{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T19:18:27Z","timestamp":1783106307361,"version":"3.54.6"},"reference-count":38,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T00:00:00Z","timestamp":1778544000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001665","name":"French National Research Agency","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000196","name":"Canada Foundation for Innovation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000196","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000156","name":"Quebec Health Research Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000156","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","msard-journal.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Multiple Sclerosis and Related Disorders"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.msard.2026.107250","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T12:35:24Z","timestamp":1778762124000},"page":"107250","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Automatic multiple sclerosis lesion segmentation in the spinal cord using 3 T and 7 T MP2RAGE images"],"prefix":"10.1016","volume":"111","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0677-8991","authenticated-orcid":false,"given":"Nilser","family":"Laines-Medina","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samira","family":"Mchinda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benoit","family":"Testud","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah","family":"Demorti\u00e8re","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emanuele","family":"Pravat\u00e0","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Govind","family":"Nair","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel S.","family":"Reich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cristina","family":"Granziera","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charidimos","family":"Tsagkas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Virginie","family":"Callot","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julien","family":"Cohen-Adad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"August","key":"10.1016\/j.msard.2026.107250_bib0001","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.neuroimage.2019.03.068","article-title":"Multi-branch convolutional neural network for Multiple sclerosis lesion segmentation","volume":"196","author":"Aslani","year":"2019","journal-title":"Neuroimage"},{"issue":"10","key":"10.1016\/j.msard.2026.107250_bib0002","doi-asserted-by":"crossref","first-page":"866","DOI":"10.1016\/S1474-4422(25)00304-7","article-title":"2024 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI for the diagnosis of multiple sclerosis","volume":"24","author":"Barkhof","year":"2025","journal-title":"Lancet Neurol."},{"key":"10.1016\/j.msard.2026.107250_bib0003","article-title":"Cortical lesions uniquely predict motor disability accrual and form rarely in the absence of new white matter lesions in multiple sclerosis","author":"Beck","year":"2023","journal-title":"medRxiv: The Preprint Server for Health Sciences"},{"key":"10.1016\/j.msard.2026.107250_bib0004","article-title":"Towards contrast-agnostic soft segmentation of the spinal cord","author":"B\u00e9dard","year":"2023","journal-title":"arXiv [Eess.IV]"},{"issue":"2","key":"10.1016\/j.msard.2026.107250_bib0005","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1148\/radiol.2332031572","article-title":"The spinal cord in multiple sclerosis: relationship of high-spatial-resolution quantitative MR imaging findings to histopathologic results","volume":"233","author":"Bot","year":"2004","journal-title":"Radiology"},{"issue":"Pt A","key":"10.1016\/j.msard.2026.107250_bib0007","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.neuroimage.2016.10.009","article-title":"SCT: spinal cord Toolbox, an open-source software for processing spinal cord MRI data","volume":"145","author":"De Leener","year":"2017","journal-title":"Neuroimage"},{"issue":"January","key":"10.1016\/j.msard.2026.107250_bib0006","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.neuroimage.2017.10.041","article-title":"PAM50: unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space","volume":"165","author":"De Leener","year":"2018","journal-title":"Neuroimage"},{"key":"10.1016\/j.msard.2026.107250_bib0008","first-page":"687","article-title":"Improved cervical cord lesion detection in patients with multiple sclerosis using 3D MP2RAGE sequence","volume":"25","author":"Demortiere","year":"2019","journal-title":"Mult. Scler. J."},{"issue":"3","key":"10.1016\/j.msard.2026.107250_bib0009","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1093\/brain\/awy352","article-title":"Spatial distribution of multiple sclerosis lesions in the cervical spinal cord","volume":"142","author":"Eden","year":"2019","journal-title":"Brain"},{"issue":"9","key":"10.1016\/j.msard.2026.107250_bib0010","doi-asserted-by":"crossref","first-page":"575","DOI":"10.1097\/RLI.0000000000000874","article-title":"3-Dimensional fluid and white matter suppression magnetic resonance imaging sequence accelerated with compressed sensing improves multiple sclerosis cervical spinal cord lesion detection compared with standard 2-Dimensional imaging","volume":"57","author":"Emorine","year":"2022","journal-title":"Invest. Radiol."},{"issue":"6","key":"10.1016\/j.msard.2026.107250_bib0011","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1097\/RLI.0000000000000551","article-title":"Automated detection and segmentation of multiple sclerosis lesions using ultra-high-field MP2RAGE","volume":"54","author":"Fartaria","year":"2019","journal-title":"Invest. Radiol."},{"issue":"Pt 6","key":"10.1016\/j.msard.2026.107250_bib0012","doi-asserted-by":"crossref","first-page":"1601","DOI":"10.1093\/brain\/118.6.1601","article-title":"Quantitative assessment of MRI lesion load in monitoring the evolution of multiple sclerosis","volume":"118","author":"Filippi","year":"1995","journal-title":"Brain"},{"issue":"1","key":"10.1016\/j.msard.2026.107250_bib0013","doi-asserted-by":"crossref","DOI":"10.1212\/NXI.0000000000200333","article-title":"Microstructural damage and repair in the spinal cord of patients with early multiple sclerosis and association with disability at 5 years","volume":"12","author":"Gaubert","year":"2025","journal-title":"Neurol. Neuroimmunol. Neuroinflamm."},{"issue":"January","key":"10.1016\/j.msard.2026.107250_bib0014","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1016\/j.neuroimage.2018.09.081","article-title":"Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks","volume":"184","author":"Gros","year":"2019","journal-title":"Neuroimage"},{"key":"10.1016\/j.msard.2026.107250_bib0015","doi-asserted-by":"crossref","unstructured":"Gros, C., A. Lemay, O. Vincent, L. Rouhier, A. Bucquet, J. Paul Cohen, and J. Cohen-Adad. 2020. \u201cIvadomed: a Medical Imaging Deep Learning toolbox.\u201d arXiv [Eess.IV]. arXiv. http:\/\/arxiv.org\/abs\/2010.09984.","DOI":"10.21105\/joss.02868"},{"issue":"2","key":"10.1016\/j.msard.2026.107250_bib0016","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","article-title":"nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation","volume":"18","author":"Isensee","year":"2021","journal-title":"Nat. Methods"},{"key":"10.1016\/j.msard.2026.107250_bib0017","doi-asserted-by":"crossref","DOI":"10.1101\/2025.01.22.25320959","article-title":"Automatic segmentation of spinal cord lesions in MS: a robust tool for axial T2-weighted MRI scans","author":"Karthik","year":"2025","journal-title":"Radiol. Imaging"},{"issue":"3","key":"10.1016\/j.msard.2026.107250_bib0018","doi-asserted-by":"crossref","first-page":"951","DOI":"10.1007\/s11831-020-09403-7","article-title":"State-of-the-art segmentation techniques and future directions for Multiple sclerosis brain lesions","volume":"28","author":"Kaur","year":"2021","journal-title":"Arch. Comput. Methods Eng."},{"issue":"6","key":"10.1016\/j.msard.2026.107250_bib0019","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1097\/RLI.0b013e31824600e9","article-title":"MP2RAGE Multiple sclerosis magnetic resonance imaging at 3 T","volume":"47","author":"Kober","year":"2012","journal-title":"Invest. Radiol."},{"issue":"1","key":"10.1016\/j.msard.2026.107250_bib0020","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/S1474-4422(22)00289-7","article-title":"Multiple sclerosis progression: time for a new mechanism-driven framework","volume":"22","author":"Kuhlmann","year":"2023","journal-title":"Lancet Neurol."},{"key":"10.1016\/j.msard.2026.107250_bib39","doi-asserted-by":"crossref","DOI":"10.1097\/RLI.0000000000001288","article-title":"White and gray matter multiple sclerosis spinal cord lesion characteristics and individualized tissue damage assessment using 7 T T1 mapping","author":"Laines-Medina","year":"2026","journal-title":"Invest. Radiol."},{"issue":"3","key":"10.1016\/j.msard.2026.107250_bib0021","doi-asserted-by":"crossref","DOI":"10.1101\/cshperspect.a028936","article-title":"Multiple sclerosis pathology","volume":"8","author":"Lassmann","year":"2018","journal-title":"Cold. Spring. Harb. Perspect. Med."},{"key":"10.1016\/j.msard.2026.107250_bib0022","doi-asserted-by":"crossref","DOI":"10.1007\/s00330-025-11541-0","article-title":"Evaluation of a deep learning segmentation tool to help detect spinal cord lesions from combined T2 and STIR acquisitions in people with Multiple sclerosis","author":"Lod\u00e9","year":"2025","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.msard.2026.107250_bib0023","series-title":"Ivadomed\/Model_seg_ms_mp2rage: R20240610","author":"Macar","year":"2024"},{"issue":"2","key":"10.1016\/j.msard.2026.107250_bib0024","doi-asserted-by":"crossref","first-page":"1271","DOI":"10.1016\/j.neuroimage.2009.10.002","article-title":"MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field","volume":"49","author":"Marques","year":"2010","journal-title":"Neuroimage"},{"issue":"December","key":"10.1016\/j.msard.2026.107250_bib0026","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.neuroimage.2016.08.055","article-title":"High-resolution multi-parametric quantitative magnetic resonance imaging of the Human cervical spinal cord at 7T","volume":"143","author":"Massire","year":"2016","journal-title":"Neuroimage"},{"issue":"January","key":"10.1016\/j.msard.2026.107250_bib0025","article-title":"Anterior fissure, Central canal, posterior septum and more: new insights into the cervical spinal cord gray and white matter regional organization using T1 mapping at 7T","volume":"205","author":"Massire","year":"2020","journal-title":"Neuroimage"},{"key":"10.1016\/j.msard.2026.107250_bib0027","doi-asserted-by":"crossref","DOI":"10.3174\/ajnr.A9313","article-title":"An optimized MP2RAGE protocol for spinal cord imaging in multiple sclerosis","author":"Papinutto","year":"2026","journal-title":"AJNR Am. J. Neuroradiol."},{"issue":"11","key":"10.1016\/j.msard.2026.107250_bib0028","doi-asserted-by":"crossref","DOI":"10.1002\/nbm.4142","article-title":"Regional T1 mapping of the whole cervical spinal cord using an optimized MP2RAGE sequence","volume":"32","author":"Rasoanandrianina","year":"2019","journal-title":"NMR Biomed."},{"issue":"2","key":"10.1016\/j.msard.2026.107250_bib0029","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1056\/NEJMra1401483","article-title":"Multiple sclerosis","volume":"378","author":"Reich Daniel","year":"2018","journal-title":"N. Engl. J. Med."},{"issue":"9","key":"10.1016\/j.msard.2026.107250_bib0031","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.3174\/ajnr.A7964","article-title":"Contribution of the MP2RAGE 7T sequence in MS lesions of the cervical spinal cord","volume":"44","author":"Testud","year":"2023","journal-title":"AJNR Am. J. Neuroradiol."},{"issue":"2","key":"10.1016\/j.msard.2026.107250_bib0032","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/S1474-4422(17)30470-2","article-title":"Diagnosis of Multiple sclerosis: 2017 revisions of the McDonald criteria","volume":"17","author":"Thompson","year":"2018","journal-title":"Lancet Neurol."},{"issue":"July","key":"10.1016\/j.msard.2026.107250_bib0033","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.neuroimage.2017.04.034","article-title":"Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach","volume":"155","author":"Valverde","year":"2017","journal-title":"Neuroimage"},{"key":"10.1016\/j.msard.2026.107250_bib0034","article-title":"Automatic segmentation of spinal multiple sclerosis lesions: how to generalize across MRI contrasts?","author":"Vincent","year":"2020","journal-title":"ArXiv."},{"issue":"1","key":"10.1016\/j.msard.2026.107250_bib0035","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1007\/s00401-024-02700-6","article-title":"The prevalence and topography of spinal cord demyelination in multiple sclerosis: a retrospective study","volume":"147","author":"Waldman","year":"2024","journal-title":"Acta Neuropathol."},{"key":"10.1016\/j.msard.2026.107250_bib0036","series-title":"2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS)","first-page":"463","article-title":"Expert variability and deep learning performance in spinal cord lesion segmentation for multiple sclerosis patients","author":"Walsh","year":"2023"},{"key":"10.1016\/j.msard.2026.107250_bib0037","unstructured":"Warszawer, Y., N. Molinier, J. Valo\u0161ek, P.-L. Benveniste, S. B\u00e9dard, E. Shirbint, F.B. Mohamed, et al. 2025. \u201cTotalSpineSeg: robust spine segmentation with landmark-based labeling in MRI.\u201d https:\/\/doi.org\/10.13140\/RG.2.2.31318.56649."},{"key":"10.1016\/j.msard.2026.107250_bib0038","series-title":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","first-page":"1","article-title":"Measuring impact of super-resolution on spinal cord MRI scans: lesion detection sensitivity, variability, and clinical impact","author":"Wintergerst","year":"2025"}],"container-title":["Multiple Sclerosis and Related Disorders"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2211034826002865?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2211034826002865?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T18:39:25Z","timestamp":1783103965000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2211034826002865"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":38,"alternative-id":["S2211034826002865"],"URL":"https:\/\/doi.org\/10.1016\/j.msard.2026.107250","relation":{},"ISSN":["2211-0348"],"issn-type":[{"value":"2211-0348","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Automatic multiple sclerosis lesion segmentation in the spinal cord using 3 T and 7 T MP2RAGE images","name":"articletitle","label":"Article Title"},{"value":"Multiple Sclerosis and Related Disorders","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.msard.2026.107250","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"107250"}}