TY - JOUR
T1 - Neuroimaging to monitor worsening of multiple sclerosis
T2 - advances supported by the grant for multiple sclerosis innovation
AU - Oh, Jiwon
AU - Airas, Laura
AU - Harrison, Daniel
AU - Järvinen, Elina
AU - Livingston, Terrie
AU - Lanker, Stefan
AU - Malik, Rayaz A
AU - Okuda, Darin T
AU - Villoslada, Pablo
AU - de Vries, Helga E
N1 - Funding Information: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Professional medical writing and editorial assistance were funded by Merck (CrossRef Funder ID: 10.13039/100009945). Publisher Copyright: Copyright © 2023 Oh, Airas, Harrison, Järvinen, Livingston, Lanker, Malik, Okuda, Villoslada and de Vries.
PY - 2023
Y1 - 2023
N2 - 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™) programs. We review the application of recent advances, supported by the GMSI and MS-LINK™ 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.
AB - 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™) programs. We review the application of recent advances, supported by the GMSI and MS-LINK™ 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.
KW - biomarkers
KW - machine learning
KW - multiple sclerosis diagnostic imaging
KW - multiple sclerosis pathology
KW - prognostic factors
UR - http://www.scopus.com/inward/record.url?scp=85179912159&partnerID=8YFLogxK
U2 - https://doi.org/10.3389/fneur.2023.1319869
DO - https://doi.org/10.3389/fneur.2023.1319869
M3 - Review article
C2 - 38107636
SN - 1664-2295
VL - 14
SP - 1319869
JO - Frontiers in Neurology
JF - Frontiers in Neurology
M1 - 1319869
ER -