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Interictal intracranial EEG for predicting surgical success: the importance of space and time

Authors :
Wang, Yujiang
Sinha, Nishant
Schroeder, Gabrielle M.
Ramaraju, Sriharsha
McEvoy, Andrew W.
Miserocchi, Anna
de Tisi, Jane
Chowdhury, Fahmida A.
Diehl, Beate
Duncan, John S.
Taylor, Peter N.
Source :
Epilepsia 61 (2020) 1417-1426
Publication Year :
2019

Abstract

Predicting post-operative seizure freedom using functional correlation networks derived from interictal intracranial EEG has shown some success. However, there are important challenges to consider. 1: electrodes physically closer to each other naturally tend to be more correlated causing a spatial bias. 2: implantation location and number of electrodes differ between patients, making cross-subject comparisons difficult. 3: functional correlation networks can vary over time but are currently assumed as static. In this study we address these three substantial challenges using intracranial EEG data from 55 patients with intractable focal epilepsy. Patients additionally underwent preoperative MR imaging, intra-operative CT, and post-operative MRI allowing accurate localisation of electrodes and delineation of removed tissue. We show that normalising for spatial proximity between nearby electrodes improves prediction of post-surgery seizure outcomes. Moreover, patients with more extensive electrode coverage were more likely to have their outcome predicted correctly (ROC-AUC >0.9, p<<0.05), but not necessarily more likely to have a better outcome. Finally, our predictions are robust regardless of the time segment. Future studies should account for the spatial proximity of electrodes in functional network construction to improve prediction of post-surgical seizure outcomes. Greater coverage of both removed and spared tissue allows for predictions with higher accuracy.

Details

Database :
arXiv
Journal :
Epilepsia 61 (2020) 1417-1426
Publication Type :
Report
Accession number :
edsarx.1909.07932
Document Type :
Working Paper
Full Text :
https://doi.org/10.1111/epi.16580