Prediction of evolution of Multiple Sclerosis

Prediction of evolution of Multiple Sclerosis

Multiple sclerosis (MS) is a chronic, non-communicable, incurable inflammatory disorder of the brain and spinal cord. The body’s immune system incorrectly attacks its central nervous system, causing variable, unpredictable symptoms. It is the leading cause of non-traumatic disability of young and middle-aged adults in many developed countries. It affects more than 2.5 million people worldwide and though it remains impossible to cure MS, early and effective treatment can slow down progression.

State-of-the-art literature, which shows that predicting disability progression due to MS can be achieved to a significant degree. However, to date, there is no Decision Support System for MS progression available to facilitate the accurate prediction of MS and be able to be employed in a sufficiently trustworthy manner in a real-world setting. Several methodological issues still remain, such as the lack of assessment of probabilistic calibration, possible bias in the cohort selection and mainly the lack of using high-dimensional data which are essential for sensitive predictions of progression.

AINIGMA technologies offers a DSS which evaluates different types of biomarkers in order to offer a multimodal estimation of the evolution of MS. We facilitate the following biomarkers in model fusion approaches: Neuro-imaging biomarkers which are considered to be the gold standard for disease activity.  Electrophysiological biomarkers such as Evoked Potential disturbances which are widely utilised in MS to demonstrate the involvement of sensor, visual, auditory and motor pathways and can be considered as a functional counterpart of the anatomical findings on MRI and digital biomarkers. The devices from which digital biomarkers stem are quite broad, and range from wearables that collect patients’ activity during digitized cognitive tests (e.g., the MS  Performance Test, and speech test) to digitalized diagnostic procedures (e.g., optical coherence tomography) and biomarkers extracted from serious games.