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Updated: Sep 10, 2026
Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Published on: September 12, 2011
A psychometric evaluation of diffusion basis spectrum imaging indicates altered white matter microstructure
Luisa Kaluza1, Anne Kühnel2, Ekaterina Kuskova3
1Section of Medical Psychology, Department of Psychiatry and Psychotherapy, University Hospital Bonn, University of Bonn, Bonn, Germany; Department of Neuroimmunology and Neuromuscular Diseases, Centre for Neurology, University Hospital Bonn, University of Bonn, Bonn, Germany.
Abstract:
An inflammatory subtype of major depressive disorder (MDD) is associated with treatment resistance pointing to an unmet need for adjunctive treatments. To evaluate treatment-related changes in brain inflammation, diffusion basis spectrum imaging (DBSI) is a promising non-radiation-based technique for longitudinal designs which has been verified with histopathology. However, its use as an endpoint in clinical trials is dependent on its individual-level reliability to robustly track changes. Therefore, our goal was to evaluate the short-term test-retest reliability of DBSI-based measures to quantify potential alterations in patients with MDD. To this end, we used two DBSI runs acquired in 94 participants (including 43 participants with MDD) about 1.5 h apart. Fiber fraction (reflecting axonal/dendrite density) and hindered fraction (reflecting edema) showed moderate to high test-retest reliability in both gray and white matter regions, whereas restricted fraction (reflecting cellularity) showed lower values in gray and white matter. Group-level reliability was similar in participants with MDD, except for lower reliability of hindered fraction in gray matter. Re-identification rates of individual brain maps were higher using voxel-level white matter signatures compared to gray matter regions of interest (ROIs) (p<.001). Crucially, participants with MDD showed reduced fiber fraction (tmax=4.68, k=38) and elevated hindered fraction (tmax=4.74, k=32) in the cingulate bundle, consistent with edematous microstructure changes (i.e., a proxy of increased white matter inflammation), while gray matter ROI-based classification failed to identify cases. We conclude that DBSI is a promising technique to track inflammatory signatures in MDD, particularly in white matter tracts. Since several frontal and subcortical gray matter ROIs showed insufficient reliability, their assessment would require multiple DBSI runs to provide robust estimates.
