High-frequency oscillations recorded with surface EEG in neonates with seizures

Scalp high-frequency oscillations differentiate neonates with seizures from healthy neonates

OBJECTIVE

We aimed to investigate (1) whether an automated detector can capture scalp high-frequency oscillations (HFO) in neonates and (2) whether scalp HFO rates can differentiate neonates with seizures from healthy neonates.

METHODS

We considered 20 neonates with EEG-confirmed seizures and four healthy neonates. We applied a previously validated automated HFO detector to determine scalp HFO rates in quiet sleep.

RESULTS

Etiology in neonates with seizures included hypoxic-ischemic encephalopathy in 11 cases, structural vascular lesions in 6, and genetic causes in 3. The HFO rates were significantly higher in neonates with seizures (0.098 ± 0.091 HFO/min) than in healthy neonates (0.038 ± 0.025 HFO/min; P = 0.02) with a Hedge's g value of 0.68 indicating a medium effect size. The HFO rate of 0.1 HFO/min/ch yielded the highest Youden index in discriminating neonates with seizures from healthy neonates. In neonates with seizures, etiology, status epilepticus, EEG background activity, and seizure patterns did not significantly impact HFO rates.

SIGNIFICANCE

Neonatal scalp HFO can be detected automatically and differentiate neonates with seizures from healthy neonates. Our observations have significant implications for neuromonitoring in neonates. This is the first step in establishing neonatal HFO as a biomarker for neonatal seizures.

Quantitative analysis of high-frequency activity in neonatal EEG

OBJECTIVE

To determine the presence and potential utility of independent high-frequency activity recorded from scalp electrodes in the electroencephalogram (EEG) of newborns.

METHODS

We compare interburst intervals and continuous activity at different frequencies for EEGs retrospectively recorded at 256 Hz from 4 newborn groups: 1) 36 preterms (<32 weeks' gestational age, GA); 2) 12 preterms (32-37 weeks' GA); 3) 91 healthy full terms; 4) 15 full terms with hypoxic-ischemic encephalopathy (HIE). At 4 standard frequency bands (delta, 0.5-3 Hz; theta, 3-8 Hz; alpha, 8-15 Hz; beta, 15-30 Hz) and 3 higher-frequency bands (gamma1, 30-48 Hz; gamma2, 52-99 Hz; gamma3, 107-127 Hz), we compared power spectral densities (PSDs), quantitative features, and machine learning model performance. Feature selection and further machine learning methods were performed on one cohort.

RESULTS

We found significant (P < 0.01) differences in PSDs, quantitative analysis, and machine learning modelling at the higher-frequency bands. Machine learning models using only high-frequency features performed best in preterm groups 1 and 2 with a median (95% confidence interval, CI) Matthews correlation coefficient (MCC) of 0.71 (0.12-0.88) and 0.66 (0.36-0.76) respectively. Interburst interval-detector models using both high- and standard-bandwidths produced the highest median MCCs in all four groups. High-frequency features were largely independent of standard-bandwidth features, with only 11/84 (13.1%) of correlations statistically significant. Feature selection methods produced 7 to 9 high-frequency features in the top 20 feature set.

CONCLUSIONS

This is the first study to identify independent high-frequency activity in newborn EEG using in-depth quantitative analysis. Expanding the EEG bandwidths of analysis has the potential to improve both quantitative and machine-learning analysis, particularly in preterm EEG.

Epileptic high-frequency oscillations occur in neonates with a high risk for seizures

Introduction

Scalp high-frequency oscillations (HFOs, 80-250 Hz) are increasingly recognized as EEG markers of epileptic brain activity. It is, however, unclear what level of brain maturity is necessary to generate these oscillations. Many studies have reported the occurrence of scalp HFOs in children with a correlation between treatment success of epileptic seizures and the reduction of HFOs. More recent studies describe the reliable detection of HFOs on scalp EEG during the neonatal period.

Methods

In the present study, continuous EEGs of 38 neonates at risk for seizures were analyzed visually for the scalp HFOs using 30 min of quiet sleep EEG. EEGs of 14 patients were of acceptable quality to analyze HFOs.

Results

The average rate of HFOs was 0.34 ± 0.46/min. About 3.2% of HFOs occurred associated with epileptic spikes. HFOs were significantly more frequent in EEGs with abnormal vs. normal background activities (p = 0.005).

Discussion

Neonatal brains are capable of generating HFOs. HFO could be a viable biomarker for neonates at risk of developing seizures. Our preliminary data suggest that HFOs mainly occur in those neonates who have altered background activity. Larger data sets are needed to conclude whether HFO occurrence is linked to seizure generation and whether this might predict the development of epilepsy.

EEG in neonatal seizures: where to look and what to see

INTRODUCTION

Neonatal seizures are frequent and carry a detrimental prognostic outlook. Diagnosis is based on EEG confirmation. Classification has recently changed.

AREAS COVERED

We consulted original papers, book chapters, atlases, and reviews to provide a narrative overview on EEG characteristics of neonatal seizures. We searched PubMed, without time restrictions (last visited: 31 May 2022). Additional papers were extracted from the references list of selected papers. We describe the typical neonatal ictal EEG discharges morphology, location, and propagation, together with age-dependent features. Etiology-dependent electroclinical features, when identifiable, are presented for both acute symptomatic neonatal seizures and neonatal-onset epilepsies and developmental/epileptic encephalopathies. The few ictal variables known to predict long-term outcome have been discussed.

EXPERT OPINION

Multimodal neuromonitoring in critically ill newborns, high-density EEG, and functional neuroimaging might increase our insight into the neurophysiological bases of seizures in newborns. Increasing availability of long-term monitoring with conventional video-EEG and automated detection methods will allow clinicians and researchers to gather an ever expanding bulk of clinical and neurophysiological data to enhance accuracy with deep phenotyping. The latest classification proposal represents an input for critically revising our diagnostic abilities with respect to seizure definition, duration, and semiology, possibly further promoting clinical research.

Are High Frequency Oscillations in Scalp EEG Related to Age?

BACKGROUND

High-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.

METHODS

We 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.

RESULTS

No significant difference of HFO-rates was found between groups [U = 10.5, p = 0.429, r = 0.3].

CONCLUSIONS

Lack 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.

Case Report: High-Gamma Oscillations on an Ictal Electroencephalogram in a Newborn Patient With Hypoxic-Ischemic Encephalopathy

Fast oscillations (FOs) >40 Hz in electroencephalograms (EEGs) are associated with ictogenesis and epileptogenesis in adults and children with epilepsy. However, only a few previous studies showed FOs in neonates. Reported frequencies of such neonatal FOs were in the low-gamma (<60 Hz) band and, therefore, they were not high compared to those in pediatric patients. We herein report a newborn patient with severe hypoxic-ischemic encephalopathy (HIE), who showed pathological FOs with a frequency in the high-gamma band. She was born at a gestational age of 39 weeks 4 days by emergency cesarean section because of non-reassuring fetal status. She had focal motor seizures involving unilateral upper and lower limbs lasting for tens of seconds on days 0, 1, 4, 5, 8, and 9 and subclinical seizures on days 4-11. Phenobarbital (PB) was intravenously administered on days 0, 2, 4, 5, and 6. We found FOs that were superimposed on the ictal delta activities using visual inspection and time-frequency analysis on 8-11 days of age. Among them, we detected high-gamma (71.4-100 Hz) oscillations that appeared to be temporally independent of low-gamma activities in the ictal EEG on 11 days of age. To the best of our knowledge, this is one of the earliest reports showing pathological FOs with a frequency of >60 Hz in the high-gamma band in human neonatal seizures, which were previously observed in animal studies. Further studies are needed to elucidate the pathophysiology of ictal FOs in neonatal seizures.