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Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis

Cognitive impairment (CI) occurs in 43 to 70% of multiple sclerosis (MS) patients at both early and later disease stages. Cognitive domains typically involved in MS include attention, information processing speed, memory, and executive control. The growing use of advanced magnetic resonance imaging...

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Autores principales: Zhang, Jian, Cortese, Rosa, De Stefano, Nicola, Giorgio, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297166/
https://www.ncbi.nlm.nih.gov/pubmed/34305785
http://dx.doi.org/10.3389/fneur.2021.671894
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author Zhang, Jian
Cortese, Rosa
De Stefano, Nicola
Giorgio, Antonio
author_facet Zhang, Jian
Cortese, Rosa
De Stefano, Nicola
Giorgio, Antonio
author_sort Zhang, Jian
collection PubMed
description Cognitive impairment (CI) occurs in 43 to 70% of multiple sclerosis (MS) patients at both early and later disease stages. Cognitive domains typically involved in MS include attention, information processing speed, memory, and executive control. The growing use of advanced magnetic resonance imaging (MRI) techniques is furthering our understanding on the altered structural connectivity (SC) and functional connectivity (FC) substrates of CI in MS. Regarding SC, different diffusion tensor imaging (DTI) measures (e.g., fractional anisotropy, diffusivities) along tractography-derived white matter (WM) tracts showed relevance toward CI. Novel diffusion MRI techniques, including diffusion kurtosis imaging, diffusion spectrum imaging, high angular resolution diffusion imaging, and neurite orientation dispersion and density imaging, showed more pathological specificity compared to the traditional DTI but require longer scan time and mathematical complexities for their interpretation. As for FC, task-based functional MRI (fMRI) has been traditionally used in MS to brain mapping the neural activity during various cognitive tasks. Analysis methods of resting fMRI (seed-based, independent component analysis, graph analysis) have been applied to uncover the functional substrates of CI in MS by revealing adaptive or maladaptive mechanisms of functional reorganization. The relevance for CI in MS of SC–FC relationships, reflecting common pathogenic mechanisms in WM and gray matter, has been recently explored by novel MRI analysis methods. This review summarizes recent advances on MRI techniques of SC and FC and their potential to provide a deeper understanding of the pathological substrates of CI in MS.
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spelling pubmed-82971662021-07-23 Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis Zhang, Jian Cortese, Rosa De Stefano, Nicola Giorgio, Antonio Front Neurol Neurology Cognitive impairment (CI) occurs in 43 to 70% of multiple sclerosis (MS) patients at both early and later disease stages. Cognitive domains typically involved in MS include attention, information processing speed, memory, and executive control. The growing use of advanced magnetic resonance imaging (MRI) techniques is furthering our understanding on the altered structural connectivity (SC) and functional connectivity (FC) substrates of CI in MS. Regarding SC, different diffusion tensor imaging (DTI) measures (e.g., fractional anisotropy, diffusivities) along tractography-derived white matter (WM) tracts showed relevance toward CI. Novel diffusion MRI techniques, including diffusion kurtosis imaging, diffusion spectrum imaging, high angular resolution diffusion imaging, and neurite orientation dispersion and density imaging, showed more pathological specificity compared to the traditional DTI but require longer scan time and mathematical complexities for their interpretation. As for FC, task-based functional MRI (fMRI) has been traditionally used in MS to brain mapping the neural activity during various cognitive tasks. Analysis methods of resting fMRI (seed-based, independent component analysis, graph analysis) have been applied to uncover the functional substrates of CI in MS by revealing adaptive or maladaptive mechanisms of functional reorganization. The relevance for CI in MS of SC–FC relationships, reflecting common pathogenic mechanisms in WM and gray matter, has been recently explored by novel MRI analysis methods. This review summarizes recent advances on MRI techniques of SC and FC and their potential to provide a deeper understanding of the pathological substrates of CI in MS. Frontiers Media S.A. 2021-07-08 /pmc/articles/PMC8297166/ /pubmed/34305785 http://dx.doi.org/10.3389/fneur.2021.671894 Text en Copyright © 2021 Zhang, Cortese, De Stefano and Giorgio. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
Zhang, Jian
Cortese, Rosa
De Stefano, Nicola
Giorgio, Antonio
Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis
title Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis
title_full Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis
title_fullStr Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis
title_full_unstemmed Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis
title_short Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis
title_sort structural and functional connectivity substrates of cognitive impairment in multiple sclerosis
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297166/
https://www.ncbi.nlm.nih.gov/pubmed/34305785
http://dx.doi.org/10.3389/fneur.2021.671894
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