Abstracts

Rationale:
Planning targets for sEEG electrode placement remains a major challenge. The spatial sampling bias of sEEG means it is difficult to completely map the epileptic network. Magnetoencephalography (MEG) provides excellent spatiotemporal resolution, and can be used to plan sEEG targets. However, the most common MEG source localization approach in epilepsy, equivalent current dipole (ECD), is limited when complex epileptic networks exist; these methods often fail to fully localize the epileptogenic zone. There has been interest in applying connectivity-based analyses in MEG for epilepsy patients to map crucial ‘hub’ regions, but prospective validation of these network methods, especially for individual patients, is lacking. It is crucial to validate these novel methods and determine how to best apply them for clinical decision making. We hypothesized that MEG connectivity and network analyses will more accurately define the seizure onset zone (SOZ) compared to ECD.
Method:
MEG recordings as part of the pre-surgical evaluation were used for functional connectivity analysis and compared to ECD source analysis. Whole brain estimates of source activity were obtained a linearly constrained minimum variance beamformer, comparing 3-second baseline (no spikes) and 3-second spike phase. Second, functional connectivity was estimated using weighted phase lag index (wPLI). Finally, highly connected nodes were quantified using eigenvector centrality. Post-operative CT scans with sEEG positions were co-registered to the patients’ presurgical MRI in order to measure the Euclidean distance between the SOZ defined by sEEG to both the ECD and area of maximum hubness.
Results:
Five patients (F/M = 3/2, age at seizure onset = 3.98 ± 3.0 yrs, age at the surgery = 13.82 ± 2.1 yrs) who underwent MEG, sEEG and focal resective or Laser Interstitial Thermal Therapy (LITT). Both ECD and highest hub was concordant with SOZ defined by EEG at the lobar level. Connectivity and network-based mapping identified a primary hub that was closer to the sEEG-defined SOZ (8.46 ± 4.57 mm) compared to ECD (24.38 ± 12.77 mm) (t-test, p < 0.030). LITT was performed for 2 patients and 3 underwent resective surgeries. 4 patients had seizure free outcome (ILAE 1) at 3 years post-operative follow up, and 1 achieved seizure freedom at 1 year, however, the seizure retuned after cessation of anti-epileptic medications after 1 year follow up (ILAE 4 at 3 year follow up).
Conclusion:
MEG connectivity and graph analysis exhibited better accuracy for localization of seizure onset zone compared to conventional ECD source modeling. Therefore, MEG connectivity may offer better guidance for sEEG in clinical practice.
Funding:
:AES Postdoctoral Fellowship Award (starting July 1st 2020) will be in support of this study.