Blinded study: prospectively defined high-frequency oscillations predict seizure outcome in individual patients. Issue 3 (2nd September 2021)

• Record Type: Journal Article
• Authors: Dimakopoulos, Vasileios; Mégevand, Pierre; Boran, Ece; Momjian, Shahan; Seeck, Margitta; Vulliémoz, Serge; Sarnthein, Johannes
• Is Part Of: Brain communications. Volume 3:Issue 3(2021)
• Publication Date: 2021-09-02
• Subjects: ripples -- fast ripples -- automated detection -- epilepsy surgery -- intracranial EEG; 616
• DOI: 10.1093/braincomms/fcab209
• Languages: English
• ISSNs: 2632-1297

Abstract

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. Abstract : Dimakopoulos et al. applied a fully automated high-frequency oscillations detection algorithm on pre-surgical intracranial EEG recordings from patients that underwent resective epilepsy surgery. The analysis was blind to clinical outcome and achieved good 'prediction' of seizure outcome. The high-frequency oscillations reproducibility indicates the value of a future multicenter study to test clinical application. Graphical Abstract: