Seizure detection with automated EEG analysis: a validation study focusing on periodic patterns.

OBJECTIVE: To evaluate an automated seizure detection (ASD) algorithm in EEGs with periodic and other challenging patterns. METHODS: Selected EEGs recorded in patients over 1year old were classified into four groups: A. Periodic lateralized epileptiform discharges (PLEDs) with intermixed electrical seizures. B. PLEDs without seizures. C. Electrical seizures and no PLEDs. D. No PLEDs or seizures. Recordings were analyzed by the Persyst P12 software, and compared to the raw EEG, interpreted by two experienced neurophysiologists; Positive percent agreement (PPA) and false-positive rates/hour (FPR) were calculated. RESULTS: We assessed 98 recordings (Group A=21 patients; B=29, C=17, D=31). Total duration was 82.7h (median: 1h); containing 268 seizures. The software detected 204 (=76.1%) seizures; all ictal events were captured in 29/38 (76.3%) patients; in only in 3 (7.7%) no seizures were detected. Median PPA was 100% (range 0-100; interquartile range 50-100), and the median FPR 0/h (range 0-75.8; interquartile range 0-4.5); however, lower performances were seen in the groups containing periodic discharges. CONCLUSION: This analysis provides data regarding the yield of the ASD in a particularly difficult subset of EEG recordings, showing that periodic discharges may bias the results. SIGNIFICANCE: Ongoing refinements in this technique might enhance its utility and lead to a more extensive application

Status epilepticus of inflammatory etiology: A cohort study.

OBJECTIVE: Inflammation-related epilepsy is increasingly recognized; however, studies on status epilepticus (SE) are very infrequent. We therefore aimed to determine the frequency of inflammatory etiologies in adult SE, and to assess related demographic features and outcomes. METHODS: This was a retrospective analysis of a prospective registry of adult patients with SE treated in our center, from January 2008 to June 2014, excluding postanoxic causes. We classified SE episodes into 3 etiologic categories: infectious, autoimmune, and noninflammatory. Demographic and clinical variables were analyzed regarding their relationship to etiologies and functional outcome. RESULTS: Among the 570 SE consecutive episodes, 33 (6%) were inflammatory (2.5% autoimmune; 3.3% infectious), without any change in frequency over the study period. Inflammatory SE episodes involved younger patients (mean age 53 vs 61 years, p = 0.015) and were more often refractory to initial antiepileptic treatment (58% vs 38%, odds ratio = 2.19, 95% confidence interval = 1.07-4.47, p = 0.041), despite similar clinical outcome. Subgroup analysis showed that, compared with infectious SE episodes, autoimmune SE involved younger adults (mean age 44 vs 60 years, p = 0.017) and was associated with lower morbidity (return to baseline conditions in 71% vs 32%, odds ratio = 5.41, 95% confidence interval = 1.19-24.52, p = 0.043) without any difference in mortality. CONCLUSIONS: Despite increasing awareness, inflammatory SE etiologies were relatively rare; their occurrence in younger individuals and higher refractoriness to treatment did not have any effect on outcome. Autoimmune SE episodes also occurred in younger patients, but tended to have better outcomes in survivors than infectious SE

Evaluation of Wearable Electronics for Epilepsy: A Systematic Review

Epilepsy is a neurological disorder that affects 50 million people worldwide. It is characterised by seizures that can vary in presentation, from short absences to protracted convulsions. Wearable electronic devices that detect seizures have the potential to hail timely assistance for individuals, inform their treatment, and assist care and self-management. This systematic review encompasses the literature relevant to the evaluation of wearable electronics for epilepsy. Devices and performance metrics are identified, and the evaluations, both quantitative and qualitative, are presented. Twelve primary studies comprising quantitative evaluations from 510 patients and participants were collated according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Two studies (with 104 patients/participants) comprised both qualitative and quantitative evaluation components. Despite many works in the literature proposing and evaluating novel and incremental approaches to seizure detection, there is a lack of studies evaluating the devices available to consumers and researchers, and there is much scope for more complete evaluation data in quantitative studies. There is also scope for further qualitative evaluations amongst individuals, carers, and healthcare professionals regarding their use, experiences, and opinions of these devices

An Electrophysiological Investigation of Established and Novel Animal Models of Epileptogenesis

Temporal lobe epilepsy, defined by the increased propensity to display spontaneous seizures originating in the temporal lobe, is a pervasive condition presenting in nearly 1% of the global population. Epilepsy is also significantly comorbid with several affective and neurological disorders, including autism spectrum disorder (ASD). Despite significant inroads in the understanding of epilepsy throughout the past few decades, the underlying processes contributing to the slow development of epilepsy, known as epileptogenesis, are largely unknown. Utilizing 24/7 video EEG, these studies aimed to explore electrophysiological and behavioral changes within animals during the development of epilepsy. First, these experiments focused on a well-established animal model using pilocarpine-induced status-epilepticus to trigger epileptogenesis. Within this model, these studies charted electrophysiological biomarkers of epileptogenesis that serve predictive value in determining the time-course and risk for spontaneous seizures. Development of an active biomarker was able to chart the long-term changes in hippocampal auditory evoked potentials indicative of epilepsy risk. Continuous monitoring of animals within this model was then used to solidify quantitative characteristics of seizure subtypes and epilepsy progression that should serve as a definitive framework for future epilepsy studies. These findings indicated that seizures associated with mild behavioral impairments in animals, reflective of partial seizures in the human population, present with similar electrographic and temporal characteristics as more severe convulsive seizures. Additionally, this work demarcated between spectral characteristic indicative of bona-fide seizures and alternative electrographic events that may be benign. Together, both studies within the pilocarpine model demonstrated the progressive nature of epileptogenesis. Finally, the relational aspects of epileptogenesis in conjunction with co-occurring ASD was assessed using a novel stress-terbutaline animal model of ASD and epilepsy comorbidity by targeting stress-induced inflammation with repeated immunizations of a heat-killed immunomodulatory microbe Mycobacterium vaccae. Results from this final experiment demonstrated a divergence of ASD-like behavior from the development of spontaneous seizures, identifying common pathological mediator, but delineating between mechanisms of comorbidity expression. The amelioration of ASD-like behavior, despite progressive epileptogenesis, suggests that these comorbid disorders may be more separate than initially thought.</p

Doctor of Philosophy

dissertationOne in 26 people in America will develop epilepsy at some point in their life. Approximately one-third of patients with epilepsy do not have full control of their seizures on their current antiseizure drug (ASD) regimen. In the past 20 years, 16 new ASDs have been made available to the patient with epilepsy. However, the percentage of pharmacoresistant patients has remained relatively constant. Thus, it is necessary to explore alternative avenues to explain the lack of seizure control in these patients. It is unknown how the practice of nonadherence contributes to the percentage of refractory patients. An animal model of nonadherence would permit the study of nonadherence and its consequences on seizure control. To model nonadherence, a computer-automated system was created to dose animals with antiseizure drugs (ASDs) using a drug-in-food protocol. Two studies were conducted and serve as a first-pass characterization. In the first study, newly-diagnosed epileptic rats were administered carbamazepine (CBZ) at varying levels of adherence. Two groups, one adherent (100%), and one nonadherent (50%), were compared to placebo control (0%). The 50% group displayed similar seizure frequency and severity to the placebo controls, while the 100% adherent group were observed to have fewer seizures overall. This suggesting that taking medication 50% of the time had no measurable effect on seizure control. In the second study, a group of newly diagnosed epileptic rats was subjected to a two-week on (100%), two-week off (0%) and two-week on CBZ (100%) paradigm. Despite numerous seizures after discontinuation of CBZ treatment, animals regained the same level of seizure control when CBZ treatment was reinstituted. Finally, nonadherence can lead to status epilepticus (SE), a severe seizure lasting several minutes. In an effort to aid drug discovery, a new and simple method which results in an unbiased method to assess the duration and severity of the electrographic component of SE was created. This method has been used to quantify the response of electrographic SE to novel investigational compounds. Together, this dissertation aims to aid in the treatment of epilepsy by providing etiologically relevant models of nonadherence and analysis of electrographic SE

EEG-based grading of Immune Effector Cell-Associated Neurotoxicity Syndrome

CAR-T cell therapy is an effective cancer therapy for multiple refractory/relapsed hematologic malignancies but is associated with substantial toxicity, including Immune Effector Cell Associated Neurotoxicity Syndrome (ICANS). Improved detection and assessment of ICANS could improve management and allow greater utilization of CAR-T cell therapy, however, an objective, specific biomarker has not been identified. We hypothesized that the severity of ICANS can be quantified based on patterns of abnormal brain activity seen in electroencephalography (EEG) signals. We conducted a retrospective observational study of 120 CAR-T cell therapy patients who had received EEG monitoring. We determined a daily ICANS grade for each patient through chart review. We used visually assessed EEG features and machine learning techniques to develop the Visual EEG-Immune Effector Cell Associated Neurotoxicity Syndrome (VE-ICANS) score and assessed the association between VE-ICANS and ICANS. We also used it to determine the significance and relative importance of the EEG features. We developed the Visual EEG-ICANS (VE-ICANS) grading scale, a grading scale with a physiological basis that has a strong correlation to ICANS severity (R = 0.58 [0.47-0.66]) and excellent discrimination measured via area under the receiver operator curve (AUC = 0.91 for ICANS ≥ 2). This scale shows promise as a biomarker for ICANS which could help to improve clinical care through greater accuracy in assessing ICANS severity

Interrogating spatiotemporal patterns of resting state neuronal and hemodynamic activity in the awake mouse model

Since the advent of functional magnetic resonance imaging (fMRI) and the rise in popularity of its use for resting state functional connectivity mapping (rs-FCM) to non-invasively detect correlated networks of brain activity in human and animal models, many resting state FCM studies have reported differences in these networks under pathologies such as Alzheimer’s or schizophrenia, highlighting the potential for the method’s diagnostic relevance. A common underlying assumption of this analysis, however, is that the blood oxygen level dependent (BOLD) signal of fMRI is a direct measurement of local neural activity. The BOLD signal is in fact a measurement of the local changes in concentration of deoxy-hemoglobin (HbR). Thus, it is imperative that neurovascular coupling—the relationship between neuronal activity and subsequent hemodynamic activity—be better characterized to enable accurate interpretation of resting state fMRI in the context of clinical usage. This dissertation first describes the development and utility of WFOM paradigm for the robust and easily adaptable imaging of simultaneous neuronal and hemodynamic activity in awake mouse models of health or disease in strains with genetically encoded fluorescent calcium reporters. Subsequent exploration of resting state WFOM data collected in Thy1-GCaMP3 and Thy1-GCaMP6f mouse strains is then presented, namely the characterization of spatiotemporal patterns of neuronal and hemodynamic activity and different modulatory depths of neuronal activity via a toolbox of unsupervised blind source separation (e.g. k-means clustering) and supervised (e.g. non-negative least squares, Pearson correlation) analysis tools. The presence of these different modulatory depths of neuronal activity were then confirmed in another Thy1-jRGECO1a mouse strain using the same imaging scheme. Finally, the dissertation documents the application of the WFOM paradigm and select analysis tools to a novel mouse model of diffusely infiltrating glioma, through which neuronal and hemodynamic activity changes during diffusely infiltrating glioma development which impact temporal coherence of the tumor region activity relative to non-tumor regions activity were recorded and analyzed. The paradigm also allowed for recording of numerous spontaneous occurrences of interictal neuronal activity during which neurovascular coupling is modified in the tumor, as well as occurrences of non-convulsive generalized seizure activity (during which neurovascular is non-linear and cortex eventually suffers hypoxia). The detection of spatiotemporal patterns and different modulatory depths of activity in the awake mouse cortex, as well as observation of changes in functional activity in the context of diffusely infiltrating glioma, provide us with new insights into the possible mechanisms underlying variations in resting state connectivity networks found in resting state fMRI studies comparing health and disease states

Mining Biomarkers Of Epilepsy From Large-Scale Intracranial Electroencephalography

Epilepsy is a chronic neurological disorder characterized by seizures. Affecting over 50 million people worldwide, the quality of life of a patient with uncontrolled epilepsy is degraded by medical, social, cognitive, and psychological dysfunction. Fortunately, two-thirds of these patients can achieve adequate seizure control through medications. Unfortunately, one-third cannot. Improving treatment for this patient population depends upon improving our understanding of the underlying epileptic network. Clinical therapies modulate this network to some degree of success, including surgery to remove the seizure onset zone or neuromodulation to alter the brain\u27s dynamics. High resolution intracranial EEG (iEEG) is often employed to study the dynamics of cortical networks, from interictal patterns to more complex quantitative features. These interictal patterns include epileptiform biomarkers whose detection and mapping, along with seizures and neuroimaging, form the mainstay of data for clinical decision making around drug therapy, surgery, and devices. They are also increasingly important to assess the effects of epileptic physiology on brain functions like behavior and cognition, which are not well characterized. In this work, we investigate the significance and trends of epileptiform biomarkers in animal and human models of epilepsy. We develop reliable methods to quantify interictal patterns, applying state of the art techniques from machine learning, signal processing, and EEG analysis. We then validate these tools in three major applications: 1. We study the effect of interictal spikes on human cognition, 2. We assess trends of interictal epileptiform bursts and their relationship to seizures in prolonged recordings from canines and rats, and 3. We assess the stability of long-term iEEG spanning several years. These findings have two main impacts: (1) they inform the interpretation of interictal iEEG patterns and elucidate the timescale of post-implantation changes. These findings have important implications for research and clinical care, particularly implantable devices and evaluating patients for epilepsy surgery. (2) They provide an analytical framework to enable others to mine large-scale iEEG datasets. In this way we hope to make a lasting contribution to accelerate collaborative research not only in epilepsy, but also in the study of animal and human electrophysiology in acute and chronic conditions

Investigating the use of medicines in management of children and young people with epilepsy using data from primary care in the UK

Background: Epilepsy is a serious chronic neurological disorder that has a higher incidence in children and young people (CYP) than in adults. Epilepsy negatively impacts physical and psychosocial quality of life of CYP. Good outcomes of epilepsy are associated with optimal choice of drug treatment and adequate adherence to the prescribed medicines. Research on the patterns of medication use and adherence to prescribed medicines in CYP remains limited. The long-term clinical outcomes and costs of treating epilepsy have not been extensively studied in CYP in the UK. Aim of the study: This thesis aimed to investigate the pattern of antiepileptic drug (AED) prescribing and the dynamic of medication adherence in CYP with epilepsy. The long-term clinical outcomes and direct costs of treating epilepsy in CYP were estimated at population level. Methods: This study is an observational cohort study of CYP, age 0-17 years, identified from The Health Improvement Network (THIN) primary care database from the UK between January 1988 and December 2004. Four different analyses were carried out on this cohort. First, a cross-sectional design repeated annually was employed to estimate the incidence and prevalence of epilepsy and the pattern of AED prescribing in this population. Secondly, the long-term adherence to prescribed AEDs was calculated using the medication possession ratio (MPR) method. Applying panel data analysis and the Generalised Estimating Equation (GEE) multivariate regression, factors that may have been associated with adherence to the prescribed AEDs were examined. Thirdly, seizure outcomes in terms of seizure frequency and remission of seizures and potential associated factors were assessed using the method of multiple failure survival analysis. Finally, the direct costs of treating epilepsy in CYP in primary care were estimated and stratified by the number of years after the first recording of epilepsy in THIN data. Results: Of total 528,760 CYP born on or after 1st January 1988 and registered in general practices contributed to THIN until 31st December 2004, 2020 CYP were identified who had a diagnosis of epilepsy, from under 1 up to 16.3 years of age (mean=5.6; SD=4.1). The annual incidence of epilepsy in CYP stratified by calendar years ranged from 44.4 (95% CI=31.9-61.8) to 61.2 (95% CI=50.6 -74.1) per 100,000 person-years. Incidence of epilepsy was significantly higher in children with greater socioeconomic deprivation than those with lower deprivation. Around 60% of CYP with epilepsy were prescribed monotherapy each year. Old AEDs such as carbamazepine and sodium valproate were the most frequently prescribed drugs and often prescribed as monotherapy to control epilepsy throughout 1990-2003. Prescribing of lamotrigine, a new AED, increased from 0.07 per person-years in 1992 to 2 per person-years in 2003. The calculated annual adherence to AEDs showed that around 50% of CYP adhered to at least 80% of the prescribed medications each year. Demographic characteristics of CYP were of little significance to affect adherence levels. The incidence of seizures was 0.73 (95% CI=0.71-0.75) per person-years. Incidence of seizures was higher in younger children up to 2 years and decreased with increasing age. A proportion of 94% (95% CI=93%, 96%) of CYP achieved 1 year remission of seizures, 80% (95% CI= 78%, 83%) achieved 2 years and 47% (95% CI=43%, 50%) achieved 5 years remission of seizures. The mean total direct cost associated with treating epilepsy in CYP, according to information in the general practice records that also indicated specialist and hospital care, was estimated at £ 1,153 (SD=1,808) per child in the first year following epilepsy diagnosis and at £459 (SD=1,633) per child for subsequent years. The costs of hospital care and AEDs represented the highest contribution to the total direct costs of epilepsy. The annual direct cost was significantly higher in younger children up to 2 years old. No significant difference in the annual costs was observed between CYP who adhered to at least 80% of medications and those who adhered to less than 80%. Conclusions: The incidence of epilepsy was highest in young children and CYP of higher socioeconomic deprivation. Old AEDs were most often prescribed as first-line drugs and as monotherapy to control epilepsy. Of newer AEDs, there was an increasing trend of prescribing lamotrigine and topiramate as add-on therapy. Long-term adherence to prescribed AEDs was suboptimal in one-half of CYP and positively associated with higher seizure frequency. Inpatient hospital care and drugs were the major contributors to the direct costs of treating epilepsy in CYP. Non-adherence to prescribed medicines was associated with higher hospital care costs but not with total direct costs as the medicines themselves made large contribution to the direct cost

Underlying Mechanisms of Epilepsy

This book is a very provocative and interesting addition to the literature on Epilepsy. It offers a lot of appealing and stimulating work to offer food of thought to the readers from different disciplines. Around 5% of the total world population have seizures but only 0.9% is diagnosed with epilepsy, so it is very important to understand the differences between seizures and epilepsy, and also to identify the factors responsible for its etiology so as to have more effective therapeutic regime. In this book we have twenty chapters ranging from causes and underlying mechanisms to the treatment and side effects of epilepsy. This book contains a variety of chapters which will stimulate the readers to think about the complex interplay of epigenetics and epilepsy