Snapshot from Aug 03, 2026 at 07:00 UTC. For live data and tracking: View Live
Tech medical breakthrough

AI reveals MS cortical lesions

Analysis based on 7 articles · First reported Jul 07, 2026 · Last updated Jul 10, 2026

Sentiment
40
Attention
3
Articles
7
Market Impact
General
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The breakthrough could enhance MS drug development by enabling better assessment of treatment effects on cortical lesions, potentially benefiting companies like F. Hoffmann-La Roche — Genentech. However, clinical adoption is years away, so near-term market impact is limited.

biotechnology healthcare artificial intelligence

A University at Buffalo-led team published a paper in Tata Communications on July 7, 2026, demonstrating that AI-enhanced image processing can detect cortical lesions in multiple sclerosis (MS) patients from conventional MRI scans. Cortical lesions in the brain's gray matter are strongly linked to MS progression and cognitive impairment but have been largely invisible on standard MRI. The researchers applied techniques including a new method called multimodal cortical lesion enhancement (MMCLE) to MRI data from the phase III ORATORIO trial of Ocrelizumab, detecting over 10,000 cortical lesions across 732 patients. The method showed high accuracy (86% detection, 8.4% false-positive rate) and reproducibility across scanners. The work was supported in part by F. Hoffmann-La Roche — Genentech, the manufacturer of Ocrelizumab. The findings enable reanalysis of existing clinical trial data and may improve future MS research and treatment monitoring.

per
Senior author and director of BNAC, contributed to the study's leadership and visibility.
Importance 80.0 Sentiment 40.0
per
First and corresponding author, key developer of the AI method.
Importance 80.0 Sentiment 40.0
subs
Provided funding and data from the ORATORIO trial; the method could help evaluate Ocrelizumab's effect on cortical lesions.
Importance 60.0 Sentiment 30.0
oth
The drug studied in the ORATORIO trial; the new method may reveal its impact on cortical lesions.
Importance 50.0 Sentiment 30.0
stock
Published the study, gaining scientific attention.
Importance 30.0 Sentiment 0.0
per
Co-author from UB, contributed to the research.
Importance 20.0 Sentiment 0.0
per
Co-author from UB, contributed to the research.
Importance 20.0 Sentiment 0.0
per
Co-author from UB, contributed to the research.
Importance 20.0 Sentiment 0.0
per
Co-author from Vrije Universiteit Amsterdam, contributed to the research.
Importance 20.0 Sentiment 0.0
per
Co-author from Vrije Universiteit Amsterdam, contributed to the research.
Importance 20.0 Sentiment 0.0
per
Co-author from Vrije Universiteit Amsterdam, contributed to the research.
Importance 20.0 Sentiment 0.0
per
Co-author from F. Hoffmann-La Roche — Genentech, contributed to the research.
Importance 20.0 Sentiment 0.0
per
Co-author from F. Hoffmann-La Roche — Genentech, contributed to the research.
Importance 20.0 Sentiment 0.0
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