ArticleNeuroImage. Clinical2018
Predicting seizure outcome of vagus nerve stimulation using MEG-based network topology.
Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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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
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prognostic factors in vagus nerve stimulation for drug-resistant epilepsy. Results from a systematic review and meta-analysis of the literature.Neurosurgical review · 2026Pooled it
- Factors predicting the response to vagus nerve stimulation (VNS) in pediatric patients with drug- resistant epilepsy: a systematic review and meta-analysis.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2025Pooled it
- A Review of Vagus Nerve Stimulation for Disease: Comprehensive Theory and Evidence for Mechanisms of Action.Comprehensive physiology · 2026Review
- Preoperative MEG reveals differential brain network characteristics in drug-resistant epilepsy patients based on vagus nerve stimulation response.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Predicting response to neuromodulation therapies in drug-resistant epilepsy using machine learning models: a meta-analysis and systematic review.Bioelectronic medicine · 2025Review
- Vagus nerve stimulation for epilepsy: A narrative review of factors predictive of response.Epilepsia · 2024Review
- Genetic fingerprinting with heritable phenotypes of the resting-state brain network topology.Communications biology · 2024Article
- A predictive model combining connectomics and entropy biomarkers to discriminate long-term vagus nerve stimulation efficacy for pediatric patients with drug-resistant epilepsy.CNS neuroscience & therapeutics · 2024Article
- Research progress on the electrophysiological indicators to predict the efficacy of vagus nerve stimulation for drug-refractory epilepsy.Acta epileptologica · 2024Review
- Vagus Nerve Stimulation Therapy for Drug-Resistant Epilepsy in Children-A Literature Review.Journal of clinical medicine · 2024Review
- Article
- Brain functional connectivity-based prediction of vagus nerve stimulation efficacy in pediatric pharmacoresistant epilepsy.CNS neuroscience & therapeutics · 2023Article
- Entropy in scalp EEG can be used as a preimplantation marker for VNS efficacy.Scientific reports · 2023Article
- Brain-clinical signatures for vagus nerve stimulation response.CNS neuroscience & therapeutics · 2023Article
- Prediction of the Responsiveness to Vagus-Nerve Stimulation in Patients with Drug-Resistant Epilepsy via Directed-Transfer-Function Analysis of Their Perioperative Scalp EEGs.Journal of clinical medicine · 2022Article
- Individual-specific networks for prediction modelling - A scoping review of methods.BMC medical research methodology · 2022Article
- Reproducibility of graph measures derived from resting-state MEG functional connectivity metrics in sensor and source spaces.Human brain mapping · 2022Article
- [Key technologies for intelligent brain-computer interaction based on magnetoencephalography].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2022Article
- Prediction of Vagal Nerve Stimulation Efficacy in Drug-Resistant Epilepsy (PRECISE): Prospective Study for Pre-implantation Prediction/Study Design.Frontiers in neurology · 2022Article
- Electrophysiological Biomarkers in Genetic Epilepsies.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2021Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Vagus nerve stimulation (VNS) is a low-risk surgical option for patients with drug resistant epilepsy, although it is impossible to predict which patients may respond to VNS treatment. Resting-state magnetoencephalography (rs-MEG) connectivity analysis has been increasingly utilized to investigate the impact of epilepsy on brain networks and identify alteration of these networks after different treatments; however, there is no study to date utilizing this modality to predict the efficacy of VNS treatment. We investigated whether the rs-MEG network topology before VNS implantation can be used to predict efficacy of VNS treatment. Twenty-three patients with epilepsy who had MEG before VNS implantation were included in this study. We also included 89 healthy control subjects from the Human Connectome Project. Using the phase-locking value in the theta, alpha, and beta frequency bands as a measure of rs-MEG functional connectivity, we calculated three global graph measures: modularity, transitivity, and characteristic path length (CPL). Our results revealed that the rs-MEG graph measures were significantly heritable and had an overall good test-retest reliability, and thus these measures may be used as potential biomarkers of the network topology. We found that the modularity and transitivity in VNS responders were significantly larger and smaller, respectively, than those observed in VNS non-responders. We also observed that the modularity and transitivity in three frequency bands and CPL in delta and beta bands were significantly different in controls than those found in responders or non-responders, although the values of the graph measures in controls were closer to those of responders than non-responders. We used the modularity and transitivity as input features of a naïve Bayes classifier, and achieved an accuracy of 87% in classification of non-responders, responders, and controls. The results of this study revealed that MEG-based graph measures are reliable biomarkers, and that these measures may be used to predict seizure outcome of VNS treatment.
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