The progression of disability in MS is complex and difficult to predict, particularly over short timeframes. There is still a lack of biological signs (biomarkers) that can accurately predict the progression of MS, which makes it difficult to tailor MS treatment plans to the individual. Identifying new predictors of progression may enable earlier intervention with highly effective treatments in people who are at greatest risk of MS disease progression.
Predicting progression in MS is difficult, especially over short time periods, so the team set out to improve this using brain and spinal cord scans (magnetic resonance imaging; MRI) and routine clinical information such as disability scores, age and treatment history.
For this project, Dr Dongang Wang and his team focused on improving how disease progression in MS can be predicted, using advanced artificial intelligence (AI) technology.
The main aims were to:
By combining advanced AI with data from more than 900 people with MS in MSBase, the world’s largest international MS registry, Dr Wang and his team aimed to improve the accuracy of predicting disease progression for individual patients.
Over the past year, Dr Wang and his team have used and refined AI tools to help predict how MS may progress in individual patients over the next three years.
The researchers worked with advanced AI models, including large language models and vision-language models, that combined existing information from brain scans with clinical data. When tested using data from multiple centres, these models showed good accuracy in identifying people at higher risk of worsening disability.
The study also showed that adding detailed measurements from MRI scans, such as changes in white matter and grey matter, improved the models’ ability to predict future MS progression.
These findings show that combining AI with MRI and clinical data could help doctors better predict MS progression, identify people at higher risk of worsening disability, and support earlier, more personalised treatment decisions, with the potential to improve long-term outcomes for people living with MS.
As a result of this preliminary work, Dr Wang has secured two additional grants to further develop the research.
Updated 31 March 2026
Dr Geng Zhan
Dr Chenyu Wang
Professor Michael Barnett
Dr Heidi Beadnall
$25,000
2024
1 year
Past project
