The study in brief
MS is divided into four subtypes: clinically isolated syndrome, relapsing remitting, primary and secondary progressive MS and are used to guide the timing and choice of treatments. However, these subtypes are based on observed symptoms, such as relapses and disability which can be difficult to measure and may not reflect the underlying biology driving the course of someone’s MS.
Researchers wanted to find out if there are hidden patterns in MRI brain scans taken over time that would better identify biological differences in MS activity and detect progression earlier.
The international team used MRI scans previously taken in clinical trials involving 6322 people with MS. Data was extracted from the scans and machine learning (artificial intelligence) used to identify subgroups with similar patterns of change in brain structures over time. Results from the initial findings were tested against a second set of MRI scans from 3,068 people with MS. Read on.