ArticleBrain communications2022
Protocol for multicentre comparison of interictal high-frequency oscillations as a predictor of seizure freedom.
Article in Brain communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05332990 (Multicenter Comparison of Interictal High Frequency Oscillations as a Predictor of Seizure Freedom), which is not on this map. Cited by 12 papers.
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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.
The trial behind it
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.
Multicenter Comparison of Interictal High Frequency Oscillations as a Predictor of Seizure Freedom
Who cites it
12 citing papers in PubMed.
- Common Data Elements for Preclinical High-Frequency Oscillations in Epilepsy.Epilepsy currents · 2026Review
- Predicting surgical outcome in drug-resistant epilepsy by combining interictal biomarkers within a machine learning framework.Scientific reports · 2026Article
- Predicting Surgical Outcome in Drug-Resistant Epilepsy by Combining Interictal Biomarkers within a Machine Learning Framework.Research square · 2026Article
- Multicentre analysis of seizure outcome predicted by removal of high-frequency oscillations.Brain : a journal of neurology · 2025Observational
- Machine learning on interictal intracranial EEG predicts surgical outcome in drug resistant epilepsy.NPJ digital medicine · 2025Article
- Deep learning in intracranial EEG for seizure detection: advances, challenges, and clinical applications.Frontiers in neuroscience · 2025Review
- Spikes on ripples are better interictal biomarkers of epilepsy than spikes or ripples.Brain communications · 2025Article
- Robust compression and detection of epileptiform patterns in ECoG using a real-time spiking neural network hardware framework.Nature communications · 2024Article
- High frequency oscillations in relation to interictal spikes in predicting postsurgical seizure freedom.Scientific reports · 2023Article
- Passive and active markers of cortical excitability in epilepsy.Epilepsia · 2023Review
- Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy.Brain : a journal of neurology · 2023Article
- Automatic Detection of High-Frequency Oscillations With Neuromorphic Spiking Neural Networks.Frontiers in neuroscience · 2022Review
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
In drug-resistant focal epilepsy, interictal high-frequency oscillations (HFOs) recorded from intracranial EEG (iEEG) may provide clinical information for delineating epileptogenic brain tissue. The iEEG electrode contacts that contain HFO are hypothesized to delineate the epileptogenic zone; their resection should then lead to postsurgical seizure freedom. We test whether our prospective definition of clinically relevant HFO is in agreement with postsurgical seizure outcome. The algorithm is fully automated and is equally applied to all data sets. The aim is to assess the reliability of the proposed detector and analysis approach. We use an automated data-independent prospective definition of clinically relevant HFO that has been validated in data from two independent epilepsy centres. In this study, we combine retrospectively collected data sets from nine independent epilepsy centres. The analysis is blinded to clinical outcome. We use iEEG recordings during NREM sleep with a minimum of 12 epochs of 5 min of NREM sleep. We automatically detect HFO in the ripple (80-250 Hz) and in the fast ripple (250-500 Hz) band. There is no manual rejection of events in this fully automated algorithm. The type of HFO that we consider clinically relevant is defined as the simultaneous occurrence of a fast ripple and a ripple. We calculate the temporal consistency of each patient's HFO rates over several data epochs within and between nights. Patients with temporal consistency <50% are excluded from further analysis. We determine whether all electrode contacts with high HFO rate are included in the resection volume and whether seizure freedom (ILAE 1) was achieved at ≥2 years follow-up. Applying a previously validated algorithm to a large cohort from several independent epilepsy centres may advance the clinical relevance and the generalizability of HFO analysis as essential next step for use of HFO in clinical practice.
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