High-density full-head on-scalp MEG for epilepsy
Presented During:
Friday, June 27, 2025: 11:30 AM - 12:45 PM
Brisbane Convention & Exhibition Centre
Room:
M4 (Mezzanine Level)
Poster No:
1943
Submission Type:
Abstract Submission
Authors:
Svenja Knappe1, Isabelle Buard2, K. Jeramy Hughes3, Orang Alem4, Tyler Maydew5, Eugene Kronberg6, Peter Teale6, Teresa Cheung7
Institutions:
1University of Colorado, Boulder, CO, 2Anschutz Medical Centre/University of Colorado, Aurora, CO, 3FieldLine Inc, Boulder, CO, 4FieldLine Medical, Louiseville, CO, 5FieldLine Inc., Boulder, CO, 6University of Colorado, Denver, CO, 7Fraser Health Authority/Simon Fraser University, Burnaby, British Columbia
First Author:
Co-Author(s):
Introduction:
Optically-pumped magnetometers (OPMs) have been identified as a possible candidate for use in evaluations of patients with epilepsy. OPMs combine high spatial and temporal resolution with the ability to track brain activity even when a subject is moving, making them ideal for long-term monitoring - especially for children who have difficulty staying still. OPMs offer the advantage of being cryogen-free, potentially lowering operational costs and simplifying the setup compared to traditional MEG systems. Although several research sites have begun using wearable OPM-based MEG systems in children and adults with epilepsy (Feys et al., 2022; Hillebrand et al., 2023; Pedersen et al., 2022; Sequeiros & Hamandi, 2024; Vivekananda et al., 2020), the technology has not yet been systematically tested in larger groups. We present first results of an ongoing cross-validation study performed in 12 adult patients with drug-resistant focal epilepsy to date. To assess the OPM data quality, subjects underwent simultaneously EEG and MEG recordings on a cryogenic MEG system and an on-scalp MEG system. Interictal activity was localized from resting-state recordings and the locations were compared between the recordings with different modalities. In addition, somatosensory-evoked activity was recorded and localized. The goal of the study is to compare the data quality between OPM-based MEG and conventional cryogenic MEG, using simultaneous EEG and MEG recordings.
Methods:
For each patient, resting-state activity was recorded for 30 min in supine position. Simultaneous EEG using a 10-20 montage and MEG data with a 248-channel cryogenic MEG system (4D Neuroimaging, San Diego, CA) were collected. Co-registration with the subject's anatomy was performed by digitizing the positions of five head-position indicator (HPI) coils with respect to three fiducials and localizing them with the MEG system.
The same EEG montage and HPI coils were then used to record 30 min of resting-state activity simultaneously with EEG and an 80+ sensor OPM-MEG system (FieldLine HEDscan) (Alem et al., 2023). The HPI coils were re-localized and digitized with respect to the OPM sensors. Since the OPM sensors were in contact with the scalp, head shape was inferred from the sensor locations aiding the co-registration process. In addition, somatosensory-evoked activity was recorded.
The data were filtered with a bandpass filter from 3 – 70 Hz and a line filter. A kurtosis beamformer (Hall et al., 2018; Scott et al., 2016; Ukai et al., 2004) was calculated without noise correction or marking of bad segments. Thresholds in the volumetric images were used to identify the peak locations of high kurtosis, where yirtual channels were computed. Peaks were marked for comparison with the EEG signals and for dipole fits. For the somatosensory data, an event-related beamformer (Jobst et al., 2018) was applied on the filtered data to identify the S1 locations.
The same EEG montage and HPI coils were then used to record 30 min of resting-state activity simultaneously with EEG and an 80+ sensor OPM-MEG system (FieldLine HEDscan) (Alem et al., 2023). The HPI coils were re-localized and digitized with respect to the OPM sensors. Since the OPM sensors were in contact with the scalp, head shape was inferred from the sensor locations aiding the co-registration process. In addition, somatosensory-evoked activity was recorded.
The data were filtered with a bandpass filter from 3 – 70 Hz and a line filter. A kurtosis beamformer (Hall et al., 2018; Scott et al., 2016; Ukai et al., 2004) was calculated without noise correction or marking of bad segments. Thresholds in the volumetric images were used to identify the peak locations of high kurtosis, where yirtual channels were computed. Peaks were marked for comparison with the EEG signals and for dipole fits. For the somatosensory data, an event-related beamformer (Jobst et al., 2018) was applied on the filtered data to identify the S1 locations.
Results:
Data is presented from a female patient with drug-resistant focal epilepsy. Figure 1 shows three data segments: on-scalp MEG data, simultaneous EEG data, and the time course of one virtual electrode placed at the location of maximum kurtosis. All three data series show clear interictal spikes at the same time points and exhibit similar morphology. The beamformer results are displayed as the red/orange activity in Figure 2. The corresponding dipole fit is shown as a green circle. Localizations from beamformer and dipole fit are consistent within the resolution of the 4 mm beamformer voxels. Similar findings were observed in the other patients where the kurtosis identified focal activity.
·Figure 1: Interictal activity at three different points in time measured with the on-scalp MEG (top), EEG (middle), and virtual MEG electrode (bottom). The data was bandpass filtered at 3-70 Hz and no
·Figure 2: Interictal activity localized with a kurtosis beamformer (red/orange) and a dipole fit (green circle).
Conclusions:
Good agreement was found between the on-scalp MEG and the EEG data. The kurtosis beamformer presents a convenient method for localization of interictal activity. While first results are encouraging, it still has to be cross-validated with the cryogenic MEG data. In addition, the results will have to be validated systematically in a large number of subjects.
Novel Imaging Acquisition Methods:
MEG 1
Imaging Methods Other 2
Keywords:
Epilepsy
MEG
OPTICAL
Source Localization
1|2Indicates the priority used for review
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Provide references using APA citation style.
Feys, O., et al. (2022). On-Scalp Optically Pumped Magnetometers versus Cryogenic Magnetoencephalography for Diagnostic Evaluation of Epilepsy in School-aged Children. Radiology, 304(2), 429-434. https://doi.org/10.1148/radiol.212453
Hall, M. B. H., et al. (2018). An evaluation of kurtosis beamforming in magnetoencephalography to localize the epileptogenic zone in drug resistant epilepsy patients. Clin Neurophysiol, 129(6), 1221-1229. https://doi.org/10.1016/j.clinph.2017.12.040
Hillebrand, et al. (2023). Non-invasive measurements of ictal and interictal epileptiform activity using optically pumped magnetometers. Sci Rep, 13(1), 4623. https://doi.org/10.1038/s41598-023-31111-y
Jobst, C., et al. (2018). BrainWave: A Matlab Toolbox for Beamformer Source Analysis of MEG Data. Front Neurosci, 12, 587. https://doi.org/10.3389/fnins.2018.00587
Pedersen, et al. (2022). Wearable OPM-MEG: A changing landscape for epilepsy. Epilepsia, 63(11), 2745-2753. https://doi.org/10.1111/epi.17368
Scott, J. M., et al. (2016). Localization of Interictal Epileptic Spikes With MEG: Optimization of an Automated Beamformer Screening Method (SAMepi) in a Diverse Epilepsy Population. J Clin Neurophysiol, 33(5), 414-420. https://doi.org/10.1097/wnp.0000000000000255
Sequeiros, P., & Hamandi, K. (2024). Evaluating the performance of optically pumped magnetometers (OPM) in the diagnosis and presurgical workup of focal epilepsy. J Neurol, 271(3), 1492-1494. https://doi.org/10.1007/s00415-024-12196-5
Ukai, S., et al. SAM(g2) analysis for detecting spike localization: a comparison with clinical symptoms and ECD analysis in an epileptic patient. Neurol Clin Neurophysiol, 2004, 57.
Vivekananda, U., et al. (2020). Optically pumped magnetoencephalography in epilepsy. Ann Clin Transl Neurol, 7(3), 397-401. https://doi.org/10.1002/acn3.50995