In MS, magnetic resonance imaging (MRI) plays a crucial role in visualising the brain and spinal cord, aiding in diagnosis, prognosis, and monitoring MS disease activity and the response to MS treatment.
Traditionally, MRI is used in the clinic in a “qualitative” way (for example, are there MS lesions present and where are they in the brain?) or sometimes a “semi-quantitative” way (for example, are there new or enlarging lesions compared to the previous scan?).
However, with improvements in imaging technology and artificial intelligence (AI) to analyse the images, there is potentially much more information that could be gleaned from MRI.
With the use of AI technology, the Sydney Neuroimaging Analysis Centre (SNAC) has developed its own ‘in-house’ fully automated quantitative MRI analysis.
This includes measurements of the size of MS lesions, and of the volume of the brain, which could help understand whether there are neurodegenerative processes underway. This could greatly assist neurologists in determining the effectiveness of treatments and intervening at an early stage if necessary.
Dr Beadnall says, “In the clinic people with MS (as well as their families, friends and carers) often ask questions like ‘How many MS lesions do I have?’, and ‘Do I have brain atrophy (shrinkage)?’
Currently these questions cannot be answered accurately, due to clinicians not having rapid access to quantitative MRI data in the real-world clinical setting. This project addresses this unmet need by making this data available to clinicians.”
The first aim of this project is to explore whether brain lesion number, lesions volumes and brain volumes can be efficiently calculated from routine MRI scans using automated imaging analysis. A fully automated analysis pipeline removes the need for manual analysis that can be convoluted, time-consuming and require specific expertise.
Dr Beadnall will also examine how easily this information can be accessed by neurologists in the clinic using MSBase, a large international database of MS clinical outcomes.
The next aim of the project is to assess how useful these measurements are in an MS clinical practice and how they influence clinical decisions.
The final aim is to investigate which patients with MS have their management and treatment more influenced by the brain measurements. This could be related to demographic factors (eg age, gender, location), clinical features and/or findings on their MRI. By understanding which characteristics are linked to management and treatment decisions, this aim will provide valuable insights into individualised care for people with MS.
The medical imaging-artificial intelligence product being used in this study is regulated by the Therapeutic Goods Administration (TGA). The resulting multi-step ethics applications for the study have now been completed.
The workflow and automated quantitative MRI analysis have also been finalised, with some new measures included.
Potential participants for the study have been identified based on meeting the inclusion and exclusion criteria.
The project has been extended to Mar 2026.
Updated 31 March 2025
$25,000
2023
3 year
Current project
