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MINI REVIEW article
Front. Artif. Intell.
Sec. Medicine and Public Health
Volume 8 - 2025 | doi: 10.3389/frai.2025.1478068
This article is part of the Research Topic Use of Big Data and Artificial Intelligence in Multiple Sclerosis View all 9 articles
The Role of AI for MRI-Analysis in Multiple Sclerosis -A Brief Overview
Provisionally accepted
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- 1 Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- 2 Montreal Institute for Learning Algorithm (MILA), Montreal, Quebec, Canada
- 3 Centre for Intelligent Machines, Faculty of Engineering, McGill University, Montreal, Quebec, Canada
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
Received: 27 Sep 2024; Accepted: 19 Mar 2025.
Copyright: © 2025 Falet, Nobile, Szpindel, Barile, Kumar, Durso-Finley, Arbel and Arnold. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Jean-Pierre R Falet, Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
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