Neuroimaging to monitor worsening of multiple sclerosis : advances supported by the grant for multiple sclerosis innovation

dc.contributor.authorOh Jiwon
dc.contributor.authorAiras Laura
dc.contributor.authorHarrison Daniel
dc.contributor.authorJärvinen Elina
dc.contributor.authorLivingston Terrie
dc.contributor.authorLanker Stefan
dc.contributor.authorMalik Rayaz A.
dc.contributor.authorOkuda Darin T.
dc.contributor.authorVilloslada Pablo
dc.contributor.authorde Vries Helga E.
dc.contributor.organizationfi=InFLAMES Lippulaiva|en=InFLAMES Flagship|
dc.contributor.organizationfi=PET-keskus|en=Turku PET Centre|
dc.contributor.organizationfi=kliiniset neurotieteet|en=Clinical Neurosciences|
dc.contributor.organizationfi=tyks, vsshp|en=tyks, varha|
dc.contributor.organization-code1.2.246.10.2458963.20.14646305228
dc.contributor.organization-code1.2.246.10.2458963.20.68445910604
dc.contributor.organization-code1.2.246.10.2458963.20.74845969893
dc.converis.publication-id182378488
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/182378488
dc.date.accessioned2025-08-28T02:38:14Z
dc.date.available2025-08-28T02:38:14Z
dc.description.abstract<p>Key unmet needs in multiple sclerosis (MS) include detection of early pathology, disability worsening independent of relapses, and accurate monitoring of treatment response. Collaborative approaches to address these unmet needs have been driven in part by industry–academic networks and initiatives such as the Grant for Multiple Sclerosis Innovation (GMSI) and Multiple Sclerosis Leadership and Innovation Network (MS-LINK<sup>™</sup>) programs. We review the application of recent advances, supported by the GMSI and MS-LINK<sup>™</sup> programs, in neuroimaging technology to quantify pathology related to central pathology and disease worsening, and potential for their translation into clinical practice/trials. GMSI-supported advances in neuroimaging methods and biomarkers include developments in magnetic resonance imaging, positron emission tomography, ocular imaging, and machine learning. However, longitudinal studies are required to facilitate translation of these measures to the clinic and to justify their inclusion as endpoints in clinical trials of new therapeutics for MS. Novel neuroimaging measures and other biomarkers, combined with artificial intelligence, may enable accurate prediction and monitoring of MS worsening in the clinic, and may also be used as endpoints in clinical trials of new therapies for MS targeting relapse-independent disease pathology.<br></p>
dc.identifier.eissn1664-2295
dc.identifier.jour-issn1664-2295
dc.identifier.olddbid209437
dc.identifier.oldhandle10024/192464
dc.identifier.urihttps://www.utupub.fi/handle/11111/45447
dc.identifier.urlhttps://www.frontiersin.org/articles/10.3389/fneur.2023.1319869/full
dc.identifier.urnURN:NBN:fi-fe2025082788325
dc.language.isoen
dc.okm.affiliatedauthorAiras, Laura
dc.okm.affiliatedauthorDataimport, tyks, vsshp
dc.okm.discipline3112 Neurosciencesen_GB
dc.okm.discipline3112 Neurotieteetfi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA2 Scientific Article
dc.publisherFrontiers Media
dc.publisher.countrySwitzerlanden_GB
dc.publisher.countrySveitsifi_FI
dc.publisher.country-codeCH
dc.relation.articlenumber1319869
dc.relation.doi10.3389/fneur.2023.1319869
dc.relation.ispartofjournalFrontiers in Neurology
dc.relation.volume14
dc.source.identifierhttps://www.utupub.fi/handle/10024/192464
dc.titleNeuroimaging to monitor worsening of multiple sclerosis : advances supported by the grant for multiple sclerosis innovation
dc.year.issued2023

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