Spike-Associated Networks Predict Postsurgical Outcomes in Children With Refractory Epilepsy.

PURPOSE: Up to half of the children undergoing epilepsy surgery will continue to have seizures (szs) despite a cortical resection or ablation. Functional connectivity has shown promise in better identifying the epileptogenic zone. We hypothesized that cortical areas showing high information outflow during interictal epileptiform discharges are part of the epileptogenic zone. METHODS: We identified 22 children with focal epilepsy who had undergone stereo electroencephalography, surgical resection or ablation, and had ≥1 year of postsurgical follow-up. The mean phase slope index, a directed measure of functional connectivity, was calculated for each electrode contact during interictal epileptiform discharges. The positive predictive value and negative predictive value for a sz-free outcome were calculated based on whether high information outflow brain regions were resected. RESULTS: Resection of high outflow (z-score ≥ 1) and very high outflow (z-score ≥ 2) electrode contacts was associated with higher sz freedom (high outflow: χ 2 statistic = 59.1; P < 0.001; very high outflow: χ 2 statistic = 31.3; P < 0.001). The positive predictive value and negative predictive value for sz freedom based on resection at the electrode level increased at higher z-score thresholds with a peak positive predictive value of 0.86 and a peak negative predictive value of 0.9. CONCLUSIONS: Better identification of the epileptogenic zone has the potential to improve epilepsy surgery outcomes. If the surgical plan can be modified to include these very high outflow areas, more children might achieve sz freedom. Conversely, if deficits from resecting these areas are unacceptable, ineffective surgeries could be avoided and alternative therapies offered.

Spike-associated networks and intracranial electrographic findings.

Functional connectivity is providing new insights into the network nature of epilepsy with growing clinical applications. Our objective was to validate a novel magnetoencephalography-based method to non-invasively measure the epileptic network. We retrospectively identified pediatric and adult patients with refractory focal epilepsy who underwent pre-surgical magnetoencephalography with subsequent intracranial electrographic monitoring. Magnetoencephalography tracings were visually reviewed, and interictal epileptiform discharges ("spikes") were individually marked. We then evaluated differences in whole-brain connectivity during brief epochs preceding the spikes and during the spikes using the Network-Based Statistic to test differences at the network level. In six patients with statistically-significant network differences, we observed substantial overlap between the spike-associated networks and electrographically active areas identified during intracranial monitoring (the spike-associated network was 78% and 83% sensitive for intracranial electroencephalography-defined regions in the irritative and seizure onset zones, respectively). These findings support the neurobiological validity of the spike-associated network method. Assessment of spike-associated networks has the potential to improve surgical planning in epilepsy surgery patients by identifying components of the epileptic network prior to implantation.