Robust Source Localization of Interictal Epileptiform Activity with Optically-Pumped Magnetometers
Abstract number :
2.046
Submission category :
3. Neurophysiology / 3D. MEG
Year :
2023
Submission ID :
989
Source :
www.aesnet.org
Presentation date :
12/3/2023 12:00:00 AM
Published date :
Authors :
Presenting Author: Abhishek Bhutada, BA – Virginia Tech Carilion School of Medicine
Paul Sands, PhD – Fralin Biomedical Research Institute; Jeff Soldate, PhD – Fralin Biomedical Research Institute; Jeremy Myslowski, PhD – Fralin Biomedical Research Institute; Ryan Hill, PhD – Sir Peter Mansfield Imaging Center; Niall Holmes, PhD – Sir Peter Mansfield Imaging Center; Read Montague, PhD – Fralin Biomedical Research Institute; Chinekwu Anyanwu, MD – Department of Neurology – Carilion Clinic; Stephen LaConte, PhD – Fralin Biomedical Research Institute; Mark Witcher, MD, PhD – Functional Neurosurgion, Principal Investigator, Division of Neurosurgery, Department of Surgery, Carilion Clinic
Rationale: Magnetoencephalography (MEG) measures magnetic fields above the scalp that are generated by neuronal current flows in the brain. MEG is a powerful, non-invasive brain mapping technique with high spatiotemporal precision. However, conventional MEG setups incur high maintenance costs and operate within restrictive scanning environments due to their use of cryogenically cooled sensors stored in an insulated dewar. A new generation of MEG uses Optically-Pumped Magnetometers (OPM), wearable sensors that do not require cryogenic cooling, and can be placed directly on the scalp. This practical alternative has the potential to revolutionize MEG applications. In this study, we present a robust pipeline for acquiring and analyzing brain activity with OPM-MEG to localize interictal epileptiform activity. This is the first study that directly compares source localization results from OPM-MEG to sources found through standard clinical measures.
Methods: We recruited one right-handed female participant with medically refractory epilepsy. As a part of her clinical work-up, this participant had undergone a video-electroencephalogram (video-EEG) and stereoelectroencephalography (sEEG) with the placement of bitemporal intracranial electrodes. The video-EEG captured four complex partial seizures with a right hemispheric focus. The sEEG captured five seizures arising from the right hippocampus. This guided our sensor placement for the OPM-MEG. During the OPM-MEG scan, sensors were placed bitemporal to capture any interictal epileptiform activity. The participant was asked to rest with their eyes closed for about 40 minutes while we collected resting-state brain activity. Then, the participant was also asked to complete a simple button-pressing task to analyze motor activity. The OPM-MEG raw data tracings were visualized on AnyWave software to identify interictal events. Once these events were averaged, we utilized custom MATLAB code to execute standard time-frequency and linear constraint minimum variance beamforming analyses.
Results: In the raw data tracings, we captured thirty total interictal events over the course of a ten-minute window which were utilized for analysis. The standard time-frequency analysis revealed sensors overlying the right temporal region had increased activation. The beamformer localized this activity to the right temporal region which correlated with findings from video-EEG and sEEG.
Conclusions: Our study demonstrates the remarkable effectiveness of OPM-MEG in capturing and accurately localizing interictal epileptic activity, which corresponds to other clinical measurements like video-EEG and sEEG. These findings provide strong evidence supporting the use of OPM-MEG as a reliable guide for treatment options in patients with complex cases of medically refractory epilepsy.
Funding: - Medical Student Research Fund, Virginia Tech Carilion School of Medicine
- R01EB02028772A Sponsored by the National Institute of Health and the National Institute of Biomedical Imaging and Bioengineering
Neurophysiology