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

Patryk Filipiak (1, 2) , Fabien Almairac (3) , Théodore Papadopoulo (4) , Denys Fontaine (3) , Lydiane Mondot (3) , Stéphane Chanalet (3) , Rachid Deriche (4, 2) , Maureen Clerc (4, 2) , Demian Wassermann (4, 5, 6, 7)

1 ATHENA - Computational Imaging of the Central Nervous System
2 CRISAM - Inria Sophia Antipolis - Méditerranée
3 CHU Nice - Centre Hospitalier Universitaire de Nice
4 ATHENA - ATHENA
5 CEA - Commissariat à l'énergie atomique et aux énergies alternatives
6 PARIETAL - Modelling brain structure, function and variability based on high-field MRI data
7 Inria Saclay - Ile de France

Propagation of Cortico-Cortical Evoked Potentials (CCEPs) varies depending on numerous structural features of brain tissue. In this work, we show that 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 N1 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.

Domaines: Neurosciences

Patryk Filipiak, Fabien Almairac, Théodore Papadopoulo, Denys Fontaine, Lydiane Mondot, et al.. Diffusion MRI-based Connectivity Enriched with Microstructure Information Predicts the Propagation of Cortico-Cortical Evoked Potentials. ISMRM 2020 - 28th Annual Meeting & Exhibition of the International Society for Magnetic Resonance in Medicine, Aug 2020, Sydney / Virtual, Australia. ⟨hal-03008798⟩