Abstract #1720

Estimation of individual brain signature and node-wise sensibility by a community-based DW-MRI connectome analysis

Juan Luis Villarreal Haro^1,2, Gabriel Girard^1,3,4, Jean Philippe Thiran^1,4, and Alonso Ramírez-Manzanares²

¹Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, ²Computer Science Department, CIMAT, Centro de Investigación en Matemáticas, Guanajuato, Mexico, ³CIBM Center for BioMedical Imaging, Lausanne, Switzerland, ⁴Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland

In this work, we study the effect of the reconstruction pipeline s on the reproducibility and sensitivity of the DW-MRI brain connectivity graphs. The brain database we analyze contains several scan repetitions that allow us to characterize the impact of different reconstruction pipeline parameters on the connectomes' topology. We use a novel methodology to detect robust graph communities and show the level of reproducibility of the brain structure/biomarkers. Moreover, we proposed a tool to identify the less-robust graph nodes that suffer the effects of the reconstruction pipelines' variability.

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