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Focal cortical dysplasias (FCDs) are malformations of cortical development and one of the most common pathologies causing pharmacoresistant focal epilepsy. Resective neurosurgery yields high success rates, especially if the full extent of the lesion is correctly identified and completely removed. The visual assessment of magnetic resonance imaging does not pinpoint the FCD in 30%-50% of cases, and half of all patients with FCD are not amenable to epilepsy surgery, partly because the FCD could not be sufficiently localized. Computational approaches to FCD detection are an active area of research, benefitting from advancements in computer vision. Automatic FCD detection is a significant challenge and one of the first clinical grounds where the application of artificial intelligence may translate into an advance for patients' health. The emergence of new methods from the combination of health and computer sciences creates novel challenges. Imaging data need to be organized into structured, well-annotated datasets and combined with other clinical information, such as histopathological subtypes or neuroimaging characteristics. Algorithmic output, that is, model prediction, requires a technically correct evaluation with adequate metrics that are understandable and usable for clinicians. Publication of code and data is necessary to make research accessible and reproducible. This critical review introduces the field of automatic FCD detection, explaining underlying medical and technical concepts, highlighting its challenges and current limitations, and providing a perspective for a novel research environment.

OBJECTIVE: Focal cortical dysplasias (FCDs) are a common cause of drug-resistant focal epilepsy but frequently remain undetected by conventional magnetic resonance imaging (MRI) assessment. The visual detection can be facilitated by morphometric analysis of T1-weighted images, for example, using the Morphometric Analysis Program (v2018; MAP18), which was introduced in 2005, independently validated for its clinical benefits, and successfully integrated in standard presurgical workflows of numerous epilepsy centers worldwide. Here we aimed to develop an artificial neural network (ANN) classifier for robust automated detection of FCDs based on these morphometric maps and probe its generalization performance in a large, independent data set. METHODS: In this retrospective study, we created a feed-forward ANN for FCD detection based on the morphometric output maps of MAP18. The ANN was trained and cross-validated on 113 patients (62 female, mean age ± SD =29.5 ± 13.6 years) with manually segmented FCDs and 362 healthy controls (161 female, mean age ± SD =30.2 ± 9.6 years) acquired on 13 different scanners. In addition, we validated the performance of the trained ANN on an independent, unseen data set of 60 FCD patients (28 female, mean age ± SD =30 ± 15.26 years) and 70 healthy controls (42 females, mean age ± SD = 40.0 ± 12.54 years). RESULTS: In the cross-validation, the ANN achieved a sensitivity of 87.4% at a specificity of 85.4% on the training data set. On the independent validation data set, our method still reached a sensitivity of 81.0% at a comparably high specificity of 84.3%. SIGNIFICANCE: Our method shows a robust automated detection of FCDs and performance generalizability, largely independent of scanning site or MR-sequence parameters. Taken together with the minimal input requirements of a standard T1 image, our approach constitutes a clinically viable and useful tool in the presurgical diagnostic routine for drug-resistant focal epilepsy. ispartof: EPILEPSIA vol:62 issue:4 pages:1005-1021 ispartof: location:United States status: published

OBJECTIVE To ascertain factors that are related to the antiepileptic drug load in epilepsy. METHODS In this cross-sectional study, we analyzed a large cohort of conservatively treated patients with epilepsy (n = 1135) and a smaller homogeneous group of presurgical patients with neuropathologically confirmed unilateral hippocampal sclerosis (n = 91). Considered clinical variables comprised (1) presence of an underlying cerebral lesion, (2) onset and (3) duration of epilepsy, (4) seizure frequency, (5) generalized or focal to bilateral tonic-clonic seizures, (6) ictal impairment of awareness, and (7) a history of convulsive status epilepticus. In the presurgical sample, we additionally considered (8) the degree of pathology (hippocampal neuronal cell densities) instead of (1) presence of a cerebral lesion and (9) an overall rating of epilepsy severity (GASE scale). Drug load was quantified as (a) the number of concomitant antiepileptic drugs (AEDs) and (b) the total defined daily dose (DDD). RESULTS Analyses disclosed only small correlations between clinical variables and drug load indices. In the conservatively treated cohort, the multiple regression analyses revealed that epilepsy onset, cerebral lesion, history of convulsive status epilepticus, and seizure frequency combined explained only 6%-10% of variance in drug load. Nearly the same variance (5%-8%) could be explained by duration of epilepsy alone. Degree of hippocampal pathology and the epilepsy severity ratings were not related to drug load indices. SIGNIFICANCE Clinical markers of epilepsy severity were only marginally associated with drug load. Findings rather indicate that patients seem to accumulate drugs due to the chronicity of epilepsy. Overall, the drug load remained largely unexplained. The findings nevertheless call for scrutinizing multidrug therapies in patients with long-lasting epilepsies.

Objective Generalized convulsive seizures (GCS) are associated with high demands on the cardiovascular system, thereby facilitating cardiac complications. To investigate occurrence, influencing factors, and extent of cardiac stress or injury, the alterations and time course of the latest generation of cardiac blood markers were investigated after documented GCS. Methods Adult patients with refractory epilepsy who underwent video-electroencephalography (EEG) monitoring along with simultaneous one-lead electrocardiography (ECG) recordings were included. Cardiac biomarkers (cardiac troponin I [cTNI]; high-sensitive troponin T [hsTNT]; N-terminal prohormone of brain natriuretic peptide [NT-proBNP]; copeptin; suppression of tumorigenicity-2 [SST-2]; growth differentiation factor 15, [GDF-15]; soluble urokinase plasminogen activator receptor [suPAR]; and heart-type fatty acid binding protein [HFABP]) and catecholamines were measured at inclusion and at different time points after GCS. Periictal cardiac properties were assessed by analyzing heart rate (HR), HR variability (HRV), and corrected QT intervals(QTc). Results Thirty-six GCS (6 generalized-onset tonic-clonic seizures and 30 focal to bilateral tonic-clonic seizures) were recorded in 30 patients without a history of cardiac or renal disease. Postictal catecholamine levels were elevated more than twofold. A concomitant increase in HR and QTc, as well as a decrease in HRV, was observed. Elevations of cTNI and hsTNT were found in 3 of 30 patients (10%) and 6 of 23 patients (26%), respectively, which were associated with higher dopamine levels. Copeptin was increased considerably after most GCS, whereas SST-2, HFABP, and GDF-15 displayed only subtle variations, and suPAR was unaltered in the postictal period. Cardiac symptoms did not occur in any patient. Significance The use of more sensitive biomarkers such as hsTNT suggests that signs of cardiac stress occur in about 25% of the patients with GCS without apparent clinical symptoms. SuPAR may indicate clinically relevant troponin elevations. Copeptin could help to diagnose GCS, but specificity needs to be tested.

Limbic encephalitis (LE) forms a spectrum of autoimmune diseases involving temporal lobe epilepsy and memory impairment. Imaging features of LE are known to depend on the associated antibody and to occur on the brain network level. However, first studies investigating brain networks in LE have either focused on one distinct antibody subgroup or on distinct anatomical regions. In this study, brain graphs of 17 LE patients with autoantibodies against glutamic acid decarboxylase 65 (GAD-LE), four LE patients with autoantibodies against leucine-rich glioma-inactivated 1, five LE patients with autoantibodies against contactin-associated protein-like 2, 26 age- and gender-matched healthy control subjects, and 20 epilepsy control patients with hippocampal sclerosis were constructed based on T1-weighted structural magnetic resonance imaging scans and diffusion tensor imaging. GAD-LE showed significantly altered global network topology in terms of integration and segregation as compared to healthy controls and patients with hippocampal sclerosis (P < .01, analysis of variance with Tukey-Kramer post hoc tests). Linear regression linked global network measures with amygdala volume and verbal memory performance (P < .05). Alterations of local network topology show serotype dependence in hippocampus, amygdala, insula, and various cortical regions. Our findings reveal serotype-dependent patterns of structural connectivity and prove the relevance of in silico network measures on clinical grounds.

Objective We assessed the efficacy and safety of once-daily eslicarbazepine acetate in comparison with twice-daily (BID) controlled-release carbamazepine (carbamazepine-CR) monotherapy in newly diagnosed focal epilepsy patients. Methods This randomized, double-blind, noninferiority trial (NCT01162460) utilized a stepwise design with 3 dose levels. Patients who remained seizure-free for the 26-week evaluation period (level A: eslicarbazepine acetate 800 mg/carbamazepine-CR 200 mg BID) entered a 6-month maintenance period. If a seizure occurred during the evaluation period, patients were titrated to the next target level (level B: eslicarbazepine acetate 1200 mg/carbamazepine-CR 400 mg BID, level C: eslicarbazepine acetate 1600 mg/carbamazepine-CR 600 mg BID) and the evaluation period began again. The primary endpoint was the proportion of seizure-free patients for 6 months after stabilization in the per protocol set. The predefined noninferiority criteria were -12% absolute and -20% relative difference between treatment groups. Results Eight hundred fifteen patients were randomly assigned; 785 (388 in the eslicarbazepine acetate group and 397 in the carbamazepine-CR group) were included in the per protocol set, and 813 (401 in the eslicarbazepine acetate group and 412 in the carbamazepine-CR group) were included in the full analysis set for the primary analysis. Overall, 71.1% of eslicarbazepine acetate-treated patients and 75.6% of carbamazepine-CR-treated patients were seizure-free for ≥6 months at the last evaluated dose (average risk difference = -4.28%, 95% confidence interval [CI] = -10.30 to 1.74; relative risk difference = -5.87%, 95% CI = -13.50 to 2.44) in the per protocol set. Rates of treatment-emergent adverse events were similar between groups for patients in the safety set. Noninferiority was also demonstrated in the full analysis set, as 70.8% of patients with eslicarbazepine acetate and 74.0% with carbamazepine-CR were seizure-free at the last evaluated dose (average risk difference = -3.07, 95% CI = -9.04 to 2.89). Significance Treatment with eslicarbazepine acetate was noninferior to BID carbamazepine-CR. With its once-daily formulation, eslicarbazepine acetate provides a useful option for first-line monotherapy for adults with newly diagnosed epilepsy and focal onset seizures.

SummaryObjectives To evaluate dose–response relationship of BGG492 as add-on therapy to 1–3 antiepileptic drugs in patients with partial-onset seizures and to investigate safety and tolerability of BGG492. Methods This was a 12-week, randomized, double-blind, placebo-controlled, phase II dose-titration study (core study) with a 30-week, flexible-dose, open-label extension. In the core study, patients were randomized (1:2) to placebo or BGG492 100 mg t.i.d. in cohort 1, and in cohort 2 patients were randomized (1:4) to placebo or BGG492 150 mg t.i.d. On completion of the core study, eligible patients entered the extension study. Primary outcome measures were total partial seizure frequency per 28 days (core study) and safety and tolerability (extension study). Results Overall, 93 patients were randomized (150 mg [n = 44]; 100 mg [n = 24]; placebo [n = 25]), and 81 (87.1%) completed the core study. Fifty-one patients entered and 43 (84.3%) completed the extension study. In the core study, no statistically significant dose–response trend among the BGG492 treatment groups (100 and 150 mg) was observed at the 4-week double-blind maintenance period (weeks 7–10); however, there was higher percent reduction in total partial seizure frequency in the BGG492 150 mg over placebo groups (37.32%; 95% confidence interval [CI] −18.90, 66.95). Dizziness, somnolence, and fatigue were the most common adverse events (AEs), higher in the BGG492 150 mg group than in the 100 mg and placebo groups (dizziness: 14 [31.8%] vs. 3 [12.5%] and 1 [4.0%]; somnolence: 7 [15.9%] vs. 1 [4.2%] and 1 [4.0%]; fatigue: 5 [11.4%] vs. 1 [4.2%] and 1 [4.0%]). During the open-label extension study, 39 (76.5%) patients on BGG492 had AEs, and the most commonly experienced AEs were dizziness (14 [27.5%]) and somnolence (9 [17.6%]). Significance There was no significant dose–response trend in the BGG492 treatment groups (100 and 150 mg); however, higher percent reduction over placebo was observed in the BGG492 150 mg group. Safety and tolerability data were consistent with the known safety profile for BGG492, and no new safety risks were identified.