Abstracts

Rationale:
Millions epilepsy patients do not respond to medications, and surgical removal of the pathological tissue is a viable option to stop seizures. Epileptiform spikes have been proposed as a prominent biomarker for epileptogenicity, while spikes are also commented for the low specificity in localizing epileptogenic zone (EZ) to guide successful resective surgery. Renewed interest has been given to subgroups of spikes conceptualized as “green” and “red” spikes, classifying those less and more likely to index the EZ. On the other hand, high-frequency oscillations (HFOs), another promising biomarker of the EZ, have been observed frequently co-occurring with spikes. In line with this notion, we aim to investigate the possibility of distinguishing such “red spikes” by the concurrence with HFOs for accurate localization of the EZ in patients suffering from focal epilepsy.
Method:
We have collected and analyzed pre-surgical MRI and high-density EEG recordings from 10 medically intractable epilepsy patients who had multi-types of spikes (MTS) and became seizure-free after surgery for at least 12 months of follow-up. Individual head model was made, and inter-ictal spikes were extracted for each patient. These spikes were first pre-processed to remove bad channels/artifacts and automatically screened for putative HFOs via our in-house detector based on the hypothesis of concurrent HFOs and spikes. The detected events were then extracted as multichannel epochs from the noisy scalp recordings for further source imaging analysis via SPIRAL (SPIke Ripple Imaging ALgorithm). We analyzed the morphological characteristics and estimated source distribution of the concurrent activities for each patient and validated the source imaging results by comparing to the clinical evidence, surgical resection, which is modeled from the post-surgical MRI. Besides, we investigated the spike imaging results for each patient as a benchmark.            
Results:
In this cohort of patients, we found distinct morphological characteristics for the spikes concurrent with HFOs compared to those without and significant coupling phenomena between these two biomarkers. The average localization error of the spikes coupled with HFOs from surgical resection was remarkably more accurate than the other spike populations (~23% improvement, p< 0.01). Besides, we computed the overlap between the estimated source and the ground truth (surgical resection) and normalized by the area of estimation and ground truth respectively to get the sensitivity and precision of the extent estimation to evaluate the relative extent of the estimated sources; the geometric mean of these two values (termed as overlap rate) was used for validation, which ranges from 0 (no overlap) to 1 (perfect match). The spike imaging results were consistently boosted by the coupling with HFOs (p< 0.01). These results suggest that the coupled spikes and HFOs are potential pathological biomarkers, possibly demarking “red spikes” and providing accurate estimation of the EZ compared to general interictal spikes in our tested cohort.
Conclusion:
Our proposed approach to study and image the coupled spikes with HFOs, in a cohort of 10 focal epilepsy patients, demonstrated that the coupled activities in scalp EEG can be adopted as a potential and effective biomarker to delineate the EZ noninvasively. The capability of such biomarker to localize and determine the extent of the underlying brain sources could be of crucial interest in studying epileptic brain activities and making a potential impact on patient populations by providing guidance to the placement of the invasive electrode grids and additional insights to clinicians for the pre-surgical diagnosis.
Funding:
:This work was supported in part by NIH R01 NS096761 and EB021027.