ArticleBrain : a journal of neurology2019
Virtual resection predicts surgical outcome for drug-resistant epilepsy.
Article in Brain : a journal of neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 71 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
71 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Multimodal machine learning for surgical decision support in epilepsy: Current evidence and translational gaps.Epilepsia · 2026Pooled it
- Language Dysfunction Associated with Pathological Brain Connectivity in Children with Epilepsy.bioRxiv : the preprint server for biology · 2026Article
- The Influence of Recording Duration and Vigilance State on High-Frequency Oscillation Characterization in Epilepsy.Neurology · 2026Article
- The seizure embedding map: a spatio-temporal transformer for comparing patients by ictal intracranial EEG features at scale.Journal of neural engineering · 2026Article
- Artificial intelligence as a surrogate brain: bridging neural dynamical models and data.National science review · 2026Review
- The neurotoxic legacy of CAR-T cells: where do we stand?Therapeutic advances in neurological disorders · 2026Review
- Self-supervised data-driven approach defines pathological high-frequency oscillations in epilepsy.Epilepsia · 2025Article
- The Seizure Embedding Map: A Spatio-Temporal Transformer for Comparing Patients by Ictal Intracranial EEG Features at Scale.medRxiv : the preprint server for health sciences · 2025Article
- Dynamic Interplay Between Wake Slow Waves and Epileptiform Discharges in the Epileptogenic Zone.Neurology · 2025Article
- AI-based localization of the epileptogenic zone using intracranial EEG.Epilepsia open · 2025Review
- Multimodal quantitative analysis guides precise preoperative localization of epilepsy.Journal of neurology · 2025Review
- Geometric representations of brain networks can predict the surgery outcome in temporal lobe epilepsy.NPJ systems biology and applications · 2025Article
- Predicting seizure onset zones from interictal intracranial EEG using functional connectivity and machine learning.Scientific reports · 2025Article
- (+)-Borneol Enhances the Antiseizure Effects of Retigabine by both Pharmacokinetic and Pharmacodynamic Interaction.Neurochemical research · 2025Article
- Directionality of neural activity in and out of the seizure onset zone in focal epilepsy.Network neuroscience (Cambridge, Mass.) · 2025Article
- Cenobamate for Difficult-to-Treat Epilepsy - Selected Case Vignettes.Neuropsychiatric disease and treatment · 2025Article
- Localization of the epileptogenic network from scalp EEG using a patient-specific whole-brain model.Network neuroscience (Cambridge, Mass.) · 2025Article
- Co-activation of interictal epileptiform discharges localizes seizure onset zone and fluctuates with brain state.Brain communications · 2025Article
- Virtual resection evaluation based on sEEG propagation network for drug-resistant epilepsy.Scientific reports · 2024Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
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- Erratum issued
Authors and funding
18 authors.
Funding
Abstract
Patients with drug-resistant epilepsy often require surgery to become seizure-free. While laser ablation and implantable stimulation devices have lowered the morbidity of these procedures, seizure-free rates have not dramatically improved, particularly for patients without focal lesions. This is in part because it is often unclear where to intervene in these cases. To address this clinical need, several research groups have published methods to map epileptic networks but applying them to improve patient care remains a challenge. In this study we advance clinical translation of these methods by: (i) presenting and sharing a robust pipeline to rigorously quantify the boundaries of the resection zone and determining which intracranial EEG electrodes lie within it; (ii) validating a brain network model on a retrospective cohort of 28 patients with drug-resistant epilepsy implanted with intracranial electrodes prior to surgical resection; and (iii) sharing all neuroimaging, annotated electrophysiology, and clinical metadata to facilitate future collaboration. Our network methods accurately forecast whether patients are likely to benefit from surgical intervention based on synchronizability of intracranial EEG (area under the receiver operating characteristic curve of 0.89) and provide novel information that traditional electrographic features do not. We further report that removing synchronizing brain regions is associated with improved clinical outcome, and postulate that sparing desynchronizing regions may further be beneficial. Our findings suggest that data-driven network-based methods can identify patients likely to benefit from resective or ablative therapy, and perhaps prevent invasive interventions in those unlikely to do so.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.