Wu, Chengyuan

Abstract Objective This study was undertaken to evaluate the safety and effectiveness of responsive thalamic stimulation as adjunctive therapy for drug‐resistant idiopathic generalized epilepsy (IGE) with generalized tonic–clonic seizures (GTCSs). Methods NAUTILUS is a prospective, multicenter, single‐blind, randomized sham‐controlled pivotal trial. Patients were ≥12 years of age with drug‐resistant IGE and ≥2 GTCSs over a 3‐month baseline. Bilateral depth leads were targeted to the centromedian thalamus. One month later, patients were randomized to Active (responsive stimulation, n = 44) or Sham (no stimulation, n = 43). The effectiveness evaluation period (EEP) began 3 months postimplant through 1 year. After a second GTCS in the EEP, patients transitioned to open‐label active stimulation. The primary safety endpoint was the serious adverse device‐related event (SADE) rate at 84 days postimplant. The primary effectiveness endpoint was time‐to‐second‐GTCS during the EEP. Additional endpoints included median percent change in days with any generalized seizure, GTCS frequency, and responder rate (RR). Results Eighty‐seven patients were implanted across 23 US centers. The SADE rate was significantly below the performance goal (6.9%, p < .0001), with no adverse effects on cognition, mood, or sleep. The prespecified primary effectiveness endpoint was not significant. However, a post hoc mixed‐effects model considering all EEP days demonstrated greater GTCS reduction in the originally randomized Active group (61%) compared to patients originally randomized to Sham (49%, p = .030). Eighteen‐month outcomes included 76.8% median GTCS reduction, 62.5% RR, 40% GTCS‐free at that timepoint, and 77.8% median reduction in days with any generalized seizure. More than 90% of patients and 86% of physicians reported improvement on Global Impression of Change scales. Significance NAUTILUS is the first randomized controlled neuromodulation trial in IGE. Responsive thalamic stimulation provided a clinically meaningful and durable reduction in seizures with an acceptable safety profile, offering a much‐needed option for drug‐resistant IGE.

Abstract Objectives Pivotal trials have established the effectiveness of the Responsive Neurostimulation System (RNS® System) in treating focal epilepsy. In clinical trials, depth leads were primarily used to treat mesial temporal seizure onsets while cortical strip leads were used to treat neocortical seizure onsets. Here, we systematically analyze the safety and efficacy of stereoelectroencephalography (sEEG)‐guided depth leads to provide responsive stimulation to neocortical gray matter. Methods Patients were stratified as strong responders (>median cohort seizure reduction %), weak responders (>0% and ≤median cohort seizure reduction %), and anti‐responders (≤0%) based on percent seizure reduction at 1 year post‐implant (1‐Y). Pre‐operative T1‐weighted magnetic resonance imaging and post‐operative computed tomography images were merged, and the Euclidean distance between the sEEG epileptic focus (sEEG‐EF) and the nearest RNS System depth lead contacts was calculated. Results A total of 87 depth leads were implanted in 55 patients across neocortical brain regions. The median reduction in clinical seizures improved from 66.7% at 1‐Y to 77.5% at long‐term follow‐up (LTFU: 2.35 ± 0.95 years), with 10 patients (18.2%) achieving complete seizure freedom. Seven patients (12.7%) experienced six serious adverse events. At 1‐Y, shorter Euclidean distance between the sEEG‐EF and RNS System depth leads predicted improved seizure outcome in strong responders ( β = −0.84, p = 0.008) but not in weak responders ( β = 0.21, p = 0.9) or anti‐responders ( β = −20.34, p = 0.11). At LTFU, there was no significant relationship between Euclidean distance and seizure reduction in strong responders ( β = 0.77, p = 0.18), weak responders ( β = 2.05, p = 0.54), or anti‐responders ( β = 0.24, p = 0.99). Exploratory analyses at 1‐Y showed nominal associations between older age ( ρ = 0.32), longer epilepsy duration ( ρ = 0.27), and non‐mesial temporal sEEG‐EFs and greater seizure reduction; however, none survived Bonferroni correction (adjusted α = 0.0027; all post‐correction p > 0.0027), and no associations were observed at LTFU. Significance In this series, neocortical depth leads for RNS therapy had favorable safety and efficacy and proximity to the sEEG‐EF drove initial outcomes for strong responders to RNS therapy. Plain Language Summary In this multi‐center study, patients with difficult‐to‐treat seizures received brain‐responsive stimulation using a device called responsive neurostimulation (RNS), which delivers small electrical pulses to reduce seizures. We focused on patients treated with electrodes placed in the brain's outer regions (the neocortex) and guided by a mapping procedure called sEEG. On average, patients had their seizures cut by two‐thirds after one year and by more than three‐quarters with longer follow‐up, with about one in five becoming seizure‐free. The treatment was safe, and closer electrode placement to the seizure source helped explain early—but not long‐term—improvements.

Abstract The epileptic network hypothesis and epileptogenic zone hypothesis are two theories of ictogenesis. The network hypothesis posits that coordinated activity among interconnected nodes produces seizures. The epileptogenic zone hypothesis posits that distinct regions are necessary and sufficient for seizure generation. High-frequency oscillations, and particularly fast ripples, are thought to be biomarkers of the epileptogenic zone. We sought to test these theories by comparing high-frequency oscillation rates and networks in surgical responders and non-responders, with no appreciable change in seizure frequency or severity, within a retrospective cohort of 48 patients implanted with stereo-EEG electrodes. We recorded inter-ictal activity during non-rapid eye movement sleep and semi-automatically detected and quantified high-frequency oscillations. Each electrode contact was localized in normalized coordinates. We found that the accuracy of seizure onset zone electrode contact classification using high-frequency oscillation rates was not significantly different in surgical responders and non-responders, suggesting that in non-responders the epileptogenic zone partially encompassed the seizure onset zone(s) (P &gt; 0.05). We also found that in the responders, fast ripple on oscillations exhibited a higher spectral content in the seizure onset zone compared with the non-seizure onset zone (P &lt; 1 × 10−5). By contrast, in the non-responders, fast ripple had a lower spectral content in the seizure onset zone (P &lt; 1 × 10−5). We constructed two different networks of fast ripple with a spectral content &gt;350 Hz. The first was a rate–distance network that multiplied the Euclidian distance between fast ripple-generating contacts by the average rate of fast ripple in the two contacts. The radius of the rate–distance network, which excluded seizure onset zone nodes, discriminated non-responders, including patients not offered resection or responsive neurostimulation due to diffuse multifocal onsets, with an accuracy of 0.77 [95% confidence interval (CI) 0.56–0.98]. The second fast ripple network was constructed using the mutual information between the timing of the events to measure functional connectivity. For most non-responders, this network had a longer characteristic path length, lower mean local efficiency in the non-seizure onset zone, and a higher nodal strength among non-seizure onset zone nodes relative to seizure onset zone nodes. The graphical theoretical measures from the rate–distance and mutual information networks of 22 non- responsive neurostimulation treated patients was used to train a support vector machine, which when tested on 13 distinct patients classified non-responders with an accuracy of 0.92 (95% CI 0.75–1). These results indicate patients who do not respond to surgery or those not selected for resection or responsive neurostimulation can be explained by the epileptic network hypothesis that is a decentralized network consisting of widely distributed, hyperexcitable fast ripple-generating nodes.