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dc.contributor.authorDe Stefano, Nicola-
dc.contributor.authorBattaglini, Marco-
dc.contributor.authorPareto, Deborah-
dc.contributor.authorCortese, Rosa-
dc.contributor.authorZhang, Jian-
dc.contributor.authorOesingmann, Niels-
dc.contributor.authorPrados Carrasco, Ferran-
dc.contributor.authorRocca, Maria A.-
dc.contributor.authorValsasina, Paola-
dc.contributor.authorVrenken, Hugo-
dc.contributor.authorGandini Wheeler-Kingshott, Claudia A.M.-
dc.contributor.authorFilippi, Massimo-
dc.contributor.authorBarkhof, Frederik-
dc.contributor.authorRovira, Alex-
dc.contributor.otherUniversity of Siena-
dc.contributor.otherUniversitat Autònoma de Barcelona (UAB)-
dc.contributor.otherUniversity College London (UCL)-
dc.contributor.otherUniversitat Oberta de Catalunya-
dc.contributor.otherVita-Salute San Raffaele University-
dc.contributor.otherUniversity of Pavia-
dc.contributor.otherIRCCS San Raffaele Scientific Institute-
dc.date.accessioned2022-09-06T10:14:40Z-
dc.date.available2022-09-06T10:14:40Z-
dc.date.issued2022-04-02-
dc.identifier.citationDe Stefano, N., Battaglini, M., Pareto, D., Cortese, R., Zhang, J., Oesingmann, N., Prados, F., Rocca, M.A., Valsasina, P., Vrenken, H., Wheeler-Kingshott, C., Filippi, M., Barkhof, F. & Rovira, A. (2022). MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies. NeuroImage: Clinical, 34(null), 1-14. doi: 10.1016/j.nicl.2022.102972-
dc.identifier.issn2213-1582MIAR
-
dc.identifier.urihttp://hdl.handle.net/10609/146745-
dc.description.abstractThere is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.en
dc.format.mimetypeapplication/pdf-
dc.language.isoengca
dc.publisherNeuroImage: Clinicalca
dc.relation.ispartofNeuroImage: Clinical, 2022, 34-
dc.relation.ispartofseries34-
dc.relation.urihttps://www.doi.org/10.1016/j.nicl.2022.102972-
dc.rightsCC BY-NC-ND 4.0-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0-
dc.subjectMRIen
dc.subjectharmonizationen
dc.subjectmultiple sclerosisen
dc.subjectMRIca
dc.subjectharmonitzacióca
dc.subjectesclerosi múltipleca
dc.subjectMRIes
dc.subjectharmonizaciónes
dc.subjectesclerosis múltiplees
dc.subject.lcshmultiple sclerosisen
dc.titleMAGNIMS recommendations for harmonization of MRI data in MS multicenter studiesca
dc.typeinfo:eu-repo/semantics/articleca
dc.subject.lemacesclerosi múltipleca
dc.subject.lcshesesclerosis múltiplees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.doihttps://www.doi.org/10.1016/j.nicl.2022.102972-
dc.gir.idAR/0000009558-
dc.type.versioninfo:eu-repo/semantics/publishedVersion-
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