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
Synopsis
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. Purpose
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].
Conclusion
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.
Acknowledgements
We thank Laura Amort and Dr. Heike Thönneßen for
their valuable contributions in DKI data acquisition.References
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