Artificial Intelligence in Predicting Progression in Multiple Sclerosis Study

Artificial Intelligence in Predicting Progression in Multiple Sclerosis Study

The study proposal focuses on multiple sclerosis (MS), a chronic incurable disease of the central nervous system (CNS). The MS disease is characterised by recurrent transient disability progression, quantified by increase in the extended disability status score (EDSS), and subsequent remission (disappearance of symptoms and reduced EDSS score) or, alternatively, a gradual EDSS disability progression and exacerbation of associated symptoms. At the same time, the MS is characterised by multifocal inflammatory lesions disseminated throughout the white and grey matter of the CNS, which can be observed and quantified in the magnetic resonance (MR) scans. The proposed study will address the critical unmet need of computer-assisted extraction and assessment of prognostic factors based from an individual patient's brain MR scan, such as lesion count, volume, whole-brain and regional brain atrophy, and atrophied lesion volume, in order to evaluate the capability for personalized future disability progression prediction.

Inclusion Criteria:

• persons diagnosed with MS (any phenotype; according to the 2010 McDonald criteria) and CIS patients
• availability of at least two MRI exams with both FLAIR and T1-weighted scans of the same participant over a period of at least 6 months at the most recent examination
• availability of demographic, clinical data and treatment information for the same participant over a period of at least 6 months at the most recent examination
• availability of EDSS score and at least one previous EDSS scores for the same participant over a period of at least 6 months at the most recent examination

Exclusion Criteria:

• other clinically relevant systemic diseases if the researcher considers them to be significant