Literature DB >> 16169253

Semi-automatic brain region extraction (SABRE) reveals superior cortical and deep gray matter atrophy in MS.

D A Carone1, R H B Benedict, M G Dwyer, D L Cookfair, B Srinivasaraghavan, C W Tjoa, R Zivadinov.   

Abstract

In multiple sclerosis (MS), atrophy occurs in various cortical and subcortical regions. However, it is unclear whether this is mostly due to gray (GM) or white matter (WM) loss. Recently, a new semi-automatic brain region extraction (SABRE) technique was developed to quantify parenchyma volume in 13 hemispheric regions. This study utilized SABRE and tissue segmentation to examine whether regional brain atrophy in MS is mostly due to GM or WM loss, correlated with disease duration, and moderated by disease course. We studied 68 MS patients and 39 normal controls with 1.5 T brain MRI. As expected, MS diagnosis was associated with significantly lower (P < 0.001) regional brain parenchymal fractions (RBPFs). While significant findings emerged in 11 GM comparisons, only four WM comparisons were significant. The largest mean RBPF percent differences between groups (MS < NC) were in the posterior basal ganglia/thalamus region (-19.3%), superior frontal (-15.7%), and superior parietal (-14.3%) regions. Logistic regression analyses showed GM regions were more predictive of MS diagnosis than WM regions. Eight GM RBPFs were significantly correlated (P < 0.001) with disease duration compared to only one WM region. Significant trends emerged for differences in GM, but not WM between secondary progressive (SP) and relapsing-remitting MS patients. Percent differences in GM between the two groups were largest in superior frontal (-9.9%), medial superior frontal (-6.5%), and superior parietal (-6.1%) regions, with SP patients having lower volumes. Overall, atrophy in MS is diffuse and mostly related to GM loss particularly in deep GM and superior frontal-parietal regions.

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Year:  2005        PMID: 16169253     DOI: 10.1016/j.neuroimage.2005.07.053

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  18 in total

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