“Co-pilot” for disease management in MS with AI imaging

By harnessing large amounts of complex medical data more efficiently, artificial intelligence (AI) has the potential to help discover new disease mechanisms, facilitate early diagnosis, and optimise treatment strategies for chronic conditions such as MS.

In this project, Dr Chenyu Wang and Professor Michael Barnett will leverage the power of AI to develop comprehensive tools for MRI (Magnetic Resonance Imaging) scan analysis that are specifically designed to uncover and measure progression in MS before it manifests clinically, enabling early intervention to prevent future disability. These tools will transform traditional qualitative radiology reporting with accurate, quantitative measures of disease progression.

The team’s second objective is to engineer a system capable of interpreting AI-generated MRI analyses in the appropriate clinical context by benchmarking against people living without MS, as well as other people living with MS with a comparable disease phenotype.

Dr Wang and Professor Barnett aim to utilise these systems, which will support precision management of people living with MS, integrating them into research community platforms such as the MSBase Imaging Repository (MSBIR), a unique, global multi-site image analysis platform that is accelerating clinical-imaging MS research in conjunction with MSBase. In conjunction with their industry partner, Sydney Neuroimaging Analysis Centre, the team will translate these systems into practical clinical applications.

In their pursuit of this goal, the Dr Wang and Professor Barnett intend to conduct a ‘virtual clinical trial’, utilising data derived from MSBase and MSBIR, to enhance their understanding of the effectiveness of current MS treatments on disease progression in a real-world dataset.