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The association of white matter (WM) lesions and grey matter (GM) atrophy is a feature in relapsing-remitting multiple sclerosis (RRMS). The spatiotemporal distribution pattern of WM lesions, their relations to regional GM changes and the underlying dynamics are unclear. Here we combined parametric and non-parametric voxel-based morphometry (VBM) to clarify these issues. MRI data from RRMS patients with progressive (PLV, n = 45) and non-progressive WM lesion volumes (NPLV, n = 44) followed up for 12 months were analysed. Cross-sectionally, the spatial WM lesion distribution was compared using lesion probability maps (LPMs). Longitudinally, WM lesions and GM volumes were studied using FSL-VBM and SPM5-VBM, respectively. WM lesions clustered around the lateral ventricles and in the centrum semiovale with a more widespread pattern in the PLV than in the NPLV group. The maximum local probabilities were similar in both groups and higher for T2 lesions (PLV: 27%, NPLV: 25%) than for T1 lesions (PLV: 15%, NPLV 14%). Significant WM lesion changes accompanied by cortical GM volume reductions occurred in the corpus callosum and optic radiations (P = 0.01 corrected), and more liberally tested (uncorrected P < 0.01) in the inferior fronto-occipital and longitudinal fasciculi, and corona radiata in the PLV group. Not any WM or GM changes were found in the NPLV group. In the PLV group, WM lesion distribution and development in fibres, was associated with regional GM volume loss. The different spatiotemporal distribution patterns of patients with progressive compared to patients with non-progressive WM lesions suggest differences in the dynamics of pathogenesis.

Original publication

DOI

10.1002/hbm.20951

Type

Journal article

Journal

Hum Brain Mapp

Publication Date

10/2010

Volume

31

Pages

1542 - 1555

Keywords

Adult, Atrophy, Case-Control Studies, Cerebral Cortex, Female, Follow-Up Studies, Humans, Longitudinal Studies, Male, Middle Aged, Multiple Sclerosis, Relapsing-Remitting, Nerve Fibers, Myelinated, Organ Size, Time Factors