Pitfalls in Scalp High-Frequency Oscillation Detection From Long-Term EEG Monitoring

Gerner, Nathalie; Thomschewski, Aljoscha; Marcu, Adrian V.; Trinka, Eugen; Höller, Yvonne

doi:10.3389/fneur.2020.00432

Cited by 13 publications

(16 citation statements)

References 90 publications

(110 reference statements)

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“…First of all, there are physiological HFOs ( 21 ) and spurious artifacts ( 13 , 22 ) that could mimic the presence of pathological HFOs and share the same frequency range ( 23 , 24 ), which complicates the distinction of clinically relevant HFOs from artifactual or normal ones ( 25 ). When defined only by the occurrence rate, physiological HFOs cannot be disentangled from the pathological ones, which might reduce the specificity of HFOs to epileptic areas ( 26 , 27 ) or even result in conflicting findings ( 28 , 29 ). Recent studies have shown significant spatiotemporal overlap between HFOs and interictal epileptiform spikes ( 20 ), with a higher association to the epileptogenic regions compared to spikes or HFOs alone, promising an improved biomarker to epileptogenicity ( 12 , 30 , 31 ).…”

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confidence: 99%

Noninvasive high-frequency oscillations riding spikes delineates epileptogenic sources

Cai

Sohrabpour

Jiang

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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High-frequency oscillations (HFOs) are a promising biomarker for localizing epileptogenic brain and guiding successful neurosurgery. However, the utility and translation of noninvasive HFOs, although highly desirable, is impeded by the difficulty in differentiating pathological HFOs from nonepileptiform high-frequency activities and localizing the epileptic tissue using noninvasive scalp recordings, which are typically contaminated with high noise levels. Here, we show that the consistent concurrence of HFOs with epileptiform spikes (pHFOs) provides a tractable means to identify pathological HFOs automatically, and this in turn demarks an epileptiform spike subgroup with higher epileptic relevance than the other spikes in a cohort of 25 temporal epilepsy patients (including a total of 2,967 interictal spikes and 1,477 HFO events). We found significant morphological distinctions of HFOs and spikes in the presence/absence of this concurrent status. We also demonstrated that the proposed pHFO source imaging enhanced localization of epileptogenic tissue by 162% (∼5.36 mm) for concordance with surgical resection and by 186% (∼12.48 mm) with seizure-onset zone determined by invasive studies, compared to conventional spike imaging, and demonstrated superior congruence with the surgical outcomes. Strikingly, the performance of spike imaging was selectively boosted by the presence of spikes with pHFOs, especially in patients with multitype spikes. Our findings suggest that concurrent HFOs and spikes reciprocally discriminate pathological activities, providing a translational tool for noninvasive presurgical diagnosis and postsurgical evaluation in vulnerable patients.

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confidence: 99%

Noninvasive high-frequency oscillations riding spikes delineates epileptogenic sources

Cai

Sohrabpour

Jiang

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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“…Despite all these limitations, we hope to add the numerical differentiation of EEG as another way to review EEGs that include spike-associated ripples and other types of high frequencies. Because there are pitfalls of bias in the detection of scalp HFOs ( Gerner et al, 2020 ), we would like to refine the EEG differentiation method to develop a methodology to avoid such pitfalls and to make scalp HFOs a truly useful biomarker in the future.…”

Section: Discussionmentioning

confidence: 99%

Exclusion of the Possibility of “False Ripples” From Ripple Band High-Frequency Oscillations Recorded From Scalp Electroencephalogram in Children With Epilepsy

Kobayashi

Shibata

Tsuchiya

et al. 2021

Front. Hum. Neurosci.

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AimRipple-band epileptic high-frequency oscillations (HFOs) can be recorded by scalp electroencephalography (EEG), and tend to be associated with epileptic spikes. However, there is a concern that the filtration of steep waveforms such as spikes may cause spurious oscillations or “false ripples.” We excluded such possibility from at least some ripples by EEG differentiation, which, in theory, enhances high-frequency signals and does not generate spurious oscillations or ringing.MethodsThe subjects were 50 pediatric patients, and ten consecutive spikes during sleep were selected for each patient. Five hundred spike data segments were initially reviewed by two experienced electroencephalographers using consensus to identify the presence or absence of ripples in the ordinary filtered EEG and an associated spectral blob in time-frequency analysis (Session A). These EEG data were subjected to numerical differentiation (the second derivative was denoted as EEG″). The EEG″ trace of each spike data segment was shown to two other electroencephalographers who judged independently whether there were clear ripple oscillations or uncertain ripple oscillations or an absence of oscillations (Session B).ResultsIn Session A, ripples were identified in 57 spike data segments (Group A-R), but not in the other 443 data segments (Group A-N). In Session B, both reviewers identified clear ripples (strict criterion) in 11 spike data segments, all of which were in Group A-R (p < 0.0001 by Fisher’s exact test). When the extended criterion that included clear and/or uncertain ripples was used in Session B, both reviewers identified 25 spike data segments that fulfilled the criterion: 24 of these were in Group A-R (p < 0.0001).DiscussionWe have demonstrated that real ripples over scalp spikes exist in a certain proportion of patients. Ripples that were visualized consistently using both ordinary filters and the EEG″ method should be true, but failure to clarify ripples using the EEG″ method does not mean that true ripples are absent.ConclusionThe numerical differentiation of EEG data provides convincing evidence that HFOs were detected in terms of the presence of such unusually fast oscillations over the scalp and the importance of this electrophysiological phenomenon.

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“…Each of the trials lasted for 30 seconds and was separated by a short intertrial break of equal duration. The task used was the same as described by Gerner et al (29). Participants were instructed to repeatedly type a five-digit sequence presented on the screen as fast and accurate as possible with their non-dominant hand.…”

Section: Methodsmentioning

confidence: 99%

“…It would be advantageous to be able to examine HFOs in scalp EEG, in order to make this biomarker available also to patient populations without the necessity for an invasive recording. Because of the small amplitude and local propagation characteristics of HFOs it was highly debated whether HFOs can be detected in scalp EEG (16,29). Scalp-EEG measures the summated activity of large populations of neocortical neurons and is much more prone to exogenous artifacts and noise.…”

Section: Introductionmentioning

confidence: 99%

Are High Frequency Oscillations in Scalp EEG Related to Age?

et al. 2022

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BackgroundHigh-frequency oscillations (HFOs) have received much attention in recent years, particularly in the clinical context. In addition to their application as a marker for pathological changes in patients with epilepsy, HFOs have also been brought into context with several physiological mechanisms. Furthermore, recent studies reported a relation between an increase of HFO rate and age in invasive EEG recordings. The present study aimed to investigate whether this relation can be replicated in scalp-EEG.MethodsWe recorded high-density EEG from 11 epilepsy patients at rest as well as during motor performance. Manual detection of HFOs was performed by two independent raters following a standardized protocol. Patients were grouped by age into younger (<25 years) and older (>50 years) participants.ResultsNo significant difference of HFO-rates was found between groups [U = 10.5, p = 0.429, r = 0.3].ConclusionsLack of replicability of the age effect of HFOs may be due to the local propagation patterns of age-related HFOs occurring in deep structures. However, limitations such as small sample size, decreased signal-to-noise ratio as compared to invasive recordings, as well as HFO-mimicking artifacts must be considered.

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Pitfalls in Scalp High-Frequency Oscillation Detection From Long-Term EEG Monitoring

Cited by 13 publications

References 90 publications

Noninvasive high-frequency oscillations riding spikes delineates epileptogenic sources

Noninvasive high-frequency oscillations riding spikes delineates epileptogenic sources

Exclusion of the Possibility of “False Ripples” From Ripple Band High-Frequency Oscillations Recorded From Scalp Electroencephalogram in Children With Epilepsy

Are High Frequency Oscillations in Scalp EEG Related to Age?

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