Predictive Value of Imaging Markers at Multiple Sclerosis Disease Onset Based on Gadolinium- and USPIO-Enhanced MRI and Machine Learning 

Crimi, Alessandro; Commowick, Olivier; Maarouf, Adil; Ferré, Jean-Christophe; Bannier, Elise; Tourbah, Ayman; Berry, Isabelle; Ranjeva, Jean-Philippe; Edan, Gilles; Barillot, Christian

A novel characterization of Clinically Isolated Syndrome (CIS) patients according to lesion patterns is proposed. More specifically, patients are classified according to the nature of inflammatory lesions patterns. It is expected that this characterization can infer new prospective figures from the earliest imaging signs of Multiple Sclerosis (MS), since it can provide a classification of different types of lesions across patients.