Diffusion Kurtosis Metrics as Biomarker of Fibre Maturity
Grinberg Farida1,2, Ivan I. Maximov1,3, Ezequiel Farrher1, Irene Neuner1,4,5, Eileen Oberwelland6,7, Kerstin Konrad5,6,8, and N. Jon Shah1,2,5

1Institute of Neuroscience and Medicine - 4, Forschungszentrum Juelich GmbH, Juelich, Germany, 2Department of Neurology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany, 3Experimental Physics III, TU Dortmund University, Dortmund, Germany, 4Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany, 5JARA - BRAIN - Translational Medicine, Aachen, Germany, 6Institute of Neuroscience and Medicine – 3, Forschungszentrum Jülich GmbH, Juelich, Germany, 7Translational Brain Research in Psychiatry and Neurology, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, RWTH Aachen University, Aachen, Germany, 8Child Neuropsychology Section, Department of Child and Adolescent Psychiatry and Psychotherapy, RWTH Aachen University, Aachen, Germany


Diffusion tensor imaging has enabled the examination of white matter connectivity and microstructural changes across the lifespan. However, the detection of subtle microstructural changes during typical brain maturation still remains challenging. Recently, diffusion kurtosis imaging has attracted much attention as an efficient method for characterising non-Gaussian water diffusion in brain tissue. Here, we tested whether diffusion kurtosis imaging can extend our knowledge of changes in brain tissue microstructure related to normal brain development. We showed that diffusion kurtosis imaging provides useful biomarkers sensitive to the level of maturity in association, projection and commissural fibres.


Although it is well established that dynamic cognitive, emotional and behavioural development from childhood to adulthood is paralleled by significant changes in white matter (WM) brain structures, the detection of subtle microstructural changes during typical brain maturation still remains challenging. Diffusion tensor imaging (DTI) studies examined the changes in WM microstructure and connectivity across the lifespan and helped to establish the patterns of cerebral maturation and decline [1,2]. Recently, diffusion kurtosis imaging (DKI) [3], an extension of DTI that enables the quantification of the diffusion non-Gaussianity, was reported to provide richer information on tissue microstructure. However, thus far, only a few works have used DKI to study maturation or healthy ageing [4,5]. The purpose of this work was to compare the sensitivity of DTI and DKI metrics to age-related microstructural changes along specific fibres in a group of children and in a (reference) group of middle-aged adults. We aimed to explore which specific brain regions continue to develop throughout late childhood into the adulthood as revealed by DKI metrics. We used two methods for between-group analysis, whole brain Tract-Based Spatial Statistics (TBSS) and averaging over 20 anatomic regions defined by Johns Hopkins University (JHU) WM atlas.

Materials and Methods

DKI measurements were performed on a whole-body 3T Siemens MAGNETOM scanner for two groups of healthy volunteers: 20 children (middle age, 10.3) and 21 adults (middle age, 54.3). Four DTI metrics (mean (MD), axial (AD), and radial (RD) diffusivity, and fractional anisotropy (FA)), and four additional DKI metrics (mean (MK), axial (AK), and radial (RK) kurtosis, and kurtosis anisotropy (KA)) were determined on the voxel-by-voxel basis and averaged over 20 WM anatomical regions (fibres) provided by JHU WM tractography atlas available in FSL. For each fibre, we performed a) a between-group two-sided Student t-test analysis; b) a between-group age-related effect size analysis based on Cohen’s d; c) scatter plot correlation analysis for various pairs of metrics. We also performed a voxelwise TBSS comparison of the DTI and DKI data for 3 different significance levels (p<0.05, 0.01, 0.0005).

Results and Discussion

Significantly larger between-group changes of the DKI metrics in comparison to DTI alone metrics were demonstrated both by the TBSS (Fig.1) and atlas-based analysis using the Student t-test (Fig.2). Both of these methods have demonstrated much higher significance levels related to DKI metrics. For each individual fibre, the between-group differences quantified in terms of Cohen’s d were much larger for DKI than for DTI metrics. Among DTI metrics, large effect size values > 0.8 were observed for some metrics and some fibres only; the total range of Cohen’s d values for all DTI metrics was between 0.04 and 1.19. In contrast, Cohen’s d values were extremely large for all DKI parameters and all fibres; the total range was between 0.63 and 4.78. We showed that Cohen’s d related to MK (d_MK) provides a useful tool to “rank” the maturation levels of various fibres: the larger d_MK is, the more protractive is maturation. Based on this parameter, the lowest level of maturation in the children group was observed for the association fibres, cingulum (gyrus) and cingulum (hippocampus) followed by superior longitudinal fasciculus (SLF), whereas the highest level of maturation, i.e. the smallest d_MK, was observed in the commissural fibres, forceps major (the splenium) and forceps minor (the genu), see Fig. 3. These findings are in line with the general view of more early development of projection and commissural rather than of association fibres [2]. The commissural fibres, crucial for hemispheric connections, develop very rapidly and exhibit early rise of FA reaching 90% of their maximum by the age of 11 years [2]. However, it should be pointed out that, although d_MK of these fibres was the lowest in comparison to other fibres, its absolute values were large: 2.61 for forceps minor and 2.33 for forceps major, indicating that microstructural development in the corpus callosum is still ongoing. On the other hand, long-lasting maturation of the association fibres such as cingulum can be linked with protracted development of emotional and cognitive processes whereas long-lasting maturation of SLF is in line with the critical role of this tract in both emotional regulation and executive functioning [6].


Our results suggest that DKI is extremely sensitive in detecting ongoing microstructural changes beyond late childhood and provides valuable biomarkers of fibre maturity. It is particularly powerful to unravel developmental differences in major association fibres whose long-lasting maturation is linked with protracted development of emotional and cognitive processes.


We thank Laura Amort and Dr. Heike Thönneßen for their valuable contributions in DKI data acquisition.


[1] Kochunov P, Williamson DE, et al. 2012. Neurobiol Aging, 33:9–20.

[2] Lebel, C., Walker, L., et al., 2008. Neuroimage 40, 1044-1055.

[3] Jensen, J.H., Helpern, J.A., et al., 2005. Magn. Reson. Med. 53, 1432-1440.

[4] Paydar, A., Fieremans, E., et al., 2014. AJNR Am J Neuroradiol 35, 808-814.

[5] Falangola, M.F., Jensen, J.H., Babb, J.S., et al., 2008. J Magn Reson Imaging 28, 1345-1350.

[6] Makris, N., Schlerf, J.E., Hodge, S.M., et al., 2005. Neuroimage 25, 1146-1160.


Figure 1. Example of between-group differences based on TBSS analysis for 4 parameters along the FA skeleton (green). In highlighted regions (yellow) these parameters are significantly (p < 0.0005) larger in adults than in children.

Figure 2. Mean values with standard deviations of the selected DTI/DKI parameters in adults and children for different fibres. The higher “i” in pi the higher the significance level.

Figure 3. The values of d_MK averaged for the left and right ROIs of the same fibre. These values characterise the magnitude of microstructural changes between childhood and adulthood. The fibres with the highest d_MK values are assumed to exhibit most protractive maturation.

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