-
Epilepsia May 2024Computer vision (CV) shows increasing promise as an efficient, low-cost tool for video seizure detection and classification. Here, we provide an overview of the... (Review)
Review
Computer vision (CV) shows increasing promise as an efficient, low-cost tool for video seizure detection and classification. Here, we provide an overview of the fundamental concepts needed to understand CV and summarize the structure and performance of various model architectures used in video seizure analysis. We conduct a systematic literature review of the PubMed, Embase, and Web of Science databases from January 1, 2000 to September 15, 2023, to identify the strengths and limitations of CV seizure analysis methods and discuss the utility of these models when applied to different clinical seizure phenotypes. Reviews, nonhuman studies, and those with insufficient or poor quality data are excluded from the review. Of the 1942 records identified, 45 meet inclusion criteria and are analyzed. We conclude that the field has shown tremendous growth over the past 2 decades, leading to several model architectures with impressive accuracy and efficiency. The rapid and scalable detection offered by CV models holds the potential to reduce sudden unexpected death in epilepsy and help alleviate resource limitations in epilepsy monitoring units. However, a lack of standardized, thorough validation measures and concerns about patient privacy remain important obstacles for widespread acceptance and adoption. Investigation into the performance of models across varied datasets from clinical and nonclinical environments is an essential area for further research.
Topics: Humans; Seizures; Electroencephalography; Video Recording
PubMed: 38426252
DOI: 10.1111/epi.17926 -
Epilepsy & Behavior : E&B Aug 2023Auditory seizures (AS) are a rare type of focal seizures. AS are classically thought to involve a seizure onset zone (SOZ) in the temporal lobe, but there remain... (Review)
Review
BACKGROUND
Auditory seizures (AS) are a rare type of focal seizures. AS are classically thought to involve a seizure onset zone (SOZ) in the temporal lobe, but there remain uncertainties about their localizing and lateralizing value. We conducted a narrative literature review with the aim of providing an up-to-date description of the lateralizing and localizing value of AS.
METHODS
The databases PubMed, Scopus, and Google Scholar were searched for literature on AS in December 2022. All cortical stimulation studies, case reports, and case series were analyzed to assess for auditory phenomena that were suggestive of AS and to evaluate if the lateralization and/or localization of the SOZ could be determined. We classified AS according to their semiology (e.g., simple hallucination versus complex hallucination) and the level of evidence with which the SOZ could be predicted.
RESULTS
A total of 174 cases comprising 200 AS were analyzed from 70 articles. Across all studies, the SOZ of AS were more often in the left (62%) than in the right (38%) hemisphere. AS heard bilaterally followed this trend. Unilaterally heard AS were more often due to a SOZ in the contralateral hemisphere (74%), although they could also be ipsilateral (26%). The SOZ for AS was not limited to the auditory cortex, nor to the temporal lobe. The areas more frequently involved in the temporal lobe were the superior temporal gyrus (STG) and mesiotemporal structures. Extratemporal locations included parietal, frontal, insular, and rarely occipital structures.
CONCLUSION
Our review highlighted the complexity of AS and their importance in the identification of the SOZ. Due to the limited data and heterogeneous presentation of AS in the literature, the patterns associated with different AS semiologies warrant further research.
Topics: Humans; Electroencephalography; Seizures; Epilepsy, Temporal Lobe; Temporal Lobe
PubMed: 37422934
DOI: 10.1016/j.yebeh.2023.109327 -
Neuropediatrics Dec 2023Hyperventilation and seizures have a long association in the clinical literature and were known to have a relationship long before the electroencephalogram (EEG) was... (Review)
Review
Hyperventilation and seizures have a long association in the clinical literature and were known to have a relationship long before the electroencephalogram (EEG) was used to record changes in brain activity. As the use of EEG recording progressed, hyperventilation was the first activation method used to assist with diagnosis of epilepsy. Along with slowing of brain activity, hyperventilation can activate epileptiform spiking activity in patients with epilepsy. Currently, hyperventilation is used in standard practice to assist with the diagnosis of epilepsy during EEG recording. Hyperventilation activates epileptiform spiking activity more often than seizures but can trigger clinical seizures in up to 50% of patients with generalized epilepsy. It is more likely to trigger events in children with absence seizures than adults, and it acts as a trigger in patients with focal epilepsy far less often. However, while some clinicians suggest that its diagnostic value is limited, especially in adults with focal epilepsies, others suggest that it is simple, safe, and an important diagnostic tool, even in these patients. This review presents the history of hyperventilation and seizures, its use in the clinical practice, and possible mechanisms involved.
Topics: Child; Adult; Humans; Hyperventilation; Seizures; Epilepsy; Epilepsies, Partial; Electroencephalography
PubMed: 37813123
DOI: 10.1055/s-0043-1774808 -
Epilepsy Research Aug 2023Generalised spike and wave discharges (SWDs) are pathognomonic EEG signatures for diagnosing absence seizures in patients with Genetic Generalized Epilepsy (GGE). The...
OBJECTIVE
Generalised spike and wave discharges (SWDs) are pathognomonic EEG signatures for diagnosing absence seizures in patients with Genetic Generalized Epilepsy (GGE). The Genetic Absence Epilepsy Rats from Strasbourg (GAERS) is one of the best-validated animal models of GGE with absence seizures.
METHODS
We developed an SWDs detector for both GAERS rodents and GGE patients with absence seizures using a neural network method. We included 192 24-hour EEG sessions recorded from 18 GAERS rats, and 24-hour scalp-EEG data collected from 11 GGE patients.
RESULTS
The SWDs detection performance on GAERS showed a sensitivity of 98.01% and a false positive (FP) rate of 0.96/hour. The performance on GGE patients showed 100% sensitivity in five patients, while the remaining patients obtained over 98.9% sensitivity. Moderate FP rates were seen in our patients with 2.21/hour average FP. The detector trained within our patient cohort was validated in an independent dataset, TUH EEG Seizure Corpus (TUSZ), that showed 100% sensitivity in 11 of 12 patients and 0.56/hour averaged FP.
CONCLUSIONS
We developed a robust SWDs detector that showed high sensitivity and specificity for both GAERS rats and GGE patients.
SIGNIFICANCE
This detector can assist researchers and neurologists with the time-efficient and accurate quantification of SWDs.
Topics: Rats; Animals; Epilepsy, Absence; Rats, Wistar; Epilepsy, Generalized; Seizures; Electroencephalography; Disease Models, Animal
PubMed: 37364342
DOI: 10.1016/j.eplepsyres.2023.107181 -
Epilepsia Sep 2023Previous studies suggested that patients with epilepsy might be able to forecast their own seizures. This study aimed to assess the relationships between premonitory...
OBJECTIVE
Previous studies suggested that patients with epilepsy might be able to forecast their own seizures. This study aimed to assess the relationships between premonitory symptoms, perceived seizure risk, and future and recent self-reported and electroencephalographically (EEG)-confirmed seizures in ambulatory patients with epilepsy in their natural home environments.
METHODS
Long-term e-surveys were collected from patients with and without concurrent EEG recordings. Information obtained from the e-surveys included medication adherence, sleep quality, mood, stress, perceived seizure risk, and seizure occurrences preceding the survey. EEG seizures were identified. Univariate and multivariate generalized linear mixed-effect regression models were used to estimate odds ratios (ORs) for the assessment of the relationships. Results were compared with the seizure forecasting classifiers and device forecasting literature using a mathematical formula converting OR to equivalent area under the curve (AUC).
RESULTS
Fifty-four subjects returned 10 269 e-survey entries, with four subjects acquiring concurrent EEG recordings. Univariate analysis revealed that increased stress (OR = 2.01, 95% confidence interval [CI] = 1.12-3.61, AUC = .61, p = .02) was associated with increased relative odds of future self-reported seizures. Multivariate analysis showed that previous self-reported seizures (OR = 5.37, 95% CI = 3.53-8.16, AUC = .76, p < .001) were most strongly associated with future self-reported seizures, and high perceived seizure risk (OR = 3.34, 95% CI = 1.87-5.95, AUC = .69, p < .001) remained significant when prior self-reported seizures were added to the model. No correlation with medication adherence was found. No significant association was found between e-survey responses and subsequent EEG seizures.
SIGNIFICANCE
Our results suggest that patients may tend to self-forecast seizures that occur in sequential groupings and that low mood and increased stress may be the result of previous seizures rather than independent premonitory symptoms. Patients in the small cohort with concurrent EEG showed no ability to self-predict EEG seizures. The conversion from OR to AUC values facilitates direct comparison of performance between survey and device studies involving survey premonition and forecasting.
Topics: Humans; Seizures; Epilepsy; Electroencephalography; Multivariate Analysis; Surveys and Questionnaires
PubMed: 37303239
DOI: 10.1111/epi.17678 -
Journal of Biological Physics Jun 2024Epilepsy is a type of brain disorder triggered by an abrupt electrical imbalance of neuronal networks. An electroencephalogram (EEG) is a diagnostic tool to capture the...
Epilepsy is a type of brain disorder triggered by an abrupt electrical imbalance of neuronal networks. An electroencephalogram (EEG) is a diagnostic tool to capture the underlying brain mechanisms and detect seizure onset in epileptic patients. To detect seizures, neurologists need to manually monitor EEG recordings for long periods, which is challenging and susceptible to errors depending on expertise and experience. Therefore, automatic identification of seizure and seizure-free EEG signals becomes essential. This study introduces a method based on the features extracted from the phase space reconstruction for classifying seizure and seizure-free EEG signals. The computed features are derived from the elliptical area and interquartile range of the Euclidean distance by varying percentage values of data points ranging from 50 to 100%. We consider two public datasets and evaluate these features in each EEG epoch that includes the healthy, interictal, preictal, and ictal stages of epileptic subjects, utilizing the K-nearest neighbor classifier for classification. Results show that the features have higher values during the seizure than the seizure-free EEG signals and healthy subjects. Furthermore, the proposed features can effectively discriminate seizure EEG signals from the seizure-free and normal subjects with 100% accuracy, sensitivity, and specificity in both datasets. Likewise, the classification between the preictal stage and seizure EEG signals attains 98% accuracy. Overall, the reconstructed phase space features significantly enhance the accuracy of detecting epileptic EEG signals compared with existing methods. This advancement holds great potential in assisting neurologists in swiftly and accurately diagnosing epileptic seizures from EEG signals.
Topics: Electroencephalography; Humans; Seizures; Signal Processing, Computer-Assisted; Automation
PubMed: 38466526
DOI: 10.1007/s10867-024-09654-6 -
Epilepsia Jan 2024Hemimegalencephaly (HME) is a rare congenital brain malformation presenting predominantly with drug-resistant epilepsy. Hemispheric disconnective surgery is the mainstay... (Observational Study)
Observational Study
OBJECTIVES
Hemimegalencephaly (HME) is a rare congenital brain malformation presenting predominantly with drug-resistant epilepsy. Hemispheric disconnective surgery is the mainstay of treatment; however, little is known about how postoperative outcomes compare across techniques. Thus we present the largest single-center cohort of patients with HME who underwent epilepsy surgery and characterize outcomes.
METHODS
This observational study included patients with HME at University of California Los Angeles (UCLA) from 1984 to 2021. Patients were stratified by surgical intervention: anatomic hemispherectomy (AH), functional hemispherectomy (FH), or less-than-hemispheric resection (LTH). Seizure freedom, functional outcomes, and operative complications were compared across surgical approaches. Regression analysis identified clinical and intraoperative variables that predict seizure outcomes.
RESULTS
Of 56 patients, 43 (77%) underwent FH, 8 (14%) underwent AH, 2 (4%) underwent LTH, 1 (2%) underwent unknown hemispherectomy type, and 2 (4%) were managed non-operatively. At median last follow-up of 55 months (interquartile range [IQR] 20-92 months), 24 patients (49%) were seizure-free, 17 (30%) required cerebrospinal fluid (CSF) shunting for hydrocephalus, 9 of 43 (21%) had severe developmental delay, 8 of 38 (21%) were non-verbal, and 15 of 38 (39%) were non-ambulatory. There was one (2%) intraoperative mortality due to exsanguination earlier in this cohort. Of 12 patients (29%) requiring revision surgery, 6 (50%) were seizure-free postoperatively. AH, compared to FH, was not associated with statistically significant improved seizure freedom (hazard ratio [HR] = .48, p = .328), although initial AH trended toward greater odds of seizure freedom (75% vs 46%, p = .272). Younger age at seizure onset (HR = .29, p = .029), lack of epilepsia partialis continua (EPC) (HR = .30, p = .022), and no contralateral seizures on electroencephalography (EEG) (HR = .33, p = .039) independently predicted longer duration of seizure freedom.
SIGNIFICANCE
This study helps inform physicians and parents of children who are undergoing surgery for HME by demonstrating that earlier age at seizure onset, absence of EPC, and no contralateral EEG seizures were associated with longer postoperative seizure freedom. At our center, initial AH for HME may provide greater odds of seizure freedom with complications and functional outcomes comparable to those of FH.
Topics: Child; Humans; Hemimegalencephaly; Treatment Outcome; Epilepsy; Hemispherectomy; Seizures; Electroencephalography
PubMed: 37873610
DOI: 10.1111/epi.17807 -
Pharmacotherapy Oct 2023Maintaining seizure control with lamotrigine is complicated by altered pharmacokinetics and existence of subpopulations in whom clearance increases or remains constant...
INTRODUCTION
Maintaining seizure control with lamotrigine is complicated by altered pharmacokinetics and existence of subpopulations in whom clearance increases or remains constant during pregnancy.
OBJECTIVE
Our objective was to characterize the potential for particular dosing scenarios to lead to increased seizure risk or toxicity.
METHODS
Lamotrigine pharmacokinetic parameters obtained from our previous study were applied to a one-compartment model structure with subpopulations (75:25%) exhibiting different clearance changes. A single-patient simulation was conducted with typical pharmacokinetic parameter values from each subpopulation. Population-level simulations (N = 48,000) included six dosing scenarios and considered four preconception doses using the R package mrgsolve (Metrum Research Group). Thresholds for efficacy and toxicity were selected as drug concentration that are 65% lower than preconception concentrations and doubling of preconception concentrations, respectively.
RESULTS
Individual simulation results demonstrated that without dose increases, concentrations fell below 0.65 at 6-8 weeks in the high clearance change (HC) subpopulation, depending on preconception clearance. While no simulated dosing regimen allowed all women in both subpopulations to maintain preconception concentrations, some regimens provided a more balanced risk profile than others. Predicted concentrations suggested potential increased seizure risk for 7%-100% of women in the HC group depending on preconception dose and subpopulation. Additionally, in 63% of dosing scenarios for women with low clearance change (LC), there was an increased risk of toxicity (34%-100% of women).
SIGNIFICANCE
A substantial percentage of simulated individuals had concentrations low enough to potentially increase seizure risk or high enough to create toxicity. Early clearance changes indicate possible subpopulation categorization if therapeutic drug monitoring is conducted in the first trimester. An arbitrary "one-size-fits-all" philosophy may not work well for lamotrigine dosing adjustments during pregnancy and reinforces the need for therapeutic drug monitoring until a patient is determined to be in the LC or HC group.
Topics: Pregnancy; Female; Humans; Lamotrigine; Epilepsy; Pregnancy Complications; Anticonvulsants; Seizures
PubMed: 37475496
DOI: 10.1002/phar.2856 -
Epilepsia Dec 2023Limited guidance exists regarding the assessment and management of psychogenic non-epileptic seizures (PNES) in children. Our aim was to develop consensus-based... (Review)
Review
Scoping review and expert-based consensus recommendations for assessment and management of psychogenic non-epileptic (functional) seizures (PNES) in children: A report from the Pediatric Psychiatric Issues Task Force of the International League Against Epilepsy.
Limited guidance exists regarding the assessment and management of psychogenic non-epileptic seizures (PNES) in children. Our aim was to develop consensus-based recommendations to fill this gap. The members of the International League Against Epilepsy (ILAE) Task Force on Pediatric Psychiatric Issues conducted a scoping review adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-SR) standards. This was supplemented with a Delphi process sent to pediatric PNES experts. Consensus was defined as ≥80% agreement. The systematic search identified 77 studies, the majority (55%) of which were retrospective (only one randomized clinical trial). The primary means of PNES identification was video electroencephalography (vEEG) in 84% of studies. Better outcome was associated with access to counseling/psychological intervention. Children with PNES have more frequent psychiatric disorders than controls. The Delphi resulted in 22 recommendations: Assessment-There was consensus on the importance of (1) taking a comprehensive developmental history; (2) obtaining a description of the events; (3) asking about potential stressors; (4) the need to use vEEG if available parent, self, and school reports and video recordings can contribute to a "probable" diagnosis; and (5) that invasive provocation techniques or deceit should not be employed. Management-There was consensus about the (1) need for a professional with expertise in epilepsy to remain involved for a period after PNES diagnosis; (2) provision of appropriate educational materials to the child and caregivers; and (3) that the decision on treatment modality for PNES in children should consider the child's age, cognitive ability, and family factors. Comorbidities-There was consensus that all children with PNES should be screened for mental health and neurodevelopmental difficulties. Recommendations to facilitate the assessment and management of PNES in children were developed. Future directions to fill knowledge gaps were proposed.
Topics: Humans; Child; Retrospective Studies; Consensus; Seizures; Epilepsy; Mental Disorders; Electroencephalography; Randomized Controlled Trials as Topic
PubMed: 37804168
DOI: 10.1111/epi.17768 -
Journal of Neural Engineering Aug 2023Epilepsy is a neurological disorder characterized by recurrent seizures which vary widely in severity, from clinically silent to prolonged convulsions. Measuring...
Epilepsy is a neurological disorder characterized by recurrent seizures which vary widely in severity, from clinically silent to prolonged convulsions. Measuring severity is crucial for guiding therapy, particularly when complete control is not possible. Seizure diaries, the current standard for guiding therapy, are insensitive to the duration of events or the propagation of seizure activity across the brain. We present a quantitative seizure severity score that incorporates electroencephalography (EEG) and clinical data and demonstrate how it can guide epilepsy therapies.We collected intracranial EEG and clinical semiology data from 54 epilepsy patients who had 256 seizures during invasive, in-hospital presurgical evaluation. We applied an absolute slope algorithm to EEG recordings to identify seizing channels. From this data, we developed a seizure severity score that combines seizure duration, spread, and semiology using non-negative matrix factorization. For validation, we assessed its correlation with independent measures of epilepsy burden: seizure types, epilepsy duration, a pharmacokinetic model of medication load, and response to epilepsy surgery. We investigated the association between the seizure severity score and preictal network features.The seizure severity score augmented clinical classification by objectively delineating seizure duration and spread from recordings in available electrodes. Lower preictal medication loads were associated with higher seizure severity scores (= 0.018, 97.5% confidence interval = [-1.242, -0.116]) and lower pre-surgical severity was associated with better surgical outcome (= 0.042). In 85% of patients with multiple seizure types, greater preictal change from baseline was associated with higher severity.We present a quantitative measure of seizure severity that includes EEG and clinical features, validated on gold standard in-patient recordings. We provide a framework for extending our tool's utility to ambulatory EEG devices, for linking it to seizure semiology measured by wearable sensors, and as a tool to advance data-driven epilepsy care.
Topics: Humans; Seizures; Epilepsy; Electroencephalography; Brain; Electrocorticography
PubMed: 37531949
DOI: 10.1088/1741-2552/aceca1