Advanced Magnetic Source Imaging (MSI) of Ictal Data: An Evaluation of Distinct Approaches
Abstract number :
2.044
Submission category :
3. Neurophysiology / 3D. MEG
Year :
2023
Submission ID :
823
Source :
www.aesnet.org
Presentation date :
12/3/2023 12:00:00 AM
Published date :
Authors :
Presenting Author: Natascha Cardoso da Fonseca, MD, PhD – University of Texas Southwestern Medical Center
Pegah Askari, B.S. – PhD Candidate, Radiology, University of Texas Southwestern Medical Center; Amy Proskovec, PhD – Assistant professor, Radiology, University of Texas Southwestern Medical Center; Tyrell Pruitt, PhD – Postdoctoral researcher, Radiology, University of Texas Southwestern Medical Center; Sasha Alick-Lindstrom, MD – Assistant professor, Neurology, University of Texas Southwestern Medical Center; Irina Podkorytova, MD – Assistant professor, Neurology, University of Texas Southwestern Medical Center; Andrea Lowden, MD – Associate professor, Pediatrics - Division of Pediatric Neurology & Epilepsy, University of Texas Southwestern Medical Center; Afsaneh Talai, MD – Assistant professor, Pediatrics - Division of Pediatric Neurology & Epilepsy, University of Texas Southwestern Medical Center; Joseph Maldjian, MD – Professor & Division Chief, Radiology, University of Texas Southwestern Medical Center; Elizabeth Davenport, PhD – Assistant professor, Radiology, University of Texas Southwestern Medical Center
Rationale:
Seizures during MEG recordings are rare. However, they provide highly accurate localization of the seizure onset zone (SOZ), aiding invasive studies. Ictal Magnetic Source Imaging (MSI) literature is scarce and site-specific variations exist in the preferred method, with the traditional Equivalent Current Dipole (ECD) model being the most used method. However, a consensus regarding ictal MEG analysis has not been reached. Our study assessed multiple MSI techniques against stereo EEG (SEEG) SOZs as the ground truth, aiming to enhance evidence for identifying the optimal approach to ictal MEG.
Methods:
MEG scans where an ictal event was captured from April 2020 to April 2023 were included. We performed ECD fitting in MEGIN DANA software, kurtosis beamforming using an open-source semi-automated pipeline in Fieldtrip, Linearly Constrained Minimum Variance (LCMV) beamforming, and dynamic Statistical Parametric Mapping (dSPM) with Power Spectrum Density analysis in Brainstorm Software. We compared the concordance of the ictal MSI across the methods to the SEEG and calculated the mean minimum Euclidian Distance (MED) between MSI SOZs regarding the SEEG coordinates. Additionally, we compared groups within each method according to the ictal pattern. Statistical analysis was performed in GraphPad Prism 9, assuming statistical significance as p< 0.05.
Neurophysiology