{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T14:14:47Z","timestamp":1793196887510,"version":"4.5.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2025,11,29]],"date-time":"2025-11-29T00:00:00Z","timestamp":1764374400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,29]],"date-time":"2025-11-29T00:00:00Z","timestamp":1764374400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81960309"],"award-info":[{"award-number":["81960309"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82160326"],"award-info":[{"award-number":["82160326"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Gansu Province Clinical Research Center for Functional and Molecular Imaging","award":["21JR7RA438"],"award-info":[{"award-number":["21JR7RA438"]}]},{"name":"Lanzhou University Second Hospital \u201cCuiying Technology Innovation Plan\u201d Applied Basic Research Project","award":["CY2022-MS-B 01"],"award-info":[{"award-number":["CY2022-MS-B 01"]}]},{"name":"Key R&D Plan of Gansu Province","award":["23YFFA0041"],"award-info":[{"award-number":["23YFFA0041"]}]},{"name":"Science and Technology Program Project of Lanzhou Municipal Science and Technology Bureau","award":["2023-2-1"],"award-info":[{"award-number":["2023-2-1"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Neurol"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s00415-025-13455-9","type":"journal-article","created":{"date-parts":[[2025,11,29]],"date-time":"2025-11-29T08:12:16Z","timestamp":1764403936000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Nomograms integrating cortical morphometric metrics with 3D multi-parametric MRI radiomics for predicting disability progression and cognitive worsening in relapsing\u2013remitting multiple sclerosis: a multi-center validation study"],"prefix":"10.1007","volume":"272","author":[{"given":"Zhuo","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shihang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinrui","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yujing","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingsong","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjing","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhuo","family":"Shao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingqi","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fei","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xia","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangyao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanli","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yucheng","family":"Ding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Ai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1678-5688","authenticated-orcid":false,"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,29]]},"reference":[{"issue":"9","key":"13455_CR1","doi-asserted-by":"publisher","first-page":"963","DOI":"10.1212\/01.wnl.0000462309.76486.c5","volume":"84","author":"FH Jacques","year":"2015","unstructured":"Jacques FH (2015) Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology 84(9):963. https:\/\/doi.org\/10.1212\/01.wnl.0000462309.76486.c5","journal-title":"Neurology"},{"issue":"8","key":"13455_CR2","doi-asserted-by":"publisher","first-page":"1123","DOI":"10.1177\/1352458517694432","volume":"23","author":"G Kobelt","year":"2017","unstructured":"Kobelt G, Thompson A, Berg J, Gannedahl M, Eriksson J (2017) New insights into the burden and costs of multiple sclerosis in Europe. Mult Scler 23(8):1123\u20131136. https:\/\/doi.org\/10.1177\/1352458517694432","journal-title":"Mult Scler"},{"issue":"10","key":"13455_CR3","doi-asserted-by":"publisher","first-page":"860","DOI":"10.1016\/s1474-4422(20)30277-5","volume":"19","author":"RHB Benedict","year":"2020","unstructured":"Benedict RHB, Amato MP, DeLuca J, Geurts JJG (2020) Cognitive impairment in multiple sclerosis: clinical management, MRI, and therapeutic avenues. Lancet Neurol 19(10):860\u2013871. https:\/\/doi.org\/10.1016\/s1474-4422(20)30277-5","journal-title":"Lancet Neurol"},{"issue":"13","key":"13455_CR4","doi-asserted-by":"publisher","first-page":"1700","DOI":"10.1177\/1352458519848100","volume":"25","author":"XY Hu","year":"2019","unstructured":"Hu XY, Rajendran L, Lapointe E, Tam R, Li D, Traboulsee A, Rauscher A (2019) Three-dimensional MRI sequences in MS diagnosis and research. Mult Scler 25(13):1700\u20131709. https:\/\/doi.org\/10.1177\/1352458519848100","journal-title":"Mult Scler"},{"key":"13455_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2021.102705","volume":"31","author":"TA Fuchs","year":"2021","unstructured":"Fuchs TA, Dwyer MG, Jakimovski D, Bergsland N, Ramasamy DP, Weinstock-Guttman B, Hb Benedict R, Zivadinov R (2021) Quantifying disease pathology and predicting disease progression in multiple sclerosis with only clinical routine T2-FLAIR MRI. NeuroImage: Clinical 31:102705. https:\/\/doi.org\/10.1016\/j.nicl.2021.102705","journal-title":"NeuroImage: Clinical"},{"issue":"11","key":"13455_CR6","doi-asserted-by":"publisher","first-page":"5201","DOI":"10.1007\/s00415-023-11870-4","volume":"270","author":"S Noteboom","year":"2023","unstructured":"Noteboom S, van Nederpelt DR, Bajrami A, Moraal B, Caan MWA, Barkhof F, Calabrese M, Vrenken H, Strijbis EMM, Steenwijk MD, Schoonheim MM (2023) Feasibility of detecting atrophy relevant for disability and cognition in multiple sclerosis using 3D-FLAIR. J Neurol 270(11):5201\u20135210. https:\/\/doi.org\/10.1007\/s00415-023-11870-4","journal-title":"J Neurol"},{"issue":"3","key":"13455_CR7","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1097\/wco.0000000000001152","volume":"36","author":"C Mainero","year":"2023","unstructured":"Mainero C, Treaba CA, Barbuti E (2023) Imaging cortical lesions in multiple sclerosis. Curr Opin Neurol 36(3):222\u2013228. https:\/\/doi.org\/10.1097\/wco.0000000000001152","journal-title":"Curr Opin Neurol"},{"key":"13455_CR8","doi-asserted-by":"publisher","DOI":"10.1155\/2013\/627870","volume":"2013","author":"JM Honce","year":"2013","unstructured":"Honce JM (2013) Gray matter pathology in MS: neuroimaging and clinical correlations. Mult Scler Int 2013:627870. https:\/\/doi.org\/10.1155\/2013\/627870","journal-title":"Mult Scler Int"},{"issue":"4","key":"13455_CR9","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1177\/135245859900500415","volume":"5","author":"F Barkhof","year":"1999","unstructured":"Barkhof F (1999) MRI in multiple sclerosis: correlation with expanded disability status scale (EDSS). Mult Scler 5(4):283\u2013286. https:\/\/doi.org\/10.1177\/135245859900500415","journal-title":"Mult Scler"},{"issue":"2","key":"13455_CR10","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1111\/jon.12822","volume":"31","author":"CC Park","year":"2021","unstructured":"Park CC, Thongkham DW, Sadigh G, Saindane AM, Chu R, Bakshi R, Allen JW, Hu R (2021) Detection of cortical and deep gray matter lesions in multiple sclerosis using DIR and FLAIR at 3T. J Neuroimaging 31(2):408\u2013414. https:\/\/doi.org\/10.1111\/jon.12822","journal-title":"J Neuroimaging"},{"key":"13455_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.msard.2024.106186","author":"TR Mostardeiro","year":"2025","unstructured":"Mostardeiro TR, Schmitt LG, de Campos FTX, Xi Y, Brondani Torri G, Carvalho BM, Feltrin FS (2025) Multiple sclerosis lesion detection with 3D double inversion recovery (DIR) as compared to 3D fluid low attenuation inversion recovery (T2-FLAIR): a systematic review and meta-analysis. Mult Scler Relat Disord. https:\/\/doi.org\/10.1016\/j.msard.2024.106186","journal-title":"Mult Scler Relat Disord"},{"issue":"5","key":"13455_CR12","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1136\/jnnp-2014-310142","volume":"87","author":"SH van de Pavert","year":"2016","unstructured":"van de Pavert SH, Muhlert N, Sethi V, Wheeler-Kingshott CA, Ridgway GR, Geurts JJ, Ron M, Yousry TA, Thompson AJ, Miller DH, Chard DT, Ciccarelli O (2016) DIR-visible grey matter lesions and atrophy in multiple sclerosis: partners in crime? J Neurol Neurosurg Psychiatry 87(5):461\u2013467. https:\/\/doi.org\/10.1136\/jnnp-2014-310142","journal-title":"J Neurol Neurosurg Psychiatry"},{"issue":"1","key":"13455_CR13","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1186\/s12883-016-0718-9","volume":"16","author":"O Geisseler","year":"2016","unstructured":"Geisseler O, Pflugshaupt T, Bezzola L, Reuter K, Weller D, Schuknecht B, Brugger P, Linnebank M (2016) The relevance of cortical lesions in patients with multiple sclerosis. BMC Neurol 16(1):204. https:\/\/doi.org\/10.1186\/s12883-016-0718-9","journal-title":"BMC Neurol"},{"issue":"4","key":"13455_CR14","doi-asserted-by":"publisher","first-page":"1003","DOI":"10.1002\/hbm.25274","volume":"42","author":"E Lommers","year":"2021","unstructured":"Lommers E, Guillemin C, Reuter G, Fouarge E, Delrue G, Collette F, Degueldre C, Balteau E, Maquet P, Phillips C (2021) Voxel-based quantitative MRI reveals spatial patterns of grey matter alteration in multiple sclerosis. Hum Brain Mapp 42(4):1003\u20131012. https:\/\/doi.org\/10.1002\/hbm.25274","journal-title":"Hum Brain Mapp"},{"issue":"9","key":"13455_CR15","doi-asserted-by":"publisher","first-page":"995","DOI":"10.1136\/jnnp-2020-325610","volume":"92","author":"E Colato","year":"2021","unstructured":"Colato E, Stutters J, Tur C, Narayanan S, Arnold DL, Gandini Wheeler-Kingshott CAM, Barkhof F, Ciccarelli O, Chard DT, Eshaghi A (2021) Predicting disability progression and cognitive worsening in multiple sclerosis using patterns of grey matter volumes. J Neurol Neurosurg Psychiatry 92(9):995\u20131006. https:\/\/doi.org\/10.1136\/jnnp-2020-325610","journal-title":"J Neurol Neurosurg Psychiatry"},{"issue":"1","key":"13455_CR16","doi-asserted-by":"publisher","first-page":"41","DOI":"10.2463\/mrms.rev.2021-0096","volume":"21","author":"M Goto","year":"2022","unstructured":"Goto M, Abe O, Hagiwara A, Fujita S, Kamagata K, Hori M, Aoki S, Osada T, Konishi S, Masutani Y, Sakamoto H, Sakano Y, Kyogoku S, Daida H (2022) Advantages of using both voxel- and surface-based morphometry in cortical morphology analysis: a review of various applications. Magn Reson Med Sci 21(1):41\u201357. https:\/\/doi.org\/10.2463\/mrms.rev.2021-0096","journal-title":"Magn Reson Med Sci"},{"key":"13455_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2012.11.009","author":"PA Narayana","year":"2012","unstructured":"Narayana PA, Govindarajan KA, Goel P, Datta S, Lincoln JA, Cofield SS, Cutter GR, Lublin FD, Wolinsky JS (2012) Regional cortical thickness in relapsing remitting multiple sclerosis: a multi-center study. Neuroimage Clin. https:\/\/doi.org\/10.1016\/j.nicl.2012.11.009","journal-title":"Neuroimage Clin"},{"key":"13455_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.msard.2022.104187","author":"D Oship","year":"2022","unstructured":"Oship D, Jakimovski D, Bergsland N, Horakova D, Uher T, Vaneckova M, Havrdova E, Dwyer MG, Zivadinov R (2022) Assessment of T2 lesion-based disease activity volume outcomes in predicting disease progression in multiple sclerosis over 10 years. Mult Scler Relat Disord. https:\/\/doi.org\/10.1016\/j.msard.2022.104187","journal-title":"Mult Scler Relat Disord"},{"issue":"3","key":"13455_CR19","doi-asserted-by":"publisher","first-page":"802","DOI":"10.1007\/s00415-019-09643-z","volume":"267","author":"E Tavazzi","year":"2020","unstructured":"Tavazzi E, Bergsland N, Kuhle J, Jakimovski D, Ramanathan M, Maceski AM, Tomic D, Hagemeier J, Kropshofer H, Leppert D, Dwyer MG, Weinstock-Guttman B, Benedict RHB, Zivadinov R (2020) A multimodal approach to assess the validity of atrophied T2-lesion volume as an MRI marker of disease progression in multiple sclerosis. J Neurol 267(3):802\u2013811. https:\/\/doi.org\/10.1007\/s00415-019-09643-z","journal-title":"J Neurol"},{"issue":"7","key":"13455_CR20","doi-asserted-by":"publisher","first-page":"4364","DOI":"10.1007\/s00330-023-10529-y","volume":"34","author":"X Luo","year":"2024","unstructured":"Luo X, Li H, Xia W, Quan C, ZhangBao J, Tan H, Wang N, Bao Y, Geng D, Li Y, Yang L (2024) Joint radiomics and spatial distribution model for MRI-based discrimination of multiple sclerosis, neuromyelitis optica spectrum disorder, and myelin-oligodendrocyte-glycoprotein-IgG-associated disorder. Eur Radiol 34(7):4364\u20134375. https:\/\/doi.org\/10.1007\/s00330-023-10529-y","journal-title":"Eur Radiol"},{"issue":"8","key":"13455_CR21","doi-asserted-by":"publisher","first-page":"5700","DOI":"10.1007\/s00330-022-08653-2","volume":"32","author":"X Luo","year":"2022","unstructured":"Luo X, Piao S, Li H, Li Y, Xia W, Bao Y, Liu X, Geng D, Wu H, Yang L (2022) Multi-lesion radiomics model for discrimination of relapsing-remitting multiple sclerosis and neuropsychiatric systemic lupus erythematosus. Eur Radiol 32(8):5700\u20135710. https:\/\/doi.org\/10.1007\/s00330-022-08653-2","journal-title":"Eur Radiol"},{"issue":"11","key":"13455_CR22","doi-asserted-by":"publisher","first-page":"1927","DOI":"10.3174\/ajnr.A7274","volume":"42","author":"G Pontillo","year":"2021","unstructured":"Pontillo G, Tommasin S, Cuocolo R, Petracca M, Petsas N, Ugga L, Carotenuto A, Pozzilli C, Iodice R, Lanzillo R, Quarantelli M, Brescia Morra V, Tedeschi E, Pantano P, Cocozza S (2021) A combined radiomics and machine learning approach to overcome the clinicoradiologic paradox in multiple sclerosis. AJNR Am J Neuroradiol 42(11):1927\u20131933. https:\/\/doi.org\/10.3174\/ajnr.A7274","journal-title":"AJNR Am J Neuroradiol"},{"issue":"Pt 11","key":"13455_CR23","doi-asserted-by":"publisher","first-page":"3287","DOI":"10.1093\/brain\/awv258","volume":"138","author":"T Kalincik","year":"2015","unstructured":"Kalincik T, Cutter G, Spelman T, Jokubaitis V, Havrdova E, Horakova D, Trojano M, Izquierdo G, Girard M, Duquette P, Prat A, Lugaresi A, Grand\u2019Maison F, Grammond P, Hupperts R, Oreja-Guevara C, Boz C, Pucci E, Bergamaschi R, Lechner-Scott J, Alroughani R, Van Pesch V, Iuliano G, Fernandez-Bola\u00f1os R, Ramo C, Terzi M, Slee M, Spitaleri D, Verheul F, Cristiano E, S\u00e1nchez-Menoyo JL, Fiol M, Gray O, Cabrera-Gomez JA, Barnett M, Butzkueven H (2015) Defining reliable disability outcomes in multiple sclerosis. Brain 138(Pt 11):3287\u20133298. https:\/\/doi.org\/10.1093\/brain\/awv258","journal-title":"Brain"},{"issue":"5","key":"13455_CR24","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1177\/1352458517690821","volume":"23","author":"RH Benedict","year":"2017","unstructured":"Benedict RH, DeLuca J, Phillips G, LaRocca N, Hudson LD, Rudick R (2017) Validity of the symbol digit modalities test as a cognition performance outcome measure for multiple sclerosis. Mult Scler 23(5):721\u2013733. https:\/\/doi.org\/10.1177\/1352458517690821","journal-title":"Mult Scler"},{"issue":"6","key":"13455_CR25","doi-asserted-by":"publisher","first-page":"1310","DOI":"10.1109\/tmi.2010.2046908","volume":"29","author":"NJ Tustison","year":"2010","unstructured":"Tustison NJ, Avants BB, Cook PA, Zheng Y, Egan A, Yushkevich PA, Gee JC (2010) N4ITK: improved N3 bias correction. IEEE Trans Med Imaging 29(6):1310\u20131320. https:\/\/doi.org\/10.1109\/tmi.2010.2046908","journal-title":"IEEE Trans Med Imaging"},{"issue":"3","key":"13455_CR26","doi-asserted-by":"publisher","first-page":"1460","DOI":"10.1007\/s00330-020-07174-0","volume":"31","author":"M Ligero","year":"2021","unstructured":"Ligero M, Jordi-Ollero O, Bernatowicz K, Garcia-Ruiz A, Delgado-Mu\u00f1oz E, Leiva D, Mast R, Suarez C, Sala-Llonch R, Calvo N, Escobar M, Navarro-Martin A, Villacampa G, Dienstmann R, Perez-Lopez R (2021) Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis. Eur Radiol 31(3):1460\u20131470. https:\/\/doi.org\/10.1007\/s00330-020-07174-0","journal-title":"Eur Radiol"},{"key":"13455_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.msard.2025.106531","author":"Z Wang","year":"2025","unstructured":"Wang Z, Xu X, Jia F, Ren W, Wang J, Liu Y, Jiang J, Zhou L, Ai K, Zhang J (2025) Glymphatic dysfunction in relapsing-remitting multiple sclerosis and its association with brain structural damage and cognitive impairment. Mult Scler Relat Disord. https:\/\/doi.org\/10.1016\/j.msard.2025.106531","journal-title":"Mult Scler Relat Disord"},{"issue":"2","key":"13455_CR28","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","volume":"18","author":"F Isensee","year":"2021","unstructured":"Isensee F, Jaeger PF, Kohl SAA, Petersen J, Maier-Hein KH (2021) Nnu-net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods 18(2):203\u2013211. https:\/\/doi.org\/10.1038\/s41592-020-01008-z","journal-title":"Nat Methods"},{"key":"13455_CR29","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2202-15-106","volume":"15","author":"S Magon","year":"2014","unstructured":"Magon S, Gaetano L, Chakravarty MM, Lerch JP, Naegelin Y, Stippich C, Kappos L, Radue EW, Sprenger T (2014) White matter lesion filling improves the accuracy of cortical thickness measurements in multiple sclerosis patients: a longitudinal study. BMC Neurosci 15:106. https:\/\/doi.org\/10.1186\/1471-2202-15-106","journal-title":"BMC Neurosci"},{"issue":"9","key":"13455_CR30","doi-asserted-by":"publisher","first-page":"2062","DOI":"10.1002\/hbm.21344","volume":"33","author":"M Battaglini","year":"2012","unstructured":"Battaglini M, Jenkinson M, De Stefano N (2012) Evaluating and reducing the impact of white matter lesions on brain volume measurements. Hum Brain Mapp 33(9):2062\u20132071. https:\/\/doi.org\/10.1002\/hbm.21344","journal-title":"Hum Brain Mapp"},{"issue":"1","key":"13455_CR31","doi-asserted-by":"publisher","DOI":"10.1186\/s12987-024-00525-9","volume":"21","author":"JJ Eisma","year":"2024","unstructured":"Eisma JJ, McKnight CD, Hett K, Elenberger J, Han CJ, Song AK, Considine C, Claassen DO, Donahue MJ (2024) Deep learning segmentation of the choroid plexus from structural magnetic resonance imaging (MRI): validation and normative ranges across the adult lifespan. Fluids Barriers CNS 21(1):21. https:\/\/doi.org\/10.1186\/s12987-024-00525-9","journal-title":"Fluids Barriers CNS"},{"issue":"1","key":"13455_CR32","doi-asserted-by":"publisher","DOI":"10.1186\/s40708-021-00128-2","volume":"8","author":"AD Gilmore","year":"2021","unstructured":"Gilmore AD, Buser NJ, Hanson JL (2021) Variations in structural MRI quality significantly impact commonly used measures of brain anatomy. Brain Inform 8(1):7. https:\/\/doi.org\/10.1186\/s40708-021-00128-2","journal-title":"Brain Inform"},{"key":"13455_CR33","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1016\/j.neuroimage.2012.09.050","volume":"65","author":"R Dahnke","year":"2013","unstructured":"Dahnke R, Yotter RA, Gaser C (2013) Cortical thickness and central surface estimation. Neuroimage 65:336\u2013348. https:\/\/doi.org\/10.1016\/j.neuroimage.2012.09.050","journal-title":"Neuroimage"},{"key":"13455_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2024.103701","volume":"44","author":"X Pang","year":"2024","unstructured":"Pang X, Wu D, Wang H, Zhang J, Yu Y, Zhao Y, Li Q, Ni L, Wang K, Zhang D, Tian Y (2024) Cortical morphological alterations in adolescents with major depression and non-suicidal self-injury. Neuroimage Clin 44:103701. https:\/\/doi.org\/10.1016\/j.nicl.2024.103701","journal-title":"Neuroimage Clin"},{"issue":"2","key":"13455_CR35","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1148\/radiol.2020191145","volume":"295","author":"A Zwanenburg","year":"2020","unstructured":"Zwanenburg A, Valli\u00e8res M, Abdalah MA, Aerts H, Andrearczyk V, Apte A, Ashrafinia S, Bakas S, Beukinga RJ, Boellaard R, Bogowicz M, Boldrini L, Buvat I, Cook GJR, Davatzikos C, Depeursinge A, Desseroit MC, Dinapoli N, Dinh CV, Echegaray S, El Naqa I, Fedorov AY, Gatta R, Gillies RJ, Goh V, G\u00f6tz M, Guckenberger M, Ha SM, Hatt M, Isensee F, Lambin P, Leger S, Leijenaar RTH, Lenkowicz J, Lippert F, Losneg\u00e5rd A, Maier-Hein KH, Morin O, M\u00fcller H, Napel S, Nioche C, Orlhac F, Pati S, Pfaehler EAG, Rahmim A, Rao AUK, Scherer J, Siddique MM, Sijtsema NM, Socarras Fernandez J, Spezi E, Steenbakkers R, Tanadini-Lang S, Thorwarth D, Troost EGC, Upadhaya T, Valentini V, van Dijk LV, van Griethuysen J, van Velden FHP, Whybra P, Richter C, L\u00f6ck S (2020) The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology 295(2):328\u2013338. https:\/\/doi.org\/10.1148\/radiol.2020191145","journal-title":"Radiology"},{"key":"13455_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2025.111956","volume":"184","author":"C Zhou","year":"2025","unstructured":"Zhou C, Zhou J, Lv Y, Batuer M, Huang J, Zhong J, Zhong H, Qin G (2025) The impact of the novel CovBat harmonization method on enhancing radiomics feature stability and machine learning model performance: a multi-center, multi-device study. Eur J Radiol 184:111956. https:\/\/doi.org\/10.1016\/j.ejrad.2025.111956","journal-title":"Eur J Radiol"},{"key":"13455_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2024.111438","volume":"175","author":"Z Chen","year":"2024","unstructured":"Chen Z, Wang Z, Liu S, Zhang S, Zhou Y, Zhang R, Yang W (2024) Nomograms based on multiparametric MRI radiomics integrated with clinical-radiological features for predicting the response to induction chemotherapy in nasopharyngeal carcinoma. Eur J Radiol 175:111438. https:\/\/doi.org\/10.1016\/j.ejrad.2024.111438","journal-title":"Eur J Radiol"},{"issue":"4","key":"13455_CR38","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.220232","volume":"5","author":"TJ Bradshaw","year":"2023","unstructured":"Bradshaw TJ, Huemann Z, Hu J, Rahmim A (2023) A guide to cross-validation for artificial intelligence in medical imaging. Radiol Artif Intell 5(4):e220232. https:\/\/doi.org\/10.1148\/ryai.220232","journal-title":"Radiol Artif Intell"},{"key":"13455_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.msard.2023.105348","author":"Z Yan","year":"2024","unstructured":"Yan Z, Yuan S, Zhu Q, Wang X, Shi Z, Zhang Y, Liu J, Feng J, Wei Y, Yin F, Chen S, Li Y (2024) Radiomics models based on cortical damages for identification of multiple sclerosis with cognitive impairment. Mult Scler Relat Disord. https:\/\/doi.org\/10.1016\/j.msard.2023.105348","journal-title":"Mult Scler Relat Disord"},{"issue":"3","key":"13455_CR40","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1148\/radiol.2019192515","volume":"294","author":"DA Bluemke","year":"2020","unstructured":"Bluemke DA, Moy L, Bredella MA, Ertl-Wagner BB, Fowler KJ, Goh VJ, Halpern EF, Hess CP, Schiebler ML, Weiss CR (2020) Assessing radiology research on artificial intelligence: a brief guide for authors, reviewers, and readers-from the Radiology editorial board. Radiology 294(3):487\u2013489. https:\/\/doi.org\/10.1148\/radiol.2019192515","journal-title":"Radiology"},{"issue":"3","key":"13455_CR41","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1007\/s00415-025-12979-4","volume":"272","author":"M Azzimonti","year":"2025","unstructured":"Azzimonti M, Preziosa P, Pagani E, Meani A, Margoni M, Rubin M, Gueye M, Esposito F, Filippi M, Rocca MA (2025) Cervical spinal cord gray matter damage predicts disability worsening in multiple sclerosis: a longitudinal study. J Neurol 272(3):228. https:\/\/doi.org\/10.1007\/s00415-025-12979-4","journal-title":"J Neurol"},{"issue":"12","key":"13455_CR42","doi-asserted-by":"publisher","first-page":"4834","DOI":"10.1007\/s00415-021-10605-7","volume":"268","author":"S Tommasin","year":"2021","unstructured":"Tommasin S, Cocozza S, Taloni A, Giann\u00ec C, Petsas N, Pontillo G, Petracca M, Ruggieri S, De Giglio L, Pozzilli C, Brunetti A, Pantano P (2021) Machine learning classifier to identify clinical and radiological features relevant to disability progression in multiple sclerosis. J Neurol 268(12):4834\u20134845. https:\/\/doi.org\/10.1007\/s00415-021-10605-7","journal-title":"J Neurol"},{"issue":"10","key":"13455_CR43","doi-asserted-by":"publisher","first-page":"1312","DOI":"10.1177\/1352458515581874","volume":"21","author":"A Martins Da Silva","year":"2015","unstructured":"Martins Da Silva A, Cavaco S, Moreira I, Bettencourt A, Santos E, Pinto C, Gon\u00e7alves A, Coutinho E, Sam\u00f5es R, Dias CC, Teixeira-Pinto A, Da Silva BM, Montalban X (2015) Cognitive reserve in multiple sclerosis: protective effects of education. Mult Scler 21(10):1312\u20131321. https:\/\/doi.org\/10.1177\/1352458515581874","journal-title":"Mult Scler"},{"issue":"14","key":"13455_CR44","doi-asserted-by":"publisher","first-page":"1938","DOI":"10.1177\/1352458519891984","volume":"26","author":"AI Wallach","year":"2020","unstructured":"Wallach AI, Waltz M, Casper TC, Aaen G, Belman A, Benson L, Chitnis T, Gorman M, Graves J, Harris Y, Lotze TE, Mar S, Moodley M, Ness JM, Rensel M, Rodriguez M, Rose JW, Schreiner T, Tillema JM, Waubant E, Weinstock-Guttman B, Charvet LE, Krupp LB (2020) Cognitive processing speed in pediatric-onset multiple sclerosis: baseline characteristics of impairment and prediction of decline. Mult Scler 26(14):1938\u20131947. https:\/\/doi.org\/10.1177\/1352458519891984","journal-title":"Mult Scler"},{"key":"13455_CR45","doi-asserted-by":"publisher","DOI":"10.1016\/j.msard.2022.103838","volume":"65","author":"X Dong","year":"2022","unstructured":"Dong X, Xu G, Wang J, Yin N, Meng N (2022) Clinical and MRI predictors of cognitive decline in patients with relapsing-remitting multiple sclerosis: a 2-year longitudinal study. Mult Scler Relat Disord 65:103838. https:\/\/doi.org\/10.1016\/j.msard.2022.103838","journal-title":"Mult Scler Relat Disord"},{"issue":"9","key":"13455_CR46","doi-asserted-by":"publisher","first-page":"2605","DOI":"10.1093\/brain\/awy202","volume":"141","author":"AJC Eijlers","year":"2018","unstructured":"Eijlers AJC, van Geest Q, Dekker I, Steenwijk MD, Meijer KA, Hulst HE, Barkhof F, Uitdehaag BMJ, Schoonheim MM, Geurts JJG (2018) Predicting cognitive decline in multiple sclerosis: a 5-year follow-up study. Brain 141(9):2605\u20132618. https:\/\/doi.org\/10.1093\/brain\/awy202","journal-title":"Brain"},{"issue":"11","key":"13455_CR47","doi-asserted-by":"publisher","first-page":"5211","DOI":"10.1007\/s00415-023-11907-8","volume":"270","author":"I Kletenik","year":"2023","unstructured":"Kletenik I, Cohen AL, Glanz BI, Ferguson MA, Tauhid S, Li J, Drew W, Polgar-Turcsanyi M, Palotai M, Siddiqi SH, Marshall GA, Chitnis T, Guttmann CRG, Bakshi R, Fox MD (2023) Multiple sclerosis lesions that impair memory map to a connected memory circuit. J Neurol 270(11):5211\u20135222. https:\/\/doi.org\/10.1007\/s00415-023-11907-8","journal-title":"J Neurol"},{"issue":"9","key":"13455_CR48","doi-asserted-by":"publisher","first-page":"1004","DOI":"10.1001\/jamaneurol.2015.1241","volume":"72","author":"DM Harrison","year":"2015","unstructured":"Harrison DM, Roy S, Oh J, Izbudak I, Pham D, Courtney S, Caffo B, Jones CK, van Zijl P, Calabresi PA (2015) Association of cortical lesion burden on 7-T magnetic resonance imaging with cognition and disability in multiple sclerosis. JAMA Neurol 72(9):1004\u20131012. https:\/\/doi.org\/10.1001\/jamaneurol.2015.1241","journal-title":"JAMA Neurol"},{"issue":"2","key":"13455_CR49","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1148\/radiol.2015151169","volume":"278","author":"RJ Gillies","year":"2016","unstructured":"Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278(2):563\u2013577. https:\/\/doi.org\/10.1148\/radiol.2015151169","journal-title":"Radiology"},{"issue":"1","key":"13455_CR50","doi-asserted-by":"publisher","first-page":"99","DOI":"10.3174\/ajnr.A5915","volume":"40","author":"G Pontillo","year":"2019","unstructured":"Pontillo G, Cocozza S, Lanzillo R, Russo C, Stasi MD, Paolella C, Vola EA, Criscuolo C, Borrelli P, Palma G, Tedeschi E, Morra VB, Elefante A, Brunetti A (2019) Determinants of deep gray matter atrophy in multiple sclerosis: a multimodal MRI study. AJNR Am J Neuroradiol 40(1):99\u2013106. https:\/\/doi.org\/10.3174\/ajnr.A5915","journal-title":"AJNR Am J Neuroradiol"},{"issue":"2","key":"13455_CR51","doi-asserted-by":"publisher","first-page":"2049","DOI":"10.21037\/qims-23-1287","volume":"14","author":"Z Shi","year":"2024","unstructured":"Shi Z, Ma Y, Ding S, Yan Z, Zhu Q, Xiong H, Li C, Xu Y, Tan Z, Yin F, Chen S, Li Y (2024) Radiomics derived from T2-FLAIR: the value of 2- and 3-classification tasks for different lesions in multiple sclerosis. Quant Imaging Med Surg 14(2):2049\u20132059. https:\/\/doi.org\/10.21037\/qims-23-1287","journal-title":"Quant Imaging Med Surg"}],"container-title":["Journal of Neurology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00415-025-13455-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00415-025-13455-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00415-025-13455-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T15:30:45Z","timestamp":1765812645000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00415-025-13455-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,29]]},"references-count":51,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["13455"],"URL":"https:\/\/doi.org\/10.1007\/s00415-025-13455-9","relation":{},"ISSN":["0340-5354","1432-1459"],"issn-type":[{"value":"0340-5354","type":"print"},{"value":"1432-1459","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,29]]},"assertion":[{"value":"24 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 October 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 October 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 November 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}},{"value":"The study was reviewed and approved by the Institutional Review Boards of the Second Hospital of Lanzhou University (Approval No. [2024A-1077]). Written informed consent was obtained from all participants prior to enrollment in accordance with the ethical standards of the Declaration of Helsinki.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}],"article-number":"792"}}