Transfer Function Models for the Localization of Seizure Onset Zone From Cortico-Cortical Evoked Potentials.

Golnoosh Kamali,Christopher Coogan,Rachel June Smith,Mark Hays,Sridevi V Sarma,Nathan E Crone,Joon Y Kang

doi:10.3389/fneur.2020.579961

Abstract

Surgical resection of the seizure onset zone (SOZ) could potentially lead to seizure-freedom in medically refractory epilepsy patients. However, localizing the SOZ can be a time consuming and tedious process involving visual inspection of intracranial electroencephalographic (iEEG) recordings captured during passive patient monitoring. Cortical stimulation is currently performed on patients undergoing invasive EEG monitoring for the main purpose of mapping functional brain networks such as language and motor networks. We hypothesized that evoked responses from single pulse electrical stimulation (SPES) can also be used to localize the SOZ as they may express the natural frequencies and connectivity of the iEEG network. To test our hypothesis, we constructed patient specific transfer function models from the evoked responses recorded from 22 epilepsy patients that underwent SPES evaluation and iEEG monitoring. We then computed the frequency and connectivity dependent “peak gain” of the system as measured by the norm from systems theory. We found that in cases for which clinicians had high confidence in localizing the SOZ, the highest peak gain transfer functions with the smallest “floor gain” (gain at which the dipped 3dB below DC gain) corresponded to when the clinically annotated SOZ and early spread regions were stimulated. In more complex cases, there was a large spread of the peak-to-floor (PF) ratios when the clinically annotated SOZ was stimulated. Interestingly for patients who had successful surgeries, our ratio of gains, agreed with clinical localization, no matter the complexity of the case. For patients with failed surgeries, the PF ratio did not match clinical annotations. Our findings suggest that transfer function gains and their corresponding frequency responses computed from SPES evoked responses may improve SOZ localization and thus surgical outcomes.

Highlights

Epilepsy is a widespread neurological disease that affects nearly 1% of the world’s population [1]
We hypothesized that the seizure onset zone (SOZ) is distinguishable from other brain regions in that it generates the “largest” network response to the “smallest” pulse input or “kick.” To test this hypothesis, we investigated a property of transfer functions that reflected the epileptogenic nature of the EEG network
We first assessed whether the single input-multi output (SIMO) transfer function models were able to accurately reconstruct cortical evoked potentials (CCEPs) by calculating the percentage of data points that lied within the 95% confidence interval of the mean from the 50 stimulation trials

Summary

INTRODUCTION

Epilepsy is a widespread neurological disease that affects nearly 1% of the world’s population [1]. Current computational approaches to analyzing seizure networks from CCEPs either compute iEEG features on individual channels, such as the N1 peak amplitudes and signal latencies [21, 25, 36, 42, 43], or they compute static pairwise correlations, organize these correlations into adjacency matrices, and derive graph-theoretic measures [44, 45]. We found that the PF ratio correlates well with clinically annotated SOZ and early spread regions for more straightforward clinical cases and with greater accuracy than current visual assessment approaches This computational tool may aid clinicians in the identification of the epileptogenic network and thereby improve surgical outcomes

18 FocalA to BilateralTC

RESULTS

DISCUSSION

Study Limitations

ETHICS STATEMENT