{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T11:53:34Z","timestamp":1785412414334,"version":"3.56.0"},"reference-count":45,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Deanship of Scientific Research at King Saud University through the Ongoing Research Funding Program","award":["ORF-2026-780"],"award-info":[{"award-number":["ORF-2026-780"]}]},{"award":["ORF-2026-780"],"award-info":[{"award-number":["ORF-2026-780"]}],"id":[{"id":"https:\/\/ror.org\/02f81g417","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Brain Sciences"],"abstract":"<jats:p>Background\/Objectives: Disability in relapsing\u2013remitting multiple sclerosis (RRMS) reflects multiple pathological processes that may not be fully captured by individual MRI markers. Because an EDSS score \u2265 3 represents a clinically meaningful threshold of moderate-to-higher disability, this study evaluated the cross-sectional ability of brain volumetric measures and IVIM-DWI parameters to identify patients with RRMS who had EDSS \u2265 3. Methods: This retrospective cross-sectional study included 189 patients with RRMS who had complete EDSS, lesion count, IVIM-DWI, and brain volumetric MRI data. Patients were stratified into EDSS &lt; 3 and EDSS \u2265 3 groups. Single-marker ROC analyses were performed for lesion count, IVIM-DWI parameters, absolute volumetric measures, and fractional volumetric measures. Combined ROC models were constructed to assess the discriminatory performance of integrating lesion burden, volumetric MRI, and IVIM-DWI metrics. Internal model stability was evaluated using 5-fold cross-validation. Results: Patients with EDSS \u2265 3 had higher lesion count, higher ADC and D values, lower gray matter, white matter, and brain parenchymal volumes, higher CSF volume, higher CSF fraction, and lower brain parenchymal fraction (BPF). In single-marker ROC analysis, BPF and CSF fraction showed the strongest discriminatory performance (AUC = 0.705), followed by lesion count (AUC = 0.696), whereas absolute BV showed minimal discriminatory value (AUC = 0.503). The core lesion count + BPF model achieved an AUC of 0.757 and a cross-validated AUC of 0.737. Adding perfusion fraction (f) produced the numerically highest cross-validated performance, with an AUC of 0.769 and a cross-validated AUC of 0.746, although the incremental improvement over lesion count + BPF was modest and not statistically significant. Conclusions: Fractional volumetric measures showed stronger discriminatory performance than absolute BV for EDSS \u2265 3 stratification in RRMS. The lesion count + BPF + f model achieved the highest cross-validated performance among the evaluated MRI models; however, overall discrimination was moderate, and the incremental improvement associated with f was not statistically significant. These exploratory findings require evaluation in larger longitudinal cohorts with external validation.<\/jats:p>","DOI":"10.3390\/brainsci16070743","type":"journal-article","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T05:32:01Z","timestamp":1784007121000},"page":"743","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["MRI Markers of EDSS \u2265 3 in Relapsing\u2013Remitting Multiple Sclerosis: An Assessment of Lesion Burden, Brain Volumetry, and IVIM-DWI Metrics"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6404-8762","authenticated-orcid":false,"given":"Sami A.","family":"Alghamdi","sequence":"first","affiliation":[{"name":"Radiological Sciences Department, College of Applied Medical Sciences, King Saud University, P.O. Box 145111, Riyadh 4545, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9769-2514","authenticated-orcid":false,"given":"Othman I.","family":"Alomair","sequence":"additional","affiliation":[{"name":"Radiological Sciences Department, College of Applied Medical Sciences, King Saud University, P.O. Box 145111, Riyadh 4545, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7539-766X","authenticated-orcid":false,"given":"Manal H.","family":"Alosaimi","sequence":"additional","affiliation":[{"name":"Radiological Sciences Department, College of Applied Medical Sciences, King Saud University, P.O. Box 145111, Riyadh 4545, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6608-6922","authenticated-orcid":false,"given":"Abdullah H.","family":"Abujamea","sequence":"additional","affiliation":[{"name":"Medical Physics Section, King Saud University Medical City, King Saud University, Riyadh 2925, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0138-7924","authenticated-orcid":false,"given":"Salman","family":"Aljarallah","sequence":"additional","affiliation":[{"name":"Department of Medicine, College of Medicine, King Saud University, P.O. Box 145111, Riyadh 2925, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1992-0654","authenticated-orcid":false,"given":"Nuha M.","family":"Alkhawajah","sequence":"additional","affiliation":[{"name":"Department of Medicine, College of Medicine, King Saud University, P.O. Box 145111, Riyadh 2925, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0857-524X","authenticated-orcid":false,"given":"Yazeed I.","family":"Alashban","sequence":"additional","affiliation":[{"name":"Radiological Sciences Department, College of Applied Medical Sciences, King Saud University, P.O. Box 145111, Riyadh 4545, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/S1474-4422(18)30451-4","article-title":"Association between Pathological and MRI Findings in Multiple Sclerosis","volume":"18","author":"Filippi","year":"2019","journal-title":"Lancet Neurol."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Lassmann, H. (2019). Pathogenic Mechanisms Associated with Different Clinical Courses of Multiple Sclerosis. Front. Immunol., 9.","DOI":"10.3389\/fimmu.2018.03116"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3147","DOI":"10.1093\/brain\/awac016","article-title":"How Patients with Multiple Sclerosis Acquire Disability","volume":"145","author":"Lublin","year":"2022","journal-title":"Brain"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1212\/WNL.0000000000000560","article-title":"Defining the Clinical Course of Multiple Sclerosis: The 2013 Revisions","volume":"83","author":"Lublin","year":"2014","journal-title":"Neurology"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"a028928","DOI":"10.1101\/cshperspect.a028928","article-title":"Clinical Course of Multiple Sclerosis","volume":"8","author":"Klineova","year":"2018","journal-title":"Cold Spring Harb. Perspect. Med."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1444","DOI":"10.1212\/WNL.33.11.1444","article-title":"Rating Neurologic Impairment in Multiple Sclerosis: An Expanded Disability Status Scale (EDSS)","volume":"33","author":"Kurtzke","year":"1983","journal-title":"Neurology"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/S1474-4422(12)70059-5","article-title":"Disability Outcome Measures in Multiple Sclerosis Clinical Trials: Current Status and Future Prospects","volume":"11","author":"Cohen","year":"2012","journal-title":"Lancet Neurol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"82","DOI":"10.4274\/csmedj.galenos.2022.2022-11-11","article-title":"Expanded Disability Status Scale (EDSS) in Multiple Sclerosis","volume":"2","author":"Demir","year":"2022","journal-title":"Cam Sakura Med. J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1900","DOI":"10.1093\/brain\/awq076","article-title":"Evidence for a Two-Stage Disability Progression in Multiple Sclerosis","volume":"133","author":"Leray","year":"2010","journal-title":"Brain"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.1212\/WNL.0b013e318230a17d","article-title":"Age and Disability Accumulation in Multiple Sclerosis","volume":"77","author":"Scalfari","year":"2011","journal-title":"Neurology"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1914","DOI":"10.1093\/brain\/awq118","article-title":"The Natural History of Multiple Sclerosis, a Geographically Based Study 10: Relapses and Long-Term Disability","volume":"133","author":"Scalfari","year":"2010","journal-title":"Brain"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"695","DOI":"10.54029\/2023itk","article-title":"Could Tear Endothelin-1 Levels be Associated with Disability in Multiple Sclerosis?","volume":"28","author":"Sehitoglu","year":"2023","journal-title":"Neurol. Asia"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.clineuro.2018.02.014","article-title":"Effect of Comorbidities on the Course of Multiple Sclerosis","volume":"167","author":"Puz","year":"2018","journal-title":"Clin. Neurol. Neurosurg."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Xue, H., Yang, Z., Wang, L., Jiang, Y., Li, J., Wu, M., Wang, G., Zhang, Y., and Zhang, M. (2021). Factors Influencing the Degree of Disability in Patients with Multiple Sclerosis. Front. Neurol., 12.","DOI":"10.3389\/fneur.2021.714631"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1828","DOI":"10.12688\/f1000research.11932.1","article-title":"Resolving the Clinico-Radiological Paradox in Multiple Sclerosis","volume":"6","author":"Chard","year":"2017","journal-title":"F1000Research"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.neurad.2023.11.007","article-title":"MRI Features and Disability in Multiple Sclerosis: A Systematic Review and Meta-Analysis","volume":"51","author":"Nabizadeh","year":"2024","journal-title":"J. Neuroradiol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1111\/ene.14723","article-title":"A Model for Interrogating the Clinico-Radiological Paradox in Multiple Sclerosis: Internuclear Ophthalmoplegia","volume":"28","author":"Balk","year":"2021","journal-title":"Eur. J. Neurol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1093\/brain\/awv398","article-title":"The Topograpy of Demyelination and Neurodegeneration in the Multiple Sclerosis Brain","volume":"139","author":"Haider","year":"2016","journal-title":"Brain"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"866","DOI":"10.1016\/S1474-4422(25)00304-7","article-title":"2024 MAGNIMS\u2013CMSC\u2013NAIMS Consensus Recommendations on the Use of MRI for the Diagnosis of Multiple Sclerosis","volume":"24","author":"Barkhof","year":"2025","journal-title":"Lancet Neurol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1016\/S1474-4422(25)00270-4","article-title":"Diagnosis of Multiple Sclerosis: 2024 Revisions of the McDonald Criteria","volume":"24","author":"Montalban","year":"2025","journal-title":"Lancet Neurol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1016\/S1474-4422(21)00095-8","article-title":"2021 MAGNIMS\u2013CMSC\u2013NAIMS Consensus Recommendations on the Use of MRI in Patients with Multiple Sclerosis","volume":"20","author":"Wattjes","year":"2021","journal-title":"Lancet Neurol."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Alghamdi, S.A., Alomair, O.I., and Abujamea, A.H. (2026). Multimodal Quantitative MRI of White and Gray Matter: Associations with Myelin-Related Metrics in the Healthy Adult Brain Using Synthetic MRI and IVIM-DWI. J. Clin. Med., 15.","DOI":"10.3390\/jcm15114240"},{"key":"ref_23","first-page":"10S","article-title":"Measuring Brain Atrophy in Multiple Sclerosis","volume":"17","author":"Battaglini","year":"2007","journal-title":"J. Neuroimaging"},{"key":"ref_24","first-page":"101476","article-title":"The Effect Of Disease-Modifying Therapies on Brain Volume Loss and Disability Accumulation in Multiple Sclerosis: A Systematic Review and Network Meta-Analysis","volume":"59","author":"Cagol","year":"2025","journal-title":"Lancet Reg. Health\u2013Eur."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1212\/WNL.0000000000003542","article-title":"Brain MRI Atrophy Quantification in MS: From Methods to Clinical Application","volume":"88","author":"Rocca","year":"2017","journal-title":"Neurology"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1038\/s41582-020-0314-x","article-title":"MAGNIMS Consensus Recommendations on the Use of Brain and Spinal Cord Atrophy Measures in Clinical Practice","volume":"16","author":"Pareto","year":"2020","journal-title":"Nat. Rev. Neurol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"17562864241303681","DOI":"10.1177\/17562864241303681","article-title":"A Systematic Literature Review of the Association Between Global Brain Atrophy and the Expanded Disability Status Scale Score in People with Multiple Sclerosis","volume":"18","author":"Zivadinov","year":"2025","journal-title":"Ther. Adv. Neurol. Disord."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"125","DOI":"10.2463\/mrms.rev.2019-0124","article-title":"Perfusion-Driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends","volume":"20","author":"Iima","year":"2021","journal-title":"Magn. Reson. Med. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1148\/radiology.161.2.3763909","article-title":"MR Imaging of Intravoxel Incoherent Motions: Application to Diffusion and Perfusion in Neurologic Disorders","volume":"161","author":"Breton","year":"1986","journal-title":"Radiology"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Lipi\u0144ski, K., and Bogorodzki, P. (2024). Evaluation of Whole Brain Intravoxel Incoherent Motion (IVIM) Imaging. Diagnostics, 14.","DOI":"10.20944\/preprints202402.1054.v1"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1016\/j.nicl.2018.08.030","article-title":"Intravoxel Incoherent Motion MRI in Neurological and Cerebrovascular Diseases","volume":"20","author":"Paschoal","year":"2018","journal-title":"NeuroImage Clin."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Alomair, O.I., Alghamdi, S.A., Abujamea, A.H., AlfIfi, A.Y., Alashban, Y.I., and Kurniawan, N.D. (2025). Investigating the Role of Intravoxel Incoherent Motion Diffusion-Weighted Imaging in Evaluating Multiple Sclerosis Lesions. Diagnostics, 15.","DOI":"10.3390\/diagnostics15101260"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Alomair, O.I., Alghamdi, S.A., Abujamea, A.H., Aljarallah, S., Alkhawajah, N.M., Alshuhri, M.S., Alashban, Y.I., and Kurniawan, N.D. (2025). The Utility of Intravoxel Incoherent Motion Metrics in Assessing Disability in Relapsing\u2013Remitting Multiple Sclerosis. Diagnostics, 15.","DOI":"10.3390\/diagnostics15162113"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Alomair, O.I., Alshuhri, M.S., Al-Mubarak, H.F., Alghamdi, S.A., Abujamea, A.H., Aljarallah, S., Alkhawajah, N.M., Alashban, Y.I., and Kurniawan, N.D. (2025). IVIM-DWI-Based Radiomics for Lesion Phenotyping and Clinical Status Prediction in Relapsing\u2013Remitting Multiple Sclerosis. J. Clin. Med., 14.","DOI":"10.3390\/jcm14196753"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"195","DOI":"10.4103\/tjem.tjem_182_23","article-title":"Receiver Operating Characteristic Curve Analysis in Diagnostic Accuracy Studies: A Guide to Interpreting the Area Under the Curve Value","volume":"23","author":"Aksel","year":"2023","journal-title":"Turk. J. Emerg. Med."},{"key":"ref_36","first-page":"627","article-title":"Receiver Operating Characteristic (ROC) Curve Analysis for Medical Diagnostic Test Evaluation","volume":"4","year":"2013","journal-title":"Casp. J. Intern. Med."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"25","DOI":"10.4097\/kja.21209","article-title":"Receiver Operating Characteristic Curve: Overview and Practical Use for Clinicians","volume":"75","author":"Nahm","year":"2022","journal-title":"Korean J. Anesthesiol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1116","DOI":"10.1016\/j.neuroimage.2006.01.015","article-title":"User-Guided 3D Active Contour Segmentation of Anatomical Structures: Significantly Improved Efficiency and Reliability","volume":"31","author":"Yushkevich","year":"2006","journal-title":"Neuroimage"},{"key":"ref_39","first-page":"e79914","article-title":"Conventional and Advanced Magnetic Resonance Imaging Biomarkers of Multiple Sclerosis in the Brain","volume":"17","author":"Alomair","year":"2025","journal-title":"Cureus"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Gaser, C., Dahnke, R., Thompson, P.M., Kurth, F., Luders, E., and The Alzheimer\u2019s Disease Neuroimaging Initiative (2024). CAT: A Computational Anatomy Toolbox for the Analysis of Structural MRI Data. GigaScience, 13.","DOI":"10.1093\/gigascience\/giae049"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1002\/ana.25145","article-title":"Deep Gray Matter Volume Loss Drives Disability Worsening in Multiple Sclerosis","volume":"83","author":"Eshaghi","year":"2018","journal-title":"Ann. Neurol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.jns.2008.11.018","article-title":"Gray Matter Atrophy Correlates with MS Disability Progression Measured with MSFC but not EDSS","volume":"282","author":"Rudick","year":"2009","journal-title":"J. Neurol. Sci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1082","DOI":"10.1136\/jnnp-2012-304094","article-title":"Brain Atrophy and Lesion Load Predict Long Term Disability in Multiple Sclerosis","volume":"84","author":"Popescu","year":"2013","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1111\/jon.12688","article-title":"Brain MRI Predicts Worsening Multiple Sclerosis Disability over 5 Years in the SUMMIT Study","volume":"30","author":"Bakshi","year":"2020","journal-title":"J. Neuroimaging"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"H\u00e4nninen, K., Viitala, M., Paavilainen, T., Karhu, J.O., Rinne, J., Koikkalainen, J., L\u00f6tj\u00f6nen, J., and Soilu-H\u00e4nninen, M. (2020). Thalamic Atrophy Predicts 5-Year Disability Progression in Multiple Sclerosis. Front. Neurol., 11.","DOI":"10.3389\/fneur.2020.00606"}],"container-title":["Brain Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-3425\/16\/7\/743\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T05:34:44Z","timestamp":1784007284000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-3425\/16\/7\/743"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,14]]},"references-count":45,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["brainsci16070743"],"URL":"https:\/\/doi.org\/10.3390\/brainsci16070743","relation":{},"ISSN":["2076-3425"],"issn-type":[{"value":"2076-3425","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,14]]}}}