Validation of an automatic pipeline for probabilistic tractography in drug-resistant epileptic patients.

Diffusion Tensor Imaging (DTI) is a special technique of Magnetic Resonance Imaging (MRI) employed for fiber-tracking (FT) studies for pre-intervention planning activities. The aim of this work is to validate the FT probabilistic workflow in drug-resistant epileptic patients explored by stereoelectroencephalography (SEEG) at ASST Niguarda hospital. The method is based on anatomical Regions-of-Interest (ROIs) definition in a common brain template co-registered on each patient's image. The pipeline was developed in Python language using probtrackx algorithm for FT available in FSL platform (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/) with ROIs as input. The accuracy of our method, able to define the different tracks, was assessed comparing results with pathways previously elaborated during clinical practice, in which ROIs were drawn manually in each patient's images. Electrophysiology data, recorded from deep intracerebral electrodes during SEEG procedures, is the reference method for the clinical validation of FT preoperative planning.