{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T19:49:51Z","timestamp":1792698591943,"version":"4.5.0"},"reference-count":99,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T00:00:00Z","timestamp":1713225600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Introduction<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusion<\/jats:title>\n<jats:p>This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0300415","type":"journal-article","created":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T17:59:50Z","timestamp":1713290390000},"page":"e0300415","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":26,"title":["Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5411-0809","authenticated-orcid":true,"given":"Nima Broomand","family":"Lomer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kamal AmirAshjei","family":"Asalemi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alia","family":"Saberi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kasra","family":"Sarlak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,4,16]]},"reference":[{"issue":"3","key":"pone.0300415.ref001","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/S1474-4422(14)70267-4","article-title":"Environmental risk factors and multiple sclerosis: an umbrella review of systematic reviews and meta-analyses","volume":"14","author":"L Belbasis","year":"2015","journal-title":"Lancet Neurol"},{"issue":"7","key":"pone.0300415.ref002","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1016\/S1474-4422(14)70041-9","article-title":"Multiple sclerosis genetics","volume":"13","author":"S Sawcer","year":"2014","journal-title":"Lancet Neurol"},{"issue":"1","key":"pone.0300415.ref003","first-page":"1","article-title":"Multiple Sclerosis: Pathogenesis, Symptoms, Diagnoses and Cell-Based Therapy","volume":"19","author":"N Ghasemi","year":"2017","journal-title":"Cell J"},{"issue":"1","key":"pone.0300415.ref004","doi-asserted-by":"crossref","first-page":"54","DOI":"10.37897\/RJN.2023.1.9","article-title":"Migraine headache in Multiple Sclerosis. 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