Intraoperative electrocorticography using high-frequency oscillations or spikes to tailor epilepsy surgery in the Netherlands (the HFO trial): a randomised, single-blind, adaptive non-inferiority trial

Background Intraoperative electrocorticography is used to tailor epilepsy surgery by analysing interictal spikes or spike patterns that can delineate epileptogenic tissue. High-frequency oscillations (HFOs) on intraoperative electrocorticography have been proposed as a new biomarker of epileptogenic tissue, with higher specificity than spikes. We prospectively tested the non-inferiority of HFO-guided tailoring of epilepsy surgery to spike-guided tailoring on seizure freedom at 1 year.Methods The HFO trial was a randomised, single-blind, adaptive non-inferiority trial at an epilepsy surgery centre (UMC Utrecht) in the Netherlands. We recruited children and adults (no age limits) who had been referred for intraoperative electrocorticography-tailored epilepsy surgery. Participants were randomly allocated (1:1) to either HFO-guided or spike-guided tailoring, using an online randomisation scheme with permuted blocks generated by an independent data manager, stratified by epilepsy type. Treatment allocation was masked to participants and clinicians who documented seizure outcome, but not to the study team or neurosurgeon. Ictiform spike patterns were always considered in surgical decision making. The primary endpoint was seizure outcome after 1 year (dichotomised as seizure freedom [defined as Engel 1A-11 vs seizure recurrence [Engel 1C-4]). We predefined a non-inferiority margin of 10% risk difference. Analysis was by intention to treat, with prespecified subgroup analyses by epilepsy type and for confounders. This completed trial is registered with the Dutch Trial Register, Toetsingonline ABR.NL44527.041.13, and ClinicalTrials.gov, NCT02207673.Findings Between Oct 10, 2014, and Jan 31,2020,78 individuals were enrolled to the study and randomly assigned (39 to HFO-guided tailoring and 39 to spike-guided tailoring). There was no loss to follow-up. Seizure freedom at 1 year occurred in 26 (67%) of 39 participants in the HFO-guided group and 35 (90%) of 39 in the spike-guided group (risk difference -23.5%, 90% CI -39.1 to -7.9; for the 48 patients with temporal lobe epilepsy, the risk difference was -25.5%, -45.1 to -6.0, and for the 30 patients with extratemporal lobe epilepsy it was -20.3%, -46.0 to 5.4). Pathology associated with poor prognosis was identified as a confounding factor, with an adjusted risk difference of-7.9% (90% CI -20.7 to 4.9; adjusted risk difference -12.5%, -31.0 to 5.9, for temporal lobe epilepsy and 5.8%, -7.7 to 19.5, for extratemporal lobe epilepsy). We recorded eight serious adverse events (five in the HFO-guided group and three in the spike-guided group) requiring hospitalisation. No patients died.Interpretation HFO-guided tailoring of epilepsy surgery was not non-inferior to spike-guided tailoring on intraoperative electrocorticography. After adjustment for confounders, HFOs show non-inferiority in extratemporal lobe epilepsy. This trial challenges the clinical value of HFOs as an epilepsy biomarker, especially in temporal lobe epilepsy. Further research is needed to establish whether HFO-guided intraoperative electrocorticography holds promise in extratemporal lobe epilepsy. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd

High Frequency Oscillations in Epilepsy: Towards Clinical Application

In patients with a focal source of epileptic seizures, epilepsy surgery can be a treatment option. The location of the epileptogenic brain region is determined by various non-invasive imaging and neurophysiological recordings, including electroencephalgorphy (EEG) and magnetoencephalography (MEG). In some patients invasive EEG is used to pinpoint the focus even more precisely. These recordings are traditionally searched for so-called spikes, whose location is an indicator for the epileptogenic zone. High frequency oscillations (HFOs), divided into ripples (80 – 250 Hz) and fast ripples (250 – 500 Hz), might be a better marker for the epileptogenic zone than spikes. Retrospective research shows that their location is related to the seizure onset zone, and that removal of brain areas that generate HFOs is related to increased chance of seizure freedom. The aim of this thesis was to move forward to clinical application of HFOs, by improving detection and identification of HFOs in both invasive and non-invasive recordings, by determining the value of HFO analysis for identification of the epileptogenic zone and by exploring the clinical opportunities of HFOs in non-invasive recordings in non-surgical patients with (suspected) epilepsy. We automatically detected ripples and fast ripples in intra-operative electrocorticography (ECoG) before and after surgical resection of the epileptogenic focus and showed that the amount of spikes, ripples and fast ripples all decrease after the resection, irrespective of the outcome. The presence of fast ripples after the resection predicted seizure recurrence, especially when they were present already before the resection. We showed that ripples preceded spikes in non-invasive EEG, indicating that they are different phenomena, promoted by certain brain states. In children with Rolandic spikes in EEG, who are not eligible for surgery, the presence of several ripples was related to the number of seizures a child experienced. We identified ripples in MEG similar to EEG by the use of beamformer virtual sensors. By using an automatic detection algorithm ripples were detected in 64% of the patients, usually in the location of the expected epileptogenic zone. We used the same beamformer virtual sensors to increase the yield of ripples in EEG. Ripples related to the epileptogenic zone in EEG were also found in patients without spikes, and simultaneously recorded MEG and EEG showed they are complimentary techniques, with only 24% of the ripples occurring simultaneously in both techniques. Our findings show that the use of HFO analysis has benefits in epilepsy surgery, although caution is advised with respect to physiological HFOs. Repeated recording of intra-operative ECoG can identify patients who are at risk of seizure recurrence. Analysis of ripples in EEG and MEG during presurgical workup can confirm a suspected epileptogenic region, and might be used to evaluate seizure activity. Further proof of the added value of HFO analysis above spike analysis will encourage more people the perf

High Frequency Oscillations in Epilepsy: Towards Clinical Application

In patients with a focal source of epileptic seizures, epilepsy surgery can be a treatment option. The location of the epileptogenic brain region is determined by various non-invasive imaging and neurophysiological recordings, including electroencephalgorphy (EEG) and magnetoencephalography (MEG). In some patients invasive EEG is used to pinpoint the focus even more precisely. These recordings are traditionally searched for so-called spikes, whose location is an indicator for the epileptogenic zone. High frequency oscillations (HFOs), divided into ripples (80 – 250 Hz) and fast ripples (250 – 500 Hz), might be a better marker for the epileptogenic zone than spikes. Retrospective research shows that their location is related to the seizure onset zone, and that removal of brain areas that generate HFOs is related to increased chance of seizure freedom. The aim of this thesis was to move forward to clinical application of HFOs, by improving detection and identification of HFOs in both invasive and non-invasive recordings, by determining the value of HFO analysis for identification of the epileptogenic zone and by exploring the clinical opportunities of HFOs in non-invasive recordings in non-surgical patients with (suspected) epilepsy. We automatically detected ripples and fast ripples in intra-operative electrocorticography (ECoG) before and after surgical resection of the epileptogenic focus and showed that the amount of spikes, ripples and fast ripples all decrease after the resection, irrespective of the outcome. The presence of fast ripples after the resection predicted seizure recurrence, especially when they were present already before the resection. We showed that ripples preceded spikes in non-invasive EEG, indicating that they are different phenomena, promoted by certain brain states. In children with Rolandic spikes in EEG, who are not eligible for surgery, the presence of several ripples was related to the number of seizures a child experienced. We identified ripples in MEG similar to EEG by the use of beamformer virtual sensors. By using an automatic detection algorithm ripples were detected in 64% of the patients, usually in the location of the expected epileptogenic zone. We used the same beamformer virtual sensors to increase the yield of ripples in EEG. Ripples related to the epileptogenic zone in EEG were also found in patients without spikes, and simultaneously recorded MEG and EEG showed they are complimentary techniques, with only 24% of the ripples occurring simultaneously in both techniques. Our findings show that the use of HFO analysis has benefits in epilepsy surgery, although caution is advised with respect to physiological HFOs. Repeated recording of intra-operative ECoG can identify patients who are at risk of seizure recurrence. Analysis of ripples in EEG and MEG during presurgical workup can confirm a suspected epileptogenic region, and might be used to evaluate seizure activity. Further proof of the added value of HFO analysis above spike analysis will encourage more people the perf

High frequency oscillations in intra-operative electrocorticography before and after epilepsy surgery

Objective Removal of brain tissue showing high frequency oscillations (HFOs; ripples: 80–250 Hz and fast ripples: 250–500 Hz) in preresection electrocorticography (preECoG) in epilepsy patients seems a predictor of good surgical outcome. We analyzed occurrence and localization of HFOs in intra-operative preECoG and postresection electrocorticography (postECoG). Methods HFOs were automatically detected in one-minute epochs of intra-operative ECoG sampled at 2048 Hz of fourteen patients. Ripple, fast ripple, spike, ripples on a spike (RoS) and not on a spike (RnoS) rates were analyzed in pre- and postECoG for resected and nonresected electrodes. Results Ripple, spike and fast ripple rates decreased after resection. RnoS decreased less than RoS (74% vs. 83%; p = 0.01). Most fast ripples in preECoG were located in resected tissue. PostECoG fast ripples occurred in one patient with poor outcome. Patients with good outcome had relatively high postECoG RnoS rates, specifically in the sensorimotor cortex. Conclusions Our observations show that fast ripples in intra-operative ECoG, compared to ripples, may be a better biomarker for epileptogenicity. Further studies have to determine the relation between resection of epileptogenic tissue and physiological ripples generated by the sensorimotor cortex. Significance Fast ripples in intra-operative ECoG can help identify the epileptogenic zone, while ripples might also be physiological

High frequency oscillations and high frequency functional network characteristics in the intraoperative electrocorticogram in epilepsy

Objective: High frequency oscillations (HFOs; >80 Hz), especially fast ripples (FRs, 250–500 Hz), are novel biomarkers for epileptogenic tissue. The pathophysiology suggests enhanced functional connectivity within FR generating tissue. Our aim was to determine the relation between brain areas showing FRs and ‘baseline’ functional connectivity within EEG networks, especially in the high frequency bands. Methods: We marked FRs, ripples (80–250 Hz) and spikes in the electrocorticogram of 14 patients with refractory temporal lobe epilepsy. We assessed ‘baseline’ functional connectivity in epochs free of epileptiform events within these recordings, using the phase lag index. We computed the Eigenvector Centrality (EC) per channel in the FR and gamma band network. We compared EC between channels that did or did not show events at other moments in time. Results: FR-band EC was higher in channels with than without spikes. Gamma-band EC was lower in channels with ripples and FRs. Conclusions: We confirmed previous findings of functional isolation in the gamma-band and found a first proof of functional integration in the FR-band network of channels covering presumed epileptogenic tissue. Significance: ‘Baseline’ high-frequency network parameters might help intra-operative recognition of epileptogenic tissue without the need for waiting for events. These findings can increase our understanding of the ‘architecture’ of epileptogenic networks and help unravel the pathophysiology of HFOs