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Abstract #0348

Using microstructure informed tractography to reduce discrepancy in the density of structural connectomes. An application to Multiple Sclerosis.

Simona Schiavi1,2, Maria Petracca3, Matteo Battocchio1, Mohamed Mounir El Mendili3, Matilde Inglese2,3, and Alessandro Daducci1

1Department of Computer Science, University of Verona, Verona, Italy, 2DINOGMI, University of Genoa/IRCCS AOU San Martino-IST, Genoa, Italy, 3Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States

Graph theory is a valuable framework to study brain connectivity and has been widely applied to investigate pathological conditions such as Multiple Sclerosis (MS). However, differences in topology between groups of subjects could be affected by discrepancy in density. Here we propose to use microstructure informed tractography to directly account for such density differences and provide a fair comparison between MS patients and healthy subjects. Our results show the capability of the proposed method to control for density and support the appropriateness of global efficiency and clustering coefficient for the characterization of comprehensive functions such as cognition in MS.

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