardiac motion can obscure the axilla, making interpretation of this area more difficult and potentially obscuring findings. Radial acquisitions are less motion sensitive due to more frequent sampling of the center of k-space and prior work has suggested these methods for breast MRI. In this study, we report results from a reader study to assess image quality of a 3D stack-of-stars radial acquisition compared with Cartesian imaging for breast MRI.

3537
Computer 105
The influence of Sampling on Compressed Sensing accelerated high resolution Vessel Wall Imaging
Sen Jia1,2, Jing Cheng1,2, Lei Zhang2, Xin Liu2, and Dong Liang2

1University of Chinese Academy of Sciences, Shenzhen, China, 2Shenzhen Institutes of Advanced Technology, Shenzhen, China

This study aims to accelerate high resolution whole brain and neck vessel wall imaging using combined Compressed Sensing and Parallel Imaging. The influence of sampling choices with different control of sampling density and randomness on CSPI reconstruction were investigated on retrospectively and prospectively accelerated in vivo datasets, with emphasis on the sharpness of vessel wall borders which was critically demanded by detecting potential vessel wall thickening and atherosclerotic plaques for ischemic stroke patients. 

3538
Computer 106
Evaluation of Sparse Sampling for Improved Image Quality of 19F Fluorinated Gas Lung Ventilation MRI
Adam Maunder1, Guilhem Collier1, Fraser Robb1,2, Madhwesha Rao1, and Jim Wild1

1POLARIS, Academic Radiology, University of Sheffield, Sheffield, United Kingdom, 2GE Healthcare Inc., Aurora, OH, United States

In an effort to improve image SNR per unit time and effective resolution in 19F-fluorinated gas ventilation imaging the application of compressed sensing was investigated. Simulations of sparse sampling were performed using a 3D 3He ventilation imaging dataset as a gold standard. Sparse and fully sampled image fidelity was quantified by the mean-square error and coefficient of variation of signal intensity. Simulations of low resolution and sparsely sampled images with equivalent acceleration factor were also compared. Based on the simulations prospective lung images using sparse sampling with C3F8 gas were then acquired in a healthy volunteer with acceleration factor of 4.

3539
Computer 107
On the importance of adapting compressed sensing for images with significant spatial phase variations
Jérémie P. Fouquet1, Michael Paquette2, Réjean Lebel1, Maxime Descoteaux2, and Martin Lepage1

1Centre d'imagerie moléculaire de Sherbrooke, department of Médecine nucléaire et radiobiologie, Université de Sherbrooke, Sherbrooke, QC, Canada, 2Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, QC, Canada

We explore the limits of compressed sensing (CS) in the practical setting of T2*-weighted imaging of the brain. Surprisingly, those limits are rapidly reached due in part to the presence of spatial phase variations. While conventional CS performs well for synthetic phase-free images, it is equally performant to or even outperformed by a simple zero-padding of the k-space center for acquired complex-valued images. Clearly, CS must be adapted to images including spatial phase variations, and our results point toward new solutions to achieve this adaptation.

3540
Computer 108
Evaluating the Normalised Iterative Hard Thresholding Algorithm for Compressed Sensing Reconstruction on 7T Cardiac cine MRI.
Sofia Dimoudi1, Matthew D Robson1, Jared Tanner2, and Aaron T Hess1

1Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom, 2Mathematical Institute, University of Oxford, Oxford, United Kingdom

We present our updated results in the evaluation of the Normalised Iterative Hard Thresholding Algorithm (NIHT) for parallel imaging and compressed sensing reconstructions of highly accelerated Cardiac cine MRI at 7 Tesla.  We compare imaging performance with three other parallel imaging and compressed sensing methods, including regularisation in the temporal dimension.

3541
Computer 109
3D Real-Time MRI of Vocal Tract Shaping
Yongwan Lim1, Yinghua Zhu1, Sajan Goud Lingala1, Dani Byrd1, Shrikanth S Narayanan1, and Krishna S Nayak1

1University of Southern California, Los Angeles, CA, United States

We demonstrate a new three-dimensional (3D) real-time MRI technique for the study of dynamic vocal tract shaping during human speech production. This, for the first time, enables a comprehensive assessment of vocal tract area function dynamics. We used a minimum-phase 3D slab excitation, stack-of-spirals gradient echo sequence, pseudo golden-angle view order in kx-ky, linear Cartesian order along kz, and sparse SENSE image reconstruction with spatiotemporal finite difference constraints. This provides 2.4 x 2.4 x 5.8 mm3 spatial resolution, 72 ms temporal resolution, and a 200 x 200 x 70 mm3 field-of-view, which covers the entire adult human vocal tract. 

3542
Computer 110
Accelerated volumetric renal perfusion using pseudo-continuous ASL and a 3D Fast-Spin-Echo readout with Compressed Sensing
Manuel Taso1, Li Zhao1, Arnaud Guidon2, Daniel V. Litwiller3, and David C. Alsop1

1Division of MRI Research, department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States, 2Global MR Applications and Workflow, GE Healthcare, Boston, MA, United States, 3Global MR Applications and Workflow, GE Healthcare, New York, NY, United States

While ASL is a promising technique to measure renal perfusion in multiple applications, its translation into clinical practice is still challenged by its motion-sensitivity and limited spatial coverage. In the current work, we propose an implementation of an undersampled Cartesian 3D-FSE readout with pseudo-continuous ASL labeling and Compressed-sensing reconstruction for fast whole kidney perfusion measurement. Results show that even at high acceleration factors (≈15), acceptable quality whole kidney ASL images could be obtained in less than a minute with increased motion-robustness. Furthermore, the CS acceleration enables acquiring multiple averages, providing increased coverage with similar SNR than mostly used 2D readouts. 

3543
Computer 111
Rapid Parallel MRI Reconstruction Utilizing the Wavelet Filter Bank
Efrat Shimron1, Andrew G. Webb2, and Haim Azhari1

1Department of Biomedical Engineering, Technion - Israel Institute of Technology, Haifa, Israel, 2Department of Radiology, Leiden University, Leiden, Netherlands

A novel method for reconstruction from highly undersampled parallel MRI data is proposed. The method computes the Stationary Wavelet Transform (SWT) of the unknown MR image directly from sub-sampled k-space measurements, and then recovers the image using the Inverse SWT filter bank. Experiments with in-vivo data show that this method produces high quality reconstructions, comparable to Compressed Sensing (CS) reconstructions. However, unlike CS, the proposed method is non-iterative. Moreover, it is simple, fast, and allows flexible (random or ordered) k-space undersampling schemes. 

3544
Computer 112
Accelerating Compressed Sensing in Cartesian Parallel Imaging Reconstructions using an Efficient and Effective Circulant Preconditioner
Jeroen van Gemert1, Kirsten Koolstra2, Peter Börnert3, Andrew Webb2, and Rob Remis1

1Circuits and Systems Group, Delft University of Technology, Delft, Netherlands, 2C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Leiden, Netherlands, 3Philips Research Hamburg, Hamburg, Germany

Reconstruction methods in parallel imaging and compressed sensing problems are generally very time consuming, especially for a large number of coil elements. In this work, the image is reconstructed using the Split Bregman algorithm (SB). We present an efficient and effective preconditioner that reduces the number of iterations in the linear least squares step of SB by almost a factor of 5 as alternative to extra variable splitting. The designed preconditioner works for Cartesian sampling schemes and for different coil configurations. It has negligible initialization time and leads to an overall speedup factor of 2.5.

3545
Computer 113
Synergistic reconstruction of undersampled multi-contrast MRI using weighted quadratic priors
ABOLFAZL MEHRANIAN1, Claudia Prieto1, Radhouene Neji1,2, Colm J. McGinnity3, Alexander J. Hammers3, and Andrew J. Reader1

1School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom, 2MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom, 3School of Biomedical Engineering and Imaging Sciences, King’s College London & Guy’s and St Thomas’ PET Centre, London, United Kingdom

We propose a simple and robust methodology for synergistic multi-contrast MR image reconstruction to improve image quality of undersampled MR data beyond what is achieved from conventional independent reconstruction methods. The advantages of the proposed methodology are threefold: i) it exploits quadratic priors that are mutually weighted using all available MR images, leading to preservation of unique features, ii) the weighting coefficients are independent of the relative signal intensity and contrast of different MR images and iii) the algorithm is based on a well-established parallel imaging iterative reconstruction, which makes the synergistic reconstruction of undersampled MR data clinically feasible

3546
Computer 114
Parallel imaging compressed sensing for MRI-only radiation dosimetry of post-implant prostate cancer brachytherapy
Jeremiah Sanders1, Steven Frank2, Hao Song1, Paula Berner2, Aradhana Venkatesan3, and Jingfei Ma1

1Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States, 2Radiation Oncology, MD Anderson Cancer Center, Houston, TX, United States, 3Diagnostic Radiology, MD Anderson Cancer Center, Houston, TX, United States

Researchers recently demonstrated that both anatomical structures and implanted radioactive seeds can be visualized with high-resolution balanced steady-state free precession (bSSFP) imaging using positive-MRI-signal seed markers and an endorectal coil (ERC). However, ERC use is limited by cost, patient intolerance, and low clinical throughput. A previous preliminary study demonstrated that imaging without an ERC resulted in reduced image signal-to-noise ratio and reduced seed detection. In the current study, we investigated the feasibility of using parallel imaging compressed sensing to substantially accelerate the bSSFP acquisition and potentially enable MRI-only dosimetry of post-implant prostate cancer brachytherapy without an ERC.

3547
Computer 115
Self-calibrating nonlinear MR image reconstruction algorithms for variable density sampling and parallel imaging
Loubna EL GUEDDARI1, Carole LAZARUS1, Hanaé CARRIE1, Alexandre VIGNAUD2, and Philippe CIUCIU1

1CEA/NeuroSpin & INRIA Parietal, Gif-sur-Yvette, France, 2CEA/NeuroSpin, Gif-sur-Yvette, France

Compressed Sensing has allowed a significant reduction of acquisition times in MRI. However, to maintain high signal-to-noise ratio during acquisition, CS is usually combined with parallel imaging (PI). Here, we propose a new self-calibrating MRI reconstruction framework that handles non-Cartesian CS and PI. Sensitivity maps are estimated from the data in the center of k-space while MR images are iteratively reconstructed by minimizing a nonsmooth criterion using the proximal optimized gradient method, which converges faster than FISTA. Comparison with L1-ESPIRiT suggests that our approach performs better both visually and numerically on 8-fold accelerated Human brain data collected at 7 Tesla.

3548
Computer 116
Locally Low Rank Regularization for Magnetic Resonance Fingerprinting
Gastao Cruz1, Aurelien Bustin1, Olivier Jaubert1, Torben Schneider2, René M Botnar1, and Claudia Prieto1

1School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2Philips Healthcare, Guildford, United Kingdom

Magnetic Resonance Fingerprinting (MRF) estimates simultaneous, multi-parametric maps from a dynamic series of highly undersampled time-point images. At very high undersampling factors, some of these artefacts may propagate into the parametric maps leading to errors. Here we propose the use of locally low rank regularization for a low rank approximation reconstruction to enable highly accelerated MRF. The proposed approach was evaluated in simulations and in-vivo­ brain acquisitions. Results show that the proposed approach enables accurate MRF reconstructions from ~600 time-point images with one radial spoke per time-point. 

3549
Computer 117
Accelerating T2 Mapping Using a Self-trained Kernel PCA Model
Chaoyi Zhang1, Ukash Nakarmi1, Hongyu Li1, Yihang Zhou2, Dong Liang3, and Leslie Ying1,4

1Electrical Engineering, University at Buffalo, SUNY, Buffalo, NY, United States, 2Medical Physics and Research department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, 3Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Shenzhen, China, 4Biomedical Engineering, University at Buffalo, SUNY, Buffalo, NY, United States

Kernel Principal component analysis(KPCA) model has recently been proposed to accelerate dynamic cardiac imaging. In this abstract, we study the effectiveness of KPCA for MR T2 mapping from highly under-sampled data acquired at different echo time. Different from dynamic cardiac imaging where only morphological information is needed, the quantitative values are highly important in parameter mapping. Here we use a self-trained KPCA model to guarantee the accuracy of the reconstructed T2 maps. The experimental results show that the proposed method can recover the T2 map with high fidelity at high acceleration factors.

3550
Computer 118
Accelerated real-time spiral MRI for high-resolution velum imaging using low rank and sparse decomposition and Chebyshev based off-resonance correction
Xue Feng1, Catherine M Pelland1, Silvia S Blemker1, and Craig H Meyer1

1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States

In this study, an accelerated real-time spoiled spiral GRE sequence was developed for high-resolution velum imaging during speech to evaluate VPI. The low rank plus sparse decomposition was used to reconstruction highly undersampled (6x) dynamic image series. Chebysheve based off-resonance correction was used to reduce local blurring around velum after L+S reconstruction. The developed method generated high quality dynamic images with minimal temporal blurring and reduced blurring at 1.5 T, which can then be used to track velum movements for further analysis.

3551
Computer 119
Highly Accelerated 3D Chemical-Shift Magnetic Resonance Imaging Using 4D Compressed Sensing
Jian-xiong Wang1, Xiaodong Wen1, Crystal Harrison1, A Dean Sherry1, and Craig R Malloy1

1Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States

Compressed Sensing method using 4D operators and functions to treat the entire 4D data as unity can perform high reduction rate of acceleration and preserve excellent data fidelity. This work demonstrated its effectiveness on 3D chemical-shift-imaging with reduction rate R=16 or 6.25% sampling ratio and up to R=32 or 3.125% sampling ratio. The method has been implemented onto MRI scanner for real-time sparse 3D CSI acquisition. The excellent data fidelity are demonstrated with 3D CSI images of phantom and in-vivo hyperpolarized [1-13C]pyruvate and its production metabolites.

3552
Computer 120
MR image reconstruction using the Chambolle-Pock algorithm
Jing Cheng1, Sen Jia1, Haifeng Wang1, and Dong Liang1

1Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences, Shenzhen, China

The combination of Parallel imaging (PI) and compressed sensing (CS) allow high quality MR image reconstruction from partial k-space data. However, most CS-PI MRI methods suffer from detail loss with large acceleration and complicated parameter selection. In this work, we describe and evaluate an efficient and robust algorithm to overcome these limitations. The experimental results on in vivo data show that, the proposed method using a first-order primal-dual algorithm can successfully remove undersampling artifacts while keeping the details with little parameter tuning compared with the existing advanced method.


Electronic Poster

Hyperpolarisation: Technical Developments

Exhibition Hall Monday 16:15 - 17:15

3553
Computer 1
A Late-Stage Deuteration Method for T1 Prolongation and Enhanced In Vivo Signal to Noise Ratio of Hyperpolarized 13C Substrates
Céline Taglang1, David E. Korenchan1, Cornelius von Morze1, Chloé Najac1, Joseph E. Blecha1, Justin Yu1, Sukumar Subramaniam1, Robert Bok1, Henry VanBrocklin1, Renuka Sriram1, John Kurhanewicz1, David M. Wilson1, and Robert R. Flavell1

1Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States

One of the fundamental limitations of hyperpolarized 13C technology is the effective lifetime of the signal, which decays in keeping with the spin-lattice relaxation constant T1. We have developed a robust late stage deuteration methodology which is broadly applicable to amino and alpha hydroxyl acids, including commonly used probes such as alanine and lactate. This methodology enables significant T1 prolongation, yielding an effective doubling of in vivo signal to noise ratio at relevant imaging time-points. We tested [1-13C, 2-2H]alanine prepared via this method both in vitro and in vivo. This broadly applicable methodology may facilitate implementation and translation of hyperpolarized 13C MRI probes.

3554
Computer 2
Spiral-In/Out Multi Spin-Echo Acquisitions for Increased SNR in Dynamic Hyperpolarized 13C MRI
Shuyu Tang1, Robert Bok1, Eugene Milshteyn1, Daniel Vigneron1, and Peder Larson1

1University of California at San Francisco, San Francisco, CA, United States

The long T2 relaxation time of hyperpolarized 13C-labeled metabolites at 3T allows efficient use of hyperpolarized signal by multi spin-echo readouts. This work presents a novel 13C sequence that uses spiral in/out acquisitions at multiple spin echoes, each formed by a single adiabatic pulse to improve signal-to-noise ratio(SNR) in dynamic hyperpolarized 13C MRI. The proposed sequence was tested in vivo on a normal rat on a clinical 3T scanner. Results show that the proposed method has improved SNR for 15 dynamic acquisitions over 30s.

3555
Computer 3
Developing a Regional Bolus Tracking and Real-time B1 Calibration Method for Hyperpolarized 13C MRI
Shuyu Tang1, Eugene Milshteyn1, Galen Reed2, Jeremy Gordon1, Robert Bok1, Daniel B. Vigneron1, and Peder Larson1

1University of California at San Francisco, San Francisco, CA, United States, 2HeartVista, Los Altos, CA, United States

Acquisition timing and B1 calibration are two key factors that affect the quality and accuracy of hyperpolarized 13C MRI. This project developed a new approach using regional bolus tracking to trigger Bloch-Siegert B1 mapping and real-time regional RF power compensation, followed by dynamic imaging of hyperpolarized 13C metabolites. The feasibility of applying the proposed framework for in vivo hyperpolarized 13C imaging was demonstrated on healthy rats and tumor-bearing mice on a clinical 3T scanner. This proposed method was designed to improve efficient use of hyperpolarized magnetization as well as the accuracy and robustness of hyperpolarized 13C MRI. 

3556
Computer 4
A perfused heart system to simulate first pass observation of rat cardiac metabolism with hyperpolarized [1-¹³C]pyruvate and determination of LDH flux using selective excitation
Gal Sapir1, Talia Harris1, Assad Azar1, Atara Nardi-Schreiber1, Ayelet Gamliel1, Jacob Sosna1, Moshe J. Gomori1, and Rachel Katz-Brull1

1Radiology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel

Aberrant cardiac metabolism is linked to major health issues in the Western world including diabetes and heart failure. New tools are needed to investigate these conditions and to allow better diagnosis. In this work we used dissolution dynamic nuclear polarization NMR spectroscopy (dDNP-NMR) to investigate [1-13C]pyruvate metabolism in the isolated rat heart. A perfusion system simulating in vivo first-pass hemodynamics was used to measure the enzymatic flux through lactate dehydrogenase (LDH) using product selective excitation. LDH flux was found to be 52 ± 8 nmol lactate/s/g wet weight (n=3). 

3557
Computer 5
The effect of ¹H-decoupling on hyperpolarized ¹³C signal decay – a study on choline chloride analogs and comparison to the effect of deuterium substitution of directly bonded protons
Sivaranjan Uppala1, Gamliel Ayelet1, Atara Nardi Schreiber1, Talia Harris1, Jacob Sosna1, J. Moshe Gomori1, and Rachel Katz-Brull1

1Hadassah-Hebrew University Medical Center, Jerusalem, Israel

The spin-lattice relaxation time (T1) of a DNP molecular probe is a key parameter in acquiring NMR signals in dissolution-DNP (d-DNP) experiments. Using molecular probes with long T1, NMR spin signals can survive for a duration sufficient for the study of metabolism (1-3 min). Deuteration of directly bonded 13C protonated positions has been useful in prolonging the visibility of hyperpolarized labeled 13C sites that are otherwise protonated. Here, we sought to investigate whether proton irradiation could affect the T1 of such 13C nuclei when such positions are in their naturally abundant form, i.e. directly bonded to protons.

3558
Computer 6
Optimizing signal-to-noise ratio for hyperpolarized carbon-13 magnetic resonance imaging using a hybrid flip angle scheme
Lauren Smith1, Trevor Wade1,2, Alireza Akbari1,2, Conrad Rockel1, Lanette Friesen-Waldner1, and Charles McKenzie1,2,3

1Medical Biophysics, Western University, London, ON, Canada, 2Robarts Research Institute, London, ON, Canada, 3Maternal, Fetal & Newborn Health, Children's Health Research Institute, London, ON, Canada

Hyperpolarized 13C imaging can provide useful metabolic information; however, rapid decay of hyperpolarized signal leads to reduced signal-to-noise ratio (SNR) images. We demonstrate an RF excitation scheme that dynamically changes the RF spectral profile and amplitude to achieve flip angles that vary throughout the acquisition independently for each metabolite. This preserves signal during a dynamic imaging experiment maintaining more signal for later time-points than using a constant RF pulse. Increased in vivo SNR at later time points of [1-13C]pyruvate and its metabolites was shown by dynamic imaging experiments in guinea pigs with both constant and variable flip angle schemes. 

3559
Computer 7
Optimized Single Shot 3D Sequence for High Resolution Hyperpolarized 13C Imaging
Jiazheng Wang1, Richard L Hesketh1, Alan J Wright1, and Kevin M Brindle1,2

1Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom, 2Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom

We have developed a single-shot 3D sequence for hyperpolarized 13C MRI, which uses a spatial-spectral (SpSp) pulse for excitation, a train of adiabatic pulses for refocusing, and a stack-of-spirals acquired through a fast-spin-echo train. The sequence achieved an isotropic image resolution of 1.25x1.25x1.25 mm3 in vivo on a 7 T animal system, where hyperpolarized [1-13C]pyruvate and [1-13C]lactate were imaged alternately at a frame rate of 2 s per metabolite. Signals from extra spirals acquired from later spin echoes were averaged with those from the early echoes to give a high signal-to-noise ratio (SNR) as well as high spatial resolution.

3560
Computer 8
Multichannel Hyperpolarized 13C MRI in a Patient with Liver Metastases using Multi-slice EPI and an Alternating Projection Method for Denoising
Rie B Hansen1, Jeremy W Gordon2, Peter J Shin2, Zihan Zhu2,3, Daniele Mammoli2, Pamela N Munster4, Rahul Aggarwal4, Michael A Ohliger2, Peder EZ Larson2, Lars G Hanson1, Jan H Ardenkjær-Larsen1, and Daniel B Vigneron2

1Department of Electrical Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark, 2Department of Radiology and Biomedical Imaging, UCSF, San Francisco, CA, United States, 3UC Berkeley-UCSF Graduate Program in Bioengineering, UC Berkeley and UCSF, San Francisco, CA, United States, 4Department of Medicine, UCSF, San Francisco, CA, United States

Hyperpolarized 13C-pyruvate for monitoring metabolism of liver metastases in vivo is being investigated for clinical trials of new therapeutics. This study applied advances in multichannel receive arrays and sequence design for human 13C liver imaging and investigated a new denoising method. The method is based on an alternating projection method to enforce structuredness and low-rankness, and is applied with automatic threshold estimation. In vivo data demonstrate improved quality of kinetic modeling after denoising. However, simulations revealed certain unresolved pitfalls.

3561
Computer 9
Slice Profile Induced Errors in Metabolic Quantification of Hyperpolarized Pyruvate.
Christopher M Walker1 and James A Bankson1

1Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States

Hyperpolarized pyruvate is being explored as a quantitative imaging biomarker of metabolism. Non-ideal slice excitation of hyperpolarized magnetization can result in temporally evolving slice profiles. This work evaluates the impact of slice profile on quantitative analysis of hyperpolarized pyruvate using a perfused Bloch-McConnell simulator.  Results indicate that the slice profile can cause significant bias in the measured apparent metabolic exchange constant. Primary sources of bias are excess signal from the slice penumbra and the offset between metabolite slices. Therefore, it will be critical to properly account for the slice profile when attempting to quantify hyperpolarized signal using slice selective excitations.

3562
Computer 10
Improving robustness of hyperpolarized 13C MRSI using k-t spiral acquisitions
Erin Adamson1, Benjamin Cox1,2,3, and Sean Fain1,4,5

1Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 2Morgridge Institute for Research, Madison, WI, United States, 3Laboratory for Optical and Computational Instrumentation, University of Wisconsin-Madison, Madison, WI, United States, 4Radiology, University of Wisconsin-Madison, Madison, WI, United States, 5Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States

Hyperpolarized 13C MRSI with chemical shift encoding relies on a priori knowledge of the N 13C-labeled metabolite resonances and N+1 echoes to fully determine the reconstruction. However, the a priori frequencies may shift due to B0 inhomogeneity, local susceptibilities, or motion, causing spectral leakage, blurring, and biased quantitative measures. To address these uncertainties, we apply IDEAL-based k-t spiral imaging with field-of-view oversampling to further constrain the signal model-based reconstruction in situations where the echo-spacing may be suboptimal, and we test the results in digital simulations, phantom experiments, and in vivo studies of murine renal metabolism. Results support improved metabolic quantification.

3563
Computer 11
Mitigating Chemical Exchange Effects in Advanced Pulse Sequences for pH Imaging with Hyperpolarized [13C]bicarbonate
David E Korenchan1, Jeremy W Gordon1, Sukumar Subramaniam1, Renuka Sriram1, Peder E Z Larson1,2, Robert R Flavell1, and John Kurhanewicz1,2

1Radiology and Biomedical Imaging, UC San Francisco, San Francisco, CA, United States, 2Bioengineering, UC San Francisco, San Francisco, CA, United States

Imaging extracellular acidification in tumors will likely lead to better characterization of tumor aggressiveness and treatment efficacy. Hyperpolarized (HP) [13C]bicarbonate magnetic resonance spectroscopic imaging (MRSI) can map pH in murine tumors, but images generally suffer from low signal-to-noise ratio (SNR) and coarse spatial resolution. Although sophisticated pulse sequences can boost SNR, pH accuracy can be compromised due to bidirectional [13C]bicarbonate <-> 13CO2 chemical exchange during imaging. We investigated several pulse sequences and excitation/refocusing schemes, and a modified 2D echo-planar imaging sequence with spectral-spatial excitation demonstrated the best combination of spatial resolution, pH accuracy, and potential for future clinical implementation.

3564
Computer 12
Modeling In Vivo Metabolism of Hyperpolarized Pyruvate in Human Brain Tumor Patients.
Daniele Mammoli1, Jeremy Gordon1, Adam Autry1, Peder EZ Larson1, Hsin-Yu Chen1, Mark Van Criekinge1, Lucas Carvajal1, Ilwoo Park2, James B Slater1, Robert Bok1, Jason Crane1, Markus Ferrone3, John Kurhanewicz1, Susan Chang4, and Daniel B Vigneron1

1Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, 2Chonam National University Medical School and Hospital, Chonam, Korea, Democratic People's Republic of, 3Clinical Pharmacy, University of California San Francisco, San Francisco, CA, United States, 4Neurological Surgery, University of California San Francisco, San Francisco, CA, United States

We show preliminary results of hyperpolarized [1-13C]pyruvate injected in 9 patients affected with glioma.

Raw data showed excellent SNR. Variable bolus delivery and magnitude images introduced errors in modeling the conversion of pyruvate into lactate: kinetic models were presented and compared quantitatively to address these issues.

Finally, reliable and spatially-resolved maps of kPL rates were obtained, which can be useful in future to assess the clinical relevance of the method for both diagnosis and response to therapy.


3565
Computer 13
Comparison between 8- and 32-channel phased-array receive coils for in vivo hyperpolarized C-13 brain imaging
Adam Autry1, Jeremy W Gordon1, Lucas Carvajal1, Ilwoo Park2, Daniele Mammoli1, Hsin-Yu Chen1, Susan Chang3, Yan Li1, Duan Xu1, Daniel Vigneron1, and Sarah J Nelson1,4

1Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, 2Department of Radiology, Chonam National University Medical School and Hospital, Chonam, Republic of Korea, 3Department of Neurosurgery, University of California, San Francisco, San Francisco, CA, United States, 4Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States

This study sought to evaluate the performance of the first 32-channel head coil for in vivo hyperpolarized 13C brain imaging by comparison against a conventional 8-channel receiver array. Initial phantom experiments characterized the B1+ homogeneity and SNR profiles associated with each hardware configuration via EPI-based imaging techniques. As part of a clinical trial, in vivo dynamic EPI data were also acquired from patients with brain tumors. Phantom and patient data revealed improved uniformity, coverage, and SNR with the 32-channel array that will promote higher resolution and acceleration. In vivo data also demonstrated unprecedented detection of bicarbonate using both hardware platforms.

3566
Computer 14
Probing renal pH and aminopeptidase N activity with hyperpolarized [1-13C]alaninamide
Alice Radaelli1, Hikari Ananda Infinity Yoshihara1, Ryunosuke Hata2, Shinsuke Sando3, and Rolf Gruetter1,4

1Laboratory for Functional and Metabolic Imaging (LIFMET), EPFL, Lausanne, Switzerland, 2Department of Chemistry and Biochemistry, Kyushu University, Fukuoka, Japan, 3Department of Chemistry and Biotechnology, The University of Tokyo, Tokyo, Japan, 4Center for Biomedical Imaging (CIBM), Lausanne, Switzerland

The detection of aminopeptidase N (APN) activity can give information on tumor development. Hyperpolarized L-[1-13C]alaninamide is a specific, sensitive probe of APN activity in kidney homogenate. Here, we characterized its in vivo metabolic response in the rat kidney. In addition to being an APN substrate, L-[1-13C]alaninamide is sensitive to pH and also reacts with dissolved carbon dioxide. To avoid spectral overlap, alaninamide is best suited as an APN probe in acidic environments, and it may have additional applications as a multifunctional sensor of pH and CO2.

3567
Computer 15
Susceptibility-Induced Distortion Correction in Hyperpolarized Echo Planar Imaging
Jack J J J Miller1,2,3, Angus Z Lau1,4, and Damian J Tyler1,3

1Oxford Centre for Clinical Magnetic Resonance Research, University of Oxford, Oxford, United Kingdom, 2Department of Physics, University of Oxford, Oxford, United Kingdom, 3Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom, 4Sunnybrook Research Institute, Toronto, ON, Canada

Echo Planar Imaging is an attractive rapid imaging readout that can image hyperpolarized compounds in vivo. By alternating the sign of the phase encoding gradient waveform, spatial offsets arising from uncertain frequency shifts can be determined. We show here that blip-reversed EPI can also be used to correct for susceptibility and $$$B_0$$$ inhomogeneity effects that would otherwise produce image-domain distortion in the heart, through the use of an estimated deformation field that is calculated from the acquired data. 

3568
Computer 16
Extended Signal Modelling and Regularization for Multi-Echo Hyperpolarized Metabolic Image Reconstruction
Julia Busch1, Valeriy Vishnevskiy1, Maximilian Fuetterer1, Claudio Santelli1, Constantin von Deuster1, Sophie Marie Peereboom1, Mareike Sauer2, Thea Fleischmann2, Nikola Cesarovic2, Christian Torben Stoeck1, and Sebastian Kozerke1

1Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland, 2Division of Surgical Research, University Hospital Zurich, Zurich, Switzerland

The IDEAL signal model for hyperpolarized metabolic imaging is extended and spatiotemporal regularization and b0-map recalibration is included. The approach is tested on simulated data and in-vivo metabolic imaging data of the heart. Allowing variable b0-fields and including sparsity regularization signal leakage and ghosting can be significantly reduced (average reduction of root-mean-square error (RMSE) by 16% and 30%). Spatial and temporal regularization of the metabolite intensities considerably improved accuracy of the estimate in terms of RMSE with additional reductions by 68% and 20%, respectively. Thus, the metabolic conversion of [1-13C]pyruvate into [1-13C]lactate and 13C-bicarbonate can be measured with improved accuracy.

3569
Computer 17
Combined FDG-PET and hyperpolarized pyruvate-MRSI (hyperPET) for cancer metabolic phenotyping – a pilot study
Sissel Bisgaard1, Andreas Ettrup Clemmensen1, Abubakr Eldirdiri2, Helle Hjorth Johannesen1, Jan Henrik Ardenkjær-Larsen2, Adam Espe Hansen1, and Andreas Kjær1

1Department of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging, Rigshospitalet and University of Copenhagen, Copenhagen, Denmark, 2Center for Hyperpolarization in Magnetic Resonance, DTU Elektro, Technical University of Denmark, Kgs. Lyngby, Denmark

Molecular imaging of cancer metabolism in vivo is increasingly employed in clinical settings. Both 18F-FDG PET and hyperpolarized [1-13C]pyruvate MRSI are sensitive to glucose metabolism but differ in which part of the glycolytic pathway is probed. We hypothesize that hyperPET may improve cancer specific metabolic phenotyping. Simultaneous 18F-FDG PET and hyperpolarized [1-13C]pyruvate MRSI (hyperPET) was used in a pilot study, examining the metabolic characteristics exhibited by four different cancer cell lines in nude mice. The results indicated that the combined modalities may distinguish between cancer types.

3570
Computer 18
Improved Hyperpolarized Cerebral Perfusion Imaging Using a Sucrose/Water Glassing Matrix for tert-Butanol
Gopal Varma1, Patricia Coutinho de Souza1, Cody Callahan1, David C Alsop1, and Aaron K Grant1

1Division of MR Research, Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States

Perfusion imaging is a promising application for hyperpolarized tracers, as they provide high signal with no endogenous background.  Hyperpolarized 13C labeled tert-butanol is a freely diffusible perfusion agent with long T1 and T2 relaxation times in vivo. Prior work has shown that tert-butanol can be polarized to 5-10% using dynamic nuclear polarization through addition of glycerol as a glassing agent.  Here we investigate a formulation based on a water/sucrose/tert-butanol mixture that yields a 1.6-fold improvement in polarization, and illustrate its use in 3D cerebral perfusion imaging in rats.

3571
Computer 19
A robust approach to generate high polarization levels of metabolites within seconds with para-hydrogen
Sergey Korchak1, Shengjun Yang1, Salvatore Mamone1, and Stefan Glöggler1

1NMR Signal Enhancement, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany

Hyperpolarization of metabolites is a promising approach for in vivo disease detection and observation of treatment responses.1-4 Among hyperpolarization techniques, para-hydrogen induced polarization (PHIP) represents an inexpensive approach to generate polarization within a few seconds.5-11 Here, we are introducing a pulsed magnetic resonance method to polarize metabolites that enables us to efficiently transfer proton polarization to a 13C nucleus of interest. This becomes especially possible by attaching an optimized molecular sidearm to a metabolite of choice (here: acetate, glycine and pyruvate) which is para-hydrogenated and the polarization subsequently transferred. We have achieved high levels of metabolite precursor polarization (P >10%) with para-hydrogen within 15 seconds. Cleavage of the sidearm yields hyperpolarized metabolites.

3572
Computer 20
Hyperpolarization without a polarizer: in vivo 13C-MRI using SAMBADENA
Andreas B. Schmidt1,2, Stephan Berner1,3,4, Moritz Braig1, Mirko Zimmermann1, Jürgen Hennig1, Dominik von Elverfeldt1, and Jan-Bernd Hövener2,4

1Radiology - Medical Physics, University Medical Center Freiburg, Freiburg, Germany, 2Radiology and Neuroradiology, University Medical Center Schleswig-Holstein, Kiel, Germany, 3German Consortium for Cancer Research (DKTK), Heidelberg, Germany, 4German Cancer Research Center (DKFZ), Heidelberg, Germany

Hyperpolarization (HP) enhances the sensitivity of MR by several orders of magnitude and allows the detection of metabolism non-invasively and in vivo. However, well-established methods are costly, complex and require a dedicated “polarizer” next to the MRI system. SAMBADENA is, to date, the simplest and most cost-effective method to generate 13C-HP > 20 % for MRI. Within seconds HP is achieved within the MRI and little additional hardware is required. Here, the first in-vivo applications of SAMBADENA are reported, demonstrating its potential to be a fast, simple, low-cost alternative method for HP-MRI.

3573
Computer 21
Considerations for Spin Order Transfer to 13C-labeled pyruvate precursors by Parahydrogen-induced Polarization for in vivo applications
Neil James Stewart1, Mitsushi Tomohiro1, Yoshiki Uchio1, Kensuke Takoshima1, and Shingo Matsumoto1

1Graduate School of Information Science & Technology, Hokkaido University, Sapporo, Japan

The recent achievement of 13C-pyruvate polarization by side-arm para-hydrogen induced polarization (SA-PHIP) in-vitro has renewed interest in PHIP, which has been limited by a lack of biologically-relevant directly-polarizable compounds. To investigate the achievable polarization of 13C-pyruvate by SA-PHIP for in-vivo metabolic MRI, density matrix simulations of polarization transfer by magnetic field cycling (MFC) and spin-order transfer (SOT) pulse sequences were performed for target precursors. MFC-based approaches were confirmed to be suitable for polarization transfer over the long-range J-couplings present in SA-PHIP precursors. Additionally, simulated polarization levels with SOT approaches were reasonable for representative 13C-pyruvate precursors, promising for metabolic MRI. 

3574
Computer 22
Feasibility of Imaging Lung Cancer Using Hyperpolarized MRI Technology
Mehrdad Pourfathi1, Luis Loza1, Stephen Kadlecek1, Ian Duncan1, Diane Lim2, Shampa Chatterjee3, Kai Ruppert1, Sarmad Siddiqui1, Harrilla Profka1, Yan Liu2, Jessica Kim2, Hooman Hamedani1, Yi Xin1, Faraz Amzajerdian1, Maurizio Cereda4, Ryan Baron1, Mary Spencer1, Tahmina Achekzai1, Jose Conejo-Garcia5, and Rahim R. Rizi1

1Radiology, University of Pennsylvania, Philadelphia, PA, United States, 2Sleep Medicine, University of Pennsylvania, Philadelphia, PA, United States, 3Physiology, University of Pennsylvania, Philadelphia, PA, United States, 4Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, United States, 5Moffitt Cancer Center, Tampa, FL, United States

We demonstrate the feasibility of hyperpolarized MRI technology to image lung cancer in mice. We demonstrated the use of 13C MRSI to detect elevated pyruvate to lactate conversion in the tumor relative to the adjacent non-cancerous lung tissue. We also showed the feasibility of 129Xe imaging to detect non-aerated regions in the lung tissue co-localized with the tumor. The utility of these modalities combined may provide a multi-faceted tool to assess tumor's stage and its response to therapy in lung cancer.

3575
Computer 23
Improved Hyperpolarization of Solid and Mesoporous Nanoscale Silicon Particles Using TEMPO Radicals Allows In Vivo 29Si MRI
Nicholas Whiting1,2, Jingzhe Hu1,3, Shivanand Pudakalakatti1, Caitlin McCowan1,3, Hyeonglim Seo4, Youngbok Lee4, and Pratip Bhattacharya1

1The University of Texas MD Anderson Cancer Center, Houston, TX, United States, 2Rowan University, Glassboro, NJ, United States, 3Rice University, Houston, TX, United States, 4Hanyang University, Ansan, Republic of Korea

Hyperpolarized silicon microparticles have been previously demonstrated as in vivo MRI contrast agents; unfortunately, their large size and decreased mobility present limitations for targeted molecular imaging. While nanoscale silicon particles can also be hyperpolarized, their signal enhancement is typically limited by a low concentration of endogenous electrons. As such, no studies to date have demonstrated in vivo 29Si MRI of hyperpolarized nano-scale silicon. We demonstrate improved 29Si hyperpolarization with the addition of an exogenous radical species to both solid and mesoporous nanoparticle samples (30-300 nm diameter), which increases 29Si hyperpolarization and allows in vivo imaging of silicon nanoparticles.

3576
Computer 24
Macrocyclic Xenon hosts: potential inhibitors and reporters for protein aggregation in Hyper-CEST MRI
Jan Oliver Jost1, Christopher Witte1, and Leif Schröder1

1Molecular Imaging, Leibniz Forschungsinstitut für Molekulare Pharmakologie, Berlin, Germany

Contrast agents for neurodegenerative diseases such as amyloidosis are challenging for MRI due to sensitivity limitations. Using hyperpolarized Xenon with special Xe hosts in combination with chemical excitation saturation transfer (CEST) has the potential to overcome this issue. It has been demonstrated that Cucurbit[7]uril (CB7) is inhibiting the fibrillation of Aβ40/ Aβ42 by interaction with its Phe residues. In parallel, we have demonstrated that CB7 can be used as a Xe-host. Here we present first results for a concept that uses CB7 as a drug and Xe biosensor simultaneously where binding of CB7 to Aβ40 can be detected by changing the Xe-HyperCEST signal.


Electronic Poster

Molecular Imaging

Exhibition Hall Monday 16:15 - 17:15

3577
Computer 25
First-pass Perfusion MRI of Myocardial Infarction Using a Novel Manganese Chelate Contrast Agent in a Rabbit Model
Lingyi Wen1, Zhigang Yang2, Hang Fu1, Kun Zhang2, Ran Sun1, and Yingkun Guo1

1Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, China, 2Department of Radiology, West China Hospital, Sichuan University, Chengdu, China

First-pass perfusion MRI allows evaluation of myocardial perfusion in myocardial infarction (MI). While Gd3+-based contrast agents are incompatible with renal compromise, we designed and synthesized a novel manganese (Mn2+ ) based contrast agents. MI was induced in 4 rabbits, Mn2+ based and Gd3+-based first-pass perfusion MRI were performed on a 3.0T MRI scanner. All rabbits survived without significant differences in heart rate and left ventricular function. All the perfusion parameters of infarcted and normal myocardial segments correlated well between Gd-based and Mn-based perfusion imaging. Our novel Mn2+ contrast agents is safe and reliable to visualize myocardial perfusion in MI.

3578
Computer 26
Intracellular Assembly of Olsalazine Nanoparticles for CEST MR Imaging and Cancer Therapy
Yue Yuan1, Xiaoliang Qi1, Jia Zhang1, Xiaolei Song1, Michael T. McMahon2, and Jeff W.M. Bulte1

1The Russell H. Morgan Department of Radiology and Radiological Science; Cellular Imaging Section, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States

Based on a biocompatible condensation reaction caused by tumor-related proprotein convertase furin, we developed a novel probe RRVR-Olsa for tumor-targeted CEST MR imaging and chemotherapy to accomplish theranostics. Our preliminary studies indicated that, RRVR-Olsa elicited an obvious increase in CEST signal and higher cytotoxicity on furin-overexpressing HCT116 cancer cells than on furin-deficient LoVo cells and on furin inhibitor-treated HCT116 cancer cells. In vivo CEST MRI with the use of RRVR-Olsa could readily distinguish the difference of furin expression in HCT116 tumor and LoVo tumor, which we attributed to the furin-directed intracellular self-assembly of RRVR-Olsa to olsalazine nanoparticles with enhanced accumulation.

3579
Computer 27
In Vivo iCEST MRI Detection of Zinc Depletion in an Orthotopic Prostate Cancer Mouse Model
Yue Yuan1,2, Chengyan Chu1, Zhiliang Wei1,2, Xiaolei Song1,2, and Jeff W.M. Bulte1,2

1The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, Baltimore, MD, United States, 2F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States

Prostate cancer is the only known disease of the prostate that displays such a substantial decrease in tissue zinc content and neither prostatitis nor benign prostatic hyperplasia are associated with this phenotype. 19F-based iCEST MRI probe TF-BAPTA was used to show clearly a detectable difference in zinc concentration between normal and malignant prostate cell lines, and normal prostate cells with a downregulated ZIP1 transporter. Via an orthotopic prostate cancer mouse model, the feasibility of iCEST MRI to distinguish normal mouse prostate and cancerous prostate has been verified. Hence, iCEST MRI may have potential to non-invasively monitor the early malignant transformation in prostate cancer.

3580
Computer 28
Imaging and discrimination of extracellular lactate in vivo using CEST and a paramagnetic shift reagent
Andre Martins1,2, Lei Zhang2, Veronica Clavijo-Jordan1, Alexander Funk1, Carlos Platas-Iglesias3, and A. Dean Sherry1,2

1Advanced Imaging Research Center, UTSW Medical Center, Dallas, TX, United States, 2UT Dallas, Richardson, TX, United States, 3Universidade da Coruña, Coruña, Spain

Glucose taken up by cancer cells is thought to be converted largely to lactate even in the presence of abundant oxygen although the amount of pyruvate diverted into the mitochondria is largely unknown.  Hence, a method for imaging actual lactate production by tumors could be highly informative. We report in this work the design of several lanthanide-based shift reagents (SR) that form complexes with lactate and shift the lactate –OH CEST signal to a different frequency far away from water.  Given that these SR’s are confined to extracellular space, the resulting lactate –OH CEST signal becomes a specific biomarker of lactate exported from cancer cells. This method offers great promise for imaging lactate production by tumors.

3581
Computer 29
Low affinity zinc sensors for improved MRI detection of glucose-stimulated zinc(II) secretion from pancreatic beta-cells in vivo
Andre F Martins1,2, Veronica Clavijo-Jordan1, Sara Chirayil1, Shanrong Zhang1, Namini Paranawithana2, and A. Dean Sherry1,2

1Advanced Imaging Research Center, UTSW Medical Center, Dallas, TX, United States, 2UT Dallas, Richardson, TX, United States

We report here the design of several gadolinium-based MR contrast agents with different zinc affinities. The zinc sensors increased r1 in the presence of Zn2+ ions and more in the presence of serum albumin, only when zinc was present.   The sensors with a lower affinity for Zn2+ enhanced better the MR contrast produced by zinc release in mouse pancreas due to reduced background signal. These lower affinity Zn2+ agents show great promise for detecting and monitoring the pharmacological effect of drugs in diabetes.

3582
Computer 30
An Elastase Activity Reporter for EPR and OMRI as a Line-Shifting Nitroxide.
Natacha Jugniot1, Indranil Duttagupta2, Angélique Rivot1, Philippe Massot1, Colleen Cardiet1, Jean-Michel Franconi1, Pierre Voisin1, Elodie Parzy1, Eric Thiaudière1, Sylvain R.A Marque2, Abderrazzak Bentaher3, Gérard Audran2, and Philippe Mellet1

1UMR CNRS 5536, bordeaux, France, 2UMR CNRS 7273, marseille, France, 3EA7426, Faculté de Médecine Lyon Sud, Pierre Bénite, France

Neutrophils secrete proteases at inflammation sites leading to protease/inhibitor imbalance. Among them, neutrophil elastase (NE) is responsible for lung degradation via elastin fragmentation. Monitoring protease/inhibitor status non-invasively would be an important diagnostic tool. We present Meo-Suc-(Ala)2-Pro-Val-nitroxide, a line-shifting elastase activity probe for Electronic Paramagnetic Resonance (EPR) spectroscopy and Overhauser-enhanced Magnetic Resonance Imaging (OMRI). Fast and sensitive with Km= 15 ± 2.9 µM, kcat/Km= 930000 s-1.M-1, this substrate was assessed with bronchoalveolar lavage samples from Pseudomonas pneumonia mouse model. We observed a clear difference between wild type and NE deficient animals. These results can lead to new in vivo diagnostic methods and lung protection.

3583
Computer 31
Using single 19F-probe for multiplexed imaging with 19F-CEST MRI
Ronit Shusterman-Krush1, Liat Avram2, Bruce C. Gibb3, and Amnon Bar-Shir1

1Organic chemistry, Weizmann Institute of science, Rehovot, Israel, 2chemical services, Weizmann Institute of science, Rehovot, Israel, 3Chemistry, Tulane University, New Orleans, LA, United States

Heteronuclear-CEST imaging presents several unique properties when compared to 1H-CEST, which is based on water, including background-free signals, quantifyability and ability to monitor low concentrations of targets. Here we present the performance of the CEST approach in 19F-MRI framework for mapping multiple targets in a “multicolor” fashion. Specifically, the difference in binding kinetics between a 19F-agent and a molecular target (i.e., macrocyclic molecular host) and the different Δw values obtained in 19F-NMR lead to a clear 19F-CEST characteristics. The large 19F-CEST effect obtained and its Δw dependency allow the mapping of two molecular targets simultaneously using single 19F-probe. 

3584
Computer 32
Calcium-dependent molecular fMRI using a magnetic nanosensor
Benjamin B Bartelle1, Satoshi Okada1, Nan Li1, Vincent Breton-Provencher2, Mriganka Sur2, and Alan P Jasanoff1,2

1Bioengineering, MIT, Cambridge, MA, United States, 2Brain & Cognitive Sciences, MIT, Cambridge, MA, United States

Superparamagnetic iron oxide nanoparticles are a modular platform technology for sensors with sub nM sensitivity and robust biomedical applications. In this work we engineer nanoparticle sensors that display Ca2+ dependent aggregation and demonstrate the first functional MRI study of Ca2+ dynamics as well as the first in vivo demonstration of a dynamic nanosensor.

3585
Computer 33
Sensing intracellular calcium ions using a manganese-based MRI contrast agent
Benjamin B Bartelle1, Barandov Ali1, Catherine G Williamson1, Emily S Loucks1, and Alan P Jasanoff1

1Bioengineering, Massachusetts Institute of Technology, Cambridge, MA, United States

Inspired by the classical work of R. Tsien on cell-permeable calcium specific chelators using readily cleavable acetomethoxy esters (AM) of BAPTA and taking advantage of our own, novel, cell permeable manganese-based contrast agent, we developed a new MRI contrast that displays membrane permeability, cellular accumulation via cleavable ester groups, and physiological sensitivity to calcium. With this breakthrough innovation, we present a series of firsts for functional molecular imaging, reporting chemically and optogenetically induced calcium transients with MRI in living cells.   

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Labelling of collagen type I templates with a novel naturally derived contrast agent for magnetic resonance imaging in soft tissue engineering
Heinz Peter Janke1, Nihan Güvener2, Weiqiang Dou3, Jozef Cremers4, Paul Borm4, Wout Feitz5, Arend Heerschap3, Fabian Kiessling2, and Egbert Oosterwijk1

1Urology, Radboud University Medical Center; Radboud Institute for Molecular Life Sciences, Nijmegen, Netherlands, 2Experimental Molecular Imaging, Uniklinik RWTH and Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany, 3Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, Netherlands, 4Nano4Imaging, Aachen, Germany, 5Urology, Radboud University Medical Center; Radboud Institute for Molecular Life Sciences; Radboudumc Amalia Children's Hospital, Nijmegen, Netherlands

Contrast agents (CA) need to be applied for monitoring tissue-engineered implants by MR imaging. However, currently used CAs have limitations (i.e. negative contrast, label instability). In this study, Hemin-Lysine complex (HL) -as a naturally derived alternative CA- is used for active labeling of hybrid collagen-based templates. HL-labeled templates are clearly identified because of their bright signal in T1-weighted MR images. The signal of labeled templates and thus their integrity could be followed over time when subcutaneously implanted in a mouse model. Thus, loading collagen-based templates with HL appears to be a promising strategy to localize and monitor its fate upon implantation.

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The effect of liposomal encapsulation on the chemical exchange properties of diamagnetic CEST agents.
Eleni Demetriou1, Harriet Story2, Robin Bofinger2, Helen Hailes2, Alethea Tabor2, and Xavier Golay3

1Brain repair and rehabilitation, University College of London, London, United Kingdom, 2Department of Chemistry, University College of London, London, United Kingdom, 3Brain Repair and Rehabilitation, University College of London, London, United Kingdom

Liposome encapsulation of glucose or 2-deoxy-D-glucose (2-DG) may be exploited to enhance the CEST signal by reducing the overall apparent exchange rate. Here we aim to construct a complete theoretical model to measure the exchange properties of diamagnetic CEST agents. Experimentally measured exchange rates of glucose and 2-DG in the liposomal system were found to be reduced by one or two orders of magnitude due to the intermembrane exchange between the intra- and extra-liposomal compartment because of restrictions in water transfer imposed by the lipid membrane. These new theoretical and experimental findings are expected to benefit applications of diamagnetic liposomes to image biological processes.

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A mannan-based probe for multimodal imaging of cancer and immune cells
Daniel Jirak1, Andrea Galisova1, Marketa Jiratova1, Mariia Rabyk2, Martin Hruby2, and Milan Hajek1

1IKEM, Prague, Czech Republic, 2UMCH, Prague, Czech Republic

Presented mannan-based polymers have promising properties for tumor and metastasis imaging due to their biocompatibility, nanosize and specificity for the immune cells. In this study, two mannan-based polymers were tested by multimodal imaging (MRI and fluorescence). The polymers showed superior imaging properties compared to a commercially available contrast agent. FLI signal at the liver and higher signal at the injection site in the mouse with MN-Ox suggested slower elimination process due to addition of polyoxazoline chains in its structure. Both probes were visualized by MR and optical imaging modality at the injection sites and in the lymph nodes of the experimental mice suggesting their promising properties for cancer diagnosis.

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High Temporal Resolution Dynamic BOLD MRI in Tracking Kidney Response to Hypoxia and Hyperoxia in a Rat AKI model at 7T
Kaixuan Zhao1, Yingjie Mei1,2, Guixiang Yang1, and Yanqiu Feng1

1School of Biomedical Engineering, Guangdong Provincial