Abstracts

Rationale: One-third of patients with focal epilepsy suffer from drug-resistant epilepsy. Epilepsy surgery is the therapy of choice in this patient group, involving resection of the region from where seizures originate. However, up to 50% of well-selected cases are not seizure-free after epilepsy surgery. One explanation is that epilepsies originally thought to be focal may instead be network disorders. We hypothesized that the properties of epileptic networks could be delineated using interictal spike propagation seen on stereo-electroencephalography (SEEG), and that these properties could predict surgical outcomes in patients with drug-resistant epilepsy. Methods: From our SEEG database, patients with epilepsy surgery, MRI, and clinical outcomes were selected. Thirty-minute segments of awake-state and continuous interictal SEEG recordings were analyzed. Automatic spike detection was performed. Directed propagation maps were created by measuring the latency of spikes between regions, with a sign-test (Bonferroni-corrected) used to determine statistically significant propagation between channel pairs. Primary sources were defined as channels from which spikes propagated but which did not receive propagation from other channels; spikes detected at primary sources are called “primary spikes.” Primary spike concordance was calculated by dividing the number of primary spikes at resected primary sources by the total number of primary spikes. Results: A total of 33 patients met our inclusion criteria; 30 of whom had sufficient interictal activity to create directed connectivity maps. Patients with post-surgical outcome score of Engel I were placed in the good outcome group (n= 16) and those with scores of Engel II – IV were placed in the poor outcome group (n=14). Patients with good surgical outcome had higher primary spike concordance (mean = 84.8 ± 26.7%, n = 16) as compared to those with poor surgical outcome (mean = 25.4 ± 35.7%, n= 14; p < 0.001). Using a receiver operating characteristic (ROC) curve, we determined the preferred values of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), when the primary spike concordance was set to 70%, visually selected as a knee in the ROC curve (figure 1). The Primary spike concordance method achieved a sensitivity of 87.5%, specificity = 85.7%, PPV = 87.5%, and NPV = 85.7%. Conclusions: The PPV of 87.5% and NPV of 85.7% imply that resection of primary sources which contribute to at least 70% of primary spikes leads to good outcomes, while resection of <70% of primary spikes leads to poor outcomes. Delineating primary epileptic sources using SEEG spike propagation maps may define the regions that are important for resection. Resection of primary sources that contribute the most primary spikes may lead to better outcomes in patients with focal drug-resistant epilepsy. Funding: No funding