OBJECTIVE:Subscalp electroencephalographic (EEG) systems with few channels have emerged as promising solutions for ultra-long-term seizure monitoring, but the impact of montage configuration on automated seizure detection is unclear. We compared automated detection performance between full-scalp and simulated reduced montages approximating published subscalp devices, and assessed variation by epilepsy type, lateralization, and localization. METHODS:We conducted a retrospective cross-sectional study of consecutive epilepsy monitoring unit (EMU) admissions from January 2017 to December 2024 at the Hospital of the University of Pennsylvania. Admissions with at least one clinician-annotated seizure and at least one interictal segment of ≥20 min from any seizure were included. We simulated reduced bipolar montages from standard 10-20 scalp EEG. Three validated detectors, a one-class support vector machine (SVM), a convolutional neural network (SPaRCNet), and a long short-term memory autoregressive model with neural dynamic divergence method (NDD), were applied to montages and evaluated using event-level F1 scores. We additionally evaluated the contributions of patient, detector, and montage to performance variance and associations between performance and epilepsy characteristics using linear mixed-effects models. RESULTS:A total of 466 admissions from 436 patients (mean [SD] age = 39.0 [14.4] years; 54.4% female) met inclusion criteria, comprising 1683 seizures and 1527 interictal clips. SPaRCNet achieved the highest performance (mean [SD] F1 = .61 [.30]), followed by NDD (.56 [.28]) and SVM (.39 [.25]). Absolute decreases in F1 score with reduced montages were modest (≤.09). Patient admission accounted for the most of performance variance (29.2%), followed by detector (10.3%), whereas montage contributed minimally (.4%). Performance between full and reduced montages was correlated (ρ = .29-.73). SIGNIFICANCE:Automated seizure detection performance was primarily driven by patient and algorithm factors rather than montage. Findings support the feasibility of seizure monitoring with reduced montages approximating chronic subscalp device geometries, despite the need for improved detection algorithms, and suggest that EMU-based full-montage performance could help identify candidates for these devices.
OBJECTIVE:Interictal electroencephalographic (EEG) activities are generally considered asymptomatic. Pulse wave amplitude drop (PWAD) is a marker of autonomic nervous system (ANS) reactivity linked to cardiovascular risk. Generalized paroxysmal fast activity (GPFA) is a major EEG pattern in different epileptic conditions. We investigated whether GPFA, even when clinically silent, triggers ANS activation measured by PWAD. METHODS:We retrospectively analyzed 511 GPFA events during sleep from 21 patients undergoing polysomnography. We characterized GPFA events and their association with PWAD. RESULTS:Among 511 GPFA events, 26.4% were clinically asymptomatic without PWAD (Group 1), 40.5% were clinically silent with PWAD ≥ 30% as the only detected sign (Group 2), and 33.1% were clinically symptomatic (Group 3). Compared to Groups 1 and 2, Group 3 events had longer duration (p = .007 and p < .0001), had higher heart rate variation (p < .001), and were more often symmetric (p < .001). Group 3 GPFA occurred more often in N1 sleep compared to Group 2 (32.1 vs. 18.1%, p = .004). Unexpectedly, PWAD was poorly correlated with GPFA duration (r = .068). Finally, Group 2 GPFA-associated PWADs more closely resembled microarousal-associated PWADs than apnea/hypopnea-associated PWADs in temporal profile. SIGNIFICANCE:PWAD uncovers autonomic responses in most GPFA, challenging the concept that "interictal" implies asymptomatic. This repetitive ANS activation raises questions about its potential long-term clinical consequences. These findings support the use of pulse oximetry during video-EEG to detect subclinical autonomic changes, although further studies are needed to determine their clinical significance and whether they should influence the management of interictal activities.
OBJECTIVE:Drug-resistant epilepsy (DRE) remains a significant clinical challenge, affecting approximately 30% of patients. Deep brain stimulation (DBS) of the centromedian thalamic nucleus (CM) has emerged as a viable therapy for generalized and multifocal seizures. Although high-frequency stimulation (HFS) is the clinical standard, emerging evidence suggests that low-frequency stimulation (LFS) may offer comparable efficacy with improved safety and battery longevity. METHODS:We conducted a prospective, open-label, within-subject study involving 10 patients with generalized or multifocal DRE already treated with CM-DBS. Patients were transitioned from HFS (130-180 Hz) to LFS (6-10 Hz). Primary outcomes included seizure frequency reduction and safety. Secondary outcomes assessed behavioral and cognitive changes using the Vineland Adaptive Behavior Scales, Third Edition (VABS-III). RESULTS:Four patients with absence seizures (44%) had an improvement in seizure frequency noted immediately in the 1st month. One patient (11%) had a transient deterioration in absence seizure frequency in the 1st month but from the 3rd month onward had a 50% improvement compared to the baseline. The other four patients did not have any significant change in any seizure frequency. A substantial reduction in implantable pulse generator energy consumption was observed. Caregivers reported qualitative improvements in social behavior and cognitive engagement, although VABS-III scores did not reach statistical significance. One patient was excluded due to behavioral deterioration during the LFS transition phase. SIGNIFICANCE:This is the first prospective study addressing the efficacy and safety of low-frequency (LF) versus high-frequency CM-DBS in patients with generalized or multifocal epilepsy. LF CM-DBS is a potentially safer and more energy-efficient alternative to HFS, maintaining clinical efficacy in selected patients with generalized or multifocal DRE. These findings warrant further investigation through larger, randomized, double-blind trials.
OBJECTIVE:In temporal lobe epilepsy (TLE), patients often present with neurobehavioral comorbidities encompassing affective and cognitive difficulties. Whereas the latter have been related to atypical connectivity of mesiotemporal and frontotemporal circuits, the brain basis of affective symptoms remains incompletely understood. Here, we assessed functional network substrates of affective symptoms and examined their relationship to structural magnetic resonance imaging (MRI), cognition, and clinical parameters. METHODS:We studied 42 drug-resistant patients who underwent multimodal 3-T MRI as well as self-report questionnaires of affective and cognitive functions outside the scanner, alongside 41 age- and sex-matched healthy controls. Partial least squares (PLS), a brain-wide multivariate associative technique, examined relationships between resting-state functional MRI connectivity strength (FCS) and affective measures. Linear models assessed relationships with morphology and microstructure, as well as cognitive and clinical parameters. RESULTS:Moderate to severe anxiety was present in 79% of patients, with concealing and adjustment as coping strategies, and 40% experienced depression. Quality of life scores were below published norm for epilepsy. PLS analysis revealed a latent component that accounted for 67% of the covariance between FCS and affective symptoms, linking weaker connectivity in temporoparietal and prefrontal cortices, as well as mesiotemporal, thalamic, and pallidal regions, to anxiety, low energy/fatigue, medication-related complaints, and reduced quality of life. Among cognitive domains, verbal memory positively correlated with the same brain areas. Cortices with the strongest covariance between FCS and affective variables presented with marked atrophy and myelin alterations (indexed by T1/fluid-attenuated inversion recovery decreases). Controlling for verbal memory and metrics of brain structure, the temporal-parietal network remained the most compromised. SIGNIFICANCE:Dysconnectivity of the temporal-parietal network emerges as a key contributor to affective symptoms in TLE, and limbic network dysfunction additionally impacts cognition. These findings emphasize the importance of multidisciplinary care targeting both emotion regulation and stress reduction, alongside cognitive rehabilitation, for improved well-being and quality of life.
OBJECTIVE:The detection of subtle epileptogenic lesions such as focal cortical dysplasias (FCDs) is a clinical challenge in the management of drug-resistant focal epilepsy (DRFE). Ultra-high-field (UHF) magnetic resonance imaging (MRI) offers increased signal-to-noise ratios and spatial resolution compared to 3-T MRI and may improve diagnostic yield. METHODS:We recruited n = 21 DRFE patients (with 3-T MRI findings: two positive, three equivocal, 16 negative) undergoing presurgical workup and n = 20 healthy controls for 9.4-T MRI (.8 mm isotropic magnetization-prepared 2 rapid acquisition gradient echo [MP2RAGE], slabs of .375 × .375 × .8 mm T2*-weighted gradient echo) and 3-T MRI (magnetization prepared rapid acquisition gradient echo [MPRAGE], magnetization-prepared 2 rapid acquisition gradient echo [MP2RAGE], fluid-attenuated inversion recovery [FLAIR]) acquisitions. Visual review for possible epileptogenic lesions was performed by clinical experts. For histopathologically confirmed FCDs, we extracted surface-based quantitative features (cortical thickness, quantitative T1, FLAIR, T2*, and quantitative susceptibility mapping values) across cortical depths and distances from the lesion center and performed high-resolution cortical profiling of 9.4-T T2* values. RESULTS:In two patients with histopathologically confirmed FCD IIb, lesions were visible with distinct qualitative and quantitative features at both field strengths. One of these type IIb FCDs showed a focal cortical T2* reduction at 9.4 T that could be quantified via automated cortical profiling, consistent with the previously described "black line sign." No new epileptogenic lesions were identified at 9.4 T in 3-T MRI-negative patients, who also had no histological evidence of such lesions. SIGNIFICANCE:9.4-Tesla MRI findings in epileptogenic lesions underlying DRFE are consistent with those on 3-T MRI. UHF T2*-weighted sequences may be useful to detect the black line sign and thereby refine surgical or ablation targeting for some FCDs. Assessment of the diagnostic yield of 9.4-T MRI was limited by the lack of 3-T MRI-negative but histopathologically confirmed cases and by the unavailability of parallel transmit and FLAIR at 9.4 T. Further optimization of UHF protocols and analysis methods on larger cohorts may enhance clinically applicable diagnostic benefits.
OBJECTIVE:Capillary microsampling offers a minimally invasive alternative to venipuncture for therapeutic drug monitoring (TDM) of anti-seizure medications (ASMs). We evaluated the feasibility and reliability of volumetric absorptive microsampling (VAMS) and quantitative dried blood spot (qDBS) devices for ambulatory self-collection and at-home use in persons with epilepsy (PwE). METHODS:PwE attending the Epilepsy Centre of the IRCCS-Istituto delle Scienze Neurologiche di Bologna (Italy) were enrolled between October 2023 and October 2024. Participants performed supervised self-collection using VAMS and qDBS in ambulatory setting and at-home self-collection with VAMS devices. Sample quality, delivery success, and patient-reported outcomes (ease, pain, and clarity of instructions) were recorded. Carbamazepine, lacosamide, lamotrigine, and levetiracetam were quantified using a validated ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method. Reliability was assessed by comparing at-home VAMS with ambulatory VAMS and cross-validating qDBS with VAMS and venous plasma samples using Bland-Altman analysis and linear regression. RESULTS:A total of 105 PwE (66% female, mean age 41 years) performed at-home and ambulatory self-collection using VAMS and qDBS devices. Most at-home VAMS samples (88%) were received by the laboratory within 7 days, and 86.8% met high-quality criteria. For lacosamide, lamotrigine, and levetiracetam, we found strong correlations between at-home and ambulatory VAMS (Pearson's r ranging from .88 to .98) and low mean bias (<1.0 μg/mL). Conversely, carbamazepine showed lower reliability (r = .31; p = .49; bias = 2.05 μg/mL). Cross-validation of qDBS vs plasma confirmed good agreement (slope = .92, .63-1.21) with no significant systematic bias. Patient feedback indicated that self-collection was easy and minimally painful, although age>60 years impacted sampling quality, particularly for qDBS (p = .04). SIGNIFICANCE:VAMS-based self-collection is feasible and reliable for at-home TDM, provided that high-quality sampling is ensured. qDBS represents a reliable alternative for ambulatory monitoring. Future work should focus on optimizing sampling procedures for older adults and improving logistics for home-based microsampling.
OBJECTIVE:Given the reciprocal interaction between tumor biology and seizure activity, seizure outcomes in low-grade glioma (LGG) may be dynamic and influenced by both tumor- and treatment-related factors. We aimed to identify factors associated with seizure occurrence across distinct clinical stages, including diagnosis, surgery, long-term follow-up, and antiseizure medication (ASM) withdrawal. METHODS:We retrospectively analyzed patients with World Health Organization grade 1-2 glioma who underwent surgery between January 2001 and February 2025 and experienced seizures during their disease course. Clinical, radiological, molecular, and treatment-related variables, along with longitudinal seizure data, were collected. Seizure outcomes were evaluated at 6 and 12 months and at final follow-up, including time to postoperative seizure recurrence and recurrence after ASM withdrawal. RESULTS:Among 100 patients (mean postoperative follow-up = 89.9 months), 70.0% achieved seizure freedom during the final year of follow-up. At 6 months, gross total resection (odds ratio [OR] = 3.45, 95% confidence interval [CI] = 1.19-10.01, p = .02) and preoperative tumor volume (OR = .99, 95% CI = .97-1.00, p = .048) were independently associated with seizure outcomes. At 12 months, preoperative tumor volume (OR = .99, 95% CI = .98-1.00, p = .04) was significant. Conversely, seizure at presentation was the sole independent determinant of favorable long-term seizure outcome (OR = 6.37, 95% CI = 2.07-19.61, p < .01) and the only predictor of reduced postoperative seizure recurrence in survival analysis (hazard ratio = .26, 95% CI = .11-.62, p < .01). ASM withdrawal was successful in 67.7%. Although tumor progression showed a trend toward an association with recurrence in univariate analyses, no independent predictors were identified in Cox regression for ASM withdrawal outcomes. SIGNIFICANCE:This time-resolved analysis suggests that early seizure control is primarily influenced by surgical and tumor burden-related factors, whereas long-term seizure outcomes and recurrence appear to be predominantly determined by the clinical presentation at diagnosis rather than treatment-related variables. These findings suggest that postoperative seizure prognosis in LGG reflects pre-existing epileptogenic vulnerability and may not be adequately captured by single time point assessments.
OBJECTIVE:Although the centromedian nucleus of the thalamus (CM) is an increasingly considered deep brain stimulation (DBS) target for drug-resistant epilepsy (DRE), there is significant variability in programming practices, which may contribute to heterogenous outcomes. We systematically described stimulation parameters for CM-DBS and their association with seizure outcomes to inform a standardized, evidence-informed programming framework. METHODS:We performed a Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA)-guided systematic review and meta-analysis of published studies pertaining to CM-DBS including all dates through March 2026. Eligible studies included patients with DRE treated with CM-DBS, extractable seizure outcomes, and reported stimulation parameters. Study-level data and extractable patient-level data were synthesized. The primary outcome was percent seizure reduction at the last follow-up. Using random-effects meta-analysis we summarized study-level efficacy and performed regression analyses to assess associations with diagnosis, seizure semiology, and stimulation parameters. RESULTS:Thirty studies including 269 individuals met inclusion criteria. Median seizure reduction was 71.5% and 200 participants (74.6%) with seizure outcome data were responders (>50% seizure reduction), which likely represents an upper bound on true efficacy given the predominance of non-randomized studies at serious-to-critical risk of bias. Generalized tonic-clonic seizures were associated with greater seizure reduction. Tonic seizures were associated with worse outcome, yet this was attenuated after accounting for study clustering. Stimulation parameters varied substantially across studies. No single nominal stimulation parameter demonstrated a robust clinically actionable association with outcome; however, estimated total electrical energy delivered was associated with greater seizure reduction on multivariable modeling, yet this was attenuated when accounting for clustering between studies. SIGNIFICANCE:These findings map the landscape of programming of CM-DBS, while emphasizing the need for standardized reporting of stimulation parameters, contact localization, and stimulation exposure to enable prospective optimization. On this basis, we propose a pragmatic, evidence-informed programming framework for CM-DBS that emphasizes postoperative contact localization, standardized initial stimulation settings, and stepwise titration of stimulation exposure.
OBJECTIVE:Epileptic arousals (EAs) are seizures characterized solely by arousal from sleep. EAs are unrecognized in current seizure classifications. Their subtle semiology and inconsistently detectable ictal activity in scalp electroencephalography (EEG) complicate differentiation from physiological arousals (PAs). This study characterizes EAs using simultaneous intracranial electroencephalography (iEEG) and scalp EEG with electrocardiography (ECG), exploring their neural and autonomic dynamics. METHODS:We retrospectively analyzed presurgical video-EEG monitoring data of 20 focal epilepsy patients (2010-2023). EAs were identified visually. Their seizure-onset zones (SOZs) and seizure-propagation zones (SPZs) were defined in Montreal Neurological Institute (MNI) space and compared to other seizure types. The detectability of ictal activity of EAs in scalp EEG was evaluated. Associations with SOZs/SPZs were assessed using logistic regression. Heart rate dynamics were compared between EAs and PAs evaluating distribution modality, variability, and receiver operating characteristic (ROC) analysis. RESULTS:Among 507 seizures, 133 (26.2%) were EAs. SOZs of EAs partially overlapped with other seizure types (Jaccard similarity index 0.47). Two-thirds (66.9%) of EAs were undetectable by scalp EEG. Detectability increased with broader maximal SPZs (odds ratio [OR] = 3.16; ROC-AUC [area under the curve] = 0.891). Heart rate increased during both EAs and PAs (p < 0.001), yet modulation was greater during EAs (p = 0.007, ROC-AUC = 0.995) and showed a multimodal distribution (p < 0.001). SIGNIFICANCE:EAs are common, yet underrecognized. They arise from partially distinct networks and may exhibit a specific autonomic signature, supporting their recognition as a separate seizure type. Reliance on scalp EEG alone risks missing patients with a high EA burden. Undetected EAs can perpetuate epileptic activity and sleep fragmentation.
OBJECTIVE:Drug-resistant epilepsy is a common, severe manifestation of the genetic disorder tuberous sclerosis complex (TSC). Although significant mechanistic and therapeutic advances have been made in TSC, treatments for seizures remain largely ineffective. Decreased expression of the potassium-chloride cotransporter KCC2 is associated with depolarizing γ-aminobutyric acid (GABA) signaling and increased neuronal excitability in the immature brain and in certain pathological states. In this study, we investigated abnormalities in KCC2 expression and function in a mouse model of TSC-related epilepsy. METHODS:Tsc1GFAPCKO mice were used to investigate KCC2 expression by Western blotting and immunohistochemistry. The effects of KCC2 pharmacological modulators on KCC2 expression and seizures in Tsc1GFAPCKO mice were tested by Western blotting and video-electroencephalography. RESULTS:KCC2 expression was decreased in Tsc1GFAPCKO mice compared with controls, including prior to the onset of seizures. The decrease in KCC2 expression was reversed by the mTOR inhibitor rapamycin as well as select KCC2 modulators. These KCC2 modulators also decreased seizures in Tsc1GFAPCKO mice. SIGNIFICANCE:Decreased KCC2 expression may lead to impaired GABAergic inhibition and increased neuronal excitability, contributing to epileptogenesis in TSC. Potentiation of KCC2 expression may represent a novel, effective therapeutic approach for epilepsy in TSC.
OBJECTIVE:Quantitative assessment of extent of tissue resection following epilepsy surgery requires accurate delineation of the resection cavity on postoperative magnetic resonance imaging (MRI). Current methods for resection cavity masking are time-consuming and labor-intensive, and existing automated approaches exhibit variable segmentation accuracy, particularly on extratemporal resections. We developed MELD-PostOp, a deep learning tool trained and evaluated on a large, heterogeneous cohort to automatically segment resection cavities. METHODS:The study included 1.5- and 3T postoperative three-dimensional T1-weighted MRI images from the Multicentre Epilepsy Lesion Detection (MELD) project (nsubjects = 969, 27 centers) and from the EPISURG dataset (n = 133). The cohort included children and adults, alongside a range of resection locations, pathologies, and MRI characteristics. Resection cavities were individually segmented in 285 subjects and used to train an nnU-Net prototype model. The prototype model was used to generate an additional 680 resection masks, which were subsequently quality-controlled, edited, and combined with the original 285 to train the final MELD-PostOp model (n = 965). A Stratified Test Cohort (n = 50) and Independent Test Cohort (n = 87) were withheld for model evaluation. Performance was evaluated using Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), number of predicted clusters, and inference runtime, and compared against established tools (Epic-CHOP, ResectVol, and RESSEG). RESULTS:MELD-PostOp achieved a median DSC of .85 and HD95 of 3.61 on the combined test cohort, outperforming Epic-CHOP (DSC .69, HD95 9.67), ResectVol (DSC .66, HD95 15.05), and RESSEG (DSC .43, HD95 32.67), with significant improvements seen in both temporal and especially extratemporal resections. The model detected 98.5% (135/137) of resection cavities. MELD-PostOp runtime was 17 s per MRI, compared to 612 s (ResectVol), 3205 s (Epic-CHOP), and 4 s (RESSEG). MELD-PostOp performance remained high across clinical and imaging subgroups (median DSC > .8). SIGNIFICANCE:MELD-PostOp is an open-source research tool that provides an accurate, efficient, and generalizable solution for postoperative resection cavity segmentation using only postoperative MRI scans.
OBJECTIVE:We assessed the timing, dosing, and effectiveness of diazepam nasal spray in a large dataset of seizures treated in the out-of-hospital setting, using as reference the International League Against Epilepsy criteria for tonic-clonic status epilepticus (SE) and its treatment. METHODS:We analyzed pooled data from two studies evaluating the use of diazepam nasal spray as acute treatment for seizures in the out-of-hospital setting, a phase 1/2a pharmacokinetics and safety study (patients aged 2-5 years) and a phase 3 long-term safety study (patients aged 6-65 years). For this analysis, tonic-clonic SE episodes were defined as seizures lasting beyond time point t1 (5 min). Responder analyses examined SE termination by time point t2 (30 min after seizure start) and SE termination ≤20 min after dose administration. SE recurrence at ≤1, 12, and 24 h after SE termination was also assessed. Rate of SE episodes for which ≥2 doses of diazepam nasal spray were administered was a proxy for effectiveness. We also reported safety data. RESULTS:Of episodes with sufficient data for classification, a total of 402 episodes were categorized as tonic-clonic SE. The majority of tonic-clonic SE episodes terminated by t2 (248 [61.7%]) and nearly half terminated within 20 min after dose administration (200 [49.8%]). SE recurrence after SE termination was low, with <5% of tonic-clonic SE episodes followed by a recurrence in ≤24 h. Rate of usage of ≥2 doses for tonic-clonic SE episodes was low (5% [20 seizure episodes]). Serious treatment-emergent events of SE occurred in 6.6% of patients with tonic-clonic SE episodes. SIGNIFICANCE:These findings support the safety and effectiveness of diazepam nasal spray for treating episodes of tonic-clonic SE and strengthen the evidence of the benefits of immediate-use antiseizure medication for seizure emergencies, including early SE.
OBJECTIVE:This study was undertaken to characterize sleep architecture assessed by polysomnography (PSG) in children with epilepsy versus matched nonepilepsy clinical comparators and disentangle disease from antiseizure medication (ASM) effects. METHODS:In this cross-sectional analysis of the Nationwide Children's Hospital Sleep DataBank (3647 PSG studies from 3392 patients aged ≤18 years), a clinical cohort referred for PSG, we compared 560 PSG studies in children with epilepsy to 3087 studies in nonepilepsy clinical comparators. Propensity score matching (1:1) on age, sex, and body mass index percentile yielded 560 pairs. Fifteen PSG outcomes were compared using Wilcoxon signed-rank tests with Hedges g and false discovery rate (FDR) correction. A secondary analysis compared 208 matched pairs of on- versus off-ASM epilepsy patients. Seven sensitivity analyses addressed age subgroups, medication exclusions, and comorbidity matching. RESULTS:Children with epilepsy had reduced rapid eye movement (REM) sleep (median 18.2% vs. 20.9%, g = -.32 [95% confidence interval = -.41 to -.24], FDR p < .001), lower sleep efficiency (g = -.14, p = .007), shorter total sleep time (g = -.12, p = .015), prolonged REM latency (g = .14, p = .029), and lower arousal index (g = -.12, p = .013). ASM use amplified the REM deficit (15.8% vs. 19.8%, g = -.48, p < .001). The effect followed a developmental gradient: strongest at age < 6 years (g = -.38, p < .001), intermediate at 6-12 years (g = -.31, p = .002), and not detected at >12 years (g = -.07, p = .953). Excluding benzodiazepine users attenuated the signal (g = -.24), whereas excluding melatonin users preserved it (g = -.29). SIGNIFICANCE:In the largest pediatric epilepsy PSG study to date, epilepsy is associated with an REM-predominant sleep disruption concentrated in children younger than 6 years and amplified by ASMs, although the independent contribution of epilepsy itself remains uncertain. These cross-sectional findings identify early childhood as a period of heightened vulnerability that warrants prospective study.
Autoimmune encephalitis usually presents with short-duration neuropsychiatric syndromes, mainly behavioral with cognitive dysfunction, recurrent seizures, and movement disorders. Among them, anti-LGI1 encephalitis has faciobrachial dystonic seizure as a pathognomic feature. The two cases reported here exemplify another peculiar feature of anti-LGI1 encephalitis, which has rarely been reported and is therefore not typically emphasized. Both cases were initially treated for cardiac symptoms until the full-blown features of encephalitis became evident. The key to preventing adverse outcomes is early detection, as anti-LGI1 encephalitis is largely reversible when treated early with immunotherapy, whereas a delay in diagnosis can lead to permanent damage or fatal outcomes.
OBJECTIVE:Interictal epileptiform spikes (IESs) are widely used biomarkers of epileptogenic tissue in presurgical epilepsy evaluation. However, their reliability for seizure onset zone (SOZ) localization in high-density intracranial electroencephalography (iEEG) remains inconsistent. It is underexplored whether this variability reflects methodological differences across detection algorithms or a limitation of IESs as a biomarker. This study evaluates whether IES detection alone provides sufficient spatial specificity for accurate SOZ localization in iEEG. METHODS:We systematically benchmarked eight established IES detection algorithms using iEEG recordings from 35 patients with drug-resistant focal epilepsy. To provide a clinically meaningful reference, algorithm performance was evaluated against the clinically defined SOZ. To refine detection outputs and move beyond only IES detection, we applied masking strategies to isolate informative IES subsets based on rate, amplitude, frequency, and co-occurrence with high-frequency oscillations (HFOs). Conceptually, masking acts as a spatial refinement strategy that progressively restricts diffuse IES activity to more focal, pathologically relevant event populations. RESULTS:Despite substantial variability in detection characteristics, SOZ localization performance (ratio of events originating from SOZ divided by total number of events) converged within a narrow range (.23-.51), suggesting that IESs exhibit an intrinsic ceiling in SOZ localization performance when used alone. Amplitude-based masking yielded modest improvements, whereas frequency-based masking reduced performance. In contrast, IES-HFO co-occurrence markedly improved localization, particularly when combined with rate-based masking, achieving a median SOZ localization ratio of .89, exceeding IESs (.37) and HFOs (.63) evaluated independently. SIGNIFICANCE:These findings demonstrate that IES-based SOZ localization may require moving beyond detection-only approaches. The integration of informed, biomarker-driven masking strategies provides a more robust framework for identifying the activity most relevant to the epileptogenic network and paves the way for future incorporation into the clinical decision-making pipeline.
OBJECTIVE:The Dravet Disease-Associated Neuropsychiatric Disorders (D-DAND) scale is a new caregiver-administered interview designed to assess the wide range of developmental and behavioral comorbidities in Dravet syndrome (DS) beyond seizures. D-DAND's preliminary psychometric properties in a large patient sample are reported. METHODS:D-DAND was developed by a panel of experts and later standardized with caregivers of 123 individuals with DS (age = 3-41 years); a subsample of 43 caregivers were interviewed twice (~2 weeks apart) to evaluate test-retest reliability; another subsample of 80 were also administered with other scales that are widely used despite not being tailored to DS (Vineland Adaptive Behavior Scales, Child Behavior Checklist, Childhood Autism Rating Scale, Behavior Rating Inventory of Executive Function, Sleep Disturbance Scale for Children). RESULTS:The D-DAND captured a broad spectrum of abilities and dysfunctions across multiple functional domains. Test-retest reliability was excellent (overall score: r ≈ .98, median across domains: r ≈ .89), thus allowing for high sensitivity to time-related changes. As expected, D-DAND scores showed high correlations with some standardized measures (e.g., Vineland scales) and low correlation with others, suggesting that D-DAND measures unique, Dravet-specific features that other, widely used tools fail to detect. SIGNIFICANCE:D-DAND is a novel, reliable tool for comprehensive evaluation of DS beyond seizures. It enables systematic tracking of developmental and behavioral issues in DS, facilitating early identification of needs and more personalized, whole-person care.
More than 25 years have passed since the first randomized controlled trial (RCT) established that surgery is superior to continued anti-seizure medication (ASM) for drug-resistant temporal lobe epilepsy, and nearly as long since a joint practice parameter urged that appropriate surgical candidates be referred to a specialized center for evaluation-guidance that subsequent consensus has since broadened to all patients with drug-resistant epilepsy. Despite Class I evidence and durable guidelines, epilepsy surgery remains one of the most underutilized effective interventions in medicine: fewer than 1% of potentially eligible patients are referred, and those who are referred reach a center on average two decades after seizure onset. This critical review, framed primarily around U.S. data and supplemented by a dedicated assessment of the global picture, examines the scope and burden of drug-resistant epilepsy (DRE), the foundational evidence and guideline history, and the magnitude, patterns, and causes of persistent underutilization, including a distinct discussion of pediatric care and of disparities by race, insurance, and geography. We then turn to grounds for optimism. Surgical candidacy has materially expanded through minimally invasive approaches to both monitoring (stereo-electroencephalography) and treatment (laser interstitial thermal therapy and neuromodulation), and indications have broadened to include selected generalized and multifocal epilepsies through thalamic neuromodulation. Contemporary International League Against Epilepsy (ILAE) recommendations go further still, extending referral even to selected patients who are seizure-free on medication but harbor a surgically accessible lesion. We also raise a counterbalancing concern: the welcome diffusion of minimally invasive options should not eclipse resective and disconnective surgery, which remain the only potentially curative options validated by RCTs. We conclude that, 25 years on, underutilization persists as a major and partly remediable problem, and we offer recommendations for closing the surgical gap.
OBJECTIVE:Despite the reported high prevalence of catamenial epilepsy (CE), the condition remains poorly defined, with lack of consensus on what entails a menstrual-related seizure exacerbation. Emerging evidence of multiday cycles of seizure activity, including about-monthly cycles, present in both men and women, further confound the existence of CE. Issues of misdiagnosis, attribution bias, and potentially inappropriate hormonal therapies are relevant downstream effects of poorly defined CE. The purpose of this focused review was to examine the current literature on defining CE, alongside non-specific monthly seizure cycles, and appraise the most commonly utilized diagnostic methods. Against this background, we aim to identify limitations with current CE diagnostics in order to improve the methods of studying epilepsy chronobiology. METHODS:A scoping review on all primary source literature reporting on CE using the Ovid MEDLINE and EMBASE databases was conducted. Studies were limited to clinical trials and case reports, which were then classified by the CE definition utilized and length of diagnostic monitoring. This was repeated for literature on non-specific, multidien seizure cycles. RESULTS:Overall, 70 CE studies were included of the 233 studies screened (30.0%). Of these, most did not define or specify CE criteria utilized (52.9%). Studies predominantly did not specify the duration of seizure and menstrual-data recording before the establishment of a CE diagnosis (47.1%), and if specified, was most frequently for 3 months or less (32.9%). In general, the literature on multidien seizure cycles (n = 33) had longer average recording periods (24 months), more multimodal recording, balanced sexes, and conducted more significance testing. SIGNIFICANCE:Current definitions on CE are fragmented in the literature. The common methods of workup cannot reliably differentiate CE from other monthly rhythms evident equally in men, women, and children. Current time-based diagnoses of CE have limited ability to extrapolate into an accurate long-term rhythm.
