Grading system for assessing the confidence in the epileptogenic zone reported in published studies: A Delphi consensus study.

OBJECTIVE: This study was undertaken to develop a standardized grading system based on expert consensus for evaluating the level of confidence in the localization of the epileptogenic zone (EZ) as reported in published studies, to harmonize and facilitate systematic reviews in the field of epilepsy surgery. METHODS: We conducted a Delphi study involving 22 experts from 18 countries, who were asked to rate their level of confidence in the localization of the EZ for various theoretical clinical scenarios, using different scales. Information provided in these scenarios included one or several of the following data: magnetic resonance imaging (MRI) findings, invasive electroencephalography summary, and postoperative seizure outcome. RESULTS: The first explorative phase showed an overall interrater agreement of .347, pointing to large heterogeneity among experts' assessments, with only 17% of the 42 proposed scenarios associated with a substantial level of agreement. A majority showed preferences for the simpler scale and single-item scenarios. The successive Delphi voting phases resulted in a majority consensus across experts, with more than two thirds of respondents agreeing on the rating of each of the tested single-item scenarios. High or very high levels of confidence were ascribed to patients with either an Engel class I or class IA postoperative seizure outcome, a well-delineated EZ according to all available invasive EEG (iEEG) data, or a well-delineated focal epileptogenic lesion on MRI. MRI signs of hippocampal sclerosis or atrophy were associated with a moderate level of confidence, whereas a low level was ascribed to other MRI findings, a poorly delineated EZ according to iEEG data, or an Engel class II-IV postoperative seizure outcome. SIGNIFICANCE: The proposed grading system, based on an expert consensus, provides a simple framework to rate the level of confidence in the EZ reported in published studies in a structured and harmonized way, offering an opportunity to facilitate and increase the quality of systematic reviews and guidelines in the field of epilepsy surgery.

Deep learning approaches for seizure video analysis: A review.

Seizure events can manifest as transient disruptions in the control of movements which may be organized in distinct behavioral sequences, accompanied or not by other observable features such as altered facial expressions. The analysis of these clinical signs, referred to as semiology, is subject to observer variations when specialists evaluate video-recorded events in the clinical setting. To enhance the accuracy and consistency of evaluations, computer-aided video analysis of seizures has emerged as a natural avenue. In the field of medical applications, deep learning and computer vision approaches have driven substantial advancements. Historically, these approaches have been used for disease detection, classification, and prediction using diagnostic data; however, there has been limited exploration of their application in evaluating video-based motion detection in the clinical epileptology setting. While vision-based technologies do not aim to replace clinical expertise, they can significantly contribute to medical decision-making and patient care by providing quantitative evidence and decision support. Behavior monitoring tools offer several advantages such as providing objective information, detecting challenging-to-observe events, reducing documentation efforts, and extending assessment capabilities to areas with limited expertise. The main applications of these could be (1) improved seizure detection methods; (2) refined semiology analysis for predicting seizure type and cerebral localization. In this paper, we detail the foundation technologies used in vision-based systems in the analysis of seizure videos, highlighting their success in semiology detection and analysis, focusing on work published in the last 7 years. We systematically present these methods and indicate how the adoption of deep learning for the analysis of video recordings of seizures could be approached. Additionally, we illustrate how existing technologies can be interconnected through an integrated system for video-based semiology analysis. Each module can be customized and improved by adapting more accurate and robust deep learning approaches as these evolve. Finally, we discuss challenges and research directions for future studies.

Accepting multiple conditions in psychiatry: From comorbidity to multimorbidity.

The concept of multimorbidity in psychiatry refers to the coexistence of multiple health conditions without conceptualizing a central disorder referring to a patient-centered approach that views every diagnosis equally. It emphasizes a shift from focusing on an index disorder to considering interrelated symptoms crucial in psychiatry due to frequent multimorbidity patterns. In clinical practice, multimorbidity guides patient-centered care helping to address the holistic needs of patients and challenging the organization of mental health care. In research, multimorbidity reshapes study outcomes and promotes the development of patient-reported outcome questionnaires, also posing ethical challenges and advocating for the inclusion of multimorbid patients in personalized interventions. Finally, multimorbidity in psychiatry has public health implications aligning with the socioecological systems perspective. This notion aims to improve prognosis, care, and health costs while impacting global mortality and challenging the conceptualization and organization of psychiatric care.

Characteristics and Neural Correlates of Emotional Behavior during Prefrontal Seizures.

OBJECTIVE: This study was undertaken to characterize clinical expression and intracerebral electroencephalographic (EEG) correlates of emotional expression during prefrontal epileptic seizures. METHODS: We performed a descriptive analysis of seizure semiology in patients explored with stereo-EEG (SEEG) for pharmacoresistant prefrontal epilepsy, using a semiquantitative score for seizure-related emotional behavior. Two independent observers scored occurrence and intensity of objective emotional features (face/body movements/vocalization/overall appearance), testing interobserver reliability. Intracerebral electrophysiological changes were documented. Cluster analysis and principal component analysis (PCA) compared behavioral signs with neural SEEG correlates. For each patient, the clinical and anatomoelectrophysiological scores were established, based on a prototypical emotional seizure. RESULTS: Forty-two patients (469 seizures) were included. Interobserver correlation for emotional signs was satisfactory (kappa = 0.6-0.8). Prevalence of any subjective and/or objective ictal emotional phenomena was 79% (33/42); objective emotional signs occurred in 27 of 42 subjects (64%). Negatively valenced emotional semiology (ictal feeling of fear, defensive and/or aggressive behaviors) was much more prevalent than positively valenced, prosocial behaviors. Cluster analysis and PCA identified 4 groups with different occurrence of emotional signs and cerebral correlates. Two main clusters of negatively valenced behavior were identified: "active threat response," associated with seizure organizations involving posterior orbitofrontal cortex, anterior cingulate, and dorsolateral and/or ventrolateral prefrontal cortex; and "passive fear," associated with amygdala, other mesial temporal structures, and posterior orbitofrontal cortex. INTERPRETATION: Emotional behaviors, especially fear/threat response, are common in prefrontal seizures, reflecting the role of the prefrontal cortex in emotional control. Different cortical seizure localizations were associated with "passive fear" and "active threat response" seizure behaviors at the group level. ANN NEUROL 2022;92:1052-1065.

Potential new roles for glycogen in epilepsy.

Seizures often originate in epileptogenic foci. Between seizures (interictally), these foci and some of the surrounding tissue often show low signals with 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) in many epileptic patients, even when there are no radiologically detectable structural abnormalities. Low FDG-PET signals are thought to reflect glucose hypometabolism. Here, we review knowledge about metabolism of glucose and glycogen and oxidative stress in people with epilepsy and in acute and chronic rodent seizure models. Interictal brain glucose levels are normal and do not cause apparent glucose hypometabolism, which remains unexplained. During seizures, high amounts of fuel are needed to satisfy increased energy demands. Astrocytes consume glycogen as an additional emergency fuel to supplement glucose during high metabolic demand, such as during brain stimulation, stress, and seizures. In rodents, brain glycogen levels drop during induced seizures and increase to higher levels thereafter. Interictally, in people with epilepsy and in chronic epilepsy models, normal glucose but high glycogen levels have been found in the presumed brain areas involved in seizure generation. We present our new hypothesis that as an adaptive response to repeated episodes of high metabolic demand, high interictal glycogen levels in epileptogenic brain areas are used to support energy metabolism and potentially interictal neuronal activity. Glycogenolysis, which can be triggered by stress or oxidative stress, leads to decreased utilization of plasma glucose in epileptogenic brain areas, resulting in low FDG signals that are related to functional changes underlying seizure onset and propagation. This is (partially) reversible after successful surgery. Last, we propose that potential interictal glycogen depletion in epileptogenic and surrounding areas may cause energy shortages in astrocytes, which may impair potassium buffering and contribute to seizure generation. Based on these hypotheses, auxiliary fuels or treatments that support glycogen metabolism may be useful to treat epilepsy.

Interictal HFO and FDG-PET correlation predicts surgical outcome following SEEG.

OBJECTIVE: This study aimed to investigate the quantitative relationship between interictal 18 F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and interictal high-frequency oscillations (HFOs) from stereo-electroencephalography (SEEG) recordings in patients with refractory epilepsy. METHODS: We retrospectively included 32 patients. FDG-PET data were quantified through statistical parametric mapping (SPM) t test modeling with normal controls. Interictal SEEG segments with four, 10-min segments were selected randomly. HFO detection and classification procedures were automatically performed. Channel-based HFOs separating ripple (80-250 Hz) and fast ripple (FR; 250-500 Hz) counts were correlated with the surrounding metabolism T score at the individual and group level, respectively. The association was further validated across anatomic seizure origins and sleep vs wake states. We built a joint feature FR × T reflecting the FR and hypometabolism concordance to predict surgical outcomes in 28 patients who underwent surgery. RESULTS: We found a negative correlation between interictal FDG-PET and HFOs through the linear mixed-effects model (R2  = .346 and .457 for ripples and FRs, respectively, p < .001); these correlations were generalizable to different epileptogenic-zone lobar localizations and vigilance states. The FR × T inside the resection volume could be used as a predictor for surgical outcomes with an area under the curve of 0.81. SIGNIFICANCE: The degree of hypometabolism is associated with HFO generation rate, especially for FRs. This relationship would be meaningful for selection of SEEG candidates and for optimizing SEEG scheme planning. The concordance between FRs and hypometabolism inside the resection volume could provide prognostic information regarding surgical outcome.

Post-traumatic stress disorder (PTSD), cognitive control, and perceived seizure control in patients with epilepsy: An exploratory study.

Epilepsy is often linked to various psychiatric symptoms, with anxiety, depression, and interictal dysphoric disorders being the most prevalent. Few studies have investigated posttraumatic stress disorder (PTSD) in epilepsy, but they suggest a notable prevalence of PTSD. PTSD is known to be associated with cognitive impairments, particularly memory and executive functions. Our proposed exploratory study aims to investigate executive attentional control and emotional inhibition in patients with drug-resistant epilepsy (DRE) who exhibit PTSD symptoms compared with a healthy control group. Additionally, some PWE can manage their seizures using emotional and cognitive strategies, we find it relevant to explore the connection between their regulation abilities, cognitive control performance, and PTSD symptoms. We included 54 PWE and 60 healthy participants. They completed anxiety and depression scales as well as two questionnaires assessing PTSD symptoms and a questionnaire that measured the perceived self-control of seizures. We measured executive control using an executive control task (Attention Network Test, ANT) and an emotional Go/No-Go task. We found a positive correlation between PTSD scores (PDS-5) and performance at the ANT task. In contrast, in the emotional inhibition (Go/No-Go) task, behavioral inhibition errors were positively correlated with PTSD scores, specifically with hypervigilance symptoms in PTSD+ patients. There was a positive correlation between response reaction times in an aversive condition and PTSD scores: the more severe the PTSD symptoms, the faster the PWE identified stimuli in the angry face condition of the Go/No-Go task. Regarding perceived seizure control, we found correlations between alertness and PTSD symptoms associated with seizure anticipation during the inter- and peri-ictal periods. Patients with PTSD symptoms reported better seizure control. Our findings suggest that epilepsy patients with PTSD experience cognitive changes such as heightened executive attentional control, weakened emotional inhibition, and improved seizure control perception.

Correlation between fluorodeoxyglucose positron emission tomography brain hypometabolism and posttraumatic stress disorder symptoms in temporal lobe epilepsy.

The relationship between posttraumatic stress disorder (PTSD) and focal epilepsy is poorly understood. It has been hypothesized that there is a complex and reciprocal potential reinforcement of the symptoms of each condition. In this study, we investigated whether there are PTSD-specific brain changes in temporal lobe epilepsy (TLE). Brain fluorodeoxyglucose positron emission tomography (PET) metabolism was compared between controls and two groups of TLE patients: one group of 15 patients fulfilling the criteria for a potential diagnosis of PTSD (TLE-PTSD+), another group of 24 patients without a diagnosis of PTSD (TLE-PTSD-), and a group of 30 healthy control participants. We compared the differences in brain PET metabolism among these three groups, and we studied their correlations with interictal and peri-ictal scales of PTSD symptoms. TLE-PTSD+ patients showed more significant hypometabolism involving right temporal and right orbitofrontal cortex in comparison to TLE-PTSD- patients and healthy subjects. Moreover, degree of reduced metabolism in these brain areas correlated with interictal and peri-ictal PTSD questionnaire scores. PTSD in temporal epilepsy is associated with specific changes in neural networks, affecting limbic and paralimbic structures. This illustrates the close intertwining of epileptogenic and psychogenic processes in these patients.

Symptom network analysis of the sleep disorders diagnostic criteria based on the clinical text of the ICSD-3.

The third edition of the International Classification of Sleep Disorders (ICSD-3) is the authoritative clinical text for the diagnosis of sleep disorders. An important issue of sleep nosology is to better understand the relationship between symptoms found in conventional diagnostic manuals and to compare classifications. Nevertheless, to our knowledge, there is no specific exhaustive work on the general structure of the networks of symptoms of sleep disorders as described in diagnostic manuals. The general aim of the present study was to use symptom network analysis to explore the diagnostic criteria in the ICSD-3 manual. The ICSD-3 diagnostic criteria related to clinical manifestations were systematically identified, and the units of analysis (symptoms) were labelled from these clinical manifestation diagnostic criteria using three rules ("Conservation", "Splitting", "Lumping"). A total of 37 of the 43 main sleep disorders with 160 units of analysis from 114 clinical manifestations in the ICSD-3 were analysed. A symptom network representing all individual ICSD-3 criteria and connections between them was constructed graphically (network estimation), quantified with classical metrics (network inference with global and local measures) and tested for robustness. The global measure of the sleep symptoms network shows that it can be considered as a small world, suggesting a strong interconnection between symptoms in the ICSD-3. Local measures show the central role of three kinds of bridge sleep symptoms: daytime sleepiness, insomnia, and behaviour during sleep symptoms. Such a symptom network analysis of the ICSD-3 structure could provide a framework for better systematising and organising symptomatology in sleep medicine.

Screening for epilepsy-specific anxiety symptoms: French validation of the EASI.

OBJECTIVES: (1) To translate and validate the Epilepsy Anxiety Survey Instrument (EASI) in French people with epilepsy (PWE); (2) to further investigate the screening properties of each dimension of the EASI in terms of Diagnostic and Statistical Manual of Mental Disorders (DSM) anxiety disorders and of epilepsy-specific anxiety disorders, namely, anticipatory anxiety of seizures (AAS) and epileptic social phobia. METHODS: Following back-translation, the French EASI was tested in PWE > 18 years using the Mini-International Neuropsychiatric Interview (MINI) as gold standard for DSM anxiety disorders. We added 3 original questions to explore epilepsy-specific anxiety symptoms. The Generalized Anxiety Disorders-7 (GAD-7), Neurological Disorders Depression Inventory for Epilepsy (NDDI-E), and Adverse Events Profile were performed for external validity. Receiver operator characteristics (ROC) were analyzed. RESULTS: One hundred and forty nine native French speakers with epilepsy were included. Concerning DSM disorders, around 25% had GAD, 18% Agoraphobia, and <10% Social Phobia or Panic Disorder. Concerning possible epilepsy-specific anxiety disorder, 35% had AAS and 38% had epileptic social phobia. Bi-dimensional structure of the EASI was confirmed. Internal and external validity was satisfactory. ROC analysis showed AUC of 0.83 for detection of GAD and AUC 0.79 for other DSM anxiety disorders. ROC analysis of the 8-item French brEASI showed good performance for detection of GAD (AUC 0.83) and other DSM anxiety disorders (AUC 0.76) but not for epilepsy-specific anxiety symptoms (AUC 0.63). Conversely, dimension 2 of the French EASI (=10 items) allowed good detection of epilepsy-specific anxiety symptoms (AUC 0.78); cutoff > 4, sensitivity 82.4, specificity 66.7. CONCLUSION: Epilepsy-specific anxiety symptoms were prevalent, in around 60%. The French version of the EASI showed robust performance. The French 8-item brEASI allows screening for all DSM anxiety disorders with superior performance than the GAD-7, but is less suited to screening for epilepsy-specific anxiety. We propose the "Epilepsy-Specific Anxiety" (ESA) 10-item screening instrument, based on dimension 2 of the EASI, as a complementary clinical and research tool.

On seizure semiology.

The clinical expression of seizures represents the main symptomatic burden of epilepsy. Neural mechanisms of semiologic production in epilepsy, especially for complex behaviors, remain poorly known. In a framework of epilepsy as a network rather than as a focal disorder, we can think of semiology as being dynamically produced by a set of interconnected structures, in which specific rhythmic interactions, and not just anatomical localization, are likely to play an important part in clinical expression. This requires a paradigm shift in how we think about seizure organization, including from a presurgical evaluation perspective. Semiology is a key data source, albeit with significant methodological challenges for its use in research, including observer bias and choice of semiologic categories. Better understanding of semiologic categorization and pathophysiological correlates is relevant to seizure classification systems. Advances in knowledge of neural mechanisms as well as anatomic correlates of different semiologic patterns could help improve knowledge of epilepsy networks and potentially contribute to therapeutic innovations.

Interictal 18F-FDG brain PET metabolism in patients with postictal EEG suppression.

OBJECTIVE: Postictal generalized suppression (PGES) may be associated with SUDEP risk. We aimed to study metabolic changes on 18Fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) in patients with focal to bilateral (generalized) seizures (GTCS) and PGES on stereoelectroencephalography (SEEG). METHODS: We analyzed interictal brain metabolism in a group of 19 patients with widespread postictal suppression (PGES+) associated with SEEG-recorded GTCS. This group was compared to 25 patients without widespread suppression (PGES-) as defined by SEEG, matched for epilepsy localization and lateralization. Frequency of GTCS was observed to be higher in the PGES+ group (high risk group for SUDEP). Analysis of metabolic data was performed by statistical parametric mapping (SPM) on the whole-brain, and principal component analysis (PCA) on AAL (automated anatomical labeling) atlas. RESULTS: Statistical parametric mapping showed right temporal pole hypometabolism in the PGES+ group (T-score = 3.90; p < 0.001; k = 185), in comparison to the PGES- group. Principal component analysis showed association between the metabolic values of certain regions of interest and PGES+/PGES- groups, confirmed by a significant difference (p < 0.05) in the values of the right dorsal temporal pole and of the left temporal pole between the two groups. Principal component analysis showed two dimensions significantly related to the PGES+/PGES- partition, involving the following regions: right temporal pole, right parahippocampal gyrus, right Rolandic operculum, bilateral paracentral lobule, right precuneus, right thalamus, right caudate and pallidum, bilateral cerebellum, left temporal pole, left Heschl's gyrus, left calcarine region, and left caudate, with loss of connection in PGES+ patients. Metabolic differences were independent of epilepsy localization and lateralization and persisted after correction for GTCS frequency. SIGNIFICANCE: Interictal metabolic changes within a predominantly right-sided network involving temporal lobe and connected cortical and subcortical structures were seen in patients with frequent GTCS presenting widespread postictal suppression.

Post-traumatic stress disorder (PTSD) in patients with epilepsy.

Anxiety and depression in epilepsy are strongly documented but post-traumatic stress disorder (PTSD) is underestimated and poorly known. We studied the links between psycho-traumagenic events (TE), onset of epilepsy, and severity of PTSD symptoms in patients with epilepsy. The study included 54 patients with epilepsy and 61 controls. We used validated questionnaires to screen for anxiety, depression, and PTSD symptoms and we conducted an interview to measure the prevalence of TE. We developed an original exploratory questionnaire to assess the presence of PTSD during interictal and peri-ictal periods. The results show that patients reported more exposure to a TE and presented significantly more severe PTSD symptoms than controls. Seventy-eight percent of patients (vs. 52% of controls) had been exposed to a TE, and 26% (vs. 7%) had a score above the diagnostic threshold of the PTSD scale. In addition, 18.6% of patients reported that their epilepsy began at the same time as they began to experience PTSD symptoms following a TE. Patients with high PTSD scores (above the threshold, n = 14) reported significantly more depression symptoms than patients without PTSD and reported PTSD symptoms both during the ictal and peri-ictal periods. Within the whole group of patients, anxiety (72%) and depression (33%) symptoms significantly correlated with PTSD symptoms reported by the scale. This study shows that patients with epilepsy have increased prevalence of self-reported PTSD symptoms. We describe the clinical picture specific to patients with epilepsy, which may include classical PTSD symptoms but also specific peri-ictal symptoms.

Electrical stimulation for seizure induction during SEEG exploration: a useful predictor of postoperative seizure recurrence?

OBJECTIVE: Direct electrical stimulations of cerebral cortex are a traditional part of stereoelectroencephalography (SEEG) practice, but their value as a predictive factor for seizure outcome has never been carefully investigated. PATIENTS AND METHOD: We retrospectively analysed a cohort of 346 patients operated on for drug-resistant focal epilepsy after SEEG exploration. As potential predictors we included: aetiology, MRI data, age of onset, duration of epilepsy, age at surgery, topography of surgery and whether a seizure was induced by either low frequency electrical stimulation (LFS) or high frequency electrical stimulation. RESULTS: Of 346 patients, 63.6% had good outcome (no seizure recurrence, Engel I). Univariate analysis demonstrated significant correlation with favourable outcome (Engel I) for: aetiology, positive MRI and seizure induced by stimulation. At multivariate analysis, informative MRI, type II focal cortical dysplasia and tumour reduced the risk of seizure recurrence (SR) by 47%, 58% and 81%, respectively. Compared with the absence of induced seizures, the occurrence of ictal events after LFS significantly predicts a favourable outcome on seizures, with only 44% chance of disabling SR at last follow-up. CONCLUSION: Among the already known predictors outcome, seizure induction by LFS therefore represents a positive predictive factor for seizure outcome after surgery.

Relationship between PET metabolism and SEEG epileptogenicity in focal lesional epilepsy.

PURPOSE: This study aims to evaluate the performance of 18F-FDG PET for distinguishing the epileptogenic zone (EZ) from propagation and non-involved zones at brain area level, as defined using stereo-EEG (SEEG), in patients with pharmacoresistant epilepsy due to malformations of cortical development (MCD). Additionally, we seek to determine the relationship between 18F-FDG-PET data and post-surgical seizure outcome. METHODS: Thirty-eight patients with MCD were explored with 18F-FDG PET and SEEG. We compared PET metabolism of each patient to a control population of healthy subjects. Based on MRI and SEEG, we separated 4 distinct zones at individual level: lesional, epileptogenic non-lesional, propagation, and non-involved. Then, we analysed (1) difference of PET metabolism within these four distinct zones; (2) performance of PET in defining the EZ within the SEEG-sampled areas; and (3) relation between extension of PET hypometabolism and post-surgical seizure outcome. RESULTS: We found (1) a gradient of PET hypometabolism from non-involved to propagation, then to epileptogenic and lesional zones (p < 0.001); (2) good performance of PET in defining the EZ (AUC of ROC curve = 0.82); (3) poorer post-surgical prognosis associated with PET hypometabolism extension beyond SEEG sampling (p = 0.024). CONCLUSION: 18F-FDG-PET has good accuracy in determining EZ in patients with MCD even if the hypometabolism is not limited to the EZ. Furthermore, hypometabolic extension is unfavourably associated with post-surgical prognosis.

Transient cortico-cortical disconnection during psychogenic nonepileptic seizures (PNES).

Psychogenic nonepileptic seizures (PNES) are paroxysmal clinical events that are often misdiagnosed as epileptic seizures, but which are not associated with electrographic discharge. Brain connectivity changes occurring during PNES are not known. We studied functional connectivity (Fc) in two patients with drug-resistant epilepsy, explored by stereotactic electroencephalography (EEG), in whom we recorded both epileptic seizures (ES) and PNES. Functional connectivity using pair-wise nonlinear correlation was computed between signals from seven brain areas: amygdala, hippocampus, lateral temporal cortex, anterior insula, orbitofrontal cortex, prefrontal cortex, and lateral parietal cortex. We assessed changes in global Fc during PNES in comparison with a background period. During PNES, a global decrease of Fc occurred between the different brain regions studied, compared with the interictal period. In both patients, decreased Fc was prominent in connections involving the anterior insula and parietal cortex. In conclusion, some PNES are associated with ictal functional disconnection between brain areas, particularly involving the parietal cortices and the anterior insula.

Quantitative analysis of hyperkinetic seizures and correlation with seizure onset zone.

OBJECTIVE: Hyperkinetic epileptic seizures (HKS) are difficult to characterize and localize according to semiologic features. We propose a multicriteria scale to help visual analysis and report results of cerebral localization. METHODS: We assessed seizures from 37 patients with HKS, explored with stereoelectroencephalography during presurgical evaluation. We used a multicriteria scale (hyperkinetic seizure scale [HSS]) with 10 semiologic features, scored independently by two neurologists. The item scores were used to group seizures using the k-means method. Semiologic features were correlated with the seizure onset zone (SOZ) localization (temporal, prefrontal dorsolateral, prefrontal ventromesial, parietal, insular). RESULTS: Fifty-five seizures were analyzed, and each item of the HSS was compared between the two examiners with good interrater agreement (85.3%). Dystonia, integrated behavior, and bilateral or unilateral hyperkinetic movements were statistically significant according to localization. Three clusters were identified according to the HSS and correlated with different patterns of anatomic localization of SOZ. Cluster 1 was characterized clinically by asymmetric hyperkinetic movements associated with marked dystonia and vocalization. It mainly included parietal seizures. Cluster 2 was characterized by bilateral and symmetrical stereotyped hyperkinetic movements without dystonia. It represented half of temporal seizures and one-third of prefrontal seizures (dorsolateral). Cluster 3 was characterized by seizures with strong emotionality and vocalization with bilateral and symmetrical hyperkinetic movements and integrated behavior. It involved half of temporal seizures and a majority of prefrontal (ventromesial) seizures. SIGNIFICANCE: We propose a first attempt to quantify clinical patterns of HKS. The HSS may help to predict SOZ localization according to three main groups of hyperkinetic seizures.

Semiologic subgroups of insulo-opercular seizures based on connectional architecture atlas.

OBJECTIVE: Insulo-opercular seizures are characterized by diverse semiology, related to the insula's multiple functional roles and extensive connectivity. We aimed to identify semiologic subgroups and correlate these with insulo-opercular subregions based on connectional architecture. METHODS: We retrospectively collected a large series of 37 patients with insulo-opercular seizures explored by stereoelectroencephalography (SEEG) from three epilepsy centers. A new human brain atlas (Brainnetome Atlas, BNA) based on both anatomic and functional connections was employed to segment insulo-opercular cortex. Semiology and SEEG changes were carefully reviewed and quantified. Principal component analysis and cluster analysis were used to correlate semiologic characteristics with insulo-opercular subregions. RESULTS: Four main semiologic subgroups were identified, organized along an anteroventral to posterodorsal axis based on BNA. Group 1 was characterized by epigastric sensation and/or integrated gestural motor behaviors with or without feelings of fear or rage, involving the anteroventral insular regions and mesial temporal lobes. Group 2 was characterized by auditory sensations and symmetric proximal/axial tonic signs involving the posteroventral temporal operculum. The characteristics of group 3 were orofacial and laryngeal signs, involving the intermediate insulo-opercular regions. The features of group 4 were somatosensory signs followed by nonintegrated gestural motor behaviors and/or asymmetric tonic signs involving the posterodorsal insulo-opercular regions with propagation to the mesial frontal lobes. Thus anteroventral seizure organizations predominantly showed limbic system semiology, whereas more posterodorsal regions were associated with semiology involving mainly the sensorimotor system. Subjective symptoms proved to be particularly discriminating factors. SIGNIFICANCE: Insulo-opercular seizures can be categorized in terms of clinical semiology and correlate with connectional architecture subregions along an anteroventral-posterodorsal axis in line with the cytoarchitectonic gradient rather than the gyral anatomy of the insula cortex. This provides new insights into facilitating differential diagnosis and presurgical localization but also highlights the importance of considering connectional architecture in determining neural correlates of complex semiologic patterns.

Stereoelectroencephalography (SEEG) and epilepsy surgery in posttraumatic epilepsy: A multicenter retrospective study.

PURPOSE: Posttraumatic epilepsy (PTE) is a common cause of drug-resistant epilepsy, especially in young adults. Nevertheless, such patients are not common candidates for intracranial presurgical evaluation. We investigated the role of stereoelectroencephalography (SEEG) in defining epileptogenicity and surgical strategy in patients with PTE. METHODS: We analyzed ictal SEEG recordings from 18 patients. We determined the seizure onset zone (SOZ) by quantifying the epileptogenicity of the sampled structures, using the "epileptogenicity index" (EI). We also identified seizure onset patterns (SOPs) through visual and frequency analysis. Postsurgical outcome was assessed by Engel's classification. RESULTS: The SOZ in PTE was most often located in temporal lobes, followed by frontal lobes. The SOZ was network-organized in the majority of the cases. Half of the SOP did not contain fast discharges. Half of the recordings showed SOZ that were less extensive than the posttraumatic lesions seen on brain magnetic resonance imaging (MRI). All but one operated patient benefited from tailored cortectomy. Only 3 patients were contraindicated for surgical resection due to bilateral epileptogenicity. The overall surgical outcome was good in majority of patients (67% Engel I). CONCLUSION: Despite the potential risk of bilateral or multifocal epilepsy, patients with PTE may benefit from presurgical assessment in well-selected cases. In this context, SEEG allows guidance of tailored resections adapted to the SOZ.

Prefrontal seizure classification based on stereo-EEG quantification and automatic clustering.

PURPOSE: Frontal seizures are organized according to anatomo-functional subdivisions of the frontal lobe. Prefrontal seizures have been the subject of few detailed studies to date. The objective of this study was to identify subcategories of prefrontal seizures based on seizure onset quantification and to look for semiological differences. METHODS: Consecutive patients who underwent stereoelectroencephalography (SEEG) for drug-resistant prefrontal epilepsy between 2000 and 2018 were included. The different prefrontal regions investigated in our patients were dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), dorsomedial prefrontal cortex (DMPFC), ventromedial prefrontal cortex (VMPFC), and orbitofrontal cortex (OFC). The seizure onset zone (SOZ) was determined from one or two seizures in each patient, using the epileptogenicity index (EI) method. The presence or absence of 16 clinical ictal manifestations was analyzed. Classification of prefrontal networks was performed using the k-means automatic classification method. RESULTS: A total of 51 seizures from 31 patients were analyzed. The optimal clustering was 4 subgroups of prefrontal seizures: a "pure DLPF" group, a "pure VMPF" group, a "pure OFC" group, and a "global prefrontal" group. The first 3 groups showed a mean EI considered epileptogenic (>0.4) only in one predominant structure, while the fourth group showed a high mean EI in almost all prefrontal structures. The median number of epileptogenic structures per seizure (prefrontal or extrafrontal) was 5 for the "global prefrontal" group and 2 for the other groups. We found that the most common signs were altered consciousness, automatisms/stereotypies, integrated gestural motor behavior, and hyperkinetic motor behavior. We found no significant difference in the distribution of ictal signs between the different groups. CONCLUSION: Our study showed that although most prefrontal seizures manifest as a network of several anatomically distinct structures, we were able to determine a sublobar organization of prefrontal seizure onset with four groups.