Article ID Journal Published Year Pages File Type
5912833 Multiple Sclerosis and Related Disorders 2015 13 Pages PDF
Abstract

•To test the feasibility of the TBM analysis in MS in clinical settings.•Various deep GM and cortical GM regions showed atrophy early on in the disease.•Effects of age, gender, scanner field strength, and imaging sequence on few regional GM structures were observed.•Thalamic atrophy moderately correlated with EDSS, and T2 and T1 lesion loads.

Regional gray matter (GM) atrophy in multiple sclerosis (MS) at disease onset and its temporal variation can provide objective information regarding disease evolution. An automated pipeline for estimating atrophy of various GM structures was developed using tensor based morphometry (TBM) and implemented on a multi-center sub-cohort of 1008 relapsing remitting MS (RRMS) patients enrolled in a Phase 3 clinical trial. Four hundred age and gender matched healthy controls were used for comparison. Using the analysis of covariance, atrophy differences between MS patients and healthy controls were assessed on a voxel-by-voxel analysis. Regional GM atrophy was observed in a number of deep GM structures that included thalamus, caudate nucleus, putamen, and cortical GM regions. General linear regression analysis was performed to analyze the effects of age, gender, and scanner field strength, and imaging sequence on the regional atrophy. Correlations between regional GM volumes and expanded disability status scale (EDSS) scores, disease duration (DD), T2 lesion load (T2 LL), T1 lesion load (T1 LL), and normalized cerebrospinal fluid (nCSF) were analyzed using Pearson׳s correlation coefficient. Thalamic atrophy observed in MS patients compared to healthy controls remained consistent within subgroups based on gender and scanner field strength. Weak correlations between thalamic volume and EDSS (r=−0.133; p<0.001) and DD (r=−0.098; p=0.003) were observed. Of all the structures, thalamic volume moderately correlated with T2 LL (r=−0.492; P-value<0.001), T1 LL (r=−0.473; P-value<0.001) and nCSF (r=−0.367; P-value<0.001).

Related Topics
Life Sciences Biochemistry, Genetics and Molecular Biology Genetics
Authors
, , , , , , , ,