Jul 2, 2026 · 24 min · 11 segments
**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…
Olga CiccarelliGuest
Alan ThompsonHost
And today we're focusing on two papers that address one of the biggest questions in modern MS.
How advanced MRI biomarkers can improve our ability to diagnose MS earlier and predict who is most likely to develop it.
One paper, the first author, Dr. Lim, and the last author, Jiwon Oh, from the University of Toronto, looks at people with radiologically isolated syndromes, or RIS, and asks what particular MRI features can predict who will go on to develop clinical MS.
This is a prospective cohort study from three centres, Toronto, NIH in Bethsaida, and Flenny MS Clinic in Buenos Aires.
The second is from colleagues from Belgium, Switzerland, Los Angeles, and NIHS.
And it explores whether machine learning can combine several MRI biomarkers to diagnose MS more accurately than current imaging techniques.
Yes, I'm very happy with these choices because what makes these two studies particularly interesting is that they revolve around the same family of MRI biomarkers, the central vein sign and paramagnetic rim lesions.
Together, these two studies give us a glimpse of how new imaging biomarkers may transform diagnosis and prognosis in the coming years.
And I think maybe it might be helpful before we discuss the papers to just remind ourselves of the context.
The 2024 revisions of the MacDonald criteria marked a really significant shift in how we think about MRI biomarkers and MS. It's really the first time biomarkers such as the central vein sign and paramagnetic rim lesions have which have real pathological implications, were formally recognised as important diagnostic features.
So this is a really big step for the field and one in which I think everyone is getting used to, but it's a really exciting one.
And today we're focusing on two papers that address one of the biggest questions in modern MS.
How advanced MRI biomarkers can improve our ability to diagnose MS earlier and predict who is most likely to develop it.
One paper, the first author, Dr. Lim, and the last author, Jiwon Oh, from the University of Toronto, looks at people with radiologically isolated syndromes, or RIS, and asks what particular MRI features can predict who will go on to develop clinical MS.
This is a prospective cohort study from three centres, Toronto, NIH in Bethsaida, and Flenny MS Clinic in Buenos Aires.
The second is from colleagues from Belgium, Switzerland, Los Angeles, and NIHS.
And it explores whether machine learning can combine several MRI biomarkers to diagnose MS more accurately than current imaging techniques.
Yes, I'm very happy with these choices because what makes these two studies particularly interesting is that they revolve around the same family of MRI biomarkers, the central vein sign and paramagnetic rim lesions.
Together, these two studies give us a glimpse of how new imaging biomarkers may transform diagnosis and prognosis in the coming years.
And I think maybe it might be helpful before we discuss the papers to just remind ourselves of the context.
The 2024 revisions of the MacDonald criteria marked a really significant shift in how we think about MRI biomarkers and MS. It's really the first time biomarkers such as the central vein sign and paramagnetic rim lesions have which have real pathological implications, were formally recognised as important diagnostic features.
So this is a really big step for the field and one in which I think everyone is getting used to, but it's a really exciting one.
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