Benign Epilepsy With Centrotemporal Spikes Research Articles

A novel RyR2 mutation associated with co-morbid catecholaminergic polymorphic ventricular tachycardia (CPVT) and benign epilepsy with centrotemporal spikes (BECTS)

In this case report, we describe a 14-year-old patient with a novel RyR2 gene mutation (c.6577G > T/p.Val2193Leu), identified through a comprehensive review of medical history, examination findings, and follow-up data. The pathogenic potential of this mutation, which results in the loss of some interatomic forces and compromises the closure of the RyR2 protein pore leading to calcium leakage, was analyzed using the I-TASSER Suite to predict the structural changes in the protein. This mutation manifested clinically as co-morbid catecholaminergic polymorphic ventricular tachycardia (CPVT) and benign epilepsy with centrotemporal spikes (BECTS), a combination not previously documented in the same patient. While seizures were successfully managed with levetiracetam, the patient's exercise-induced syncope episodes could not be controlled with metoprolol, highlighting the complexity and challenge in managing CPVT associated with this novel RyR2 variation.

Antiseizure Medications Normalize Electroencephalographic Functional Connectivity and Power in Children With Benign Epilepsy With Centrotemporal Spikes

BackgroundThe decision to treat children with benign epilepsy with centrotemporal spikes (BECTS) using antiseizure medications (ASM) is controversial. Our goal is to compare the effect of ASM treatment on the alteration of electroencephalographic (EEG) functional connectivity and power across four frequency bands in children with BECTS. MethodsChildren with BECTS with two-year follow-up were retrospectively divided into ASM versus non-ASM groups. The network properties of the EEGs as based on network-based statistic and graph theory were evaluated by the following indices: global efficiency, clustering coefficient, betweenness centrality, and nodal strength in four frequency bands (delta, theta, alpha, and beta). EEG power including absolute power (AP) and relative power (RP) was analyzed in four frequency bands. ResultsIn children with BECTS with ASM treatment, there was no significant change in EEG connectivity across all bands before and after two years of ASM. In children with BECTS without ASM treatment, there was a significant increase of global efficiency, clustering coefficient, and nodal strength but not the betweenness centrality in the delta band after two years of follow-up. A decrease in AP in the delta and theta bands and a decrease in RP in the theta band were found in the ASM group after two years of treatment. ConclusionsOur results suggest that ASM may play a role in modulating the development of increasing overall brain connectivity and in downregulating overt synaptic activity, but not intrinsic focal connectivity, in the early years of BECTS. The changes in the EEG power indicate that ASM significantly normalized slow-wave band power.

Brain structural changes and molecular analyses in children with benign epilepsy with centrotemporal spikes.

Benign epilepsy with centrotemporal spikes (BECTS) is a common childhood epilepsy syndrome, accompanied by behavioral problems and cognitive impairments. Previous studies of BECTS-related brain structures applied univariate analysis and showed inconsistent results. And neurotransmitter patterns associated with brain structural alterations were still unclear. Structural images of twenty-one drug-naïve children with BECTS and thirty-five healthy controls (HCs) were scanned. Segmented gray matter volume (GMV) images were decomposed into independent components (ICs) using the source-based morphometry method. Then spatial correlation analyses were applied to examine possible relationships between GMV changes and neurotransmitter systems. Compared with HCs, drug-naïve children with BECTS showed increased volume in one GMV component (IC7), including bilateral precentral gyrus, bilateral supplementary motor area, left superior frontal cortex, bilateral middle/ inferior frontal cortex and bilateral anterior/ middle cingulate cortex. A positive correlation was observed between one GMV component (IC6) and seizure frequency. There were significantly positive correlations between abnormal GMV in IC7 and serotonergic, GABAergic and glutamatergic systems. These findings provided further evidence of changed GMV in drug-naïve children with BECTS related to their behavioral problems andcognitive impairments, and associated neurotransmitters which could help to better understand neurobiological mechanisms and underlying molecular mechanisms of BECTS. The article provides further evidence of changed gray matter volume in drug-naïve children with BECTS related to their behavioral problems and cognitive impairments as well as associated neurotransmitters. Most literature to date has applied univariate analysis and showed inconsistent results, and neurotransmitter patterns associated with brain structural alterations were still unclear. Therefore, this article uses multivariate method and JuSpace toolbox to fill the gap. Significantly increased gray matter volume was found in drug-naïve children with BECTS compared with healthy controls. Abnormal gray matter volume was significantly correlated with clinical data and specific neurotransmitters.

Atonic‐BECTS: An unusual presentation of self‐limited epilepsy in childhood

AbstractObjectivesWe describe an unusual patient with self‐limited epilepsy in childhood to aid in the accurate diagnosis and timely treatment of an atonic variant of self‐limited focal epilepsy of childhood with centrotemporal spikes.MethodsWe reviewed the medical records documenting the clinical presentation, diagnostic evaluation, and treatment. We also reviewed the relevant video electroencephalograms (EEGs).Patient DescriptionThis 3‐year‐old girl with self‐limited focal epilepsy of childhood (formerly called benign rolandic epilepsy) began having recurrent falls. Multiple clinical seizures were recorded on video EEG. The video documented generalized loss of tone resulting in falls, while the ictal EEG revealed one‐second paroxysms of 4 Hz spike‐slow‐wave discharges in the left centrotemporal region, followed by a brief generalized electrodecrement for 400 milliseconds. These findings support the diagnosis of an atypical variant of benign epilepsy with centrotemporal spikes (BECTS), known as atonic‐BECTS. Valproic acid was maximized. On follow‐up, the patient was seizure‐free with a normal EEG and normal development.DiscussionFew prior publications describe atonic‐BECTS. We present a child with atonic‐BECTS whose ictal video EEG confirms atonic seizures. While atonic seizures typically occur with generalized epilepsies, our report highlights that they can present as an atypical manifestation of self‐limited focal epilepsy in childhood.

Activation Map Reveals Language Impairment in Children with Benign Epilepsy with Centrotemporal Spikes (BECTS).

Neuropsychological evidence revealed language impairment in children with benign epilepsy with centrotemporal spikes (BECTS). This study investigates language function using task-activated fMRI. We conducted a language task fMRI study on three groups on a 3.0T MRI scanner, including a new onset drug naïve group (NODN-BECTS, n=11, age=9.6±1.6), an established epilepsy with medication-treated group (Med-BECTS, n=17, age=10.7±2.2) and a healthy control group (HC, n=18, age=10.8±1.7). We use MATLAB14 and SPM12 to pre-process and analyze the data. A one-sample t-test was used to identify task-related brain activation changes in each group, based on the general linear model (GLM). And, then two sample t-test was performed to compare different activated regions between groups. In addition, scores on the most recent Mandarin school exams were acquired to examine and contrast extra-scanner language performance. Statistical results show that some language-related brain regions (such as the left superior frontal gyrus and cerebellar vermis) were additionally activated in the NODN-BECTS group compared with the HC group. Compared with NODN-BECTS and HC groups, decreased activations were found in language-related regions in the Med-BECTS group, including the left insula, superior and middle frontal gyri, and bilateral middle occipital gyri. On the Mandarin school exams, the average score for HC was 87.3±8.2, NODN was 84.8±7.8, and Med was 78.2±13.2. There was a trend toward statistical significance between the Med and the HC (p = 0.074) as well as NODN (p = 0.092) groups. No statistically significant differences were found between the HC and the NODN-BECTS groups. Language task fMRI reveals additional areas of activation in new onset BECTS compared to healthy controls which may be compensatory in nature. Antiseizure medications (ASMs) and/or longer duration of BECTS additionally appears to affect language-related regions and reduce their functional ability.

Disrupted functional connectivity patterns of the left inferior frontal gyrus subregions in benign childhood epilepsy with centrotemporal spikes.

BackgroundBenign epilepsy with centrotemporal spikes (BECTS) is one of the most common pediatric epileptic syndromes. Recent studies have shown that BECTS can lead to significant language dysfunction. Although research supports the role of the left inferior frontal gyrus (LIFG) in BECTS, it is unclear whether the subregions of the LIFG show different change patterns in patients with this syndrome.MethodsUsing resting-state functional magnetic resonance imaging (fMRI) data in a group of 49 BECTS patients and 49 healthy controls, we investigated whether the BECTS patients show abnormal connectivity patterns of the LIFG subregions.ResultsCompared with healthy controls, the BECTS patients exhibited higher connectivity between the following: the inferior frontal sulcus (IFS) and the right anterior cingulate cortex (ACC), and the ventral area 44 (A44v) region and the left hippocampus/parahippocampus. Also, a decreased connectivity was found between the IFS and the left inferior temporal gyrus (ITG). No other significant differences in functional connectivity were found in the other 4 functional subregions of the LIFG in the BECTS.ConclusionsThese findings provide evidence for BECTS-related functional connectivity patterns of the LIFG subregions and suggest that different subregions may be involved in different neural circuits associated with language function in the BECTS.

CELSR1 variants are associated with partial epilepsy of childhood.

CELSR1 gene, encoding cadherin EGF LAG seven-pass G-type receptor 1, is mainly expressed in neural stem cells during the embryonic period. It plays an important role in neurodevelopment. However, the relationship between CELSR1 and disease of the central nervous system has not been defined. In this study, we performed trios-based whole-exome sequencing in a cohort of 356 unrelated cases with partial epilepsy without acquired causes and identified CELSR1 variants in six unrelated cases. The variants included one de novo heterozygous nonsense variant, one de novo heterozygous missense variant, and four compound heterozygous missense variants that had one variant was located in the extracellular region and the other in the cytoplasm. The patients with biallelic variants presented severe epileptic phenotypes, whereas those with heterozygous variants were associated with a mild epileptic phenotype of benign epilepsy with centrotemporal spikes (BECTS). These variants had no or low allele frequency in the gnomAD database. The frequencies of the CELSR1 variants in this cohort were significantly higher than those in the control populations. The evidence from ClinGen Clinical-Validity Framework suggested a strong association between CELSR1 variants and epilepsy. These findings provide evidence that CELSR1 is potentially a candidate pathogenic gene of partial epilepsy of childhood.

Whole-Brain Dynamic Resting-State Functional Network Analysis in Benign Epilepsy With Centrotemporal Spikes.

Benign epilepsy with centrotemporal spikes (BECTS), the most common type of epilepsy among children, is considered a network disorder. Both fMRI and EEG source imaging (ESI) studies have indicated that BECTS is associated with static resting-state functional network (SFN) alterations (e.g., decreased global efficiency) in source space. However, we find that the abovementioned alterations are not significant when the SFN calculations are performed in the scalp space using only clinical routine low-density (e.g., 19 channels) EEG recordings (shown in our results). In the context of EEG microstates, it is clear that networks in the scalp space with resting-state EEG recordings dynamically reconfigure in a well-organized way based on different functional states. We are therefore inspired to propose a whole-brain dynamic resting-state functional network (DFN) computation method based on resting-state low-density EEG recordings with four classical microstates in scalp space. Notably, on the one hand, this approach is suitable for clinical conditions, and, on the other hand, the dynamic alternations calculated with a DFN may promote our understanding of how the networks change in BECTS. We analysed the changes in a DFN in six frequency bands (δ, θ, αlow, αhigh, β, and γ) in patients with BECTS compared to those for healthy controls. Superior to traditional SFNs, the proposed DFN can reveal significant differences between individuals with BECTS and healthy controls (e.g., lower global efficiency), thus matching traditional fMRI and ESI methods in the source space. Our method directly performs DFN computations from low-density EEG recordings and avoids complex ESI computations, making it promising for clinical applications, especially in the outpatient diagnosis stage.

Functional connectivity differences in speech production networks in Chinese children with Rolandic epilepsy

Previous studies have demonstrated that language impairments are frequently observed in patients with benign epilepsy with centrotemporal spikes (BECTS). However, how BECTS affects language processing in the Chinese population remains unclear. With the use of functional magnetic resonance imaging (fMRI) in an overt picture-naming task, the present study examined functional connectivity in 27 children with BECTS and 26 healthy controls. The results indicated that children with BECTS showed altered functional connectivity associated with speech production between the left precuneus and the right cerebellum, between the right precuneus and the bilateral thalamus and the left superior temporal gyrus, between the right cuneus and the right postcentral gyrus and the right inferior parietal lobule, and between the right cerebellum and right middle frontal gyrus. Collectively, the findings in this study demonstrate the abnormal functional connectivity basis of speech production in Chinese children with BECTS, providing clues to understanding the brain mechanisms of language-related network in patients with BECTS.

SCN1A-Related Epilepsy: Novel Mutations and Rare Phenotypes.

ObjectivesTo expand the genotypes and phenotypes of sodium voltage-gated channel alpha subunit 1 (SCN1A)-related epilepsy.MethodsWe retrospectively collected the clinical and genetic information of 22 epilepsy patients (10 males, 12 females; mean: 9.2 ± 3.9 years; 3.9–20.3 years) carrying 22 variants of SCN1A. SCN1A mutations were identified by next-generation sequencing.ResultsTwenty-two variants were identified, among which 12 have not yet been reported. The median age at seizure onset was 6 months. Sixteen patients were diagnosed with Dravet syndrome (DS), two with genetic epilepsy with febrile seizures plus [one evolved into benign epilepsy with centrotemporal spikes (BECTS)], one with focal epilepsy, one with atypical childhood epilepsy with centrotemporal spikes (ABECTS) and two with unclassified epilepsy. Fourteen patients showed a global developmental delay/intellectual disability (GDD/ID). Slow background activities were observed in one patient and epileptiform discharges were observed in 11 patients during the interictal phase.SignificanceThis study enriches the genotypes and phenotypes of SCN1A-related epilepsy. The clinical characteristics of patients with 12 previously unreported variants were described.

Cortical Excitability, Synaptic Plasticity and Learning in Benign Epilepsy with Centrotemporal Spikes (BECTS)

Cortical Excitability, Synaptic Plasticity and Learning in Benign Epilepsy with Centrotemporal Spikes (BECTS)

EMD-WOG-2DCNN based EEG signal processing for Rolandic seizure classification

Objective Approximately 65 million people have epilepsy around the world. Recognition of epilepsy types is the basis to determine the treatment method and predict the prognosis in epilepsy patients. Childhood benign epilepsy with centrotemporal spikes (BECTS) or benign Rolandic epilepsy is the most common focal epilepsy in children, accounting for 15–20% of childhood epilepsies. These EEG patterns of individuals usually predict good treatment responses and prognosis. Until now, the interpretation of EEG still depends entirely on experienced neurologists, which may be a lengthy and tedious task. Method In this article, we proposed a novel machine learning model that efficiently distinguished Rolandic seizures from normal EEG signals. The proposed machine learning model processes the identification procedure in the following order (1) creating preliminary EEG features using signal empirical mode decomposition, (2) applying weighted overlook graph (WOG) to represent the decomposed EMD of IMF, and (3) classifying the results through a two Dimensional Convolutional Neural Network (2DCNN). The performance of our classification model is compared with other representative machine learning models. Results The model offered in this article gains an accuracy performance exceeding 97.6% in the Rolandic dataset, which is higher than other classification models. The effect of the model on the Bonn public dataset is also comparable to existing methods and even performs better in some subsets. Conclusion The purpose of this study is to introduce the most common childhood benign epilepsy type and propose a model that meets the real clinical needs to distinguish this Rolandic EEG pattern from normal signals accurately. Significance Future research will optimize the model to categorize other types of epilepsies beyond BECTS and finally implement them in the hospital system.

Aberrant Dynamics of Regional Coherence Measured by Resting-State fMRI in Children With Benign Epilepsy With Centrotemporal Spikes (BECTS).

Objective: To explore the dynamic features of intrinsic brain activity measured by fMRI in children with benign epilepsy with centrotemporal spikes (BECTS) and examine whether these indexes were associated with behaviors.Methods: We recruited 26 children with BECTS (10.35 ± 2.91 years) and 26 sex-, and age-matched (11.35 ± 2.51 years) healthy controls (HC) and acquired resting-state functional magnetic resonance imaging (rs-fMRI) and behavioral data. Dynamic regional homogeneity (dReHo), including mean and coefficient of variation (CV) metrics derived from the rs-fMRI data, and were compared between the BECTS and the HC groups.Results: Significantly decreased mean dReHo in bilateral supramarginal gyrus, left middle temporal gyrus (MTG.L), left postcentral gyrus and superior occipital gyrus were found in children with BECTS. Meanwhile, increased CV of dReHo in MTG.L and right fusiform in children with BECTS was revealed compared with HC. Further analyses of functional connectivity revealed decreased global signal FC existed in similar regions, linked with linguistic, social cognition, and sensorimotor processes, in children with BECTS compared with HCs. Moreover, the association analyses showed that the CV of dReHo in MTG.L was positively associated with age and a negative correlation was found between mean dReHo of MTG.L and disease duration. Besides, the CV of dReHo in MTG.L was found positively associated with the intelligence quotient (IQ) language scores and full IQ scores in children with BECTS, and the CV of dReHo in the left inferior temporal gyrus and Rolandic operculum were positively correlated with IQ operation scores and full IQ scores.Conclusion: Aberrant dynamic regional coherence in sensorimotor, linguistic, and lateral temporal regions suggests dynamical interplay that underlying cognitive performance in children with BECTS, suggesting an intrinsic dynamic mechanism for BECTS.

Interictal epileptiform discharges changed epilepsy-related brain network architecture in BECTS.

To investigate directed information flow of epileptiform activity in benign epilepsy with centrotemporal spikes (BECTS) during ictal epileptiform discharges (IEDs) and non-IEDs periods. In this multi-center study, a total of 188 subjects, including 50 BECTS and 138 normal children's controls (NCs) from three different centers (Center 1: females/males, 38/55; mean age, 9.33 ± 2.6years; Center 2: females/males,7/10; mean age, 8.59 ± 2.32years; Center 3: females/males, 14/14; mean age, 13 ± 3.42years) were recruited. The BECTS were classified into IEDs (females/males, 12/15; mean age, 8.15 ± 1.68years) and non-IEDs (females/males, 10/13; mean age, 9.09 ± 1.98years) subgroups depending on presence of central-temporal spikes from an EEG-fMRI examination. Three new methods, structural equation parametric modeling, dynamic causal modeling and granger causality density (GCD) were used to determine optimal network architectures for BECTS. Three multicentric NCs determined a reliable and consistent network architecture by structural equation parametric modeling method. Further analyses were used for IEDs and non-IEDs to determine the brain network architecture by structural equation parametric modeling, dynamic causal modeling and GCD, respectively. The brain network architecture of IEDs substate, non-IEDs substate and NCs are different. IEDs promoted the driving effect of the Rolandic areas with more output information flows, and increased the targeted effect of the top of pre-/post-central gyrus with more input information flows. The information flow arises from the Rolandic areas, and subsequently propagates to the top of pre-/post-central gyrus and thalamus. From non-IEDs status to IEDs status, the thalamus load may play an important role in the modulation and regulation of epileptiform activity. These findings shed new light on pathophysiological mechanism of directed localization of epileptiform activity in BECTS.

Altered functional connectivity in newly diagnosed benign epilepsy with unilateral or bilateral centrotemporal spikes: A multi-frequency MEG study

ObjectiveRolandic epilepsy (RE) is one of the most common forms of epilepsy syndromes in children. The condition is usually accompanied with either unilateral or bilateral centrotemporal epileptic discharge. Despite the term “benign”, many studies have reported that children with benign epilepsy with centrotemporal spikes (BECTS) display a range of pervasive cognitive difficulties. In addition, existing research suggests that unilateral and bilateral centrotemporal spikes may affect cognition through different mechanisms. Consequently, the present study aimed to investigate cognitive impairment and the resting-state network topology of children with benign epilepsy with unilateral centrotemporal spikes (U-BECTS) and with bilateral centrotemporal spikes (B-BECTS). MethodsThis study recruited 14 children with U-BECTS and 14 with B-BECTS. Thereafter, cognition was assessed in 28 children with BECTS and 14 healthy controls, using the fourth edition of the Wechsler Intelligence Scale (WISC-IV). Additionally, the functional network of the brain was constructed through magnetoencephalography (MEG) to record the resting-state brain magnetic signals of the brain and by computing virtual sensor waveforms at the source level. Moreover, graph theory (GT) analysis was used to assess the properties of the brain network. ResultsChildren in the B-BECTS group had an earlier onset of epilepsy compared to those in the U-BECTS category. In addition, both the B-BECTS and U-BECTS groups had lower Full Scale Intelligence Quotient (FSIQ), Verbal Comprehension Index (VCI), and Working Memory Index (WMI) scores, compared to the healthy controls although only children in the B-BECTS category had lower Perceptual Reasoning Index (PRI) scores. The results also showed that both BECTS groups had increased frontal cortex connectivity in specific frequency bands. Notably, children with B-BECTS showed a more disorderly and randomized network in the 1–4-Hz and 80–250-Hz frequency bands. Moreover, GT analysis showed that children with B-BECTS had lower clustering coefficient and characteristic path length in the 80–250-Hz frequency bands and higher connection strength in the 4–8-Hz frequency bands. On the other hand, the U-BECTS group had a higher clustering coefficient in the 8–12-Hz frequency bands, compared to the healthy controls. Correlation analysis revealed that there were negative correlations between network parameters, clinical characteristics, and neuropsychological data in the U-BECTS category. ConclusionThe findings revealed that children with BECTS display a diffuse early cognitive deficit. In addition, resting-state suboptimal network topology may be the mechanism of cognitive impairment in children with BECTS. The study also showed that and children with B-BECTS may be at a higher risk of cognitive impairment.

Brain metabolic characteristics distinguishing typical and atypical benign epilepsy with centro-temporal spikes.

Atypical benign epilepsy with centro-temporal spikes (BECTS) have less favorable outcomes than typical BECTS, and thus should be accurately identified for adequate treatment. We aimed to investigate the glucose metabolic differences between typical and atypical BECTS using 18F-fluorodeoxyglucose positron emission tomography ([18F]FDG PET) imaging, and explore whether these differences can help distinguish. Forty-six patients with typical BECTS, 31 patients with atypical BECTS and 23 controls who underwent [18F]FDG PET examination were retrospectively involved. Absolute asymmetry index (|AI|) was applied to evaluate the severity of metabolic abnormality. Glucose metabolic differences were investigated among typical BECTS, atypical BECTS, and controls by using statistical parametric mapping (SPM). Logistic regression analyses were performed based on clinical, PET, and hybrid features. The |AI| was found significantly higher in atypical BECTS than in typical BECTS (p = 0.040). Atypical BECTS showed more hypo-metabolism regions than typical BECTS, mainly located in the fronto-temporo-parietal cortex. The PET model had significantly higher area under the curve (AUC) than the clinical model (0.91 vs. 0.70, p = 0.006). The hybrid model had the highest sensitivity (0.90), specificity (0.85), and accuracy (0.87) of all three models. Atypical BECTS showed more widespread and severe hypo-metabolism than typical BECTS, depending on which the two groups can be well distinguished. The combination of metabolic characteristics and clinical variables has the potential to be used clinically to distinguish between typical and atypical BECTS. • Distinguishing between typical and atypical BECTS is very important for the formulation of treatment regimens in clinical practice. • Atypical BECTS showed more widespread and severe hypo-metabolism than typical BECTS, mainly located in the fronto-temporo-parietal cortex. • The logistic regression model based on PET outperformed that based on clinical characteristics in classification of typical and atypical BECTS, and the hybrid model achieved the best classification performance.

Effects of levetiracetam and oxcarbazepine monotherapy on intellectual and cognitive development in children with benign epilepsy with centrotemporal spikes

Levetiracetam (LEV) and oxcarbazepine (OXC) are commonly used in the treatment of epilepsy, but their efficacy and safety have seldom been compared for the treatment of children with benign epilepsy with centrotemporal spikes (BECTS). We thus assessed the efficacy of LEV and OXC monotherapy in the treatment of children with BECTS, and the effect of this treatment on children’s intelligence and cognitive development. This was a randomized, single-center trial. Children with BECTS were randomized (1:1) into LEV and OXC groups, and were assessed at 1, 3 and 6 months after treatment. The primary outcomes were the frequency of seizures and changes in intelligence and cognitive function. Secondary outcomes were electroencephalogram (EEG) results and safety. Seventy children were enrolled and randomized to the LEV group or the OXC group, and 32 of the 35 children in each group completed the study. After 6 months, the effective treatment rate of the OXC group was significantly higher than that of the LEV group (78.12 vs. 53.12%, p = 0.035). However, no significant inter-group difference was observed in EEG improvement (p = 0.211). In terms of intelligence and cognitive development, children in the OXC group exhibited significantly improved choice reaction time, mental rotation, and Wisconsin Card Sorting Test results (all p < 0.05). Both LEV and OXC were well tolerated, with 18.75 and 21.88% of children reporting mild adverse events (p = 0.756). OXC monotherapy was more effective than LEV for children with BECTS. In addition, children with OXC monotherapy had higher improvements in children’s intelligence and cognitive function than those with LEV monotherapy.

Evaluation of auditory spectral resolution abilities in children with benign epilepsy with centrotemporal spikes using spectral temporally modulated ripple test

PurposeSpectral resolution is imperative for complex listening tasks such as understanding speech in the presence of background noise and has a significant role in children, particularly classroom learning. The present study evaluated the auditory spectral resolution abilities of children with Benign epilepsy with centrotemporal spikes (BECTS). MethodThis cross-sectional study conducted from August 2017 to March 2020 recruited 23 children with clinical and electrographic features consistent with BECTS as cases. Fifteen age and sex matched typically developing children (TDC) were taken as controls. Spectral resolution abilities were evaluated using the recently developed Spectral temporally modulated Ripple test (SMRT). ResultsThe mean age of the cases was 10.63 ± 1.91 years with a slight male preponderance (69%). The mean (±SD) SMRT thresholds in the cases and controls were 5.90 (±1.91) and 7.21 (±1.03) respectively. The auditory spectral resolution threshold measured by SMRT in children with BECTS was observed to be significantly lower when compared to the controls (p of 0.021). ConclusionChildren with BECTS have a lower spectral resolution threshold by SMRT.

Early prediction of encephalopathic transformation in children with benign epilepsy with centro-temporal spikes

BackgroundMost children with Benign epilepsy with centro-temporal spikes (BECTS) undergo remission during late adolescence and do not require treatment. In a small group of patients, the condition may evolve to encephalopathic syndromes including epileptic encephalopathy with continuous spike-and-wave during sleep (ECSWS), or Landau-Kleffner Syndrome (LKS). Development of prediction models for early identification of at-risk children is of utmost importance. AimTo develop a predictive model of encephalopathic transformation using data-driven approaches, reveal complex interactions to identify potential risk factors. MethodsData were collected from a cohort of 91 patients diagnosed with BECTS treated between the years 2005–2017 at a pediatric neurology institute. Data on the initial presentation was collected based on a novel BECTS ontology and used to discover potential risk factors and to build a predictive model. Statistical and machine learning methods were compared. ResultsA subgroup of 18 children had encephalopathic transformation. The least absolute shrinkage and selection operator (LASSO) regression Model with Elastic Net was able to successfully detect children with ECSWS or LKS. Sensitivity and specificity were 0.83 and 0.44. The most notable risk factors were fronto-temporal and temporo-parietal localization of epileptic foci, semiology of seizure involving dysarthria or somatosensory auras. ConclusionNovel prediction model for early identification of patients with BECTS at risk for ECSWS or LKS. This model can be used as a screening tool and assist physicians to consider special management for children predicted at high-risk. Clinical application of machine learning methods opens new frontiers of personalized patient care and treatment.

Frequency-Dependent Interictal Neuromagnetic Activities in Children With Benign Epilepsy With Centrotemporal Spikes: A Magnetoencephalography (MEG) Study.

Objective: This study aimed to investigate interictal neuromagnetic activities in the low- to high-frequency ranges in patients with benign epilepsy with centrotemporal spikes (BECTS), especially those without interictal epileptiform discharges (IEDs).Methods: We studied 21 clinically-diagnosed BECTS patients and 11 age-matched healthy controls (HC) using high-sampling magnetoencephalography (MEG). Neuromagnetic sources were assessed with accumulated source imaging (ASI). The MEG data were analyzed in seven frequency bands. The MEG recordings distinguished BECTS without IEDs (n = 10) from those with IEDs (n = 11) and HC (n = 11).Results: At 1–4 Hz, the neuromagnetic activities in healthy subjects tended to locate at the precuneus/posterior cingulate, while those of the BECTS patients without IEDs tended to locate at the medial frontal cortex (MFC) compared to BECTS patients with IEDs. The MEG source imaging at 30–80 Hz revealed that BECTS patients without IEDs had higher occurrences of interictal brain activity in the medial temporal lobe (MTL) compared to controls and the brain activity strength seemed to be weaker. There was a significant correlation between the source strength of the interictal gamma oscillations of BECTS patients without IEDs and the duration of epilepsy.Conclusions: IEDs might disrupt the default mode network (DMN). Aberrant brain activities in BECTS patients without IEDs were associated with cognitive areas of the brain. The strength of gamma oscillations in the chronic epilepsy state reflected the duration of BECTS.Significance: MEG could reveal the aberrant neural activities in BECTS patients during the interictal period, and such abnormality is frequency-dependent. Gamma oscillations could be used to identify BECTS patients without IEDs.