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Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies
Multiple Sclerosis (MS) is a chronic neurodegenerative disorder that affects the central nervous system (CNS) and results in progressive clinical disability and cognitive decline. Currently, there are no specific imaging parameters available for the prediction of longitudinal disability in MS patien...
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Published in: | PloS one 2024-04, Vol.19 (4), p.e0300415 |
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description | Multiple Sclerosis (MS) is a chronic neurodegenerative disorder that affects the central nervous system (CNS) and results in progressive clinical disability and cognitive decline. Currently, there are no specific imaging parameters available for the prediction of longitudinal disability in MS patients. Magnetic resonance imaging (MRI) has linked imaging anomalies to clinical and cognitive deficits in MS. In this study, we aimed to evaluate the effectiveness of MRI in predicting disability, clinical progression, and cognitive decline in MS.
In this study, according to PRISMA guidelines, we comprehensively searched the Web of Science, PubMed, and Embase databases to identify pertinent articles that employed conventional MRI in the context of Relapsing-Remitting and progressive forms of MS. Following a rigorous screening process, studies that met the predefined inclusion criteria were selected for data extraction and evaluated for potential sources of bias.
A total of 3028 records were retrieved from database searching. After a rigorous screening, 53 records met the criteria and were included in this study. Lesions and alterations in CNS structures like white matter, gray matter, corpus callosum, thalamus, and spinal cord, may be used to anticipate disability progression. Several prognostic factors associated with the progression of MS, including presence of cortical lesions, changes in gray matter volume, whole brain atrophy, the corpus callosum index, alterations in thalamic volume, and lesions or alterations in cross-sectional area of the spinal cord. For cognitive impairment in MS patients, reliable predictors include cortical gray matter volume, brain atrophy, lesion characteristics (T2-lesion load, temporal, frontal, and cerebellar lesions), white matter lesion volume, thalamic volume, and corpus callosum density.
This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time. |
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In this study, according to PRISMA guidelines, we comprehensively searched the Web of Science, PubMed, and Embase databases to identify pertinent articles that employed conventional MRI in the context of Relapsing-Remitting and progressive forms of MS. Following a rigorous screening process, studies that met the predefined inclusion criteria were selected for data extraction and evaluated for potential sources of bias.
A total of 3028 records were retrieved from database searching. After a rigorous screening, 53 records met the criteria and were included in this study. Lesions and alterations in CNS structures like white matter, gray matter, corpus callosum, thalamus, and spinal cord, may be used to anticipate disability progression. Several prognostic factors associated with the progression of MS, including presence of cortical lesions, changes in gray matter volume, whole brain atrophy, the corpus callosum index, alterations in thalamic volume, and lesions or alterations in cross-sectional area of the spinal cord. For cognitive impairment in MS patients, reliable predictors include cortical gray matter volume, brain atrophy, lesion characteristics (T2-lesion load, temporal, frontal, and cerebellar lesions), white matter lesion volume, thalamic volume, and corpus callosum density.
This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0300415</identifier><identifier>PMID: 38626023</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Atrophy - diagnostic imaging ; Atrophy - pathology ; Biology and Life Sciences ; Brain - diagnostic imaging ; Brain - pathology ; Gray Matter - diagnostic imaging ; Gray Matter - pathology ; Humans ; Magnetic Resonance Imaging - methods ; Medicine and Health Sciences ; Multiple Sclerosis - diagnostic imaging ; Multiple Sclerosis - pathology ; Multiple Sclerosis, Relapsing-Remitting - pathology ; Research and Analysis Methods ; White Matter - pathology</subject><ispartof>PloS one, 2024-04, Vol.19 (4), p.e0300415</ispartof><rights>Copyright: © 2024 Lomer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>2024 Lomer et al 2024 Lomer et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c475t-f8e3b09979c544ac1a5b0af48550cc3e8ebe2f77640b57a4d1fdd8773294ecac3</citedby><cites>FETCH-LOGICAL-c475t-f8e3b09979c544ac1a5b0af48550cc3e8ebe2f77640b57a4d1fdd8773294ecac3</cites><orcidid>0000-0002-5411-0809</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11020451/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11020451/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,37013,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38626023$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Vaithinathan, Asokan Govindaraj</contributor><creatorcontrib>Lomer, Nima Broomand</creatorcontrib><creatorcontrib>Asalemi, Kamal AmirAshjei</creatorcontrib><creatorcontrib>Saberi, Alia</creatorcontrib><creatorcontrib>Sarlak, Kasra</creatorcontrib><title>Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Multiple Sclerosis (MS) is a chronic neurodegenerative disorder that affects the central nervous system (CNS) and results in progressive clinical disability and cognitive decline. Currently, there are no specific imaging parameters available for the prediction of longitudinal disability in MS patients. Magnetic resonance imaging (MRI) has linked imaging anomalies to clinical and cognitive deficits in MS. In this study, we aimed to evaluate the effectiveness of MRI in predicting disability, clinical progression, and cognitive decline in MS.
In this study, according to PRISMA guidelines, we comprehensively searched the Web of Science, PubMed, and Embase databases to identify pertinent articles that employed conventional MRI in the context of Relapsing-Remitting and progressive forms of MS. Following a rigorous screening process, studies that met the predefined inclusion criteria were selected for data extraction and evaluated for potential sources of bias.
A total of 3028 records were retrieved from database searching. After a rigorous screening, 53 records met the criteria and were included in this study. Lesions and alterations in CNS structures like white matter, gray matter, corpus callosum, thalamus, and spinal cord, may be used to anticipate disability progression. Several prognostic factors associated with the progression of MS, including presence of cortical lesions, changes in gray matter volume, whole brain atrophy, the corpus callosum index, alterations in thalamic volume, and lesions or alterations in cross-sectional area of the spinal cord. For cognitive impairment in MS patients, reliable predictors include cortical gray matter volume, brain atrophy, lesion characteristics (T2-lesion load, temporal, frontal, and cerebellar lesions), white matter lesion volume, thalamic volume, and corpus callosum density.
This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time.</description><subject>Atrophy - diagnostic imaging</subject><subject>Atrophy - pathology</subject><subject>Biology and Life Sciences</subject><subject>Brain - diagnostic imaging</subject><subject>Brain - pathology</subject><subject>Gray Matter - diagnostic imaging</subject><subject>Gray Matter - pathology</subject><subject>Humans</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Medicine and Health Sciences</subject><subject>Multiple Sclerosis - diagnostic imaging</subject><subject>Multiple Sclerosis - pathology</subject><subject>Multiple Sclerosis, Relapsing-Remitting - pathology</subject><subject>Research and Analysis Methods</subject><subject>White Matter - pathology</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVkU9v1DAQxS0EomXhGyDkI5dd7NiOEy6oqvhTqRIc4GxNnEnwyrGDnWzVb4-XXar2NNbMvDfP-hHylrMdF5p_2Mc1BfC7OQbcMcGY5OoZueStqLZ1xcTzR-8L8irnPWNKNHX9klyUUtWsEpdk-ZGwd3aJKdM40Gn1i5s90mw9pphdpnOKY8KcXQwf6RXN93nBCRZnacKDw7ujzMZwwLCUFfB0gjHgaZ5LI1ikrvRcGGle1t5hfk1eDOAzvjnXDfn15fPP62_b2-9fb66vbrdWarVshwZFx9pWt1ZJCZaD6hgMslGKWSuwwQ6rQetask5pkD0f-r7RWlStRAtWbMjNybePsDdzKjHSvYngzL9GTKOBVJJ6NDVnFkAMHIWUSnddWw0115bbroVWQvH6dPKa127C3pbvJvBPTJ9OgvttxngwnLOKScWLw_uzQ4p_VsyLmVy26D0EjGs2gkkmKn7ktSHytGoLg5xweLjDmTnSN2f65kjfnOkX2bvHGR9E_3GLv78-s1Y</recordid><startdate>20240416</startdate><enddate>20240416</enddate><creator>Lomer, Nima Broomand</creator><creator>Asalemi, Kamal AmirAshjei</creator><creator>Saberi, Alia</creator><creator>Sarlak, Kasra</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-5411-0809</orcidid></search><sort><creationdate>20240416</creationdate><title>Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies</title><author>Lomer, Nima Broomand ; Asalemi, Kamal AmirAshjei ; Saberi, Alia ; Sarlak, Kasra</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c475t-f8e3b09979c544ac1a5b0af48550cc3e8ebe2f77640b57a4d1fdd8773294ecac3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Atrophy - diagnostic imaging</topic><topic>Atrophy - pathology</topic><topic>Biology and Life Sciences</topic><topic>Brain - diagnostic imaging</topic><topic>Brain - pathology</topic><topic>Gray Matter - diagnostic imaging</topic><topic>Gray Matter - pathology</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Medicine and Health Sciences</topic><topic>Multiple Sclerosis - diagnostic imaging</topic><topic>Multiple Sclerosis - pathology</topic><topic>Multiple Sclerosis, Relapsing-Remitting - pathology</topic><topic>Research and Analysis Methods</topic><topic>White Matter - pathology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lomer, Nima Broomand</creatorcontrib><creatorcontrib>Asalemi, Kamal AmirAshjei</creatorcontrib><creatorcontrib>Saberi, Alia</creatorcontrib><creatorcontrib>Sarlak, Kasra</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lomer, Nima Broomand</au><au>Asalemi, Kamal AmirAshjei</au><au>Saberi, Alia</au><au>Sarlak, Kasra</au><au>Vaithinathan, Asokan Govindaraj</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2024-04-16</date><risdate>2024</risdate><volume>19</volume><issue>4</issue><spage>e0300415</spage><pages>e0300415-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Multiple Sclerosis (MS) is a chronic neurodegenerative disorder that affects the central nervous system (CNS) and results in progressive clinical disability and cognitive decline. Currently, there are no specific imaging parameters available for the prediction of longitudinal disability in MS patients. Magnetic resonance imaging (MRI) has linked imaging anomalies to clinical and cognitive deficits in MS. In this study, we aimed to evaluate the effectiveness of MRI in predicting disability, clinical progression, and cognitive decline in MS.
In this study, according to PRISMA guidelines, we comprehensively searched the Web of Science, PubMed, and Embase databases to identify pertinent articles that employed conventional MRI in the context of Relapsing-Remitting and progressive forms of MS. Following a rigorous screening process, studies that met the predefined inclusion criteria were selected for data extraction and evaluated for potential sources of bias.
A total of 3028 records were retrieved from database searching. After a rigorous screening, 53 records met the criteria and were included in this study. Lesions and alterations in CNS structures like white matter, gray matter, corpus callosum, thalamus, and spinal cord, may be used to anticipate disability progression. Several prognostic factors associated with the progression of MS, including presence of cortical lesions, changes in gray matter volume, whole brain atrophy, the corpus callosum index, alterations in thalamic volume, and lesions or alterations in cross-sectional area of the spinal cord. For cognitive impairment in MS patients, reliable predictors include cortical gray matter volume, brain atrophy, lesion characteristics (T2-lesion load, temporal, frontal, and cerebellar lesions), white matter lesion volume, thalamic volume, and corpus callosum density.
This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>38626023</pmid><doi>10.1371/journal.pone.0300415</doi><orcidid>https://orcid.org/0000-0002-5411-0809</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Atrophy - diagnostic imaging Atrophy - pathology Biology and Life Sciences Brain - diagnostic imaging Brain - pathology Gray Matter - diagnostic imaging Gray Matter - pathology Humans Magnetic Resonance Imaging - methods Medicine and Health Sciences Multiple Sclerosis - diagnostic imaging Multiple Sclerosis - pathology Multiple Sclerosis, Relapsing-Remitting - pathology Research and Analysis Methods White Matter - pathology |
title | Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies |
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