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Cortical grey matter (cGM) develops a substantial burden of pathology in multiple sclerosis (MS). Previous cross-sectional studies have suggested a relationship between measures of cortical atrophy and disability. Our objective was to develop a method for automatically measuring the apparent cGM thickness as well as the integrity of the interface between cGM and subcortical white matter (GM/WM) both globally and regionally on T(1)-weighted MRI, and use this method in a longitudinal investigation of how these measures differed between patients with stable MS and patients with progressing disability. Measurements were made over the whole brain and for anatomically specified cortical regions, both cross-sectionally at baseline and longitudinally on two MRI scans performed on average 1 year apart. We found a higher average rate of apparent loss of cGM thickness across the whole brain in the group that progressed over the interscan interval compared to the group that remained stable (progressing = -3.13 +/- 2.88%/year, stable = 0.06 +/- 2.31%/year, P = 0.002). This difference was detected with regional measures in parietal and precentral cortex. In contrast, change in the GM/WM interface integrity did not show detectable regional differences, although the group of MS patients whose disability progressed showed a significant decrease in GM/WM interface integrity compared to the stable group (P = 0.003). Regional measures of apparent loss of cGM thickness enhance sensitivity to cortical pathological changes. A measure of integrity offers a new index of disease-associated cortical changes at the GM/WM interface. The results suggest that progression of disability in MS is associated with the progression of MRI-detectable cortical pathology.

Original publication




Journal article



Publication Date





1168 - 1175


Montreal Neurological Institute and Hospital, McConnell Brain Imaging Centre, 3801 University, WB 321, Montreal, Quebec, Canada H3A 2B4.


Neocortex, Humans, Multiple Sclerosis, Atrophy, Disease Progression, Magnetic Resonance Imaging, Disability Evaluation, Aging, Image Processing, Computer-Assisted, Adult, Middle Aged, Female, Male