Ictal Central Apnea Is Predictive of Mesial Temporal Seizure Onset: An Intracranial Investigation.

OBJECTIVE: Ictal central apnea (ICA) is a semiological sign of focal epilepsy, associated with temporal and frontal lobe seizures. In this study, using qualitative and quantitative approaches, we aimed to assess the localizational value of ICA. We also aimed to compare ICA clinical utility in relation to other seizure semiological features of focal epilepsy. METHODS: We analyzed seizures in patients with medically refractory focal epilepsy undergoing intracranial stereotactic electroencephalographic (SEEG) evaluations with simultaneous multimodal cardiorespiratory monitoring. A total of 179 seizures in 72 patients with reliable artifact-free respiratory signal were analyzed. RESULTS: ICA was seen in 55 of 179 (30.7%) seizures. Presence of ICA predicted a mesial temporal seizure onset compared to those without ICA (odds ratio = 3.8, 95% confidence interval = 1.3-11.6, p = 0.01). ICA specificity was 0.82. ICA onset was correlated with increased high-frequency broadband gamma (60-150Hz) activity in specific mesial or basal temporal regions, including amygdala, hippocampus, and fusiform and lingual gyri. Based on our results, ICA has an almost 4-fold greater association with mesial temporal seizure onset zones compared to those without ICA and is highly specific for mesial temporal seizure onset zones. As evidence of symptomatogenic areas, onset-synchronous increase in high gamma activity in mesial or basal temporal structures was seen in early onset ICA, likely representing anatomical substrates for ICA generation. INTERPRETATION: ICA recognition may help anatomoelectroclinical localization of clinical seizure onset to specific mesial and basal temporal brain regions, and the inclusion of these regions in SEEG evaluations may help accurately pinpoint seizure onset zones for resection. ANN NEUROL 2024;95:998-1008.

Reliable detection of generalized convulsive seizures using an off-the-shelf digital watch: A multisite phase 2 study.

OBJECTIVE: The aim of this study was to develop a machine learning algorithm using an off-the-shelf digital watch, the Samsung watch (SM-R800), and evaluate its effectiveness for the detection of generalized convulsive seizures (GCS) in persons with epilepsy. METHODS: This multisite epilepsy monitoring unit (EMU) phase 2 study included 36 adult patients. Each patient wore a Samsung watch that contained accelerometer, gyroscope, and photoplethysmographic sensors. Sixty-eight time and frequency domain features were extracted from the sensor data and were used to train a random forest algorithm. A testing framework was developed that would better reflect the EMU setting, consisting of (1) leave-one-patient-out cross-validation (LOPO CV) on GCS patients, (2) false alarm rate (FAR) testing on nonseizure patients, and (3) "fixed-and-frozen" prospective testing on a prospective patient cohort. Balanced accuracy, precision, sensitivity, and FAR were used to quantify the performance of the algorithm. Seizure onsets and offsets were determined by using video-electroencephalographic (EEG) monitoring. Feature importance was calculated as the mean decrease in Gini impurity during the LOPO CV testing. RESULTS: LOPO CV results showed balanced accuracy of .93 (95% confidence interval [CI] = .8-.98), precision of .68 (95% CI = .46-.85), sensitivity of .87 (95% CI = .62-.96), and FAR of .21/24 h (interquartile range [IQR] = 0-.90). Testing the algorithm on patients without seizure resulted in an FAR of .28/24 h (IQR = 0-.61). During the "fixed-and-frozen" prospective testing, two patients had three GCS, which were detected by the algorithm, while generating an FAR of .25/24 h (IQR = 0-.89). Feature importance showed that heart rate-based features outperformed accelerometer/gyroscope-based features. SIGNIFICANCE: Commercially available wearable digital watches that reliably detect GCS, with minimum false alarm rates, may overcome usage adoption and other limitations of custom-built devices. Contingent on the outcomes of a prospective phase 3 study, such devices have the potential to provide non-EEG-based seizure surveillance and forecasting in the clinical setting.

Stimulation-induced respiratory enhancement in corticothalamic regions.

OBJECTIVE: We aimed to identify corticothalamic areas and electrical stimulation paradigms that optimally enhance breathing. METHODS: Twenty-nine patients with medically intractable epilepsy were prospectively recruited in an epilepsy monitoring unit while undergoing stereoelectroencephalographic evaluation. Direct electrical stimulation in cortical and thalamic regions was carried out using low (<1 Hz) and high (≥10 Hz) frequencies, and low (<5 mA) and high (≥5 mA) current intensities, with pulse width of .1 ms. Electrocardiography, arterial oxygen saturation (SpO2 ), end-tidal carbon dioxide (ETCO2 ), oronasal airflow, and abdominal and thoracic plethysmography were monitored continuously during stimulations. Airflow signal was used to estimate breathing rate, tidal volume, and minute ventilation (MV) changes during stimulation, compared to baseline. RESULTS: Electrical stimulation increased MV in the amygdala, anterior cingulate, anterior insula, temporal pole, and thalamus, with an average increase in MV of 20.8% ± 28.9% (range = 0.2%-165.6%) in 19 patients. MV changes were associated with SpO2 and ETCO2 changes (p < .001). Effects on respiration were parameter and site dependent. Within amygdala, low-frequency stimulation of the medial region produced 78.49% greater MV change (p < .001) compared to high-frequency stimulation. Longer stimulation produced greater MV changes (an increase of 4.47% in MV for every additional 10 s, p = .04). SIGNIFICANCE: Stimulation of amygdala, anterior cingulate gyrus, anterior insula, temporal pole, and thalamus, using certain stimulation paradigms, enhances respiration. Among tested paradigms, low-frequency, low-intensity, long-duration stimulation of the medial amygdala is the most effective breathing enhancement stimulation strategy. Such approaches may pave the way for the future development of neuromodulatory techniques that aid rescue from seizure-related apnea, potentially as a targeted sudden unexpected death in epilepsy prevention method.

Subject-Specific Activation of Central Respiratory Centers during Breath-Holding Functional Magnetic Resonance Imaging.

BACKGROUND: Voluntary breath-holding (BH) triggers responses from central neural control and respiratory centers in order to restore breathing. Such responses can be observed using functional MRI (fMRI). OBJECTIVES: We used this paradigm in healthy volunteers with the view to develop a biomarker that could be used to investigate disorders of the central control of breathing at the individual patient level. METHOD: In 21 healthy human subjects (mean age±SD, 32.8 ± 9.9 years old), fMRI was used to determine, at both the individual and group levels, the physiological neural response to expiratory and inspiratory voluntary apneas, within respiratory control centers in the brain and brainstem. RESULTS: Group analysis showed that expiratory BH, but not inspiratory BH, triggered activation of the pontine respiratory group and raphe nuclei at the group level, with a significant relationship between the levels of activation and drop in SpO2. Using predefined ROIs, expiratory BH, and to a lesser extent, inspiratory BH were associated with activation of most respiratory centers. The right ventrolateral nucleus of the thalamus, right pre-Bötzinger complex, right VRG, right nucleus ambiguus, and left Kölliker-Fuse-parabrachial complex were only activated during inspiratory BH. Individual analysis identified activations of cortical/subcortical and brainstem structures related to respiratory control in 19 out of 21 subjects. CONCLUSION: Our study shows that BH paradigm allows to reliably trigger fMRI response from brainstem and cortical areas involved in respiratory control at the individual level, suggesting that it might serve as a clinically relevant biomarker to investigate conditions associated with an altered central control of respiration.

Forecasting seizure clusters from chronic ambulatory electrocorticography.

Seizure clusters are seizures that occur in rapid succession during periods of heightened seizure risk and are associated with substantial morbidity and sudden unexpected death in epilepsy. The objective of this feasibility study was to evaluate the performance of a novel seizure cluster forecasting algorithm. Chronic ambulatory electrocorticography recorded over an average of 38 months in 10 subjects with drug-resistant epilepsies was analyzed pseudoprospectively by dividing data into training (first 85%) and validation periods. For each subject, the probability of seizure clustering, derived from the Kolmogorov-Smirnov statistic using a novel algorithm, was forecasted in the validation period using individualized autoregressive models that were optimized from training data. The primary outcome of this study was the mean absolute scaled error (MASE) of 1-day horizon forecasts. From 10 subjects, 394 ± 142 (mean ± SD) electrocorticography-based seizure events were extracted for analysis, representing a span of 38 ± 27 months of recording. MASE across all subjects was .74 ± .09, .78 ± .09, and .83 ± .07 at .5-, 1-, and 2-day horizons. The feasibility study demonstrates that seizure clusters are quasiperiodic and can be forecasted to clinically meaningful horizons. Pending validation in larger cohorts, the forecasting approach described herein may herald chronotherapy during imminent heightened seizure vulnerability.

Limbic and paralimbic respiratory modulation: From inhibition to enhancement.

OBJECTIVE: Increased understanding of the role of cortical structures in respiratory control may help the understanding of seizure-induced respiratory dysfunction that leads to sudden unexpected death in epilepsy (SUDEP). The aim of this study was to characterize respiratory responses to electrical stimulation (ES), including inhibition and enhancement of respiration. METHODS: We prospectively recruited 19 consecutive patients with intractable epilepsy undergoing stereotactic electroencephalography (EEG) evaluation from June 2015 to June 2018. Inclusion criteria were patients ≥18 years in whom ES was indicated for clinical mapping of ictal onset or eloquent cortex as part of the presurgical evaluation. ES was carried out at 50 Hz, 0.2 msec, and 1-10 mA current intensity. Common brain regions sampled across all patients were amygdala (AMY), hippocampus (HG), anterior cingulate gyrus (CING), orbitofrontal cortex (OrbF), temporal neocortex (TNC), temporal pole (TP), and entorhinal cortex (ERC). Seven hundred fifty-five stimulations were conducted. Quantitative analysis of breathing signal, that is, changes in breathing rate (BR), depth (TV), and minute ventilation (MV), was carried out during ES using the BreathMetrics breathing waveform analysis toolbox. Electrocardiography, arterial oxygen saturation, end-tidal and transcutaneous carbon dioxide, nasal airflow, and abdominal and thoracic plethysmography were monitored continuously during stimulations. RESULTS: Electrical stimulation of TP and CING (at lower current strengths <3 mA) increased TV and MV. At >7-10 mA, CING decreased TV and MV. On the other hand, decreased TV and MV occurred with stimulation of mesial temporal structures such as AMY and HG. Breathing changes were dependent on stimulation intensity. Lateral temporal, entorhinal, and orbitofrontal cortices did not affect breathing either way. SIGNIFICANCE: These findings suggest that breathing responses other than apnea can be induced by ES. Identification of two regions-the temporal pole and anterior cingulate gyrus-for enhancement of breathing may be important in paving the way to future development of strategies for prevention of SUDEP.

Can Big Data guide prognosis and clinical decisions in epilepsy?

Big Data is no longer a novel concept in health care. Its promise of positive impact is not only undiminished, but daily enhanced by seemingly endless possibilities. Epilepsy is a disorder with wide heterogeneity in both clinical and research domains, and thus lends itself to Big Data concepts and techniques. It is therefore inevitable that Big Data will enable multimodal research, integrating various aspects of "-omics" domains, such as phenome, genome, microbiome, metabolome, and proteome. This scope and granularity have the potential to change our understanding of prognosis and mortality in epilepsy. The scale of new discovery is unprecedented due to the possibilities promised by advances in machine learning, in particular deep learning. The subsequent possibilities of personalized patient care through clinical decision support systems that are evidence-based, adaptive, and iterative seem to be within reach. A major objective is not only to inform decision-making, but also to reduce uncertainty in outcomes. Although the adoption of electronic health record (EHR) systems is near universal in the United States, for example, advanced clinical decision support in or ancillary to EHRs remains sporadic. In this review, we discuss the role of Big Data in the development of clinical decision support systems for epilepsy care, prognostication, and discovery.

Ictal Lid Movements: Blinks and Lid Saccades.

Two types of lid movements, blinks and lid saccades, have discrete kinematic properties and physiology. These differences are reflected in distinct phenomenology of disorders affecting their neural substrate. Proof of this principle was seen in two patients, one with parietal lobe epilepsy and the other with temporal lobe epilepsy. The lid movements in the patient with parietal lobe epilepsy were rhythmic, yoked, and had a rapid upward component that instantaneously followed a slow downward drift. These cyclic movements strikingly resembled nystagmus, but unlike typical eye nystagmus, the rapid upward component was pathological and seemed to involve a saccadic mechanism. We suggest the terms "ictal lid saccades" or "ictal lid nystagmus" to describe such a phenomenon. In contrast, the patient with temporal lobe epilepsy had ipsilateral lid movements with rapid downward trajectories resembling reflex or spontaneous blinks. The term "ictal blink" is appropriate for this phenomenon.

Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy.

Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene and drug discovery, imaging, electroencephalography, pathology, epilepsy surgery, digital technologies, and numerous others. Epilepsy data are collected in the terabytes and petabytes, pushing the limits of current capabilities. Modern computing firepower and advances in machine and deep learning, pioneered in other diseases, open up exciting possibilities for epilepsy too. However, without carefully designed approaches to acquiring, standardizing, curating, and making available such data, there is a risk of failure. Thus, careful construction of relevant ontologies, with intimate stakeholder inputs, provides the requisite scaffolding for more ambitious big data undertakings, such as an epilepsy data commons. In this review, we assess the clinical and research epilepsy landscapes in the big data arena, current challenges, and future directions, and make the case for a systematic approach to epilepsy big data.

Peri-ictal hypoxia is related to extent of regional brain volume loss accompanying generalized tonic-clonic seizures.

OBJECTIVES: Hypoxia, or abnormally low blood-oxygen levels, often accompanies seizures and may elicit brain structural changes in people with epilepsy which contribute to central processes underlying sudden unexpected death in epilepsy (SUDEP). The extent to which hypoxia may be related to brain structural alterations in this patient group remains unexplored. METHODS: We analyzed high-resolution T1-weighted magnetic resonance imaging (MRI) to determine brain morphometric and volumetric alterations in people with generalized tonic-clonic seizures (GTCS) recorded during long-term video-electroencephalography (VEEG), recruited from two sites (n = 22), together with data from age- and sex-matched healthy controls (n = 43). Subjects were sub-divided into those with mild/moderate (GTCS-hypox-mild/moderate, n = 12) and severe (GTCS-hypox-severe, n = 10) hypoxia, measured by peripheral oxygen saturation (SpO2 ) during VEEG. Whole-brain voxel-based morphometry (VBM) and regional volumetry were used to assess group comparisons and correlations between brain structural measurements as well as the duration and extent of hypoxia during GTCS. RESULTS: Morphometric and volumetric alterations appeared in association with peri-GTCS hypoxia, including volume loss in the periaqueductal gray (PAG), thalamus, hypothalamus, vermis, cerebellum, parabrachial pons, and medulla. Thalamic and PAG volume was significantly reduced in GTCS patients with severe hypoxia compared with GTCS patients with mild/moderate hypoxia. Brainstem volume loss appeared in both hypoxia groups, although it was more extensive in those with severe hypoxia. Significant negative partial correlations emerged between thalamic and hippocampal volume and extent of hypoxia, whereas vermis and accumbens volumes declined with increasing hypoxia duration. SIGNIFICANCE: Brain structural alterations in patients with GTCS are related to the extent of hypoxia in brain sites that serve vital functions. Although the changes are associative only, they provide evidence of injury to regulatory brain sites related to respiratory manifestations of seizures.

A community effort for automatic detection of postictal generalized EEG suppression in epilepsy.

Applying machine learning to healthcare sheds light on evidence-based decision making and has shown promises to improve healthcare by combining clinical knowledge and biomedical data. However, medicine and data science are not synchronized. Oftentimes, researchers with a strong data science background do not understand the clinical challenges, while on the other hand, physicians do not know the capacity and limitation of state-of-the-art machine learning methods. The difficulty boils down to the lack of a common interface between two highly intelligent communities due to the privacy concerns and the disciplinary gap. The School of Biomedical Informatics (SBMI) at UTHealth is a pilot in connecting both worlds to promote interdisciplinary research. Recently, the Center for Secure Artificial Intelligence For hEalthcare (SAFE) at SBMI is organizing a series of machine learning healthcare hackathons for real-world clinical challenges. We hosted our first Hackathon themed centered around Sudden Unexpected Death in Epilepsy and finding ways to recognize the warning signs. This community effort demonstrated that interdisciplinary discussion and productive competition has significantly increased the accuracy of warning sign detection compared to the previous work, and ultimately showing a potential of this hackathon as a platform to connect the two communities of data science and medicine.

Risks and predictive biomarkers of sudden unexpected death in epilepsy patient.

PURPOSE OF REVIEW: The current review updates our knowledge regarding sudden unexpected death in epilepsy patient (SUDEP) risks, risk factors, and investigations of putative biomarkers based on suspected mechanisms of SUDEP. RECENT FINDINGS: The overall incidence of SUDEP in adults with epilepsy is 1.2/1000 patient-years, with surprisingly comparable figures in children in recently published population-based studies. This risk was found to decrease over time in several cohorts at a rate of -7% per year, for unknown reasons. Well established risk factors include frequency of generalized tonic-clonic seizures, while adding antiepileptic treatment, nocturnal supervision and use of nocturnal listening device appear to be protective. In contrast, recent data failed to demonstrate the predictive value of heart rate variability, periictal cardiorespiratory dysfunction, and postictal generalized electroencephalography suppression. Preliminary findings suggest that brainstem and thalamic atrophy may be associated with a higher risk of SUDEP. Novel experimental and human data support the primary role of generalized tonic-clonic seizure-triggered respiratory dysfunction and the likely contribution of altered brainstem serotoninergic neurotransmission, in SUDEP pathophysiology. SUMMARY: Although significant progress has been made during the past year in the understanding of SUDEP mechanisms and investigation of numerous potential biomarkers, we are still missing reliable predictors of SUDEP beyond the well established clinical risk factors.

Cerebellar, limbic, and midbrain volume alterations in sudden unexpected death in epilepsy.

OBJECTIVE: The processes underlying sudden unexpected death in epilepsy (SUDEP) remain elusive, but centrally mediated cardiovascular or respiratory collapse is suspected. Volume changes in brain areas mediating recovery from extreme cardiorespiratory challenges may indicate failure mechanisms and allow prospective identification of SUDEP risk. METHODS: We retrospectively imaged SUDEP cases (n = 25), patients comparable for age, sex, epilepsy syndrome, localization, and disease duration who were high-risk (n = 25) or low-risk (n = 23), and age- and sex-matched healthy controls (n = 25) with identical high-resolution T1-weighted scans. Regional gray matter volume, determined by voxel-based morphometry, and segmentation-derived structure sizes were compared across groups, controlling for total intracranial volume, age, and sex. RESULTS: Substantial bilateral gray matter loss appeared in SUDEP cases in the medial and lateral cerebellum. This was less prominent in high-risk subjects and absent in low-risk subjects. The periaqueductal gray, left posterior and medial thalamus, left hippocampus, and bilateral posterior cingulate also showed volume loss in SUDEP. High-risk subjects showed left thalamic volume reductions to a lesser extent. Bilateral amygdala, entorhinal, and parahippocampal volumes increased in SUDEP and high-risk patients, with the subcallosal cortex enlarged in SUDEP only. Disease duration correlated negatively with parahippocampal volume. Volumes of the bilateral anterior insula and midbrain in SUDEP cases were larger the closer to SUDEP from magnetic resonance imaging. SIGNIFICANCE: SUDEP victims show significant tissue loss in areas essential for cardiorespiratory recovery and enhanced volumes in areas that trigger hypotension or impede respiratory patterning. Those changes may shed light on SUDEP pathogenesis and prospectively detect patterns identifying those at risk.

Serum serotonin levels in patients with epileptic seizures.

Profound cardiovascular and/or respiratory dysfunction is part of the terminal cascade in sudden unexpected death in epilepsy (SUDEP). Central control of ventilation is mediated by brainstem rhythm generators, which are influenced by a variety of inputs, many of which use the modulatory neurotransmitter serotonin to mediate important inputs for breathing. The aim of this study was to investigate epileptic seizure-induced changes in serum serotonin levels and whether there are potential implications for SUDEP. Forty-one epileptic patients were pooled into 2 groups based on seizure type as (1) generalized tonic-clonic seizures (GTCS) of genetic generalized epilepsy and focal to bilateral tonic-clonic seizures (FBTCS; n = 19) and (2) focal seizures (n = 26) based on clinical signs using surface video-electroencephalography. Postictal serotonin levels were statistically significantly higher after GTCS and FBTCS compared to interictal levels (P = .002) but not focal seizures (P = .941). The change in serotonin (postictal-interictal) was inversely associated with a shorter duration of tonic phase of generalized seizures. The interictal serotonin level was inversely associated with a shorter period of postictal generalized electroencephalographic suppression. These data suggest that peripheral serum serotonin levels may play a role in seizure features and earlier postseizure recovery; these findings merit further study.

The incidence and significance of periictal apnea in epileptic seizures.

OBJECTIVE: The aim of this study was to investigate periictal central apnea as a seizure semiological feature, its localizing value, and possible relationship with sudden unexpected death in epilepsy (SUDEP) pathomechanisms. METHODS: We prospectively studied polygraphic physiological responses, including inductance plethysmography, peripheral capillary oxygen saturation (SpO2 ), electrocardiography, and video electroencephalography (VEEG) in 473 patients in a multicenter study of SUDEP. Seizures were classified according to the International League Against Epilepsy (ILAE) 2017 seizure classification based on the most prominent clinical signs during VEEG. The putative epileptogenic zone was defined based on clinical history, seizure semiology, neuroimaging, and EEG. RESULTS: Complete datasets were available in 126 patients in 312 seizures. Ictal central apnea (ICA) occurred exclusively in focal epilepsy (51/109 patients [47%] and 103/312 seizures [36.5%]) (P < .001). ICA was the only clinical manifestation in 16/103 (16.5%) seizures, and preceded EEG seizure onset by 8 ± 4.9 s, in 56/103 (54.3%) seizures. ICA ≥60 s was associated with severe hypoxemia (SpO2 <75%). Focal onset impaired awareness (FOIA) motor onset with automatisms and FOA nonmotor onset semiologies were associated with ICA presence (P < .001), ICA duration (P = .002), and moderate/severe hypoxemia (P = .04). Temporal lobe epilepsy was highly associated with ICA in comparison to extratemporal epilepsy (P = .001) and frontal lobe epilepsy (P = .001). Isolated postictal central apnea was not seen; in 3/103 seizures (3%), ICA persisted into the postictal period. SIGNIFICANCE: ICA is a frequent, self-limiting semiological feature of focal epilepsy, often starting before surface EEG onset, and may be the only clinical manifestation of focal seizures. However, prolonged ICA (≥60 s) is associated with severe hypoxemia and may be a potential SUDEP biomarker. ICA is more frequently seen in temporal than extratemporal seizures, and in typical temporal seizure semiologies. ICA rarely persists after seizure end. ICA agnosia is typical, and thus it may remain unrecognized without polygraphic measurements that include breathing parameters.

Seizure detection: do current devices work? And when can they be useful?

PURPOSE OF REVIEW: The unpredictability and apparent randomness of epileptic seizures is one of the most vexing aspects of epilepsy. Methods or devices capable of detecting seizures may help prevent injury or even death and significantly improve quality of life. Here, we summarize and evaluate currently available, unimodal, or polymodal detection systems for epileptic seizures, mainly in the ambulatory setting. RECENT FINDINGS: There are two broad categories of detection devices: EEG-based and non-EEG-based systems. Wireless wearable EEG devices are now available both in research and commercial arenas. Neuro-stimulation devices are currently evolving and initial experiences of these show potential promise. As for non-EEG devices, different detecting systems show different sensitivity according to the different patient and seizure types. Regardless, when used in combination, these modalities may complement each other to increase positive predictive value. Although some devices with high sensitivity are promising, practical widespread use of such detection systems is still some way away. More research and experience are needed to evaluate the most efficient and integrated systems, to allow for better approaches to detection and prediction of seizures. The concept of closed-loop systems and prompt intervention may substantially improve quality of life for patients and carers.

Nonseizure SUDEP: Sudden unexpected death in epilepsy without preceding epileptic seizures.

OBJECTIVE: To describe the phenomenology of monitored sudden unexpected death in epilepsy (SUDEP) occurring in the interictal period where death occurs without a seizure preceding it. METHODS: We report a case series of monitored definite and probable SUDEP where no electroclinical evidence of underlying seizures was found preceding death. RESULTS: Three patients (two definite and one probable) had SUDEP. They had a typical high SUDEP risk profile with longstanding intractable epilepsy and frequent generalized tonic-clonic seizures (GTCS). All patients had varying patterns of respiratory and bradyarrhythmic cardiac dysfunction with profound electroencephalography (EEG) suppression. In two patients, patterns of cardiorespiratory failure were similar to those seen in some patients in the Mortality in Epilepsy Monitoring Units Study (MORTEMUS). SIGNIFICANCE: SUDEP almost always occur postictally, after GTCS and less commonly after a partial seizure. Monitored SUDEP or near-SUDEP cases without a seizure have not yet been reported in literature. When nonmonitored SUDEP occurs in an ambulatory setting without an overt seizure, the absence of EEG information prevents the exclusion of a subtle seizure. These cases confirm the existence of nonseizure SUDEP; such deaths may not be prevented by seizure detection-based devices. SUDEP risk in patients with epilepsy may constitute a spectrum of susceptibility wherein some are relatively immune, death occurs in others with frequent GTCS with one episode of seizure ultimately proving fatal, while in others still, death may occur even in the absence of a seizure. We emphasize the heterogeneity of SUDEP phenomena.

Left-insular damage, autonomic instability, and sudden unexpected death in epilepsy.

We analyzed the only two sudden unexpected death in epilepsy (SUDEP) cases from 320 prospectively recruited patients in the three-year Prevention and Risk Identification of SUDEP Mortality (PRISM) project. Both patients had surgically refractory epilepsy, evidence of left insular damage following previous temporal/temporo-insular resections, and progressive changes in heart rate variability (HRV) in monitored evaluations prior to death. Insular damage is known to cause autonomic dysfunction and increased mortality in acute stroke. This report suggests a possible role for the insula in the pathogenesis of SUDEP. The presence of intrinsic insular lesions or acquired insular damage in patients with refractory epilepsy may be an additional risk factor for SUDEP.

Increasing utilization of pediatric epilepsy surgery in the United States between 1997 and 2009.

OBJECTIVE: To examine national trends of pediatric epilepsy surgery usage in the United States between 1997 and 2009. METHODS: We performed a serial cross-sectional study of pediatric epilepsy surgery using triennial data from the Kids' Inpatient Database from 1997 to 2009. The rates of epilepsy surgery for lobectomies, partial lobectomies, and hemispherectomies in each study year were calculated based on the number of prevalent epilepsy cases in the corresponding year. The age-race-sex adjusted rates of surgeries were also estimated. Mann-Kendall trend test was used to test for changes in the rates of surgeries over time. Multivariable regression analysis was also performed to estimate the effect of time, age, race, and sex on the annual incidence of epilepsy surgery. RESULTS: The rates of pediatric epilepsy surgery increased significantly from 0.85 epilepsy surgeries per 1,000 children with epilepsy in 1997 to 1.44 epilepsy surgeries per 1,000 children with epilepsy in 2009. An increment in the rates of epilepsy surgeries was noted across all age groups, in boys and girls, all races, and all payer types. The rate of increase was lowest in blacks and in children with public insurance. The overall number of surgical cases for each study year was lower than 35% of children who were expected to have surgery, based on the estimates from the Connecticut Study of Epilepsy. SIGNIFICANCE: In contrast to adults, pediatric epilepsy surgery numbers have increased significantly in the past decade. However, epilepsy surgery remains an underutilized treatment for children with epilepsy. In addition, black children and those with public insurance continue to face disparities in the receipt of epilepsy surgery.

Lesion-negative anterior cingulate epilepsy.

MRI-negative anterior cingulate epilepsy is a rare entity. Herein, we describe a case of MRI and functional imaging-negative intractable frontal lobe epilepsy in which, initially, secondary bilateral synchrony of surface and intracranial EEG and non-lateralizing semiology rendered identification of the epileptogenic zone difficult. A staged bilateral stereotactic EEG exploration revealed a very focal, putative ictal onset zone in the right anterior cingulate gyrus, as evidenced by interictal and ictal high-frequency oscillations (at 250Hz) and induction of seizures from the same electrode contacts by 50-Hz low-intensity cortical stimulation. This was subsequently confirmed by ILAE class 1 outcome following resection of the ictal onset and irritative zones. Histopathological examination revealed focal cortical dysplasia type 1b (ILAE Commission, 2011) as the cause of epilepsy. The importance of anatomo-electro-clinical correlation is illustrated in this case in which semiological and electrophysiological features pointed to the anatomical localization of a challenging, MRI-negative epilepsy.