Three Minute Whole-heart Magnetic Resonance Angiography with Prospective Heart Tracking and Compressed Sensing Parallel Image Reconstruction
Mehdi Hedjazi Moghari1,2, Martin Uecker3,4, Sébastien Roujol5, Tal Geva1,2, and Andrew J Powell1,2

1Pediatrics, Harvard Medical School, Boston, MA, United States, 2Cardiology, Boston Children's Hospital, Boston, MA, United States, 3German Center for Cardiovascular Research (DZHK), Goettingen, Germany, 4Department of Diagnostic and Interventional Radiology, University Medical Center, Goettingen, Germany, 5Division of Imaging Sciences and Biomedical Engineering, King’s Health Partners, St. Thomas’ Hospital, King’s College London, London, United Kingdom


To accelerate whole-heart magnetic resonance angiography, we implemented a variable density Poisson disc undersampling pattern and compressed sensing parallel image reconstruction, and compared it to a standard parallel image (SENSE) acquisition in 15 patients. The compressed sensing technique was faster (mean 3.4±1.0 minutes vs 7.6±1.7 minutes) and had similar objectively measured sharpness in 4 designated regions (all p>0.05) but a lower subjective image quality scores (all p≤0.05).


Electrocardiogram and respiratory navigator (NAV)-gated 3D whole-heart magnetic resonance angiography (MRA) acquired with an intravascular gadolinium-based contrast agent and a non-selective inversion recovery (IR) pulse to null the myocardial signal generates a high-resolution anatomic dataset allowing for a comprehensive evaluation of intra-cardiac, coronary, and vascular abnormalities [1]. To improve respiratory motion compensation with this sequence, we previously implemented the “Heart-NAV” technique, which prospectively tracks the heart position rather than hemi-diaphragm location. Still, an important limitation of this sequence is a relatively long acquisition time lasting 5-15 minutes [2]. During longer acquisitions, the patients’ heart-rate, breathing pattern, and body position may change leading to reduced image quality or incomplete scans. Therefore, we sought to reduce the imaging time of this sequence by implementing a variable density Poisson disc undersampling technique that randomly samples k-space lines and using compressed sensing (CS) reconstruction algorithm to complete the scan in ≈3 minutes.

Materials and Methods

The schematic diagram of the whole-heart IR 3D SSFP MRA sequence with Heart-NAV is shown in Fig. 1. One of the startup pulses for the 3D SSFP acquisition was used to collect the centerline of k-space, and its 1-dimensional reconstruction was fed into the conventional navigator signal analysis process to prospectively gate and track respiratory-induced heart displacement. A variable density Poisson disc undersampling pattern was implemented on the scanner to randomly sample k-space lines with a variable sampling rate. The most central 2% of k-space was fully sampled. The sampling rate was then exponentially decreased from the center to periphery of k-space to sample 16-18% of the k-space lines in a radial order on Cartesian grids (Fig. 2). A nonlinear iterative CS reconstruction algorithm, L1-ESPIRiT [3], with L1-wavelet penalty and random shifting as implemented in Bart [4] was used to estimate the unacquired k-space lines and reconstruct the images. The regularization parameter was optimized on one dataset and kept constant for the whole study. To assess this approach, 15 patients (7 females; age 19±9 years) underwent 2 Heart-NAV IR 3D SSFP acquisitions on a 1.5T MR scanner (Philips Ingenia) after the administration of 0.03 mmol/kg gadofosveset trisodium (Ablavar) contrast. The first acquisition used parallel-imaging (SENSE) and the second used variable density Poisson disc k-space filling with CS reconstruction. Imaging parameters were FOV ~310(SI)×140(AP)×130(RL) mm, spatial resolution 1.2-1.5 mm; α/TE/TR 90°/2/4 ms, bandwidth 1.06 kHz, Heart-NAV acceptance window 3 mm, tracking factor 1, 28-element phased-array coil, and a reduction factor of 2 for SENSE and ~6 for CS. CS image reconstruction was performed offline (processing time 5.3±2.1 minutes). To assess the image quality, the border sharpness of the lower pulmonary vein (LPV), right pulmonary artery (RPA), ascending aorta (AAO), and ventricular septum (VS) was subjectively graded by 2 clinicians based on a 5 point-scale (1-poor/non-diagnostic; 2-fair/moderate blurring; 3-acceptable/mild blurring; 4-Good/sharp image; and 5-excellent), and objectively measured (MediaCare tool, range 0-infinity with higher values being sharper) [5]. Subjective and objective measures for the 2 acquisitions were compared using the signed-rank test and paired student t-test, respectively, and a p-value ≤0.05 was considered statistically significant. Informed consent was obtained from all subjects.


Fig. 3 shows representative 3D whole-heart MRA images acquired from 2 patients using SENSE and CS. The scan time for CS was significantly shorter (3.4±1.0 vs. 7.6±1.7; p<0.05). As shown in Table 1, there was no significant difference in the objectively measured border sharpness at all 4 locations between SENSE and CS (all p>0.05). The subjective image quality score for CS was lower than that for SENSE at all 4 locations (all p≤0.05, mean 3.46±0.64 vs. 4.33±0.83). The minimum image quality score for all locations using CS was 3.


Compared to a SENSE rate of 2, our variable density Poisson disc undersampling with CS reconstruction method for the whole-heart IR 3D SSFP MRA reduced scan time by a factor of 2.2. Objectively measured border sharpness was not significantly different but subjective image quality was reduced by approximately 1 grade. The latter finding may be related to more extensive undersampling of the k-space (18-20% vs. 50%) and the resulting reduction in signal-to-noise ratio. Future work will assess this CS approach in a larger group of children and adults, and extend it to a 3D cine acquisition.


Authors acknowledge support from Translational Research Program (TRP) fellowship and office of faculty development from Boston Children’s Hospital and Harvard Catalyst from Harvard Medical School.


[1] Makowski, Radiology, 2011; [2] Fenchel, Pediatric Radiology, 2006; [3] Uecker, MRM, 2014; [4] Uecker, ISMRM 2015, [5] Roujol, JCMR, 2014.


Fig. 1: Schematic diagram of the Heart-NAV respiratory motion compensation for whole-heart IR 3D SSFP MRA sequence. IR = inversion pulse. Fat Sup = fat suppression. FOS = fold-over suppression. SP = startup pulse. SSFP = steady-state free precession sequence. Trigger delay = onset of the ventricular motion rest period. Inversion time = time when the signal of myocardium is nulled. TR =repetition time.

Fig. 2: K-space profile ordering. The central 2% of the k-space lines are fully acquired and 16-18% of peripheral k-space is randomly acquired using a variable density Poisson disc undersampling pattern.

Fig. 3: Heart-NAV with SENSE and Heart-NAV with CS in whole-heart IR 3D SSFP MRA acquisitions with sagittal reformats in 2 patients, ages 2 and 8 years.

Table 1: Values are mean ± standard deviation. Visual score: 1-poor to 5-excellent. Sharpness measure: 0-blurred to infinity-sharp. LPV, lower pulmonary vein; RPA, right pulmonary artery; AAO, ascending aorta; VS, ventricular septum.

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)