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Abstract #1792

Grey Matter Connectome Data Analysis and Classification of Multiple Sclerosis Clinical Profiles

Berardino Barile1, Claudio Stamile2, Sabine Van Huffel3, and Dominique Sappey-Marinier4
1CREATIS (UMR5220 CNRS & U1294 INSERM, Université Claude Bernard-Lyon1 & INSA-Lyon, France, Villeurbanne, France, 2R&D Department CGnal Milan, Italy, Villeurbanne, France, 3KU Leuven, Leuven, Belgium, 4CREATIS (UMR5220 CNRS & U1294 INSERM), Université Claude Bernard-Lyon1 & INSA-Lyon, France, Villeurbanne, France


Multiple Sclerosis (MS) is an autoimmune inflammatory disease characterized by white matter (WM) lesions and gray matter (GM) degeneration leading to cognitive and physical impairments. Recently, brain connectivity techniques were developed to better characterize such brain damages in association with the clinical profiles of MS patients. In this study, we proposed a complete automated pipeline to first extract global graph metrics from the morphological brain connectivity based on GM tissue thickness and second to train a higher-level ensemble of four machine learning models for the classification of MS clinical profiles using only the T1-weighted image modality.

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