Pregabalin for the management of partial epilepsy

Pregabalin is one of the latest antiepileptic drugs introduced for the treatment of partial epilepsy. Its efficacy and safety as adjunctive therapy in refractory partial epilepsy have been established in four double-blind placebo-controlled trials (n = 1396) and 4 long-term open-label studies (n = 1480). In 3 fixed-dose trials, the proportion of patients with a ≥50% reduction in seizure frequency across the effective dose-range (150–600 mg/day) ranged between 14% and 51%, with a clear dose-response relationship. Suppression of seizure activity could be demonstrated as early as day 2. The most frequently reported CNS-related adverse events included dizziness, somnolence, ataxia and fatigue, were usually mild or moderate, and tended to be dose related. In long-term studies, weight gain was reported as an adverse event by 24% of patients. When pregabalin dose was individualized to according to response within the 150 to 600 mg/day dose range, tolerability was considerably improved compared with use of a high-dose, fixed-dose regimen (600 mg/day) without titration. In long-term studies up to 4 years, no evidence of loss efficacy was identified. During the last year on pregabalin, 3.7% of patients were seizure-free. Pregabalin appears to be a useful addition to the therapeutic armamentariun for the management of refractory partial epilepsy

Interpreting Deep Learning Models for Epileptic Seizure Detection on EEG signals

While Deep Learning (DL) is often considered the state-of-the art for Artificial Intelligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient interpretability of neural network models. We have tackled this issue by developing interpretable DL models in the context of online detection of epileptic seizure, based on EEG signal. This has conditioned the preparation of the input signals, the network architecture, and the post-processing of the output in line with the domain knowledge. Specifically, we focused the discussion on three main aspects: 1) how to aggregate the classification results on signal segments provided by the DL model into a larger time scale, at the seizure-level; 2) what are the relevant frequency patterns learned in the first convolutional layer of different models, and their relation with the delta, theta, alpha, beta and gamma frequency bands on which the visual interpretation of EEG is based; and 3) the identification of the signal waveforms with larger contribution towards the ictal class, according to the activation differences highlighted using the DeepLIFT method. Results show that the kernel size in the first layer determines the interpretability of the extracted features and the sensitivity of the trained models, even though the final performance is very similar after post-processing. Also, we found that amplitude is the main feature leading to an ictal prediction, suggesting that a larger patient population would be required to learn more complex frequency patterns. Still, our methodology was successfully able to generalize patient inter-variability for the majority of the studied population with a classification F1-score of 0.873 and detecting 90% of the seizures.Comment: 28 pages, 11 figures, 12 table

Probabilistic functional tractography of the human cortex revisited

In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.eu) by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections. Here, we wish to present a snapshot of the methods and data of F-TRACT using a pool of 213 epilepsy patients, all studied by stereo-encephalography with intracerebral depth electrodes. The CCEPs were processed using an automated pipeline with the following consecutive steps: detection of each stimulation run from stimulation artifacts in raw intracranial EEG (iEEG) files, bad channels detection with a machine learning approach, model-based stimulation artifact correction, robust averaging over stimulation pulses. Effective connectivity between the stimulated and recording areas is then inferred from the properties of the first CCEP component, i.e. onset and peak latency, amplitude, duration and integral of the significant part. Finally, group statistics of CCEP features are implemented for each brain parcel explored by iEEG electrodes. The localization (coordinates, white/gray matter relative positioning) of electrode contacts were obtained from imaging data (anatomical MRI or CT scans before and after electrodes implantation). The iEEG contacts were repositioned in different brain parcellations from the segmentation of patients' anatomical MRI or from templates in the MNI coordinate system. The F-TRACT database using the first pool of 213 patients provided connectivity probability values for 95% of possible intrahemispheric and 56% of interhemispheric connections and CCEP features for 78% of intrahemisheric and 14% of interhemispheric connections. In this report, we show some examples of anatomo-functional connectivity matrices, and associated directional maps. We also indicate how CCEP features, especially latencies, are related to spatial distances, and allow estimating the velocity distribution of neuronal signals at a large scale. Finally, we describe the impact on the estimated connectivity of the stimulation charge and of the contact localization according to the white or gray matter. The most relevant maps for the scientific community are available for download on f-tract. eu (David et al., 2017) and will be regularly updated during the following months with the addition of more data in the F-TRACT database. This will provide an unprecedented knowledge on the dynamical properties of large fiber tracts in human.Peer reviewe

A survey of the European Reference Network EpiCARE on clinical practice for selected rare epilepsies

Objective: Clinical care of rare and complex epilepsies is challenging, because evidence-based treatment guidelines are scarce, the experience of many physicians is limited, and interdisciplinary treatment of comorbidities is required. The pathomechanisms of rare epilepsies are, however, increasingly understood, which potentially fosters novel targeted therapies. The objectives of our survey were to obtain an overview of the clinical practice in European tertiary epilepsy centers treating patients with 5 arbitrarily selected rare epilepsies and to get an estimate of potentially available patients for future studies. Methods: Members of the European Reference Network for rare and complex epilepsies (EpiCARE) were invited to participate in a web-based survey on clinical practice of patients with Dravet syndrome, tuberous sclerosis complex (TSC), autoimmune encephalitis, and progressive myoclonic epilepsies including Unverricht Lundborg and Unverricht-like diseases. A consensus-based questionnaire was generated for each disease. Results: Twenty-six of 30 invited epilepsy centers participated. Cohorts were present in most responding centers for TSC (87%), Dravet syndrome (85%), and autoimmune encephalitis (71%). Patients with TSC and Dravet syndrome represented the largest cohorts in these centers. The antiseizure drug treatments were rather consistent across the centers especially with regard to Dravet syndrome, infantile spasms in TSC, and Unverricht Lundborg / Unverricht-like disease. Available, widely used targeted therapies included everolimus in TSC and immunosuppressive therapies in autoimmune encephalitis. Screening for comorbidities was routinely done, but specific treatment protocols were lacking in most centers. Significance: The survey summarizes the current clinical practice for selected rare epilepsies in tertiary European epilepsy centers and demonstrates consistency as well as heterogeneity in the treatment, underscoring the need for controlled trials and recommendations. The survey also provides estimates for potential participants of clinical trials recruited via EpiCARE, emphasizing the great potential of Reference Networks for future studies to evaluate new targeted therapies and to identify novel biomarkers.info:eu-repo/semantics/publishedVersio

Greater Response to Placebo in Children Than in Adults: A Systematic Review and Meta-Analysis in Drug-Resistant Partial Epilepsy

In a systematic review of antiepileptic drugs, Philippe Ryvlin and colleagues find that children with drug-resistant partial epilepsy enrolled in trials seem to have a greater response to placebo than adults enrolled in such trials

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice

Initiation et modulation des oscillations physiologiques et pathologiques dans le néocortex immature (rôle de la transmission GABAergique)

La période néonatale est marquée par la survenue d'oscillations neuronales spontanées jouant un rôle primodial dans la maturation fonctionnelle du cerveau et par une susceptiblité particulière aux crises d'épilepsie. Il a été suggéré qu'il existe un lien entre les mécanismes qui sous-tendent la génération d'oscillations physiologiques et d'oscillations pathologiques. Bien que les crises du nourrisson impliquent un réseau néocortical, les propriétés qui concourent à majorer l'excitabilité du néocortex immature sont peu connues. Plus spécifiquement, le rôle du GABA dans le néocortex néonatal est débattu. Au cours de notre thèse, nous avons étudié les mécanismes impliqués dans l'initiation et la modulation des oscillations physiologiques et pathologiques dans le néocortex immature en centrant sur le rôle de la transmission GABAergique. Nous montrons : (i) que le néocortex immature possède intrinsèquement un niveau d'excitabilité élevé qui prédomine dans les couches cellulaires profondes, (ii) que le GABA peut avoir une action excitatrice et pro-épileptogène, mais que celle-ci est physiologiquement modulée par l'état métabolique sous la forme d'une régulation négative par le corps cétoniques, (iii) que la répétition des activités inter-ictales peut modifier les propriétés intrinsèques de ces réseaux et faciliter la génération d'activités épileptiques, et (iv) que la modulation du GABA par l'état du métabolisme énergétique pourrait représenter un mécanisme d'adaptation de l'activité cérébrale à l'environnement du sujet. Au total, nous proposons que le néocortex immature a un niveau d'excitabilité intrinsèquement élevé qui peut-être modulé par la transmission GABAergique. La présence physiologique de taux élevés de corps cétoniques ou leur majoration à titre thérapeutique peut permettre d'abaisser l'action excitatrice du GABA et de moduler négativement la survenue d'oscillations physiologiques ou d'activités épileptiques.AIX-MARSEILLE2-BU Sci.Luminy (130552106) / SudocSudocFranceF

Méta-analyse et comparaison indirecte des anti-épileptiques de nouvelle génération

LYON1-BU Santé (693882101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF