ArticleAnnals of neurology2025
Visual Features in Stereo-Electroencephalography to Predict Surgical Outcome: A Multicenter Study.
Article in Annals of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Complementary predictive value of electromagnetic source imaging and hemodynamic responses in epilepsy surgery: A quantitative spatial analysis.Epilepsia · 2026Article
- Clinical application of artificial intelligence technology in epilepsy.Acta epileptologica · 2026Review
- The use of quantitative electroencephalography in evaluating epilepsy treatment.Acta epileptologica · 2026Review
- Thalamic interictal epileptic and non-epileptic events during NREM sleep in patients with focal epilepsy: a Stereo-EEG study.EBioMedicine · 2026Article
- Inroads into epilepsy through high-frequency oscillations: Achievements and benchmark areas for improvement.Epilepsia · 2026Review
- Sleep enhances gamma oscillations in the seizure onset zone and broadband activity in the irritative zone of focal cortical dysplasia.Epilepsia open · 2026Article
- Opposing interictal dynamics in Alzheimer's disease and epilepsy.Progress in neurobiology · 2026Article
- Drug-resistant frontal lobe epilepsy: A review.SAGE open medicine · 2025Review
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Authors and funding
21 authors.
Funding
Abstract
objectiveEpilepsy surgery needs predictive features that are easily implemented in clinical practice. Previous studies are limited by small sample sizes, lack of external validation, and complex computational approaches. We aimed to identify and validate visually stereo-electroencephalography (SEEG) features with the highest predictive value for surgical outcome, and assess the reliability of their visual extraction.
methodsWe included 177 patients with drug-resistant epilepsy who underwent SEEG-guided surgery at 4 epilepsy centers. We assessed the predictive performance of 10 SEEG features from various SEEG periods for surgical outcome, using the area under the receiver operating characteristic curve, and considering resected channels and surgical outcome as the gold standard. Findings were validated externally using balanced accuracy. Six experts, blinded to outcome, evaluated the visual reliability of the optimal feature using interrater reliability, percentage agreement (standard deviation ± SD) and Gwet's kappa (κ ± SD).
resultsThe derivation cohort comprised 100 consecutive patients, each with at least 1-year of postoperative follow up (40% temporal lobe epilepsy; 42% Engel Ia). Spatial co-occurrence of gamma spikes and preictal spikes emerged as the optimal predictive feature of surgical outcome (area under the receiver operating characteristic curve 0.82). Applying the optimized threshold from the derivation cohort, external validation in 2 datasets showed similar performances (balanced accuracy 69.2% and 73.2%). Expert interrater reliability for gamma spikes (percentage agreement, 96% ± 2%; κ, 0.63 ± 0.16) and preictal spikes (percentage agreement, 92% ± 2%; κ, 0.65 ± 0.18) were substantial.
interpretationSpatial co-occurrence of gamma spikes and preictal spikes predicts surgical outcome. These visually identifiable features may reduce the burden of SEEG analysis by reducing analysis time, and improve outcome by guiding surgical resection margins. ANN NEUROL 2025;98:547-560.
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