Scalp EEG high frequency oscillations as a biomarker of treatment response in epileptic encephalopathy with continuous spike-and-wave during sleep (CSWS)

Abstract Background: Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The demand for therapy monitoring in epilepsy has kindled interest in compact wearable electronic devices for long- term EEG recording. Spiking neural networks (SNN) have been shown to be optimal architectures for being embedded in compact low-power signal processing hardware. Methods: We analyzed 20 scalp EEG recordings from 11 patients with pediatric focal lesional epilepsy. We designed a custom SNN to detect events of interest (EoI) in the 80-250 Hz ripple band and reject artifacts in the 500-900 Hz band. Results: We identified the optimal SNN parameters to automatically detect EoI and reject artifacts. The occurrence of HFO thus detected was associated with active epilepsy with 80% accuracy. The HFO rate mirrored the decrease in seizure frequency in 8 patients (p = 0.0047). Overall, the HFO rate correlated with seizure frequency (rho = 0.83, p < 0.0001, Spearman’s correlation).Conclusions: The fully automated SNN detected clinically relevant HFO in the scalp EEG. This is a further step towards non-invasive epilepsy monitoring with a low-power wearable device.

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High-frequency oscillations in scalp EEG mirror seizure frequency in pediatric focal epilepsy

Scientific Reports ◽

10.1038/s41598-019-52700-w ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 4

Author(s):

Ece Boran ◽

Johannes Sarnthein ◽

Niklaus Krayenbühl ◽

Georgia Ramantani ◽

Tommaso Fedele

Keyword(s):

Seizure Frequency ◽

Epilepsy Surgery ◽

High Frequency ◽

Focal Epilepsy ◽

Low Noise ◽

Drug Resistant ◽

Scalp Eeg ◽

High Frequency Oscillations ◽

Custom Made ◽

Active Epilepsy

Abstract High-frequency oscillations (HFO) are promising EEG biomarkers of epileptogenicity. While the evidence supporting their significance derives mainly from invasive recordings, recent studies have extended these observations to HFO recorded in the widely accessible scalp EEG. Here, we investigated whether scalp HFO in drug-resistant focal epilepsy correspond to epilepsy severity and how they are affected by surgical therapy. In eleven children with drug-resistant focal epilepsy that underwent epilepsy surgery, we prospectively recorded pre- and postsurgical scalp EEG with a custom-made low-noise amplifier (LNA). In four of these children, we also recorded intraoperative electrocorticography (ECoG). To detect clinically relevant HFO, we applied a previously validated automated detector. Scalp HFO rates showed a significant positive correlation with seizure frequency (R2 = 0.80, p < 0.001). Overall, scalp HFO rates were higher in patients with active epilepsy (19 recordings, p = 0.0066, PPV = 86%, NPV = 80%, accuracy = 84% CI [62% 94%]) and decreased following successful epilepsy surgery. The location of the highest HFO rates in scalp EEG matched the location of the highest HFO rates in ECoG. This study is the first step towards using non-invasively recorded scalp HFO to monitor disease severity in patients affected by epilepsy.

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High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence

Computational Intelligence and Neuroscience ◽

10.1155/2018/1638097 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 6

Author(s):

Peter Höller ◽

Eugen Trinka ◽

Yvonne Höller

Keyword(s):

High Frequency ◽

Visual Detection ◽

Signal To Noise Ratio ◽

Physiological Activity ◽

Automated Detection ◽

Detection Algorithms ◽

Scalp Eeg ◽

High Frequency Oscillations ◽

Scalp Electroencephalogram ◽

Electroencephalogram Eeg

High-frequency oscillations (HFOs) in the electroencephalogram (EEG) are thought to be a promising marker for epileptogenicity. A number of automated detection algorithms have been developed for reliable analysis of invasively recorded HFOs. However, invasive recordings are not widely applicable since they bear risks and costs, and the harm of the surgical intervention of implantation needs to be weighted against the informational benefits of the invasive examination. In contrast, scalp EEG is widely available at low costs and does not bear any risks. However, the detection of HFOs on the scalp represents a challenge that was taken on so far mostly via visual detection. Visual detection of HFOs is, in turn, highly time-consuming and subjective. In this review, we discuss that automated detection algorithms for detection of HFOs on the scalp are highly warranted because the available algorithms were all developed for invasively recorded EEG and do not perform satisfactorily in scalp EEG because of the low signal-to-noise ratio and numerous artefacts as well as physiological activity that obscures the tiny phenomena in the high-frequency range.

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Scalp EEG is not a Blur: It Can See High Frequency Oscillations Although Their Generators are Small

Brain Topography ◽

10.1007/s10548-013-0321-y ◽

2013 ◽

Vol 27 (5) ◽

pp. 683-704 ◽

Cited By ~ 66

Author(s):

R. Zelmann ◽

J. M. Lina ◽

A. Schulze-Bonhage ◽

J. Gotman ◽

J. Jacobs

Keyword(s):

High Frequency ◽

Scalp Eeg ◽

High Frequency Oscillations

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33. High frequency oscillations on scalp EEG associated with periodic spasms related to malformations of cortical development

Clinical Neurophysiology ◽

10.1016/j.clinph.2012.02.034 ◽

2012 ◽

Vol 123 (9) ◽

pp. e94-e95

Author(s):

Ryoko Honda ◽

Hiroshi Otsubo ◽

Eiji Nakagawa ◽

Akio Takahashi ◽

Takanobu Kaido ◽

...

Keyword(s):

High Frequency ◽

Cortical Development ◽

Malformations Of Cortical Development ◽

Scalp Eeg ◽

High Frequency Oscillations ◽

Periodic Spasms

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Scalp high-frequency oscillation rates are higher in younger children

Brain Communications ◽

10.1093/braincomms/fcab052 ◽

2021 ◽

Vol 3 (2) ◽

Author(s):

Dorottya Cserpan ◽

Ece Boran ◽

Santo Pietro Lo Biundo ◽

Richard Rosch ◽

Johannes Sarnthein ◽

...

Keyword(s):

High Frequency ◽

Signal To Noise Ratio ◽

Paediatric Population ◽

High Frequency Oscillation ◽

Older Children ◽

Frequency Oscillation ◽

Scalp Eeg ◽

High Frequency Oscillations ◽

Median Test ◽

Generalized Epilepsy

Abstract High-frequency oscillations in scalp EEG are promising non-invasive biomarkers of epileptogenicity. However, it is unclear how high-frequency oscillations are impacted by age in the paediatric population. We prospectively recorded whole-night scalp EEG in 30 children and adolescents with focal or generalized epilepsy. We used an automated and clinically validated high-frequency oscillation detector to determine ripple rates (80–250 Hz) in bipolar channels. Children < 7 years had higher high-frequency oscillation rates (P = 0.021) when compared with older children. The median test−retest reliability of high-frequency oscillation rates reached 100% (iqr 50) for a data interval duration of 10 min. Scalp high-frequency oscillation frequency decreased with age (r = −0.558, P = 0.002), whereas scalp high-frequency oscillation duration and amplitude were unaffected. The signal-to-noise ratio improved with age (r = 0.37, P = 0.048), and the background ripple band activity decreased with age (r = −0.463, P = 0.011). We characterize the relationship of scalp high-frequency oscillation features and age in paediatric patients. EEG intervals of ≥10 min duration are required for reliable measurements of high-frequency oscillation rates. This study is a further step towards establishing scalp high-frequency oscillations as a valid epileptogenicity biomarker in this vulnerable age group.

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Towards automatic classification of pathological epileptic tissue with interictal high frequency oscillations

10.1101/2020.05.28.122416 ◽

2020 ◽

Author(s):

Michael D. Nunez ◽

Krit Charupanit ◽

Indranil Sen-Gupta ◽

Beth A. Lopour ◽

Jack J. Lin

Keyword(s):

High Frequency ◽

Negative Binomial ◽

Slow Wave Sleep ◽

Nrem Sleep ◽

Oscillatory Dynamics ◽

Scalp Eeg ◽

High Frequency Oscillations ◽

Binomial Mixture ◽

Brain States

AbstractHigh frequency oscillations (HFOs) recorded by intracranial electrodes have generated excitement for their potential to help localize epileptic tissue for surgical resection (Frauscher et al., 2017). However, previous research has shown that the number of HFOs per minute (i.e. the HFO “rate”) is not stable over the duration of intracranial recordings. The rate of HFOs increases during periods of slow-wave sleep (von Ellenrieder et al., 2017), and HFOs that are predictive of epileptic tissue may occur in oscillatory patterns (Motoi et al., 2018). We sought to further understand how between-seizure (i.e. “interictal”) HFO dynamics predict the seizure onset zone (SOZ). Using long-term intracranial EEG from 16 subjects, we fit Poisson and Negative Binomial mixture models that describe HFO dynamics and include the ability to switch between two discrete brain states. Oscillatory dynamics of HFO occurrences were found to be predictive of SOZ and were more consistently predictive than HFO rate. Using concurrent scalp-EEG in two patients, we show that the model-found brain states corresponded to (1) non-REM (NREM) sleep and (2) awake and rapid eye movement (REM) sleep. This work suggests that unsupervised approaches for classification of epileptic tissue without sleep-staging can be developed using mixture modeling of HFO dynamics.

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High-Frequency Oscillations on Interictal Epileptiform Discharges in Routinely Acquired Scalp EEG: Can It Be Used as a Prognostic Marker?

Frontiers in Human Neuroscience ◽

10.3389/fnhum.2021.709836 ◽

2021 ◽

Vol 15 ◽

Author(s):

Hanan El Shakankiry ◽

Susan T. Arnold

Keyword(s):

Prognostic Marker ◽

High Frequency ◽

Medical Center ◽

Time Base ◽

Unprovoked Seizure ◽

Scalp Eeg ◽

High Frequency Oscillations ◽

Epileptiform Discharges ◽

Significant Difference ◽

Scalp Electroencephalogram

IntroductionDespite all the efforts for optimizing epilepsy management in children over the past decades, there is no clear consensus regarding whether to treat or not to treat epileptiform discharges (EDs) after a first unprovoked seizure or the optimal duration of therapy with anti-seizure medication (ASM). It is therefore highly needed to find markers on scalp electroencephalogram (EEG) that can help identify pathological EEG discharges that require treatment.Aim of the studyThis retrospective study aimed to identify whether the coexistence of ripples/high-frequency oscillations (HFOs) with interictal EDs (IEDs) in routinely acquired scalp EEG is associated with a higher risk of seizure recurrence and could be used as a prognostic marker.Methods100 children presenting with new onset seizure to Children’s Medical Center- Dallas during 2015–2016, who were not on ASM and had focal EDs on an awake and sleep EEG recorded with sample frequency of 500 HZ, were randomly identified by database review. EEGs were analyzed blinded to the data of the patients. HFOs were visually identified using review parameters including expanded time base and adjusted filter settings.ResultsThe average age of patients was 6.3 years (±4.35 SD). HFOs were visually identified in 19% of the studied patients with an inter-rater reliability of 99% for HFO negative discharges and 78% agreement for identification of HFOs. HFOs were identified more often in the younger age group; however, they were identified in 11% of patients >5 years old. They were more frequently associated with spikes than with sharp waves and more often with higher amplitude EDs. Patients with HFOs were more likely to have a recurrence of seizures in the year after the first seizure (P < 0.05) and to continue to have seizures after 2 years (P < 0.0001). There was no statistically significant difference between the two groups with regards to continuing ASM after 2 years.ConclusionIncluding analysis for HFOs in routine EEG interpretation may increase the yield of the study and help guide the decision to either start or discontinue ASM. In the future, this may also help to identify pathological discharges with deleterious effects on the growing brain and set a new target for the management of epilepsy.

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