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Grey matter loss in relapsing–remitting multiple sclerosis: A voxel-based morphometry study
by
Salvatore, E.
, Coppola, G.
, Vacca, G.
, Orefice, G.
, Prinster, A.
, Quarantelli, M.
, Alfano, B.
, Brunetti, A.
, Morra, V.Brescia
, Salvatore, M.
, Mollica, C.
, Lanzillo, R.
in
Adult
/ Age
/ Automation
/ Brain
/ Brain - pathology
/ Data Interpretation, Statistical
/ Disability Evaluation
/ Female
/ Functional Laterality - physiology
/ Grey matter
/ Humans
/ Image Processing, Computer-Assisted
/ Magnetic Resonance Imaging
/ Male
/ Middle Aged
/ Motor cortex
/ Motor Cortex - pathology
/ MRI
/ Multiple sclerosis
/ Multiple Sclerosis, Relapsing-Remitting - pathology
/ Nonlinear Dynamics
/ Observer Variation
/ Studies
/ Voxel-based morphometry
2006
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Grey matter loss in relapsing–remitting multiple sclerosis: A voxel-based morphometry study
by
Salvatore, E.
, Coppola, G.
, Vacca, G.
, Orefice, G.
, Prinster, A.
, Quarantelli, M.
, Alfano, B.
, Brunetti, A.
, Morra, V.Brescia
, Salvatore, M.
, Mollica, C.
, Lanzillo, R.
in
Adult
/ Age
/ Automation
/ Brain
/ Brain - pathology
/ Data Interpretation, Statistical
/ Disability Evaluation
/ Female
/ Functional Laterality - physiology
/ Grey matter
/ Humans
/ Image Processing, Computer-Assisted
/ Magnetic Resonance Imaging
/ Male
/ Middle Aged
/ Motor cortex
/ Motor Cortex - pathology
/ MRI
/ Multiple sclerosis
/ Multiple Sclerosis, Relapsing-Remitting - pathology
/ Nonlinear Dynamics
/ Observer Variation
/ Studies
/ Voxel-based morphometry
2006
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Grey matter loss in relapsing–remitting multiple sclerosis: A voxel-based morphometry study
by
Salvatore, E.
, Coppola, G.
, Vacca, G.
, Orefice, G.
, Prinster, A.
, Quarantelli, M.
, Alfano, B.
, Brunetti, A.
, Morra, V.Brescia
, Salvatore, M.
, Mollica, C.
, Lanzillo, R.
in
Adult
/ Age
/ Automation
/ Brain
/ Brain - pathology
/ Data Interpretation, Statistical
/ Disability Evaluation
/ Female
/ Functional Laterality - physiology
/ Grey matter
/ Humans
/ Image Processing, Computer-Assisted
/ Magnetic Resonance Imaging
/ Male
/ Middle Aged
/ Motor cortex
/ Motor Cortex - pathology
/ MRI
/ Multiple sclerosis
/ Multiple Sclerosis, Relapsing-Remitting - pathology
/ Nonlinear Dynamics
/ Observer Variation
/ Studies
/ Voxel-based morphometry
2006
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Grey matter loss in relapsing–remitting multiple sclerosis: A voxel-based morphometry study
Journal Article
Grey matter loss in relapsing–remitting multiple sclerosis: A voxel-based morphometry study
2006
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Overview
Global grey matter (GM) loss has been reported in multiple sclerosis (MS). We addressed the question of if and where GM loss is localized by means of optimized voxel-based morphometry, applied to MRI studies of 51 patients with clinically defined relapsing–remitting MS and 34 age-matched normal subjects, segmented into normal and abnormal brain tissues using a multiparametric approach. Segmented GM volumes were subsequently compared on a voxel-by-voxel basis to highlight regions of relative GM loss (
P < 0.05, corrected for multiple comparisons at AnCova).
Additionally, localized differences in brain asymmetry between the MS and the control groups were assessed by comparing on a voxel-by-voxel basis maps of GM differences between the two hemispheres (
P < 0.05 corrected for multiple comparisons).
In MS patients, GM volume was significantly decreased at the level of the left fronto-temporal cortex and precuneus, as well as of anterior cingulate gyrus and of caudate nuclei bilaterally. The only cortical region of significant GM loss in the right hemisphere was located in the postcentral area.
Furthermore, GM loss regions were colocalized with increased GM asymmetries (Left < Right) in MS, confirming a preferential left-sided GM loss.
Caudate atrophy correlated with lesion load, while no correlation between cortical regional GM loss and disease duration, clinical status or lesion load emerged.
Our findings suggest that in RR-MS cortical GM reduction preferentially involves left fronto-temporal structures and deep GM, the latter correlating preferentially to global lesion load.
Publisher
Elsevier Inc,Elsevier Limited
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