ArticleEpilepsia2022
Correcting for physiological ripples improves epileptic focus identification and outcome prediction.
Article in Epilepsia, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- The use of quantitative electroencephalography in evaluating epilepsy treatment.Acta epileptologica · 2026Review
- Morphological Remodeling of Scalp High-Frequency Oscillations Across BASED-Stratified Groups in Infantile Epileptic Spasms Syndrome.Diagnostics (Basel, Switzerland) · 2026Article
- Epileptogenicity alters intrahippocampal ripple propagation.medRxiv : the preprint server for health sciences · 2026Article
- Inroads into epilepsy through high-frequency oscillations: Achievements and benchmark areas for improvement.Epilepsia · 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
- Self-supervised data-driven approach defines pathological high-frequency oscillations in epilepsy.Epilepsia · 2025Article
- No association between histopathology and neurophysiology in surgical specimens from pediatric focal epilepsy patients.Epilepsia · 2025Article
- The Role of Neuroinflammation and Network Anomalies in Drug-Resistant Epilepsy.Neuroscience bulletin · 2025Review
- Voxel-based and surface-based cortical morphometric MRI applications for identifying the epileptogenic zone: A narrative review.Epilepsia open · 2025Review
- Pseudo-HFOs Elimination in iEEG Recordings Using a Robust Residual-Based Dictionary Learning Framework.IEEE journal of biomedical and health informatics · 2025Article
- Source Causal Connectivity Noninvasively Predicting Surgical Outcomes of Drug-Refractory Epilepsy.CNS neuroscience & therapeutics · 2025Article
- Spikes on ripples are better interictal biomarkers of epilepsy than spikes or ripples.Brain communications · 2025Article
- Noninvasive classification of physiological and pathological high frequency oscillations in children.Brain communications · 2025Article
- Pathological and Physiological High-frequency Oscillations on Electroencephalography in Patients with Epilepsy.Neuroscience bulletin · 2024Review
- Developmental atlas of phase-amplitude coupling between physiologic high-frequency oscillations and slow waves.Nature communications · 2023Article
- Article
- Fast ripples reflect increased excitability that primes epileptiform spikes.Brain communications · 2023Article
- Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes.PloS one · 2023Article
- Characterizing physiological high-frequency oscillations using deep learning.Journal of neural engineering · 2022Article
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11 authors.
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Abstract
objectiveThe integration of high-frequency oscillations (HFOs; ripples [80-250 Hz], fast ripples [250-500 Hz]) in epilepsy evaluation is hampered by physiological HFOs, which cannot be reliably differentiated from pathological HFOs. We evaluated whether defining abnormal HFO rates by statistical comparison to region-specific physiological HFO rates observed in the healthy brain improves identification of the epileptic focus and surgical outcome prediction.
methodsWe detected HFOs in 151 consecutive patients who underwent stereo-electroencephalography and subsequent resective epilepsy surgery at two tertiary epilepsy centers. We compared how HFOs identified the resection cavity and predicted seizure-free outcome using two thresholds from the literature (HFO rate > 1/min; 50% of the total number of a patient's HFOs) and three thresholds based on normative rates from the Montreal Neurological Institute Open iEEG Atlas (https://mni-open-ieegatlas. RESEARCH: mcgill.ca/): global Atlas threshold, regional Atlas threshold, and regional + 10% threshold after regional Atlas correction.
resultsUsing ripples, the regional + 10% threshold performed best for focus identification (77.3% accuracy, 27% sensitivity, 97.1% specificity, 80.6% positive predictive value [PPV], 78.2% negative predictive value [NPV]) and outcome prediction (69.5% accuracy, 58.6% sensitivity, 76.3% specificity, 60.7% PPV, 74.7% NPV). This was an improvement for focus identification (+1.1% accuracy, +17.0% PPV; p < .001) and outcome prediction (+12.0% sensitivity, +1.0% PPV; p = .05) compared to the 50% threshold. The improvement was particularly marked for foci in cortex, where physiological ripples are frequent (outcome: +35.3% sensitivity, +5.3% PPV; p = .014). In these cases, the regional + 10% threshold outperformed fast ripple rate > 1/min (+3.6% accuracy, +26.5% sensitivity, +21.6% PPV; p < .001) and seizure onset zone (+13.5% accuracy, +29.4% sensitivity, +17.0% PPV; p < .05-.01) for outcome prediction. Normalization did not improve the performance of fast ripples. SIGNIFICANCE: Defining abnormal HFO rates by statistical comparison to rates in healthy tissue overcomes an important weakness in the clinical use of ripples. It improves focus identification and outcome prediction compared to standard HFO measures, increasing their clinical applicability.
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