Search Results (2,603)

Epilepsy is a prevalent neurological disorder affecting approximately 50 million individuals worldwide. Electroencephalogram (EEG) signals play a vital role in the diagnosis and analysis of epileptic seizures. However, traditional machine learning techniques often rely on handcrafted features, limiting their robustness and generalizability across diverse EEG acquisition settings, seizure types, and patients. To address these limitations, we propose RDPNet, a multi-scale residual dilated pyramid network with entropy-guided feature fusion for automated epileptic EEG classification. RDPNet combines residual convolution modules to extract local features and a dilated convolutional pyramid to capture long-range temporal dependencies. A dual-pathway fusion strategy integrates pooled and entropy-based features from both shallow and deep branches, enabling robust representation of spatial saliency and statistical complexity. We evaluate RDPNet on two benchmark datasets: the University of Bonn and TUSZ. On the Bonn dataset, RDPNet achieves 99.56–100% accuracy in binary classification, 99.29–99.79% in ternary tasks, and 95.10% in five-class classification. On the clinically realistic TUSZ dataset, it reaches a weighted F₁-score of 95.72% across seven seizure types. Compared with several baselines, RDPNet consistently outperforms existing approaches, demonstrating superior robustness, generalizability, and clinical potential for epileptic EEG analysis. Full article

Status epilepticus occurs when a seizure lasts more than five minutes or when multiple seizures occur with incomplete return to baseline. SE induces a myriad of pathological changes involving synaptic and extra-synaptic factors. The transition from a self-limiting seizure to a self-sustaining one is established by maladaptive receptor trafficking, whereby GABA_A receptors are progressively endocytosed while glutamatergic receptors (NMDA and AMPA) are transported to the synaptic membrane, causing excitotoxicity and alteration in glutamate-dependent downstream signaling. The subsequent influx of Ca²⁺ exposes neurons to increased levels of [Ca²⁺]i, which overwhelms mitochondrial buffering, resulting in irreversible mitochondrial membrane depolarization and mitochondrial injury. Oxidative stress resulting from mitochondrial leakage and increased production of reactive oxygen species activates the inflammasome and induces a damage-associated molecular pattern. Neuroinflammation perpetuates oxidative stress and exacerbates mitochondrial injury, thereby jeopardizing mitochondrial energy supply in a state of accelerated ATP consumption. Additionally, Ca²⁺ overload can directly damage neurons by activating enzymes involved in the breakdown of proteins, phospholipids, and nucleic acids. The cumulative effect of these effector pathways is neuronal injury and neuronal death. Surviving neurons undergo long-term alterations that serve as a substrate for epileptogenesis. This review highlights the multifaceted mechanisms underlying SE self-sustainability, pharmacoresistance, and subsequent epileptogenesis. Full article

The electroencephalogram (EEG), widely used for measuring the brain’s electrophysiological activity, has been extensively applied in the automatic detection of epileptic seizures. However, several challenges remain unaddressed in prior studies on automated seizure detection: (1) Methods based on CNN and LSTM assume that EEG signals follow a Euclidean structure; (2) Algorithms leveraging graph convolutional networks rely on adjacency matrices constructed with fixed edge weights or predefined connection rules. To address these limitations, we propose a novel algorithm: Dynamic Graph Convolutional Network with Dilated Convolution (DGDCN). By leveraging a spatiotemporal attention mechanism, the proposed model dynamically constructs a task-specific adjacency matrix, which guides the graph convolutional network (GCN) in capturing localized spatial and temporal dependencies among adjacent nodes. Furthermore, a dilated convolutional module is incorporated to expand the receptive field, thereby enabling the model to capture long-range temporal dependencies more effectively. The proposed seizure detection system is evaluated on the TUSZ dataset, achieving AUC values of 88.7% and 90.4% on 12-s and 60-s segments, respectively, demonstrating competitive performance compared to current state-of-the-art methods. Full article

Miller–Dieker Syndrome (MDS) is a rare neurodevelopmental disorder caused by a heterozygous deletion of approximately 26 genes within the MDS locus of human chromosome 17. MDS, which affects 1 in 100,000 babies, can lead to a range of phenotypes, including lissencephaly, severe neurological defects, distinctive facial abnormalities, cognitive impairments, seizures, growth retardation, and congenital heart and liver abnormalities. One hallmark feature of MDS is an unusually smooth brain surface due to abnormal neuronal migration during early brain development. Several genes located within the MDS locus have been implicated in the pathogenesis of MDS, including PAFAH1B1, YWHAE, CRK, and METTL16. These genes play a role in the molecular and cellular pathways that are vital for neuronal migration, the proper development of the cerebral cortex, and protein translation in MDS. Improved model systems, such as MDS patient-derived organoids and multi-omics analyses indicate that WNT/β-catenin signaling, calcium signaling, S-adenosyl methionine (SAM) homeostasis, mammalian target of rapamycin (mTOR) signaling, Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling, and others are dysfunctional in MDS. This review of MDS integrates details at the clinical level alongside newly emerging details at the molecular and cellular levels, which may inform the development of novel therapeutic strategies for MDS. Full article

Pyridoxine-dependent epilepsy (PDE) represents a group of rare developmental and epileptic encephalopathies. The most common PDE is caused by biallelic pathogenic variants in ALDH7A1 (PDE-ALDH7A1; OMIM #266100), which encodes α-aminoadipate semialdehyde (α-AASA) dehydrogenase, a key enzyme in lysine catabolism. Affected individuals present with seizures unresponsive to conventional anticonvulsant medications but responsive to high-dose of pyridoxine (vitamin B6). Adjunctive lysine restriction and arginine supplementation have also shown potential in improving neurodevelopmental outcomes. Given the significant benefit of early intervention, PDE-ALDH7A1 is a strong candidate for newborn screening (NBS). However, traditional biomarkers are biochemically unstable at room temperature (α-AASA and piperideine-6-carboxylate) or lack sufficient specificity (pipecolate), limiting their utility for biomarker-based NBS. The recent identification of two novel and stable biomarkers, 2S,6S-/2S,6R-oxopropylpiperidine-2-carboxylate (2-OPP) and 6-oxo-pipecolate (oxo-PIP), offers renewed potential for biochemical NBS. We evaluated the feasibility of incorporating 2-OPP, oxo-PIP, and pipecolate into routine butylated FIA-MS/MS workflows used for biochemical NBS. A total of 9402 dried blood spots (DBS), including nine confirmed PDE-ALDH7A1 patients and 9393 anonymized controls were analyzed using a single multiplex assay. 2-OPP emerged as the most sensitive biomarker, identifying all PDE-ALDH7A1 patients with 100% sensitivity and a positive predictive value (PPV) of 18.4% using a threshold above the 99.5th percentile. Combining elevated 2-OPP (above the 99.5th percentile) with either pipecolate or oxo-PIP (above the 85.0th percentile) as secondary marker detected within the same multiplex FIA-MS/MS assay further improved the PPVs to 60% and 45%, respectively, while maintaining compatibility with butanol-derivatized method. Notably, increasing the 2-OPP threshold above the 99.89th percentile, in combination with either pipecolate or oxo-PIP above the 85.0th percentile resulted in both 100% sensitivity and 100% PPV. This study supports the strong potential of 2-OPP-based neonatal screening for PDE-ALDH7A1 within existing NBS infrastructures. The ability to multiplex 2-OPP, pipecolate and oxo-PIP within a single assay offers a robust, practical, high-throughput and cost-effective approach. These results support the inclusion of PDE-ALDH7A1 in existing biochemical NBS panels. Further prospective studies in larger cohorts are needed to refine cutoffs and confirm clinical performance. Full article

Background: Spectrin proteins are critical cytoskeleton components that maintain cellular structure and mediate intracellular transport. Pathogenic variants in SPTBN1, encoding βII-spectrin, have been associated with various neurodevelopmental disorders, including developmental delay, intellectual disability, autism spectrum disorder, and epilepsy. Here we report a Korean infant with infantile epileptic spasms syndrome (IESS) and an SPTBN1 mutation and provide a review of this mutation. Methods: The genomic data of the patient were analyzed by whole exome sequencing. A comprehensive literature review was conducted to identify and analyze all reported SPTBN1 variants, resulting in a dataset of 60 unique mutations associated with neurodevelopmental phenotypes. Case Presentation: A 10-month-old Korean female presented with IESS associated with a de novo heterozygous SPTBN1 mutation (c.785A>T; p.Asp262Val). The patient exhibited global developmental delay, microcephaly, hypotonia, spasticity, and MRI findings of diffuse cerebral atrophy and corpus callosum hypoplasia. Electroencephalography revealed hypsarrhythmia, confirming the diagnosis of IESS. Seizures persisted despite initial treatment with vigabatrin and steroids. Genetic analysis identified a likely pathogenic variant within the calponin homology 2 (CH2) domain of SPTBN1. Conclusions: This is the first report of an association between IESS and an SPTBN1 CH2 domain mutation in a Korean infant. This finding expands the clinical spectrum of SPTBN1-related disorders and suggests domain-specific effects may critically influence phenotypic severity. Further functional studies are warranted to elucidate the pathogenic mechanisms of domain-specific variants. Full article

Sudden Unexpected Death in Epilepsy (SUDEP) is a leading cause of mortality among individuals with epilepsy, particularly those with drug-resistant forms. This review explores the complex multisystem mechanisms underpinning SUDEP, integrating recent findings on brain, cardiac, and pulmonary dysfunctions. Background/Objectives: The main objective of this review is to elucidate how seizures disrupt critical physiological systems, especially the brainstem, heart, and lungs, contributing to SUDEP, with emphasis on respiratory control failure and autonomic instability. Methods: The literature from experimental models, clinical observations, neuroimaging studies, and genetic analyses was systematically examined. Results: SUDEP is frequently preceded by generalized tonic–clonic seizures, which trigger central and obstructive apnea, hypoventilation, and cardiac arrhythmias. Brainstem dysfunction, particularly in areas such as the pre-Bötzinger complex and nucleus tractus solitarius, plays a central role. Genetic mutations affecting ion channels (e.g., SCN1A, KCNQ1) and neurotransmitter imbalances (notably serotonin and GABA) exacerbate autonomic dysregulation. Risk is compounded by a prone sleeping position, reduced arousal capacity, and impaired ventilatory responses. Conclusions: SUDEP arises from a cascade of interrelated failures in respiratory and cardiac regulation initiated by seizure activity. The recognition of modifiable risk factors, implementation of monitoring technologies, and targeted therapies such as serotonergic agents may reduce mortality. Multidisciplinary approaches integrating neurology, cardiology, and respiratory medicine are essential for effective prevention strategies. Full article

Background: The reproducibility of research findings continues to be a challenge in many fields, including neurosciences. It is now required that biological variables such as sex and age be considered in preclinical and clinical research. Rodents are frequently used to model clinical conditions; however, litter information is rarely presented. Some studies utilize entire litters with each animal treated as an independent sample, while others equally assign animals from each litter to different groups/treatments, and others use averaged data. These methods can yield different results. Methods: This study used different analysis methods to evaluate embryo and placenta weights from E17.5 acid-sensing ion channel 2a (ASIC2a) mice with or without seizure exposure. Results: When each embryo was treated as an individual sample, fetal and placental weight significantly differed following seizures in the ASIC2a heterozygous (+/−) and homozygous (−/−) groups. Differences in fetal weight were driven by females in the ASIC2a+/− group and both sexes in the ASIC2a−/− group. These differences were lost when an average per sex/genotype/litter was used. There was no difference in placental weight when treated individually; however, female ASIC2a−/− placentas weighed less following seizures. This difference was lost with averaged data. ASIC2a−/− fetuses from −/− dams had reduced weights post-seizure exposure. Position on the uterine horn influenced embryo and placental weight. Conclusions: Our results indicate that using full litters analyzed as individual data points should be avoided, as it can lead to Type I errors. Furthermore, studies should account for litter effects and be transparent in their methods and results. Full article

Objective: The interactions between the central nervous system (CNS) and the immune system suggest that immune mechanisms may be effective in the pathogenesis of epilepsy and epileptic seizures. Although studies on the natural immune response and epilepsy are continuing, it is not yet clear whether the interaction of the current immune system is due to epilepsy itself or antiepileptic drugs (AEDs), since epileptic patients also use AEDs There are a limited number of studies that have reported an increased incidence of upper respiratory tract infections (URTIs) in patients during levetiracetam (LEV) treatment. Therefore, we aimed to report our experience regarding the effect of LEV monotherapy on the complete blood count (CBC), immunoglobulin (Ig) levels, and lymphocyte subgroups in the interictal period in children and adolescents with epilepsy. Methods: This study enrolled 31 children who presented with epilepsy and underwent LEV monotherapy for at least one year (patient group) and 43 healthy children (control group). The CBC parameters (hemoglobin (hb), lymphocytes, leukocytes, neutrophils, and platelets), Ig levels (IgA, IgM, IgG, and IgE), and lymphocyte subsets (CD3, CD4, CD8, CD4/CD8 ratio, CD19, CD56, NKT cells, and Treg cells) were measured and compared between the two groups. The patients were also investigated regarding the frequency and types of infections that they experienced in the first month and first year of the study, and these data were compared between the patient group and the control group. In addition, the same parameters and the frequency of infection were compared among the patient subgroups (focal and generalized seizures). Results: The results of the present study indicate that there were no significant differences in the CBC parameters, lymphocyte subsets, or Ig levels between the patient group and the control group. The comparison among the patient subgroups was similar; however, the CD4/CD8 ratio was lower in the patient subgroup with focal seizures. In addition, there were no significant differences in the frequency or type of infections experienced one month and one year of the study between the patient group and the control group, and likewise for the patient subgroups (focal and generalized seizures). Conclusions: The present study demonstrated that LEV monotherapy did not increase the incidence of infection, and there were no significant effects on the CBC or on the humoral or cellular immune system in epileptic children. These findings also suggest that the CD4/CD8 ratio among lymphocyte subgroups is lower in patients with focal seizures. However, the epilepsy subgroups had a relatively small sample size; therefore, further prospective studies involving a larger patient population are needed to establish the association between LEV monotherapy and lymphocyte subgroups in patients with epilepsy. Full article

Epilepsy is a chronic neurological disease with a relatively high incidence in the pediatric population. Anti-seizure medication (ASM) may cause adverse drug reactions (ADRs), which may occur repeatedly. Objective: This study aimed to analyze the recurrence of ADRs caused by ASMs over a period of 122 months in hospitalized Mexican pediatric epilepsy patients. The patients were under monotherapy or polytherapy treatment, with valproic acid (VPA), phenytoin (PHT), and levetiracetam (LEV), among others. A total of 313 patients met the inclusion criteria: 211 experienced ADRs, whereas 102 did not. Patient sex, age, seizure type, nutritional status and related drugs were considered explanatory variables. Methods: Four statistical models were used to analyze recurrent events that were defined as “one or more ADRs occurred on a single day”, considering both the classification of ADR seriousness and the ASM causing the ADR. Results: A total of 499 recurrence events were identified. The recurrence risk was significantly greater among younger patients for both nonsevere and severe ADRs and among those with focal seizures for nonsevere ADRs. Interestingly, malnutrition was negatively associated with the risk of nonsevere ADRs, and obesity was positively associated with the risk of severe ADRs. Finally, LEV was associated with a significantly greater risk of causing nonsevere ADRs than VPA. However, LEV significantly reduced the risk of severe ADRs compared with VPA, and PHT increased the risk in comparison with VPA. In conclusion, this study offers a robust clinical tool to predict risk factors for the presence and recurrence of ASM-ADRs in pediatric patients with epilepsy. Full article

Background: Hypometabolism of the thalamus has been reported in epilepsy patients. This study aimed to investigate the prognostic value of thalamic metabolic activity in children with epilepsy. Methods: A total of 200 children with epilepsy and 237 children without epilepsy (sex- and age-matched control group) underwent 18F-FDG PET/CT in this study. Localization of the interictal hypometabolic epileptic focus was performed visually. Bilateral thalamic metabolic activity was evaluated qualitatively (thalamic FDG uptake in relation to the cerebral cortex) and semi-quantitatively (SUV max, normalized SUV (ratio to ipsilateral cerebellum), and absolute asymmetric index (AAI). Results: A total of 133 patients (66.5%) with epilepsy showed cerebral cortical hypometabolism in the interictal 18F-FDG PET study; there were 76 patients on the right side, 55 patients on the left side, and two patients on both sides. Of these 133 patients, 45 also had visually observed asymmetric hypometabolism in the thalamus. Semi-quantitatively, asymmetry was more prominent in epileptic patients. AAI was a more sensitive variable than other variables. Average AAIs were 3.89% and 7.36% in the control and epilepsy patients, respectively. Metabolic activity in the thalami was significantly reduced in epileptic patients compared to the control group. Associated hypometabolism of the ipsilateral thalamus was observed in 66.5% of epileptic patients with a focal cortical defect semi-quantitatively. Overall, 61 out of 200 patients showed thalamus hypometabolism. Some 51 out of 61 patients (83.6%) with thalamus hypometabolism showed refractory disease; however, the refractory disease was noted in 90 out of 139 (64.7%) patients without thalamus hypometabolism. Brain surgery was performed in 86 epileptic patients (43%). Some 35 out of 86 patients had thalamus hypometabolism. Recurrence of epilepsy was observed more in patients with thalamus hypometabolism (48% vs. 25%), with p ≤ 0.01. Conclusion: This study suggests that patients with thalamus metabolic abnormalities may be more medically resistant to therapy and less responsive to surgical treatments. Therefore, the thalamus metabolic abnormality could be used as a prognostic sign in pediatric epilepsy. Recent studies have also suggested that incorporating thalamic metabolic data into clinical workflows may improve the stratification of treatment-resistant epilepsy in children. Full article

Purpose: To assess the performance of 2D T2-weighted (w) Turbo Spin Echo (TSE) MRI reconstructed with a deep learning (DL)-powered super resolution reconstruction (SRR) algorithm combining compressed sensing (CS) denoising and resolution upscaling for high-resolution hippocampal imaging in patients with (epileptic) seizures and suspected hippocampal pathology. Methods: A 2D T2w TSE coronal hippocampal sequence with compressed sense (CS) factor 1 (scan time 270 s) and a CS-accelerated sequence with a CS factor of 3 (scan time 103 s) were acquired in 28 patients. Reconstructions using the SRR algorithm (CS 1-SSR-s and CS 3-SSR-s) were additionally obtained in real time. Two readers graded the images twice, based on several metrics (image quality; artifacts; visualization of anatomical details of the internal hippocampal architecture (HIA); visibility of dentate gyrus/pes hippocampi/fornix/mammillary bodies; delineation of gray and white matter). Results: Inter-readout agreement was almost perfect (Krippendorff’s alpha coefficient = 0.933). Compared to the CS 1 sequence, the CS 3 sequence significantly underperformed in all 11 metrics (p < 0.001-p = 0.04), while the CS 1-SRR-s sequence outperformed in terms of overall image quality and visualization of the left HIA and right pes hippocampi (p < 0.001-p < 0.04) but underperformed in terms of presence of artifacts (p < 0.01). Lastly, relative to the CS 1 sequence, the CS 3-SRR-s sequence was graded worse in terms of presence of artifacts (p < 0.003) but with improved visualization of the right pes hippocampi (p = 0.02). Conclusion: DL-powered SSR demonstrates its capacity to enhance imaging performance by introducing flexibility in T2w hippocampal imaging; it either improves image quality for non-accelerated imaging or preserves acceptable quality in accelerated imaging, with the additional benefit of a reduced scan time. Full article

Background/Objectives: Computed tomography (CT) of the head is vital in diagnosing neurological conditions but poses concerns regarding radiation exposure. Traditional diagnostic reference levels (DRLs) are based on anatomical regions, potentially overlooking variations in radiation requirements driven by clinical indication. This study aimed to establish clinical indication-specific DRLs (DRLCIs) for adult head CT to support precision benchmarking and optimise patient safety. Methods: A retrospective observational study was conducted using data from 378 adult patients undergoing non-contrast CT head scans between September 2022 and February 2024. Data on patient demographics, protocols, and radiation dose metrics (Computed Tomography Dose Index Volume and Dose–Length Product) were extracted using DoseWatch™ software. Protocol parameters were standardised across clinical indications such as trauma, stroke, headache, seizure, and infection. Descriptive statistics and correlation analyses were performed. Descriptive statistics, including means, standard deviations, and percentile distributions, were calculated. Correlation analyses were conducted using Pearson’s correlation coefficient to examine relationships between dose metrics and patient variables such as age and body mass index. Results: Mean CTDIvol values ranged from 50.58 mGy (trauma) to 52.90 mGy (infection), while DLP values ranged from 1052.52 to 1219.98 mGy·cm. Percentile distributions were narrow, indicating effective protocol standardisation. The strongest correlation was observed between CTDIvol and DLP (r = 0.89), while age and body mass index showed negligible influence on dose metrics. Comparative analysis showed alignment with international benchmarks from the UK, Qatar, Bahrain, and Nigeria. Conclusions: This study establishes DRLCIs for adult head CT, demonstrating consistent radiation dose delivery across indications with minimal variability. Clinical indication-based benchmarking enhances dose optimisation and aligns with global radiological protection frameworks. Full article

The assessment of the efficacy of antiseizure medications (ASMs) in animal models of acute seizures has played a critical role in these drugs’ success in clinical trials for human epilepsy. One of the most widely used animal models for this purpose is the maximal electroshock seizure (MES) model. While there are numerous published reports on the efficacy of conventional ASMs in MES models, there is a need to expand the understanding on the brain concentrations that are needed to achieve optimal levels of efficacy in this model. We assessed the pharmacokinetic/pharmacodynamic (PK/PD) profiles of six ASMs, namely carbamazepine (CBZ), phenytoin (PHT), valproic acid (VPA), lacosamide (LSM), cenobamate (CNB), and retigabine (RTG), using MES models in mice and rats. EC₅₀ values for plasma and the brain were generally higher in mice than rats, with fold differences ranging from 1.3- to 8.6-fold for plasma and from 1.2- to 11.5-fold for brain. Phenytoin showed the largest interspecies divergence. These results suggest that rats may exhibit greater sensitivity to seizure protection in the MES model, likely reflecting species differences in metabolism and brain penetration. These findings highlight the value of considering concentration–response variations and species-specific differences when assessing the efficacy of both conventional ASMs and novel compounds exhibiting anticonvulsant activity. Full article

Background and Clinical Significance: Gliomas diagnosed during pregnancy are rare, and there are no established guidelines for their management. Effective treatment requires a multidisciplinary approach to balance maternal health and pregnancy preservation. Case Presentation: We here present a case of rapidly progressing glioma in a 33-year-old pregnant woman. The patient initially presented with a generalized tonic–clonic seizure at 21 weeks’ gestation. Imaging revealed a tumor in the right cerebral lobe, involving both cortical and subcortical structures, while magnetic resonance spectroscopy suggested a low-grade glioma. The patient remained clinically stable for two months but then developed severe headaches; MRI showed a worsening mass effect. At 34 weeks’ gestation, an emergency and premature caesarean section was performed under general anesthesia. The patient then underwent a craniotomy for maximal tumor resection, which was histologically and molecularly diagnosed as IDH wild-type glioblastoma (GB). Using qPCR, we found that the GB tissue showed upregulated expression of genes involved in cell structure (GFAP, VIM) and immune response (SSP1, TSPO), as well as increased expression of genes related to potential hormone response (AR, CYP19A1, ESR1, GPER1). After surgery, the patient showed resistance to Stupp protocol therapy, which was substituted with lomustine and bevacizumab combination therapy. Conclusions: This case illustrates that glioma may progress rapidly during pregnancy, but a favorable obstetric outcome is achievable. Management of similar cases should respect both the need for timely treatment and the patient’s informed decision. Full article