Morphological Interictal Spike Analysis for Seizure Onset Zone Localization
Abstract number :
2.06
Submission category :
3. Neurophysiology / 3G. Computational Analysis & Modeling of EEG
Year :
2022
Submission ID :
2204275
Source :
www.aesnet.org
Presentation date :
12/4/2022 12:00:00 PM
Published date :
Nov 22, 2022, 05:24 AM
Authors :
Carlos Aguila, BS – University of Pennsylvania; Brian Litt, MD – University of Pennsylvania; Erin Conrad, MD – University of Pennsylvania
This abstract has been invited to present during the Broadening Representation Inclusion and Diversity by Growing Equity (BRIDGE) poster session
Rationale: Patients with drug-resistant epilepsy who undergo intracranial EEG recording for presurgical evaluation amass large amounts of interictal spike data, however this data has minimal use in clinical practice. Our current understanding of spikes and how they inform surgical planning is limited by the lack of a thorough methodology to analyze spike data. Here we present a rigorous quantitative approach to characterizing spike morphology, and we test whether spike morphology localizes the clinician-defined seizure onset zone (SOZ).
Methods: We retrospectively analyzed intracranial EEG data from patients with drug-resistant focal epilepsy who underwent presurgical planning. We automatically detected spikes using a previously validated algorithm. Spikes were then split into sequences under the condition that a set of spikes occur during the same timeframe (0.05 secs). We compared the amplitude and line length of detected spikes in sequences across different electrodes, and determined if these features of spike morphology differed between electrodes inside versus outside the SOZ.
Results: We analyzed data from 34 patients (18 female, mean age = 36.9 years, range = 19-69). We found that the amplitude of spikes occurring on SOZ electrodes was significantly greater than that of spikes outside the SOZ (paired t-test: t = 2.9, p = 0.006). The line-length of spikes occurring on SOZ electrodes was also higher than those occurring on non-SOZ electrodes (paired t-test: t = 3.0, p = 0.005).
Conclusions: Spikes occurring in the SOZ are morphologically different from those outside the SOZ. Our findings highlight that morphological features of spikes localize the SOZ. We plan to expand this work to include additional morphological features and to develop a machine learning algorithm to localize the SOZ using quantitative interictal data.
Funding: Erin Conrad received funding from NIH-NINDS (1K23NS121401-01A1) and the Burroughs Wellcome Fund Career Award for Medical Scientists.
Neurophysiology