Radiomics and Artificial Intelligence in Multiple Sclerosis MRI: A Comprehensive Review

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Authors: Konstantinos Petrou, Agapi Ploussi, Ioannis Seimenis, Efstratios Karavasilis, Georgios Velonakis, Efstathios P. Efstathopoulos
Cited by: 1
References: 36

Abstract

Radiomics is a process of extracting quantitative features from medical images, such as MRI. This process, combined with artificial intelligence (AI), has already been investigated in several studies on the management of MS. The aim of this review article was to provide an overview of the various applications of MRI radiomics in the diagnosis and prognosis of MS. The literature search was conducted in PubMed and Scopus for articles published between 2015 and 2025. A total of 26 articles met the specified criteria. Studies found that radiomics features from brain MR images, combined with AI models, were able to distinguish between healthy tissues and MS lesions, predict disability, detect disease activity, and differentiate between conditions with similar symptoms. The extraction of radiomic features and their utilization with AI models could enhance the effectiveness of MS management. However, several limitations, such as an unbalanced data set and a lack of external validation, must be addressed before they can be integrated into clinical practice.

Fields of Study & Subjects

Radiomics and Machine Learning in Medical Imaging Multiple Sclerosis Research Studies Brain Tumor Detection and Classification

Publication details

Journal / source
American Journal of Neuroradiology
Publisher
American Society of Neuroradiology (ASNR)
Volume
47
Issue
9
Pages
2249–2257
Publication date
19 February 2026
Language
EN