In multiple sclerosis (MS), magnetic resonance imaging (MRI) plays a crucial role in seeing changes in the brain and spinal cord. This helps with diagnosis, prognosis, and monitoring MS activity and the response to treatment.
Traditionally, MRI is used in the clinic to see typical features of MS, such as the presence and location of lesions in the brain. It is also used to detect changes over time, including whether new lesions have developed are existing lesions have increased in size.
However, with improvements in imaging technology and artificial intelligence (AI) to analyse the images, there is potentially much more information that could be gained 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 sensitive measurements of the size of MS lesions, and of the volume of the brain, which could help understand whether there is nerve degeneration underway. This could greatly assist neurologists in determining the effectiveness of treatments and intervening at an earlier 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 see whether brain lesion number, lesion volumes and brain volumes can be efficiently calculated from routine MRI scans using automated imaging analysis. This removes the need for manual analysis that can be complex, 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 identify which people with MS are most likely to have their management influenced by these brain measurements. This may relate to personal factors (e.g. age, sex, location), clinical features and/or MRI findings. Understanding these relationships will provide valuable insights into more individualised care for people with MS.
Good progress has been made in establishing the study and its analytical approach.
The medical imaging-artificial intelligence product being used in this study is regulated by the Therapeutic Goods Administration (TGA), and the required multi-step ethics applications have now been completed.
The workflow and automated quantitative MRI analysis have also been finalised, with some new measures included.
Potential participants have been identified based on the study’s inclusion and exclusion criteria.
The project has been extended to March 2027 to support the next phase of work.
Updated 31 March 2026
$25,000
2023
3 year
Current project
