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Blinded study: prospectively defined high-frequency oscillations predict seizure outcome in individual patients.

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TLDR
In this article, an automated, prospective definition of clinically relevant high-frequency oscillations in intracranial EEG from Montreal and tested it in recordings from Zurich was developed and validated using an automated procedure to delineate the clinically relevant area in each individual patient of an independently recorded dataset.
Abstract
Interictal high-frequency oscillations are discussed as biomarkers for epileptogenic brain tissue that should be resected in epilepsy surgery to achieve seizure freedom. The prospective classification of tissue sampled by individual electrode contacts remains a challenge. We have developed an automated, prospective definition of clinically relevant high-frequency oscillations in intracranial EEG from Montreal and tested it in recordings from Zurich. We here validated the algorithm on intracranial EEG that was recorded in an independent epilepsy centre so that the analysis was blinded to seizure outcome. We selected consecutive patients who underwent resective epilepsy surgery in Geneva with post-surgical follow-up > 12 months. We analysed long-term recordings during sleep that we segmented into intervals of 5 min. High-frequency oscillations were defined in the ripple (80-250 Hz) and the fast ripple (250-500 Hz) frequency bands. Contacts with the highest rate of ripples co-occurring with fast ripples designated the relevant area. As a validity criterion, we calculated the test-retest reliability of the high-frequency oscillations area between the 5 min intervals (dwell time ≥50%). If the area was not fully resected and the patient suffered from recurrent seizures, this was classified as a true positive prediction. We included recordings from 16 patients (median age 32 years, range 18-53 years) with stereotactic depth electrodes and/or with subdural electrode grids (median follow-up 27 months, range 12-55 months). For each patient, we included several 5 min intervals (median 17 intervals). The relevant area had high test-retest reliability across intervals (median dwell time 95%). In two patients, the test-retest reliability was too low (dwell time < 50%) so that outcome prediction was not possible. The area was fully included in the resected volume in 2/4 patients who achieved post-operative seizure freedom (specificity 50%) and was not fully included in 9/10 patients with recurrent seizures (sensitivity 90%), leading to an accuracy of 79%. An additional exploratory analysis suggested that high-frequency oscillations were associated with interictal epileptic discharges only in channels within the relevant area and not associated in channels outside the area. We thereby validated the automated procedure to delineate the clinically relevant area in each individual patient of an independently recorded dataset and achieved the same good accuracy as in our previous studies. The reproducibility of our results across datasets is promising for a multicentre study to test the clinical application of high-frequency oscillations to guide epilepsy surgery.

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Journal ArticleDOI

A neuromorphic spiking neural network detects epileptic high frequency oscillations in the scalp EEG

TL;DR: In this paper , a custom spike neural network (SNN) was designed to detect events of interest (EoI) in the 80-250 Hz ripple band and reject artifacts in the 500-900 Hz band.
Journal ArticleDOI

Protocol for multicentre comparison of interictal high-frequency oscillations as a predictor of seizure freedom

TL;DR: In this paper , an automated data-independent prospective definition of clinically relevant interictal high-frequency oscillations (HFOs) was proposed and validated in data from two independent epilepsy centres.
Journal ArticleDOI

Implementation of a Morphological Filter for Removing Spikes from the Epileptic Brain Signals to Improve Identification Ripples

TL;DR: This paper develops a reliable technique for removing spikes and sharp transients from the baseline of the brain signal using a morphological filter, which allows much more precise identification of the so-called epileptic zone, which can then be resected, which is one of the methods of epilepsy treatment.
Journal ArticleDOI

Passive and active markers of cortical excitability in epilepsy.

TL;DR: A review of the EEG-based passive and active markers of cortical excitability in epilepsy and techniques developed to facilitate their identification can be found in this article , where several different emerging tools are discussed in the context of specific EEG applications and the barriers to translate these tools into clinical practice.
Journal ArticleDOI

Previous, current, and future stereotactic EEG techniques for localising epileptic foci

TL;DR: This review covers the history and current practices in the field of intracranial EEG, particularly analyzing how stereotactic image-guidance, robot-assisted navigation, and improved imaging techniques have increased the accuracy, scope, and use of SEEG globally.
References
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Journal ArticleDOI

Automatic detection of high frequency oscillations during epilepsy surgery predicts seizure outcome

TL;DR: The authors' automatic and fully unsupervised detection of HFO events matched the expert observer's performance in both event selection and outcome prediction.
Journal ArticleDOI

The morphology of high frequency oscillations (HFO) does not improve delineating the epileptogenic zone.

TL;DR: It is hypothesized that high frequency oscillations (HFOs) with irregular amplitude and frequency more specifically reflect epileptogenicity than HFOs with stable amplitude and Frequency, and surgical outcome is better when locations with higher HFO rates are included in the resection.
Journal ArticleDOI

Intracranial EEG in the 21st Century

TL;DR: Improved techniques to record and interpret iEEG may in the future lead to a greater proportion of patients being seizure free after epilepsy surgery, and advanced computational methods such as determining the epileptogenicity index and similar measures may enhance standard clinical interpretation.
Journal ArticleDOI

An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG.

TL;DR: In this article, the authors presented a neuromorphic system that combines a neural recording headstage with a spiking neural network (SNN) processing core on the same die for processing intracranial EEG (iEEG) from epilepsy patients for the detection of high frequency oscillations (HFO), which are a biomarker for epileptogenic brain tissue.
Journal ArticleDOI

Interictal high-frequency oscillations in focal human epilepsy.

TL;DR: There is strong evidence that HFOs are spatially associated with epileptic brain, and there remain, however, significant challenges for clinical translation of H FOs as epileptogenic brain biomarkers.
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