Journal ArticleDOI
Neocortical volume decrease in relapsing–remitting MS patients with mild cognitive impairment
Maria Pia Amato,Maria Letizia Bartolozzi,Valentina Zipoli,Emilio Portaccio,M. Mortilla,Leonello Guidi,Gianfranco Siracusa,Sandro Sorbi,Antonio Federico,N. De Stefano +9 more
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TLDR
Cortical atrophy was found only in cognitively impaired patients and was significantly correlated with a poorer performance on tests of verbal memory, attention/concentration, and verbal fluency.Abstract:
Objective: To assess neocortical changes and their relevance to cognitive impairment in early relapsing–remitting (RR) multiple sclerosis (MS). Methods: Conventional MR was acquired in 41 patients with RR MS and 16 demographically matched normal control subjects (NCs). An automated analysis tool was used with conventional T1-weighted MRI to obtain measures of cortical brain volumes normalized for head size. Neuropsychological performance of MS patients was assessed using the Rao Brief Repeatable Battery. Relationship between volumetric MR measures and neuropsychological scores was assessed. Results: Neuropsychological assessment allowed for the identification of 18 cognitively preserved (MS-cp) and 23 cognitively impaired (MS-ci) MS patients. The whole MS sample showed lower values of normalized cortical volumes (NCVs) than did the NC group ( p = 0.01). Upon grouping of MS patients according to cognitive performance, NCV values were lower ( p = 0.02) in MS-ci patients than in both MS-cp patients and NCs. Moreover, there were positive correlations between NCV values and measures of verbal memory ( r = 0.51, p = 0.02), verbal fluency ( r = 0.51, p = 0.01), and attention/concentration ( r = 0.65, p r = −0.58, p Conclusions: Cortical atrophy was found only in cognitively impaired patients and was significantly correlated with a poorer performance on tests of verbal memory, attention/concentration, and verbal fluency. Gray matter pathology may contribute to the development of cognitive impairment in MS from the earliest stages of the disease.read more
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Cognitive impairment in multiple sclerosis
TL;DR: The increased use of neuroimaging techniques in patients with MS has advanced the understanding of structural and functional changes in the brain that are characteristic of this disease, although much remains to be learned.
Journal ArticleDOI
Cognitive dysfunction in multiple sclerosis.
Joana Guimarães,Maria José Sá +1 more
TL;DR: The cognitive domains most commonly impaired in MS (memory, attention, executive functions, speed of information processing, and visual–spatial abilities); the pathophysiological mechanism implied in MS cognitive dysfunction and correlated brain MRI features; the importance of neuropsychological assessment of MS patients in different stages of the disease and the influence of its course on cognitive performance.
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Grey matter pathology in multiple sclerosis.
TL;DR: This paper reviewed several exciting new hypotheses on grey matter pathogenesis, including meningeal inflammation as a cause of subpial cortical damage, but also selective vulnerability of neuronal subpopulations, growth factor dysregulation, glutamate excitotoxicity, mitochondrial abnormalities, and the "use-it-and-lose-it" principle.
Journal ArticleDOI
Cortical Lesions and Atrophy Associated With Cognitive Impairment in Relapsing-Remitting Multiple Sclerosis
Massimiliano Calabrese,Federica Agosta,Francesca Rinaldi,Irene Mattisi,Paola Grossi,Alice Favaretto,M Atzori,Valentina Bernardi,Luigi Barachino,Luciano Rinaldi,Paola Perini,Paolo Gallo,Massimo Filippi +12 more
TL;DR: The burden of CLs and tissue loss are among the major structural changes associated with cognitive impairment in relapsing-remitting MS.
Journal ArticleDOI
Multiple sclerosis-related cognitive changes: a review of cross-sectional and longitudinal studies.
TL;DR: There are consistent, albeit moderate, correlations between the progression of cognitive impairment and increasing brain lesion load and brain atrophy in MS, and among clinical predictors, incipient cognitive decline seems to be the major risk factor for further deterioration in the short-term.
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Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm
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Journal ArticleDOI
Accurate, Robust, and Automated Longitudinal and Cross-Sectional Brain Change Analysis
Stephen M. Smith,Yongyue Zhang,Mark Jenkinson,Jacqueline T. Chen,Paul M. Matthews,Antonio Federico,Nicola De Stefano +6 more
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