Temporal stability of intracranial EEG abnormality maps for localising epileptogenic tissue

TL;DR

This study demonstrates that intracranial EEG abnormality maps based on band power are temporally stable and can reliably localize epileptogenic tissue over several days, aiding in epilepsy surgery outcome prediction.

Contribution

It introduces a normative map of intracranial EEG from a large cohort and shows the stability of band power abnormalities over time for localizing epileptogenic tissue.

Findings

Band power abnormalities are consistent over time within patients.

The DRS metric effectively separates seizure-free and non-seizure-free patients.

Temporal stability of abnormalities supports their use in presurgical evaluation.

Abstract

Objective: Identifying abnormalities in interictal intracranial EEG, by comparing patient data to a normative map, has shown promise for the localisation of epileptogenic tissue and prediction of outcome. The approach typically uses short interictal segments of around one minute. However, the temporal stability of findings has not been established. Methods: Here, we generated a normative map of iEEG in non-pathological brain tissue from 249 patients. We computed regional band power abnormalities in a separate cohort of 39 patients for the duration of their monitoring period (0.92-8.62 days of iEEG data, mean 4.58 days per patient, over 4,800 hours recording). To assess the localising value of band power abnormality, we computed DRS - a measure of how different the surgically resected and spared tissue were in terms of band power abnormalities - over time. Results: In each patient, band power abnormality was relatively consistent over time. The median DRS of the entire recording period separated seizure free (ILAE = 1) and not seizure free (ILAE > 1) patients well (AUC = 0.69). This effect was similar interictally (AUC = 0.69) and peri-ictally (AUC = 0.71). Significance: Our results suggest that band power abnormality DRS, as a predictor of outcomes from epilepsy surgery, is a relatively robust metric over time. These findings add further support for abnormality mapping of neurophysiology data during presurgical evaluation.