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Review
. 2025 Apr 8:8:1478068.
doi: 10.3389/frai.2025.1478068. eCollection 2025.

The role of AI for MRI-analysis in multiple sclerosis-A brief overview

Jean-Pierre R Falet #  1   2   3 , Steven Nobile #  1 , Aliya Szpindel  1 , Berardino Barile  2   3 , Amar Kumar  2   3 , Joshua Durso-Finley  2   3 , Tal Arbel  2   3 , Douglas L Arnold  1
Affiliations
Review

The role of AI for MRI-analysis in multiple sclerosis-A brief overview

Jean-Pierre R Falet et al. Front Artif Intell. .

Abstract

Magnetic resonance imaging (MRI) has played a crucial role in the diagnosis, monitoring and treatment optimization of multiple sclerosis (MS). It is an essential component of current diagnostic criteria for its ability to non-invasively visualize both lesional and non-lesional pathology. Nevertheless, modern day usage of MRI in the clinic is limited by lengthy protocols, error-prone procedures for identifying disease markers (e.g., lesions), and the limited predictive value of existing imaging biomarkers for key disability outcomes. Recent advances in artificial intelligence (AI) have underscored the potential for AI to not only improve, but also transform how MRI is being used in MS. In this short review, we explore the role of AI in MS applications that span the entire life-cycle of an MRI image, from data collection, to lesion segmentation, detection, and volumetry, and finally to downstream clinical and scientific tasks. We conclude with a discussion on promising future directions.

Keywords: artificial intelligence; machine learning; magnetic resonance imaging; multiple sclerosis; precision medicine.

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Conflict of interest statement

DA reports consulting fees from Biogen, Celgene, Frequency Therapeutics, Genentech, Merck, Novartis, Race to Erase MS, Roche, Sanofi–Aventis, Shionogi, and Xfacto Communications, grants from Immunotec and Novartis and an equity interest in NeuroRx. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
An overview of key areas in which AI is being used for MRI-analysis in MS.
See this image and copyright information in PMC

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