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

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.

Recent advances in clinical electroencephalography

“…This however is key when attempting to implement fully automatic HFO detection algorithms in commercial software solutions. One such endeavor is the ongoing HFO multicenter study that will recruit more than 200 datasets from nine centers with the aim to performing a blinded central analysis to evaluate the detector's performance [37 ▪ ].…”

Passive and active markers of cortical excitability in epilepsy

“…(2) Data collection and processing standards need to be developed for each biomarker. If interictal, intracranial data are used, we recommend analyzing multiday recordings to account for temporal variability 24,35,38,42 . Many laboratories choose segments of slow wave sleep for HFO analysis, 42–44 whereas others report HFO detection also at other states of vigilance 35,45 .…”

“…If interictal, intracranial data are used, we recommend analyzing multiday recordings to account for temporal variability 24,35,38,42 . Many laboratories choose segments of slow wave sleep for HFO analysis, 42–44 whereas others report HFO detection also at other states of vigilance 35,45 . The low amplitude and high frequency of HFOs compared to spikes make it challenging to distinguish HFOs from artifacts.…”

“…Here, it is not the morphology of the single HFO that defines its predictive power 46 but rather the consistent appearance of HFOs over time 24,38 or the association of an HFO with an interictal epileptic discharge 28,38 . (5) Sharing benchmark datasets 24 or multicenter studies 36,42 serve to validate HFO detectors. (6) Hardware with sufficiently high sampling rate and low noise level must become widely available.…”

Robust compression and detection of epileptiform patterns in ECoG using a real-time spiking neural network hardware framework

“…During surgery, intraoperative electrocorticography (ECoG) may serve to delineate the epileptogenic zone 2 . While interictal epileptiform discharges (IED) in the ECoG are traditionally used to guide surgical decisions, high-frequency oscillations (HFO, 80–500 Hz) have been identified as a new and more precise epileptiform pattern in the intraoperative ECoG; recording HFO may help to tailor epilepsy surgery and improve postoperative seizure outcome 3 – 5 . Co-occurring IED and HFO (IED-HFO) 6 , 7 and Fast Ripple HFO (250–500 Hz) 8 have been shown to indicate epileptogenic tissue with high specificity.…”