Progression of Multiple Sclerosis with Cognitive and Radiological Correlates in a 32-Year-Old Female Patient: A Case Highlighting AI-Driven lesion Quantification
Mohanarajah Saaketthiyan1*, Blagochinnaya Ksenia1, Ruano Armas Jonathan Javier1
1Belarusian State Medical University, University in Minsk, Belarus.
*Corresponding Author: Mohanarajah Saaketthiyan, Belarusian State Medical University, University in Minsk, Belarus.
https://doi.org/10.58624/SVOANE.2025.06.031
Received: December 02, 2025
Published: December 17, 2025
Citation: Saaketthiyan M, Ksenia B, Javier RAJ. Progression of Multiple Sclerosis with Cognitive and Radiological Correlates in a 32-Year-Old Female Patient: A Case Highlighting AI-Driven lesion Quantification. SVOA Neurology 2025, 6:6, 182-186. doi. 10.58624/SVOANE.2025.06.031
Abstract
For a long period, checking on how multiple sclerosis (MS) gets worse has mostly used the Expanded Disability Status Scale (EDSS). But things seen in actual health settings and growing studies suggest that big disease action, like deterioration in thinking skills and changes seen in brain pictures, often happen without being noticed before it is found through standard neurological exam. This certain example study shows that large difference by looking at the case of a 32-year-old woman found to have relapsing-remitting MS (RRMS). Although her EDSS number stayed the same at 3.5 for some years, detailed brain skill tests showed a clear fall in how fast she could handle information, as found by the Symbol Digit Modalities Test (SDMT). Also, later MRI scans showed new spots that lit up with gadolinium and more build-up of lasting spots in brain areas tied to thinking. To exactly measure these changes, we used a thinking tool helped by computer intelligence (AI), called “Brain Snitch,” which wrote down a 22% jump in the full size of T2 spots, mostly placed around the fluid areas. Joining exact measures of thinking skills with AI-helped study of brain scans gave a full view of the disease getting worse, which was not clear when only using the EDSS. This way not only proved disease action that was not easily seen but also backed up a well-planned rise in how strong the treatment should be. The case points out the need to look further than just the EDSS for normal checks and helps with the adding of special brain tests and advanced, countable picture ways, adding AI- run spot study, to help find disease growth sooner and more fitted treatment plans for people with MS.
Keywords: Multiple Sclerosis, Demyelination, Cognitive Impairment, Mri, Edss, Disease Activity Artificial Intelligence, Brain Snitch.
