About this episode

This episode discusses how advanced MRI biomarkers and machine learning may transform the diagnosis and prognosis of multiple sclerosis.

Welcome to MS Research Briefs, a new ECTRIMS podcast series delivering an expert guided tour of important new studies in multiple sclerosis research. In each episode, leading MS experts will take a small number of recently published studies and go beyond the headline findings – exploring what the research shows and how it may influence clinical practice and future discovery. In this inaugural episode, Prof. Alan Thompson and Prof. Olga Ciccarelli discuss two studies exploring how advanced MRI biomarkers and machine learning may transform the diagnosis and prognosis of multiple sclerosis. Featured Publications Paramagnetic Rim Lesions and Development of Clinical MS in Radiologically Isolated Syndrome. JAMA Neurology. 2026;83(3):250–258. Machine learning-based combination of the central vein sign, cortical lesions and paramagnetic rim lesions: a web-based tool for the diagnosis of multiple sclerosis. Brain Communications. 2026;8(2):fcag079. Discussed in this episode Can paramagnetic rim lesions identify individuals with radiologically isolated syndrome (RIS) who are most likely to develop clinical MS? Why do paramagnetic rim lesions appear to be stronger prognostic biomarkers while…

People in this episode

Guests: Prof. Alan Thompson, Prof. Olga Ciccarelli

Topics covered

• MRI biomarkers
• machine learning
• multiple sclerosis diagnosis
• clinical practice
• prognostic biomarkers

Keywords

• multiple sclerosis
• MRI biomarkers
• machine learning
• diagnosis
• prognosis
• paramagnetic rim lesions
• central vein sign

Mentioned in this episode

Organizations: JAMA Neurology, Brain Communications

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