ArticleAnnals of neurology2020
Temporal Lobe Epilepsy Surgical Outcomes Can Be Inferred Based on Structural Connectome Hubs: A Machine Learning Study.
Article in Annals of neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 1 of them a synthesis that pooled it.
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Who cites it
66 citing papers in PubMed, 1 synthesis or guideline pooled it, 117 citations in OpenAlex.
- Artificial intelligence role in advancement of human brain connectome studies.Frontiers in neuroinformatics · 2024Pooled it
- Digital Twins as the Implementation Layer of Precision Medicine in Pediatric Neurosurgery.Journal of Korean Neurosurgical Society · 2026Review
- Learning From Our Failures: When Anterior Temporal Lobectomies Fail.Epilepsy currents · 2026Article
- Bitemporal Lobe Epilepsy: Evolving Diagnostic and Treatment Paradigms.Epilepsy currents · 2026Article
- Associations between epilepsy-related polygenic risk and brain morphology in childhood.Brain : a journal of neurology · 2026Article
- White matter signals reflect information transmission between brain regions during seizures.Brain : a journal of neurology · 2026Article
- Multimodal neuroimaging fusion in presurgical evaluation of drug-resistant epilepsy: current evidence, clinical integration, and future directions.Frontiers in neuroscience · 2026Review
- Multimodal artificial intelligence in epilepsy: antiseizure medication response, epileptogenic zone localization, and surgical outcome prediction.Frontiers in neurology · 2026Review
- Seminars in epileptology: Presurgical epilepsy evaluation.Epileptic disorders : international epilepsy journal with videotape · 2025Review
- Prediction of longitudinal outcomes and novel cluster identification in epilepsy.Scientific reports · 2025Article
- Prediction of personalized antiseizure medications response based on clinical signatures in epilepsy.Scientific reports · 2025Article
- The use of automated and AI-driven algorithms for the detection of hippocampal sclerosis and focal cortical dysplasia.Epilepsia · 2025Review
- Seizure freedom after surgical resection of diffusion-weighted magnetic resonance imaging abnormalities.Epilepsia · 2025Article
- Multimodal quantitative analysis guides precise preoperative localization of epilepsy.Journal of neurology · 2025Review
- Prospective neuroimaging and neuropsychological evaluation in adults with newly diagnosed focal epilepsy.Epilepsia · 2025Article
- Geometric representations of brain networks can predict the surgery outcome in temporal lobe epilepsy.NPJ systems biology and applications · 2025Article
- Redefining diagnostic lesional status in temporal lobe epilepsy with artificial intelligence.Brain : a journal of neurology · 2025Article
- Artificial Intelligence in Epilepsy: A Systemic Review.Journal of epilepsy research · 2025Review
- Connectomes in Temporal Lobe and Idiopathic Generalized Epilepsies.Journal of clinical medicine · 2025Review
- Change in Structural Connectivity Following Stereotactic Thermocoagulation in Mesial Temporal Lobe Epilepsy Patients.European journal of neurology · 2025Article
6 more citing papers are in PubMed but not listed here.
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Authors and funding
13 authors at 8 institutions in 3 countries.
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Abstract
objectiveMedial temporal lobe epilepsy (TLE) is the most common form of medication-resistant focal epilepsy in adults. Despite removal of medial temporal structures, more than one-third of patients continue to have disabling seizures postoperatively. Seizure refractoriness implies that extramedial regions are capable of influencing the brain network and generating seizures. We tested whether abnormalities of structural network integration could be associated with surgical outcomes.
methodsPresurgical magnetic resonance images from 121 patients with drug-resistant TLE across 3 independent epilepsy centers were used to train feed-forward neural network models based on tissue volume or graph-theory measures from whole-brain diffusion tensor imaging structural connectomes. An independent dataset of 47 patients with TLE from 3 other epilepsy centers was used to assess the predictive values of each model and regional anatomical contributions toward surgical treatment results.
resultsThe receiver operating characteristic area under the curve based on regional betweenness centrality was 0.88, significantly higher than a random model or models based on gray matter volumes, degree, strength, and clustering coefficient. Nodes most strongly contributing to the predictive models involved the bilateral parahippocampal gyri, as well as the superior temporal gyri.
interpretationNetwork integration in the medial and lateral temporal regions was related to surgical outcomes. Patients with abnormally integrated structural network nodes were less likely to achieve seizure freedom. These findings are in line with previous observations related to network abnormalities in TLE and expand on the notion of underlying aberrant plasticity. Our findings provide additional information on the mechanisms of surgical refractoriness. ANN NEUROL 2020;88:970-983.
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