Benign childhood epilepsy with centrotemporal spikes (BECTS) and developmental co-ordination disorder

Classification of self-limited epilepsy with centrotemporal spikes by classical machine learning and deep learning based on electroencephalogram data

Electroencephalogram (EEG) has been widely utilized as a valuable assessment tool for diagnosing epilepsy in hospital settings. However, clinical diagnosis of patients with self-limited epilepsy with centrotemporal spikes (SeLECTS) is challenging due to the presence of similar abnormal discharges in EEG displays compared to other types of epilepsy (non-SeLECTS) patients. To assist the diagnostic process of epilepsy, a comprehensive classification study utilizing machine learning or deep learning techniques is proposed. In this study, clinical EEG was collected from 33 patients diagnosed with either SeLECTS or non-SeLECTS, aged between 3 and 11 years. In the realm of classical machine learning, sharp wave features (including upslope, downslope, and width at half maximum) were extracted from the EEG data. These features were then combined with the random forest (RF) and extreme random forest (ERF) classifiers to differentiate between SeLECTS and non-SeLECTS. Additionally, deep learning was employed by directly inputting the EEG data into a deep residual network (ResNet) for classification. The classification results were evaluated based on accuracy, F1-score, area under the curve (AUC), and area under the precision-recall curve (AUPRC). Following a 10-fold cross-validation, the ERF classifier achieved an accuracy of 73.15 % when utilizing sharp wave feature extraction for classification. The F1-score obtained was 0.72, while the AUC and AUPRC values were 0.75 and 0.63, respectively. On the other hand, the ResNet model achieved a classification accuracy of 90.49 %, with an F1-score of 0.90. The AUC and AUPRC values for ResNet were found to be 0.96 and 0.92, respectively. These results highlighted the significant potential of deep learning methods in SeLECTS classification research, owing to their high accuracy. Moreover, feature extraction-based methods demonstrated good reliability and could assist in identifying relevant biological features of SeLECTS within EEG data.

A prospective 5-year longitudinal study detects neurocognitive and imaging correlates of seizure remission in self-limiting Rolandic epilepsy

OBJECTIVE

Self-limiting Rolandic epilepsy (RE) is the most common epilepsy in school-age children. Seizures are generally infrequent, but cognitive, language, and motor coordination problems can significantly impact the child's life. To better understand brain structure and function changes in RE, we longitudinally assessed neurocognition, cortical thickness, and subcortical volumes.

METHODS

At baseline, we recruited 30 participants diagnosed with RE and 24-healthy controls and followed up for 4.94 ± 0.8 years when the participants with RE were in seizure remission. Measures included were as follows: T1-weighted magnetic resonance brain imaging (MRI) with FreeSurfer analysis and detailed neuropsychological assessments. MRI and neuropsychological data were compared between baseline and follow-up in seizure remission.

RESULTS

Longitudinal MRI revealed excess cortical thinning in the left-orbitofrontal (p = 0.0001) and pre-central gyrus (p = 0.044). There is a significant association (p = 0.003) between a reduction in cortical thickness in the left-orbitofrontal cluster and improved processing of filtered words. Longitudinal neuropsychology revealed significant improvements in the symptoms of developmental coordination disorder (DCD, p = 0.005) in seizure remission.

CONCLUSIONS

There is evidence for altered development of neocortical regions between active seizure state and seizure remission in RE within two clusters maximal in the left-orbitofrontal and pre-central gyrus. There is significant evidence for improvement in motor coordination between active seizures and seizure remission and suggestive evidence for a decline in fluid intelligence and gains in auditory processing.

Text integration processes in children with Childhood Epilepsy with Centro-Temporal Spikes

Although Childhood Epilepsy with Centro-Temporal Spikes (CECTS) is considered a 'benign' form of epilepsy, word reading, listening comprehension, and reading comprehension difficulties have been reported. We examined two core skills for text comprehension, coherence monitoring and inference generation, in children with CECTS and compared performance with typically developing controls. Children with CECTS (n = 23; 9 females; mean age 9 y 0 m) and the comparison group (n = 38; 14 females; mean age 9 y 1 m) completed two tasks. For coherence monitoring they heard 24 narrative texts, 16 containing two inconsistent sentences, and responded to a yes/no question to assess identification of the inconsistency after each text; for inference making they heard 16 texts designed to elicit a target inference by integrating information in two sentences and responded to a yes/no question to assess generation of the inference. In both tasks there was a near condition, in which critical sentences were adjacent, and a far condition in which these sentences were separated by filler sentences. Accuracy to the question and the processing time for critical sentences in the text were measured. We used listening comprehension tasks to control for variation in word reading ability. Mixed effects analyses for each task revealed that children with CECTS show comparable levels of accuracy to age-matched peers in these tasks tapping two core text integration skills: detection of inconsistencies and generation of inferences. However, they take longer to process texts indicating a likely source of their listening and reading comprehension difficulties.

An improved BECT spike detection method with functional brain network features based on PLV

Background

Children with benign childhood epilepsy with centro-temporal spikes (BECT) have spikes, sharps, and composite waves on their electroencephalogram (EEG). It is necessary to detect spikes to diagnose BECT clinically. The template matching method can identify spikes effectively. However, due to the individual specificity, finding representative templates to detect spikes in actual applications is often challenging.

Purpose

This paper proposes a spike detection method using functional brain networks based on phase locking value (FBN-PLV) and deep learning.

Methods

To obtain high detection effect, this method uses a specific template matching method and the ‘peak-to-peak' phenomenon of montages to obtain a set of candidate spikes. With the set of candidate spikes, functional brain networks (FBN) are constructed based on phase locking value (PLV) to extract the features of the network structure during spike discharge with phase synchronization. Finally, the time domain features of the candidate spikes and the structural features of the FBN-PLV are input into the artificial neural network (ANN) to identify the spikes.

Results

Based on FBN-PLV and ANN, the EEG data sets of four BECT cases from the Children's Hospital, Zhejiang University School of Medicine are tested with the AC of 97.6%, SE of 98.3%, and SP 96.8%.

Poor School Academic Performance and Benign Epilepsy with Centro-Temporal Spikes

BACKGROUND

Poor academic performance of students with epilepsy seems to be a multifactorial problem related to difficulties in reading, writing, math, and logic skills. Poor school and academic performances refer to learning problems in a specific academic area due to learning disorders and learning difficulties not excluding the ability to learn in a different manner during school and academic life. Sometimes, school, academic difficulties, and Rolandic epilepsy can coexist together, and there may be comorbidities. Consequently, the risk of impaired academic performance in people with epilepsy is high.

METHODS

This review analyzed the relationship between Benign Epilepsy with Centro-Temporal Spikes (BECTS) and poor school and academic performance (PSAP) in children and adolescents (aged 6 to 19), and in adults (aged 20 to no age limit). The PRISMA guideline was used to guide our review strategy.

RESULTS

This research shows that Benign Epilepsy with Centro-Temporal Spikes (BECTS) and poor school and academic performances are strongly correlated. An early onset age, as well as a long persistence of seizures, correlate more closely with PSAP. On the other hand, it appears that good pharmacological control of seizures and remission from the acute phase of the pathology support better school performance.

CONCLUSIONS

This review highlights how neuropsychological aspects are also involved in patients with BECTS and PSAP, both in the greater predisposition to the establishment of other neuropsychiatric conditions and in the possibility that stigma conditions and poor academic results may have repercussions on the adaptation and functioning of these subjects. Global management of the subject with BECTS and PSAP is essential, which also pays attention to the aspects of social and scholastic inclusion, both to achieve age-appropriate educational and behavioral objectives, to give the necessary tools for the growth of the individual, and to allow a serene transition to adulthood, favoring autonomous learning and better outcomes.

Anti-Seizure Medication Treatment of Benign Childhood Epilepsy With Centrotemporal Spikes: A Systematic Review and Meta-analysis

Background: This study aimed to evaluate the efficacy and tolerability of Anti-Seizure medication (ASM) treatment in patients with BECTS. Method: We searched PubMed, Cochrane Library, Embase, MEDLINE, Web of Science, China National Knowledge Infrastructure (CNKI), WANFANG DATA, and China Science and Technology Journal Database (VIP) between 1 Jan 1990, and 1 Sep 2021, for randomized controlled studies. Data on seizure freedom rate, rate of treatment withdrawal due to serious adverse events, rate of any adverse events and dropout, 50% remission rate, the proportion of patients whose EEG to be normalized, and improvement in cognitive function were extracted by two authors independently. The pooled data were meta-analyzed using a random effects model. Results: A total of 27 studies evaluating 9 ASMs were included, 19 of which were suitable for meta-analysis. Compared with sulthiame (STM), levetiracetam (LEV) was associated with a higher probability of treatment withdrawal due to serious adverse events [RR = 5.12, 95% CI (1.19, 22.01), I ² = 0.0%], experiencing any adverse events [RR = 5.12, 95% CI (1.19, 22.01)], and dropping out for any reason [RR = 3.17, 95% CI (1.36, 10.11)], while it did not affect the seizure freedom rate [RR = 0.90, 95% CI (0.75, 1.06)]. LEV significantly improved cognitive performance relative to carbamazepine (CBZ) but had no effect on the proportion of any adverse events [RR = 0.62, 95% CI (0.25, 1.59)] and EEG to be normalized [RR = 1.27, 95% CI (0.94, 1.71)]. There was no higher probability of a 50% remission rate when comparing valproic acid (VPA) to LEV [RR = 0.96, 95% CI (0.57, 1.61)] and oxcarbazepine (OXC) [RR = 0.61, 95% CI (0.31, 1.20)]. In addition, STM was related to a higher probability of EEG normalization than placebo [RR = 4.61, 95% CI (2.12, 10.01)]. The included single studies also provided some evidence for the efficacy and/or tolerability of other ASMs in BECTS, including topiramate, lamotrigine, clobazam, and clonazepam. The risk of bias of the included studies was frequently low or unclear. Conclusion: This study indicated some discrepancies in efficacy and tolerability among ASMs used in patients with BECTS. More randomized controlled trials (RCTs) comparing ASMs with larger populations are required to ascertain the optimum antiepileptic drug treatment to guide clinicians.

Risk factors, etiologies, and comorbidities in urban pediatric epilepsy

The Seizures and Outcomes Study in Children (SOS-KIDS) identifies risk factors, etiologies, and comorbidities in a pediatric epilepsy population in a major city with diversity in socioeconomic levels. A thorough understanding of the range of issues impacting children with epilepsy is critical to establishing treatment that will produce better health outcomes. SOS-KIDS is a cross-sectional cohort study of pediatric epilepsy patients who live in Washington D.C. and are evaluated at Children's National Hospital. Families were recruited at the time of the child's routine clinic appointment or inpatient visit. Information was extracted from participants' electronic medical records (EMR) and parent reports; participants were screened for comorbidities using standardized screening measures. Data were collected from 289 participants (47% female, 53% male), and mean age was 7.9 years (2 months to 17 years). Twenty-nine percent of participants had primary generalized epilepsy, 63% focal epilepsy, 0.3% combined generalized and focal epilepsy, and 8% could not be distinguished. There were a variety of epilepsy risk factors including prematurity (10%), intraventricular hemorrhage (7%), neonatal seizures (8%), and febrile seizures (17%). The most common etiologies were cerebral malformations (13%) and genetic disorders (25%). Numerous participants had documented comorbidities including developmental delay (56%), intellectual disability (20%), headaches (16%), attention-deficit hyperactivity disorder (23%), and autism (7%). Of participants aged six years and older, depression, and anxiety were reported in 5% and 6% within the EMR, 14% and 19% in parent surveys, and 22% and 33% with standardized screening measures. We identified a wide variety of risk factors and etiologies among urban pediatric epilepsy patients, with genetic and structural being the most common. Neurologic and psychiatric comorbidities were common, but the prevalence of several psychiatric disorders reported within the EMR was substantially lower compared to that found when using parent surveys and standardized screening measures.

The epileptic network and cognition: What functional connectivity is teaching us about the childhood epilepsies

Our objective was to summarize and evaluate the rapidly expanding body of literature studying functional connectivity in childhood epilepsy. In the self-limited childhood epilepsies, awareness of cognitive comorbidities has been steadily increasing, and recent advances in our understanding of the network effects of these disorders promise insights into the underlying neurobiology. We reviewed publications addressing functional connectivity in children with epilepsy with an emphasis on studies of children with self-limited childhood epilepsies. The majority of studies have been published in the past 10 years and predominantly examine childhood epilepsy with centrotemporal spikes and childhood absence epilepsy. Cognitive network alterations are commonly observed across the childhood epilepsies. Some of these effects appear to be nonspecific to epilepsy syndrome or even to category of neurological disorder. Other patterns, such as changes in the connectivity of cortical language areas in childhood epilepsy with centrotemporal spikes, provide clues to the underlying cognitive deficits seen in affected children. The literature to date is dominated by general observations of connectivity patterns without a priori hypotheses. These data-driven studies build an important foundation for hypothesis generation and are already providing useful insights into the neuropathology of the childhood epilepsies. Future work should emphasize hypothesis-driven approaches and rigorous clinical correlations to better understand how the knowledge of network alterations can be applied to guidance and treatment for the children in our clinics.

Epilepsy and seizures in young people with 22q11.2 deletion syndrome: Prevalence and links with other neurodevelopmental disorders

OBJECTIVE

The true prevalence of epileptic seizures and epilepsy in 22q11.2 deletion syndrome (22q11.2DS) is unknown, because previous studies have relied on historical medical record review. Associations of epilepsy with other neurodevelopmental manifestations (eg, specific psychiatric diagnoses) remain unexplored.

METHODS

The primary caregivers of 108 deletion carriers (mean age 13.6 years) and 60 control siblings (mean age 13.1 years) completed a validated epilepsy screening questionnaire. A subsample (n = 44) underwent a second assessment with interview, prolonged electroencephalography (EEG), and medical record and epileptologist review. Intelligence quotient (IQ), psychopathology, and other neurodevelopmental problems were examined using neurocognitive assessment and questionnaire/interview.

RESULTS

Eleven percent (12/108) of deletion carriers had an epilepsy diagnosis (controls 0%, P = 0.004). Fifty-seven of the remaining 96 deletion carriers (59.4%) had seizures or seizurelike symptoms (controls 13.3%, 8/60, P < 0.001). A febrile seizure was reported for 24.1% (26/107) of cases (controls 0%, P < 0.001). One deletion carrier with a clinical history of epilepsy was diagnosed with an additional type of unprovoked seizure during the second assessment. One deletion carrier was newly diagnosed with epilepsy, and two more with possible nonmotor absence seizures. A positive screen on the epilepsy questionnaire was more likely in deletion carriers with lower performance IQ (odds ratio [OR] 0.96, P = 0.018), attention-deficit/hyperactivity disorder (ADHD) (OR 3.28, P = 0.021), autism symptoms (OR 3.86, P = 0.004), and indicative motor coordination disorder (OR 4.56, P = 0.021).

SIGNIFICANCE

Even when accounting for deletion carriers diagnosed with epilepsy, reports of seizures and seizurelike symptoms are common. These may be "true" epileptic seizures in some cases, which are not recognized during routine clinical care. Febrile seizures were far more common in deletion carriers compared to known population risk. A propensity for seizures in 22q11.2DS was associated with cognitive impairment, psychopathology, and motor coordination problems. Future research is required to determine whether this reflects common neurobiologic risk pathways or is a consequence of recurrent seizures.

Abnormal cortical activation during an auditory word comprehension task in benign childhood epilepsy with centrotemporal spikes: A magnetoencephalographic study

OBJECTIVE

Benign childhood epilepsy with centrotemporal spikes (BECTS), also known as rolandic epilepsy, has recently been reported to be associated with variable degrees of cognitive dysfunction. Many studies reported poor language ability in children with BECTS compared with healthy control children. To elucidate the harmful effects of BECTS on language cognition, we studied the magnetoencephalographic activity elicited by an auditory language comprehension task.

METHODS

The participants (N = 20) included 10 children diagnosed with BECTS (aged 10.8 ± 2.8 years) and 10 age-matched healthy children (control) (aged 10.6 ± 1.6 years). Cognitive function was assessed using general intellectual function and language ability. In patients with BECTS, we reviewed the clinical course and electroencephalogram (EEG) findings. We recorded the cortical responses elicited by an auditory language comprehension task using magnetoencephalography (MEG). We compared those results between groups and analyzed the correlation with cognitive scores and frequency of spikes.

RESULTS

The full-scale intelligence quotient (FSIQ) by the Wechsler Intelligence Scale for Children-4th edition was significantly reduced in the group with BECTS (96.4 ± 12.3) compared with the control group (110.0 ± 7.4). In half of the group with BECTS, the auditory comprehension score fell below the age-standard level. In the group with BECTS, the cortical activation during the task showed reduced intensity in language-associated areas such as the bilateral primary auditory cortex, left superior and mid-temporal areas, and inferior frontal area compared with those in the control group. In addition, the cortical activation in the left superior temporal area was negatively correlated with spike frequency and positively correlated with FSIQ in the group with BECTS. Conversely, the right inferior frontal and mid-temporal areas had increased the activations in the group with BECTS. From the time frequency analysis, low gamma band event-related desynchronization was reduced in the group with BECTS.

CONCLUSION

Epileptic spikes negatively influenced responsiveness to the auditory language comprehension task in the language-associated cortices. These findings suggest that epileptic spikes could have a negative impact on the functional activity in rolandic areas and become a reason to change the functional development of the language network.