How to record high‐frequency oscillations in epilepsy: A practical guideline

Zijlmans, Maeike; Worrell, Gregory A.; Dümpelmann, Matthias; Stieglitz, Thomas; Barborică, Andrei; Heers, Marcel; Ikeda, Akio; Usui, Naotaka; Quyen, Michel Le Van

doi:10.1111/epi.13814

Cited by 142 publications

(172 citation statements)

References 77 publications

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“…Visual analysis, however, entails serious obstacles making HFO assessment impossible for clinical routine; visual marking of HFOs is very time-consuming, requires expertise, and might be subjective if an interrater agreement is not sought. To overcome these drawbacks, various detectors were developed and validated over recent years (for more details, see Zijlmans et al 3 ). Automated and visual detection of HFOs yield comparable identification of the SOZ 93 ; a meta-analysis showed that removal of automatically detected HFOs and visually detected HFOs in presurgical data yield similar results with respect to good surgical outcome.…”

Section: Visual Versus Automatic Detection Of Hfosmentioning

confidence: 99%

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High‐frequency oscillations: The state of clinical research

et al. 2017

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Summary Modern electroencephalographic (EEG) technology contributed to the appreciation that the EEG signal outside the classical Berger frequency band contains important information. In epilepsy, research of the past decade focused particularly on interictal high-frequency oscillations (HFOs) > 80 Hz. The first large application of HFOs was in the context of epilepsy surgery. This is now followed by other applications such as assessment of epilepsy severity and monitoring of antiepileptic therapy. This article reviews the evidence on the clinical use of HFOs in epilepsy with an emphasis on the latest developments. It highlights the growing literature on the association between HFOs and post-surgical seizure outcome. A recent meta-analysis confirmed a higher resection ratio for HFOs in seizure-free versus non–seizure-free patients. Residual HFOs in the postoperative electrocorticogram were shown to predict epilepsy surgery outcome better than preoperative HFO rates. The review further discusses the different attempts to separate physiological from epileptic HFOs, as this might increase the specificity of HFOs. As an example, analysis of sleep microstructure demonstrated a different coupling between HFOs inside and outside the epileptogenic zone. Moreover, there is increasing evidence that HFOs are useful to measure disease activity and assess treatment response using noninvasive EEG and magnetoencephalography. This approach is particularly promising in children, because they show high scalp HFO rates. HFO rates in West syndrome decrease after adrenocorticotropic hormone treatment. Presence of HFOs at the time of rolandic spikes correlates with seizure frequency. The time-consuming visual assessment of HFOs, which prevented their clinical application in the past, is now overcome by validated computer-assisted algorithms. HFO research has considerably advanced over the past decade, and use of noninvasive methods will make HFOs accessible to large numbers of patients. Prospective multicenter trials are awaited to gather information over long recording periods in large patient samples.

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Section: Visual Versus Automatic Detection Of Hfosmentioning

confidence: 99%

“…1 HFOs are subdivided into ripples ranging from 80 to 250 Hz and fast ripples > 250 Hz. 2 For more details on the definition of HFOs, see the accompanying article in this issue by Zijlmans et al 3 on how to record HFOs. The first large application of HFOs was in the context of epilepsy surgery.…”

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confidence: 99%

High‐frequency oscillations: The state of clinical research

et al. 2017

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“…Moreover, on data from human epilepsy patients this detector not only showed the results on par or better compared to the results of others [2,18,19] but its performance on tEEG data was directly compared to performance on simultaneously recorded conventional EEG data once again confirming the advantage of TCREs over conventional disc electrodes [11]. Recording HFOs with scalp EEG is very difficult [20] but we recently showed on data from animal model [12] and human patients with epilepsy [1] that they can be recorded with tEEG.…”

Section: Discussionmentioning

confidence: 55%

“…The importance of this study stemmed from the fact that, unlike tEEG, EEG via conventional disc electrodes is limited in its ability to record HFOs from the scalp to ripples only [20].…”

Section: Animal Modelmentioning

confidence: 99%

Recent Advances in High-Frequency Oscillations and Seizure Onset Detection Using Laplacian Electroencephalography via Tripolar Concentric Ring Electrodes

Makeyev

Musngi

Lee

et al. 2017

The 4th International Electronic Conference on Sensors and Applications

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Laplacian electroencephalogram signal from novel and noninvasive tripolar concentric ring electrodes has been demonstrated to have superior performance compared to the electroencephalogram from conventional disc electrodes due to its unique capabilities which allow automatic attenuation of common movement and muscle artifacts in applications including braincomputer interface, seizure onset detection, and detection of high-frequency oscillations and seizure onset zones. This review paper covers the recent advances in the fields of high-frequency oscillations and seizure onset detection based on tripolar Laplacian electroencephalography in animal models and human data to improve the diagnostic yield of electroencephalography for epilepsy. Progression of methodologies utilized including integration of multiple sensors using exponentially embedded families and results obtained including a comparison to the results of others as well as to the performance of the same detector on simultaneously recorded electroencephalogram via conventional disc electrodes is discussed in detail. Specific advantages of using this particular sensor for these particular applications are highlighted. Promising directions for the future work and an overview of currently ongoing research are discussed along with the potential of combining the two detectors and using automatically detected high-frequency oscillations that have been shown to be indicative of early seizure development as auxiliary features for the seizure onset detection.

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“…This has led to the development of several automated HFOs detectors (Fig. 1) from different laboratories, tuned to particular datasets and HFOs definitions, recently reviewed by Zijlmans et al, [24]. …”

Section: Hfos Detectionmentioning

confidence: 99%

Progress and remaining challenges in the application of high frequency oscillations as biomarkers of epileptic brain

Khadjevand

Cimbálník

Worrell

2017

Current Opinion in Biomedical Engineering

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High-frequency oscillations (HFOs: 100 – 600 Hz) have been widely proposed as biomarkers of epileptic brain tissue. In addition, HFOs over a broader range of frequencies spanning 30 – 2000 Hz are potential biomarkers of both physiological and pathological brain processes. The majority of the results from humans with focal epilepsy have focused on HFOs recorded directly from the brain with intracranial EEG (iEEG) in the high gamma (65 – 100 Hz), ripple (100 – 250 Hz), and fast ripple (250 – 600 Hz) frequency ranges. These results are supplemented by reports of HFOs recorded with iEEG in the low gamma (30 – 65Hz) and very high frequency (500 – 2000 Hz) ranges. Visual detection of HFOs is laborious and limited by poor inter-rater agreement; and the need for accurate, reproducible automated HFOs detection is well recognized. In particular, the clinical translation of HFOs as a biomarker of the epileptogenic brain has been limited by the ability to reliably detect and accurately classify HFOs as physiological or pathological. Despite these challenges, there has been significant progress in the field, which is the subject of this review. Furthermore, we provide data and corresponding analytic code in an effort to promote reproducible research and accelerate clinical translation.

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How to record high‐frequency oscillations in epilepsy: A practical guideline

Abstract: High-frequency oscillations are promising new biomarkers in epilepsy. This review provides interested researchers and clinicians with a review of current state of the art of recording and identification and potential challenges to clinical translation.

Cited by 142 publications

References 77 publications

High‐frequency oscillations: The state of clinical research

High‐frequency oscillations: The state of clinical research

Recent Advances in High-Frequency Oscillations and Seizure Onset Detection Using Laplacian Electroencephalography via Tripolar Concentric Ring Electrodes

Progress and remaining challenges in the application of high frequency oscillations as biomarkers of epileptic brain

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