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Abstract #4493

Diffusion MRI-based Connectivity Enriched with Microstructure Information Predicts the Propagation of Cortico-Cortical Evoked Potentials

Patryk Filipiak1, Fabien Almairac2, Théodore Papadopoulo1, Denys Fontaine2, Lydiane Mondot3, Stéphane Chanalet3, Rachid Deriche1, Maureen Clerc1, and Demian Wassermann4
1INRIA Sophia Antipolis - Méditerranée, Valbonne, France, 2Service de Neurochirurgie, Centre Hospitalier Universitaire de Nice, Université Côte d’Azur, Nice, France, Nice, France, 3Service de Radiologie, Centre Hospitalier Universitaire de Nice, Université Côte d’Azur, Nice, France, Nice, France, 4INRIA, CEA, Université Paris-Saclay, Paris, France, Paris, France

The propagation of Cortico-Cortical Evoked Potentials (CCEPs) varies depending on numerous structural features of brain tissue. In this work, we show that combined dMRI-based connectivity enriched with microstructure data has the potential to measure cortico-cortical communication as it predicts CCEP-based effective connectivity. Our multiple linear regression model incorporates q-space indices like Q-space Inverse Variance, Non-Gaussianity and Return to Plane Probability with minimum streamline lengths obtained from tractography to predict delays and amplitudes of the P1 peaks in CCEPs. In our experiment, we use presurgical dMRI and intrasurgical ECoG recordings of 9 patients operated on brain tumor in the awake condition.

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