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

Clinical analysis of developmental and/or epileptic encephalopathy with spike-and-wave activation in sleep: A single tertiary care center experience in China

PURPOSE

To analyze the electroclinical features of patients with developmental and/or epileptic encephalopathy with spike-and-wave activation in sleep (DEE/EE-SWAS) and study the efficacy of different therapies on seizure control, electroencephalogram (EEG) improvements of electrical status epilepticus during sleep (ESES), and cognition outcomes.

METHODS

Patients with DEE/EE-SWAS who underwent at least one follow-up EEG 3 months after therapy were retrospectively enrolled. The demographic and clinical characteristics of the patients were analyzed. Variables that influenced the outcomes were evaluated using logistic regression models.

RESULTS

In total, 87 patients (47 males) were included. The median age at ESES recognition was 81.0 months (IQR 64.0, 96.0). Forty-six patients were diagnosed with self-limited focal epilepsies (SeLFEs) before ESES recognition, 24 with developmental and epileptic encephalopathies with spike-and-wave activation in sleep (DEE-SWAS), and 17 with other epilepsies. Steroids, benzodiazepines, and antiseizure medications (ASMs) were the initial treatment options for ESES. Patients with structural etiologies or slow EEG backgrounds at the time of ESES recognition were less likely to respond to treatment than other patients. However, only children with slow EEG backgrounds had lower odds of response in logistic regression models. Children with clinical or EEG response showed improvements in cognition.

CONCLUSION

Steroids, benzodiazepines, and ASMs are effective treatments for patients with DEE/EE-SWAS. Children with structural etiologies or slow EEG backgrounds at the time of ESES recognition may have a poor long-term prognosis. The efficacy of seizure reduction and EEG improvement is associated with cognitive improvement.

Efficacy and safety of corticosteroids and ACTH in epileptic syndromes beyond Infantile Epileptic Spasms Syndrome (IESS): A systematic review and meta-analysis

We conducted a systematic review investigating the efficacy and tolerability of adrenocorticotropic hormone (ACTH) and corticosteroids in children with epilepsies other than infantile epileptic spasm syndrome (IESS) that are resistant to anti-seizure medication (ASM). We included retrospective and prospective studies reporting on more than five patients and with clear case definitions and descriptions of treatment and outcome measures. We searched multiple databases and registries, and we assessed the risk of bias in the selected studies using a questionnaire based on published templates. Results were summarized with meta-analyses that pooled logit-transformed proportions or rates. Subgroup analyses and univariable and multivariable meta-regressions were performed to examine the influence of covariates. We included 38 studies (2 controlled and 5 uncontrolled prospective; 31 retrospective) involving 1152 patients. Meta-analysis of aggregate data for the primary outcomes of seizure response and reduction of electroencephalography (EEG) spikes at the end of treatment yielded pooled proportions (PPs) of 0.60 (95% confidence interval [CI] 0.52-0.67) and 0.56 (95% CI 0.43-0.68). The relapse rate was high (PP 0.33, 95% CI 0.27-0.40). Group analyses and meta-regression showed a small benefit of ACTH and no difference between all other corticosteroids, a slightly better effect in electric status epilepticus in slow sleep (ESES) and a weaker effect in patients with cognitive impairment and "symptomatic" etiology. Obesity and Cushing's syndrome were the most common adverse effects, occurring more frequently in trials addressing continuous ACTH (PP 0.73, 95% CI 0.48-0.89) or corticosteroids (PP 0.72, 95% CI 0.54-0.85) than intermittent intravenous or oral corticosteroid administration (PP 0.05, 95% CI 0.02-0.10). The validity of these results is limited by the high risk of bias in most included studies and large heterogeneity among study results. This report was registered under International Prospective Register of Systematic Reviews (PROSPERO) number CRD42022313846. We received no financial support.

Continuous Spike-Waves during Slow Sleep Today: An Update

In the context of childhood epilepsy, the concept of continuous spike-waves during slow sleep (CSWS) includes several childhood-onset heterogeneous conditions that share electroencephalograms (EEGs) characterized by a high frequency of paroxysmal abnormalities during sleep, which have negative effects on the cognitive development and behavior of the child. These negative effects may have the characteristics of a clear regression or of a slowdown in development. Seizures are very often present, but not constantly. The above makes it clear why CSWS have been included in epileptic encephalopathies, in which, by definition, frequent EEG paroxysmal abnormalities have an unfavorable impact on cognitive functions, including socio-communicative skills, causing autistic features, even regardless of the presence of clinically overt seizures. Although several decades have passed since the original descriptions of the electroclinical condition of CSWS, there are still many areas that are little-known and deserve to be further studied, including the EEG diagnostic criteria, the most effective electrophysiological parameter for monitoring the role of the thalamus in CSWS pathogenesis, its long-term evolution, the nosographic location of Landau-Kleffner syndrome, standardized neuropsychological and behavioral assessments, and pharmacological and non-pharmacological therapies.

Unmet needs in epileptic encephalopathy with spike-and-wave activation in sleep: A systematic review

INTRODUCTION

Developmental and/or epileptic encephalopathy with spike-and-wave activation in sleep (D/EE-SWAS), also referred to as electrical status epilepticus during sleep (ESES) or epileptic encephalopathy with continuous spike-and-wave during sleep (CSWS or EE-CSWS), is a spectrum of rare childhood epileptic encephalopathies that can lead to long-term cognitive impairment. Despite the importance of early diagnosis and intervention for D/EE-SWAS, there is a paucity of well-controlled clinical trial data to inform treatment, and no approved treatments are available. To assess correlations between diagnosis, treatment, and outcomes in D/EE-SWAS, we carried out a systematic review of the literature.

METHODS

In August 2020, we conducted comprehensive database searches using search terms including "electrical status epilepticus," "ESES," "CSWS," and "Landau-Kleffner syndrome." Two or more independent reviewers screened titles, abstracts, and full-text articles for those that met the following criteria: prospective studies (randomized controlled trials [RCTs] or open-label trials), retrospective studies (drug evaluations or observational studies/chart reviews), and case series with ≥ 10 participants. Both interventional and non-interventional studies were included (i.e., drug intervention was not an inclusion criterion). Articles published before 2012, review articles, animal studies, and studies of surgical or dietary interventions were excluded. Standardized data extraction templates were used to capture data on study design, patient characteristics, interventions, and outcomes from each of the selected publications. Study quality was assessed using the Cochrane Risk of Bias Tool for RCTs and the Newcastle-Ottawa Scale (NOS) or the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for retrospective, observational studies.

RESULTS

A total of 34 studies were included for full data extraction, most of which were uncontrolled and observational. Interpretation of study outcomes was limited by small study populations, variability in inclusion criteria, and inconsistency in methods of assessment and reporting of outcomes, which resulted in large heterogeneity in patients and their presenting symptoms. Despite these limitations, some patterns could be discerned. Several studies found that longer duration of ESES and younger age at onset were correlated with more severe language and cognitive deficits. In addition, several studies reported an association between improvement in cognitive outcomes and reduction in electroencephalogram (EEG) abnormalities and/or seizure frequency. In the 16 prospective or retrospective studies that evaluated drug treatments (e.g., antiseizure medications, corticosteroids, and high-dose diazepam), there was some improvement in EEG, seizure, and/or cognitive outcomes, although the specific outcomes and rates of improvement reported varied from study to study.

CONCLUSION

Long-term cognitive deficits remain common in D/EE-SWAS, and data gaps exist in the literature that preclude an evidence-based approach to managing this complex epilepsy indication. Early intervention with more effective medications is needed to optimize long-term outcomes. Sufficiently powered, randomized, double-blind, controlled trials with standardized methods and predefined primary and secondary outcomes are needed.

The prospective study of 54 children with electrical status epilepticus during sleep: How to simplify the electroencephalogram diagnosis and guide the treatment

OBJECTIVE

To simplify the electroencephalogram (EEG) diagnosis and guide the treatment of electrical status epilepticus during sleep (ESES).

METHODS

We recruited 54 children with ESES from December 2019 to December 2020 and compared various spike-wave index (SWI) calculation methods. Time-frequency analysis assessed the correlation between high-frequency oscillations energy and the SWI. We divided 42 children into responder and non-responder treatment groups based on the observations made during a 12-month follow-up period and evaluate different treatment and the independent risk factors of refractory ESES.

RESULTS

The SWI of 5 min before the second sleep cycle of non-rapid eye movement (NREM; long method II) and that of all NREM sleep (total method) were not significantly different (p = .06). The average energy of γ (r = .288, p = .002) and ripple (r = .203, p = .04) oscillations were correlated with the SWI. Multivariable logistic regression analysis showed that encephalomalacia was an independent risk factor for refractory ESES (OR: 10.48, 95% CI: 1.62-67.63). The clinical seizure improvement rates of anti-seizure medications (ASMs), ASMs with benzodiazepines, and ASMs with benzodiazepines and steroids after 12 months were 9.3%, 42.8%, and 53.8%, EEG improvement rate were 5.5%, 30.9% and 37%, respectively. The intelligence of the children in the responder treatment group has improved during the 1-year follow-up.

SIGNIFICANCE

These findings demonstrate EEG and clinical features of ESES and may provide basis for simplifying diagnosis and guiding the treatment of children with ESES.

Prognostic interictal electroencephalographic biomarkers and models to assess antiseizure medication efficacy for clinical practice: A scoping review

Antiseizure medication (ASM) is the primary treatment for epilepsy. In clinical practice, methods to assess ASM efficacy (predict seizure freedom or seizure reduction), during any phase of the drug treatment lifecycle, are limited. This scoping review identifies and appraises prognostic electroencephalographic (EEG) biomarkers and prognostic models that use EEG features, which are associated with seizure outcomes following ASM initiation, dose adjustment, or withdrawal. We also aim to summarize the population and context in which these biomarkers and models were identified and described, to understand how they could be used in clinical practice. Between January 2021 and October 2022, four databases, references, and citations were systematically searched for ASM studies investigating changes to interictal EEG or prognostic models using EEG features and seizure outcomes. Study bias was appraised using modified Quality in Prognosis Studies criteria. Results were synthesized into a qualitative review. Of 875 studies identified, 93 were included. Biomarkers identified were classed as qualitative (visually identified by wave morphology) or quantitative. Qualitative biomarkers include identifying hypsarrhythmia, centrotemporal spikes, interictal epileptiform discharges (IED), classifying the EEG as normal/abnormal/epileptiform, and photoparoxysmal response. Quantitative biomarkers were statistics applied to IED, high-frequency activity, frequency band power, current source density estimates, pairwise statistical interdependence between EEG channels, and measures of complexity. Prognostic models using EEG features were Cox proportional hazards models and machine learning models. There is promise that some quantitative EEG biomarkers could be used to assess ASM efficacy, but further research is required. There is insufficient evidence to conclude any specific biomarker can be used for a particular population or context to prognosticate ASM efficacy. We identified a potential battery of prognostic EEG biomarkers, which could be combined with prognostic models to assess ASM efficacy. However, many confounders need to be addressed for translation into clinical practice.

High-Frequency Oscillations and Epileptogenic Network

Epilepsy is a network disease caused by aberrant neocortical large-scale connectivity spanning regions on the scale of several centimeters. High-frequency oscillations, characterized by the 80-600 Hz signals in electroencephalography, have been proven to be a promising biomarker of epilepsy that can be used in assessing the severity and susceptibility of epilepsy as well as the location of the epileptogenic zone. However, the presence of a high-frequency oscillation network remains a topic of debate as high-frequency oscillations have been previously thought to be incapable of propagation, and the relationship between high-frequency oscillations and the epileptogenic network has rarely been discussed. Some recent studies reported that high-frequency oscillations may behave like networks that are closely relevant to the epileptogenic network. Pathological highfrequency oscillations are network-driven phenomena and elucidate epileptogenic network development; high-frequency oscillations show different characteristics coincident with the epileptogenic network dynamics, and cross-frequency coupling between high-frequency oscillations and other signals may mediate the generation and propagation of abnormal discharges across the network.

Scalp HFO rates decrease after successful epilepsy surgery and are not impacted by the skull defect resulting from craniotomy

Epilepsy surgery can achieve seizure freedom in selected pediatric candidates, but reliable postsurgical predictors of seizure freedom are missing. High frequency oscillations (HFO) in scalp EEG are a new and promising biomarker of treatment response. However, it is unclear if the skull defect resulting from craniotomy interferes with HFO detection in postsurgical recordings. We considered 14 children with focal lesional epilepsy who underwent presurgical evaluation, epilepsy surgery, and postsurgical follow-up of ≥ 1 year. We identified the nearest EEG electrodes to the skull defect in the postsurgical MRI. We applied a previously validated automated HFO detector to determine HFO rates in presurgical and postsurgical EEG. Overall, HFO rates showed a positive correlation with seizure frequency (p < 0.001). HFO rates in channels over the HFO area decreased following successful epilepsy surgery, irrespective of their proximity to the skull defect (p = 0.005). HFO rates in channels outside the HFO area but near the skull defect showed no increase following surgery (p = 0.091) and did not differ from their contralateral channels (p = 0.726). Our observations show that the skull defect does not interfere with postsurgical HFO detection. This supports the notion that scalp HFO can predict postsurgical seizure freedom and thus guide therapy management in focal lesional epilepsy.

High-frequency oscillations detected by electroencephalography as biomarkers to evaluate treatment outcome, mirror pathological severity and predict susceptibility to epilepsy

High-frequency oscillations (HFOs) in the electroencephalography (EEG) have been extensively investigated as a potential biomarker of epileptogenic zones. The understanding of the role of HFOs in epilepsy has been advanced considerably over the past decade, and the use of scalp EEG facilitates recordings of HFOs. HFOs were initially applied in large scale in epilepsy surgery and are now being utilized in other applications. In this review, we summarize applications of HFOs in 3 subtopics: (1) HFOs as biomarkers to evaluate epilepsy treatment outcome; (2) HFOs as biomarkers to measure seizure propensity; (3) HFOs as biomarkers to reflect the pathological severity of epilepsy. Nevertheless, knowledge regarding the above clinical applications of HFOs remains limited at present. Further validation through prospective studies is required for its reliable application in the clinical management of individual epileptic patients.

Recent Developments in Diagnosis of Epilepsy: Scope of MicroRNA and Technological Advancements

Epilepsy is one of the most common neurological disorders, characterized by recurrent seizures, resulting from abnormally synchronized episodic neuronal discharges. Around 70 million people worldwide are suffering from epilepsy. The available antiepileptic medications are capable of controlling seizures in around 60-70% of patients, while the rest remain refractory. Poor seizure control is often associated with neuro-psychiatric comorbidities, mainly including memory impairment, depression, psychosis, neurodegeneration, motor impairment, neuroendocrine dysfunction, etc., resulting in poor prognosis. Effective treatment relies on early and correct detection of epileptic foci. Although there are currently a few well-established diagnostic techniques for epilepsy, they lack accuracy and cannot be applied to patients who are unsupportive or harbor metallic implants. Since a single test result from one of these techniques does not provide complete information about the epileptic foci, it is necessary to develop novel diagnostic tools. Herein, we provide a comprehensive overview of the current diagnostic tools of epilepsy, including electroencephalography (EEG) as well as structural and functional neuroimaging. We further discuss recent trends and advances in the diagnosis of epilepsy that will enable more effective diagnosis and clinical management of patients.

Automatic detection of interictal ripples on scalp EEG to evaluate the effect and prognosis of ACTH therapy in patients with infantile spasms

OBJECTIVE

We aimed to explore the feasibility of using scalp-recorded high-frequency oscillations (HFOs) to evaluate the efficacy and prognosis of adrenocorticotropic hormone (ACTH) treatment in patients with infantile spasms.

METHODS

Thirty-nine children with infantile spasms were enrolled and divided into seizure-free and non-seizure-free groups after ACTH treatment. Patients who were seizure-free were further divided into relapse and non-relapse subgroups based on the observations made during a 6-month follow-up period. Scalp ripples were detected and compared during the interictal periods before and after 2 weeks of treatment.

RESULTS

After ACTH treatment, the number and channels of ripples were significantly lower, whereas the percentage decrease in the number, spectral power, and channels of ripples was significantly higher in the seizure-free group than in the non-seizure-free group. In addition, the relapse subgroup showed higher number and spectral power and wider distribution of ripples than did the non-relapse subgroup. Changes in HFOs in terms of number, spectral power, and channel of ripples were closely related to the severity of epilepsy and can indicate disease susceptibility.

SIGNIFICANCE

Scalp HFOs can be used as an effective biomarker to monitor the effect and evaluate the prognosis of ACTH therapy in patients with infantile spasms.

Application of High-Frequency Oscillations on Scalp EEG in Infant Spasm: A Prospective Controlled Study

Objective

We quantitatively analyzed high-frequency oscillations (HFOs) using scalp electroencephalography (EEG) in patients with infantile spasms (IS).

Methods

We enrolled 60 children with IS hospitalized from January 2019 to August 2020. Sixty healthy age-matched children comprised the control group. Time-frequency analysis was used to quantify γ, ripple, and fast ripple (FR) oscillation energy changes.

Results

γ, ripple, and FR oscillations dominated in the temporal and frontal lobes. The average HFO energy of the sleep stage is lower than that of the wake stage in the same frequency bands in both the normal control (NC) and IS groups (P < 0.05). The average HFO energy of the IS group was significantly higher than that of the NC group in γ band during sleep stage (P < 0.01). The average HFO energy of S and Post-S stage were higher than that of sleep stage in γ band (P < 0.05). In the ripple band, the average HFO energy of Pre-S, S, and Post-S stage was higher than that of sleep stage (P < 0.05). Before treatment, there was no significant difference in BASED score between the effective and ineffective groups. The interaction of curative efficacy × frequency and the interaction of curative efficacy × state are statistically significant. The average HFO energy of the effective group was lower than that of the ineffective group in the sleep stage (P < 0.05). For the 16 children deemed "effective" in the IS group, the average HFO energy of three frequency bands was not significantly different before compared with after treatment.

Significance

Scalp EEG can record HFOs. The energy of HFOs can distinguish physiological HFOs from pathological ones more accurately than frequency. On scalp EEG, γ oscillations can better detect susceptibility to epilepsy than ripple and FR oscillations. HFOs can trigger spasms. The analysis of average HFO energy can be used as a predictor of the effectiveness of epilepsy treatment.

Scalp high-frequency oscillation rates are higher in younger children

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.

Automated detection of ripple oscillations in long-term scalp EEG from patients with infantile spasms

Objective.Scalp high-frequency oscillations (HFOs) are a promising biomarker of epileptogenicity in infantile spasms (IS) and many other epilepsy syndromes, but prior studies have relied on visual analysis of short segments of data due to the prevalence of artifacts in EEG. Here we set out to robustly characterize the rate and spatial distribution of HFOs in large datasets from IS subjects using fully automated HFO detection techniques.Approach.We prospectively collected long-term scalp EEG data from 12 subjects with IS and 18 healthy controls. For patients with IS, recording began prior to diagnosis and continued through initiation of treatment with adrenocorticotropic hormone (ACTH). The median analyzable EEG duration was 18.2 h for controls and 84.5 h for IS subjects (∼1300 h total). Ripples (80-250 Hz) were detected in all EEG data using an automated algorithm.Main results.HFO rates were substantially higher in patients with IS compared to controls. In IS patients, HFO rates were higher during sleep compared to wakefulness (median 5.5 min^-1and 2.9 min^-1, respectively;p = 0.002); controls did not exhibit a difference in HFO rate between sleep and wakefulness (median 0.98 min^-1and 0.82 min^-1, respectively). Spatially, IS patients exhibited significantly higher rates of HFOs in the posterior parasaggital region and significantly lower HFO rates in frontal channels, and this difference was more pronounced during sleep. In IS subjects, ACTH therapy significantly decreased the rate of HFOs.Significance.Here we provide a detailed characterization of the spatial distribution and rates of HFOs associated with IS, which may have relevance for diagnosis and assessment of treatment response. We also demonstrate that our fully automated algorithm can be used to detect HFOs in long-term scalp EEG with sufficient accuracy to clearly discriminate healthy subjects from those with IS.

Recent advances in the noninvasive detection of high-frequency oscillations in the human brain

In recent decades, a significant body of evidence based on invasive clinical research has showed that high-frequency oscillations (HFOs) are a promising biomarker for localization of the seizure onset zone (SOZ), and therefore, have the potential to improve postsurgical outcomes in patients with epilepsy. Emerging clinical literature has demonstrated that HFOs can be recorded noninvasively using methods such as scalp electroencephalography (EEG) and magnetoencephalography (MEG). Not only are HFOs considered to be a useful biomarker of the SOZ, they also have the potential to gauge disease severity, monitor treatment, and evaluate prognostic outcomes. In this article, we review recent clinical research on noninvasively detected HFOs in the human brain, with a focus on epilepsy. Noninvasively detected scalp HFOs have been investigated in various types of epilepsy. HFOs have also been studied noninvasively in other pathologic brain disorders, such as migraine and autism. Herein, we discuss the challenges reported in noninvasive HFO studies, including the scarcity of MEG and high-density EEG equipment in clinical settings, low signal-to-noise ratio, lack of clinically approved automated detection methods, and the difficulty in differentiating between physiologic and pathologic HFOs. Additional studies on noninvasive recording methods for HFOs are needed, especially prospective multicenter studies. Further research is fundamental, and extensive work is needed before HFOs can routinely be assessed in clinical settings; however, the future appears promising.

Scalp EEG interictal high frequency oscillations as an objective biomarker of infantile spasms

OBJECTIVE

To investigate the diagnostic utility of high frequency oscillations (HFOs) via scalp electroencephalogram (EEG) in infantile spasms.

METHODS

We retrospectively analyzed interictal slow-wave sleep EEGs sampled at 2,000 Hz recorded from 30 consecutive patients who were suspected of having infantile spasms. We measured the rate of HFOs (80-500 Hz) and the strength of the cross-frequency coupling between HFOs and slow-wave activity (SWA) at 3-4 Hz and 0.5-1 Hz as quantified with modulation indices (MIs).

RESULTS

Twenty-three patients (77%) exhibited active spasms during the overnight EEG recording. Although the HFOs were detected in all children, increased HFO rate and MIs correlated with the presence of active spasms (p < 0.001 by HFO rate; p < 0.01 by MIs at 3-4 Hz; p = 0.02 by MIs at 0.5-1 Hz). The presence of active spasms was predicted by the logistic regression models incorporating HFO-related metrics (AUC: 0.80-0.98) better than that incorporating hypsarrhythmia (AUC: 0.61). The predictive performance of the best model remained favorable (87.5% accuracy) after a cross-validation procedure.

CONCLUSIONS

Increased rate of HFOs and coupling between HFOs and SWA are associated with active epileptic spasms.

SIGNIFICANCE

Scalp-recorded HFOs may serve as an objective EEG biomarker for active epileptic spasms.

Expert consensus on clinical applications of high-frequency oscillations in epilepsy

Studies in animal models of epilepsy and pre-surgical patients have unanimously found a strong correlation between high-frequency oscillations (HFOs, > 80 Hz) and the epileptogenic zone, suggesting that HFOs can be a potential biomarker of epileptogenicity and epileptogenesis. This consensus includes the definition and standard detection techniques of HFOs, the localizing value of pathological HFOs for epileptic foci, and different ways to distinguish physiological from epileptic HFOs. The latest clinical applications of HFOs in epilepsy and the related findings are also discussed. HFOs will advance our understanding of the pathophysiology of epilepsy.