Osman, Gamaleldin

Abstract To characterize invasive neuromodulation for insular drug‐resistant epilepsy, we retrospectively evaluated 22 patients treated with responsive neurostimulation (RNS; n = 14) or chronic subthreshold stimulation (CSS; n = 8). Stereoelectroencephalography was performed in 20 cases (91%). Median baseline seizure frequency was 10.5/month. Forty‐one percent had prior epilepsy surgery. At year 3, median seizure reduction (MSR) was 83% ( p = .01, Wilcoxon signed‐rank test), with a responder rate (RR) of 77%; MSR was 92% for CSS and 75% for RNS. There were no significant differences in MSR ( p ≥ .4) or RR ( p > .9) when comparing RNS versus CSS. Three patients achieved seizure freedom by year 3. Patients undergoing combined insular–thalamic stimulation ( n = 5) demonstrated an MSR of 84%, 86%, and 88% at 1, 2, and 3 years; seizure reduction in thalamocortical versus cortical‐only stimulation was not different ( p ≥ .1). Parasagittal lead trajectories achieved closer insular proximity than transopercular trajectories ( p < .0001, Mann–Whitney U ‐test). Median charge density at last follow‐up was 1.3 μC/cm 2 . There were no acute surgical complications and all stimulation‐related side effects resolved with programming adjustments. This study expands the limited literature on insular neuromodulation by demonstrating effectiveness of RNS and CSS, suggesting potential benefit from combined thalamocortical targeting, and defining parasagittal trajectories as a surgical approach for optimal lead proximity.

Abstract Objective Ceribell Inc.'s point‐of‐care electroencephalographic (EEG) system and artificial intelligence‐based Automated Seizure Burden Estimator (ASBE; ClarityPro) have US Food and Drug Administration clearance for diagnosing electrographic status epilepticus (ESE). The AccuRASE study using ASBE version 6 (V6) showed high negative predictive value (NPV) but limited sensitivity and positive predictive value (PPV) at certain thresholds. Version 8 (V8) is the updated algorithm trained with additional EEG samples. Methods We tested V8 on the previously used rapid‐response EEG test dataset (not used to train V8). Sensitivity, specificity, PPV, and NPV were compared against blinded expert annotations. ESE, ESE and possible ESE (ESE/pESE), electrographic seizures (ESz), and Esz with highly epileptiform patterns (Esz/HEPs) at burden thresholds of >1%, >10%, >20%, >50%, and >90% were analyzed. Additionally, we evaluated the built‐in ESE and ESE/pESE alerts (≥90% over 5 min, ≥20% over 1 h, or ≥10 continuous minutes of seizure). Results V8 showed 100% sensitivity at lower thresholds (>10%–20%) for ESE (V6 .86), without a specificity loss (V8 .9 vs. V6 .85), and retained NPV (V8 1.0 vs. V6 .99). Sensitivity at 50% threshold was .86 for ESE (V6 .71), and specificity was .94 (V6 .91); PPV for ESE was 30% for ESE and 80% for ESE/pESE. The specificity for ESE remained high for 90% burden (V8 .96, V6 .97) but the sensitivity dropped (.29 vs. V6 .43). Sensitivity was lower for ESz/HEPs (.54 → .44 at >10% threshold), although the algorithm is not designed to detect HEPs. Built‐in alert analysis showed significantly improved sensitivity for ESE (.57 → .86); specificity and NPV remained high (>.94). Significance ASBE V8 showed meaningful improvements in sensitivity, continued excellent NPV, and improved built‐in alert accuracy for ESE and ESE/pESE. The best seizure burden threshold for ruling out ESE now is 20% (vs. 10% with V6) and that for ruling in ESE/pESE with reasonable certainty is 50% (vs. 90% with V6).