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Regional Gray Matter Atrophy in Relapsing Remitting Multiple Sclerosis: Baseline Analysis of Multi-Center Data

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 impleme...

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Autores principales: Datta, Sushmita, Staewen, Terrell D., Cofield, Stacy S., Cutter, Gary R., Lublin, Fred D., Wolinsky, Jerry S., Narayana, Ponnada A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4366621/
https://www.ncbi.nlm.nih.gov/pubmed/25787188
http://dx.doi.org/10.1016/j.msard.2015.01.004
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author Datta, Sushmita
Staewen, Terrell D.
Cofield, Stacy S.
Cutter, Gary R.
Lublin, Fred D.
Wolinsky, Jerry S.
Narayana, Ponnada A.
author_facet Datta, Sushmita
Staewen, Terrell D.
Cofield, Stacy S.
Cutter, Gary R.
Lublin, Fred D.
Wolinsky, Jerry S.
Narayana, Ponnada A.
author_sort Datta, Sushmita
collection PubMed
description 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).
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spelling pubmed-43666212016-03-01 Regional Gray Matter Atrophy in Relapsing Remitting Multiple Sclerosis: Baseline Analysis of Multi-Center Data Datta, Sushmita Staewen, Terrell D. Cofield, Stacy S. Cutter, Gary R. Lublin, Fred D. Wolinsky, Jerry S. Narayana, Ponnada A. Mult Scler Relat Disord Article 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). 2015-01-17 2015-03 /pmc/articles/PMC4366621/ /pubmed/25787188 http://dx.doi.org/10.1016/j.msard.2015.01.004 Text en © 2015 Published by Elsevier B.V. This manuscript version is made available under the CC BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc/4.0/ This manuscript version is made available under the CC BY-NC-ND 4.0 license.
spellingShingle Article
Datta, Sushmita
Staewen, Terrell D.
Cofield, Stacy S.
Cutter, Gary R.
Lublin, Fred D.
Wolinsky, Jerry S.
Narayana, Ponnada A.
Regional Gray Matter Atrophy in Relapsing Remitting Multiple Sclerosis: Baseline Analysis of Multi-Center Data
title Regional Gray Matter Atrophy in Relapsing Remitting Multiple Sclerosis: Baseline Analysis of Multi-Center Data
title_full Regional Gray Matter Atrophy in Relapsing Remitting Multiple Sclerosis: Baseline Analysis of Multi-Center Data
title_fullStr Regional Gray Matter Atrophy in Relapsing Remitting Multiple Sclerosis: Baseline Analysis of Multi-Center Data
title_full_unstemmed Regional Gray Matter Atrophy in Relapsing Remitting Multiple Sclerosis: Baseline Analysis of Multi-Center Data
title_short Regional Gray Matter Atrophy in Relapsing Remitting Multiple Sclerosis: Baseline Analysis of Multi-Center Data
title_sort regional gray matter atrophy in relapsing remitting multiple sclerosis: baseline analysis of multi-center data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4366621/
https://www.ncbi.nlm.nih.gov/pubmed/25787188
http://dx.doi.org/10.1016/j.msard.2015.01.004
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