Interictal intracranial electroencephalography for predicting surgical success: The importance of space and time.

Yujiang Wang,Peter N Taylor,Sriharsha Ramaraju,Anna Miserocchi,Beate Diehl,Nishant Sinha,Gabrielle M Schroeder,Fahmida A Chowdhury,John S Duncan,Jane De Tisi,Andrew W Mcevoy

doi:10.1111/epi.16580

Yujiang Wang, Peter N Taylor + Show 9 more

Open Access

https://doi.org/10.1111/epi.16580

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Abstract

ObjectivePredicting postoperative seizure freedom using functional correlation networks derived from interictal intracranial electroencephalography (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; and (3) functional correlation networks can vary over time but are currently assumed to be static.MethodsIn this study, we address these three challenges using intracranial EEG data from 55 patients with intractable focal epilepsy. Patients additionally underwent preoperative magnetic resonance imaging (MRI), intraoperative computed tomography, and postoperative MRI, allowing accurate localization of electrodes and delineation of the removed tissue.ResultsWe show that normalizing for spatial proximity between nearby electrodes improves prediction of postsurgery seizure outcomes. Moreover, patients with more extensive electrode coverage were more likely to have their outcome predicted correctly (area under the receiver operating characteristic curve > 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 analyzed.SignificanceFuture studies should account for the spatial proximity of electrodes in functional network construction to improve prediction of postsurgical seizure outcomes. Greater coverage of both removed and spared tissue allows for predictions with higher accuracy.

Highlights

Surgery is an effective treatment for epilepsy, with more than half of patients achieving outcomes of postoperative seizure freedom.[1]
For patients not seizure-free after surgery, a possible explanation is the incomplete removal of the epileptogenic zone, defined as the area of cortex that is indispensable for seizure generation.[2]
We will address the following three questions: (1) Does spatial normalization of functional networks increase the ability to distinguish between outcome groups? (2) Does increased coverage of removed and spared tissue lead to increased distinction between outcome groups? and (3) Does the choice of timescale or timepoint affect the ability to distinguish between outcome groups?

Summary

| INTRODUCTION

Surgery is an effective treatment for epilepsy, with more than half of patients achieving outcomes of postoperative seizure freedom.[1]. The potential of using (only) interictal data is attractive in a clinical setting.[21,22] Despite initially promising results from previous studies, open questions remain about, for example, the accuracy/predictive ability of the method, whether it generalizes to all patients regardless of implantation strategy, and whether there are specific timescales or timepoints that are more predictive than others. We formulated these open questions into three concrete challenges that we will address here. IEEG functional networks fluctuate over time,[24,25] it is not currently known whether these fluctuations affect their ability to predict surgical outcome

Key Points

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| DISCUSSION