Abstracts

Normative Atlas of Sevoflurane-Activated High-Frequency Oscillation Effective Connectivity

Abstract number : 1.165
Submission category : 3. Neurophysiology / 3G. Computational Analysis & Modeling of EEG
Year : 2023
Submission ID : 59
Source : www.aesnet.org
Presentation date : 12/2/2023 12:00:00 AM
Published date :

Authors :
Presenting Author: Ethan Firestone, MS – Wayne State University School of Medicine

Hiroshi Uda, MD – Wayne State University; Naoto Kuroda, MD – Wayne State University; Kazuki Sakakura, MD – Wayne State University; Masaki Sonoda, MD, PhD – Yokohama City Univeristy; Yu Kitazawa, MD, PhD – Wayne State University; Jeong-Won Jeong, PhD – Wayne State University; Min-Hee Lee, PhD – Wayne State University; Aimee Luat, MD – Wayne State University; Michael Cools, MD – Wayne State University; Sandeep Sood, MD – Wayne State University; Eishi Asano, MD, PhD – Wayne State University

Rationale:

The major goal of presurgical evaluation for drug-resistant focal epilepsy includes mitigating the need for extraoperative, intracranial electroencephalography (iEEG) recording. Achieving this goal is a challenge because capturing spontaneous ictal signals to localize the seizure onset zone generally requires days of iEEG recording and may not occur during acute iEEG in the operating room. Sevoflurane anesthesia is a potential solution since it can reversibly activate epilepsy iEEG biomarkers such as high-frequency oscillations (HFO). However, proper interpretation of sevoflurane-induced iEEG signals is difficult due to a lack of information describing the normative distribution of these markers. Thus, to improve intraoperative localization of epileptogenic brain regions and better understand the HFO response to sevoflurane, we created a normative atlas of HFO effective connectivity at increasing concentrations of sevoflurane.



Methods:

We studied five pediatric drug-resistant focal epilepsy patients (aged 8-13 years; three males) who underwent two-stage resection at the Children’s Hospital of Michigan. iEEG was recorded during intracranial electrode implantation under an isoflurane baseline and stepwise increases of sevoflurane (from 2-4% in 1% steps); we also collected iEEG data during slow-wave sleep to serve as an additional control. We then exported signals onto a bipolar montage, applied time-frequency transformation (HFO defined at 80-300 Hz and 150-300 Hz), and used transfer entropy to quantify effective connectivity, for each anesthetic stage and frequency band. Next, we pooled all patients’ nonepileptogenic electrodes (n = 738 bipolar pairs outside of the seizure onset zone, spiking zone, MRI-lesions, and the resection area) and interpolated them onto a normalized cortical template to determine the anatomical distribution of HFO effective connectivity hubs. Linear mixed model analysis tested whether the iEEG biomarkers increased as a function of sevoflurane concentration, after controlling for the effects of age, sampled hemisphere, sex, number of antiepileptic drugs, and brain region.



Results:

Using either control period, our analysis with linear mixed models indicated a significant increase in HFO effective connectivity with increasing sevoflurane concentration, for both HFO frequency ranges. The estimated marginal mean of HFO effective connectivity across various brain regions demonstrated that 80-300 Hz transfer entropy was significantly highest in the frontal lobe and lowest in the cingulate cortex, irrespective of control condition.  Likewise, 150-300 Hz HFO were significantly highest in the frontal and parietal lobes and lowest in the cingulate cortex.



Conclusions:

Our preliminary normative model describes HFO effective connectivity dynamics, as a function of sevoflurane concentration, and it provides the estimated margin mean distribution across various brain regions.  With a larger sample size, the normative atlas is expected to be a critical reference when using sevoflurane-activated HFO to intraoperatively localize the epileptogenic zone.



Funding:

NIH F30 NS129239 (to E.F.). NIH R01 NS064033 (to E.A.). JSPS JP22J23281 (to N.K.). NIH R01 NS089659 (to J.J.).



Neurophysiology