AI tool can track effectiveness of MS treatments in study

Researchers at University College London (UCL) have developed an artificial intelligence (AI) tool that can accurately monitor how multiple sclerosis (MS) progresses and how well treatments are working – potentially transforming how the disease is managed.

The tool, described in Nature Communications, was trained on over 17,000 brain scans from 13,000 people with MS. Using advanced machine learning techniques, it identifies patterns of brain shrinkage and lesion development that are difficult to detect with the naked eye. These patterns are used to calculate a score known as the “MRI severity measure,” which reflects how much the brain has changed over time.

Unlike current methods that rely heavily on physical symptoms and can be subjective, the AI tool provides an objective, data-driven way to track the disease. It is particularly useful for identifying early signs of progression in people with progressive MS, who often experience gradual worsening without clear relapses.

The researchers said the tool can detect subtle changes in the brain that may indicate that treatment is, or isn’t, working, even before symptoms change noticeably.

By comparing MRI severity scores over time and across different treatment groups, the researchers could determine which therapies were associated with slower progression. This allows for a more tailored approach, potentially speeding up the process of finding the most effective therapy for each individual.