Long-term video-EEG Research Articles

Temporal lobe epilepsy with isolated amygdala enlargement: anatomo-electro-clinical features and long-term outcome.

Temporal lobe epilepsy with isolated amygdala enlargement (TLE-AE) still lacks a definite characterization and controversies exist. We conducted a retrospective study identifying brain MRI scans with isolated AE between 2015 and 2021. We collected clinical and paraclinical data of patients with TLE-AE and evaluated the outcome. Forty-one subjects were included (20 males; AE: right 13; left 24; bilateral 4). A strong correlation was found between AE and MRI T2-hyperintensity (right: p < 0.005; left: p < 0.003). There was no history of febrile seizures; 85,4% had focal seizures with impaired awareness, 78,1% reported auras (epigastric sensation, déjà-vu, anxiety), 37% had psychiatric disturbances, 48,6% presented with cognitive impairment. We report that AE correlates with FDG-PET temporomesial hypometabolism (right: p = 0.022; left: p = 0.053), temporal interictal activity on EEG (n = 41), and temporal ictal findings during long-term video-EEG monitoring (n = 23). Epilepsy surgery (n = 17) revealed gliosis (n = 4), inflammatory infiltrates (n = 4), or low-grade epilepsy-associated neuroepithelial tumors (n = 5) in the amygdala. Other treatments were immunotherapy (n = 6) and only antiseizure medications (n = 17), with good prognosis (58,1% seizure-free and 17,1% only with auras at last follow-up). There was no correlation between longitudinal changes in seizure frequency and amygdala size (p = 0.848) and T2-hyperintensity (p = 0.909). AE should be searched in TLE patients with typical aura, psychiatric and/or neurocognitive disturbances. The strong correlations found between AE lateralization and neurophysiological, FDG-PET, and MRI data supportinvolvement of AE in the epileptogenic network. Drug resistance should prompt presurgical study. Inflammation in amygdala specimens and response after immunotherapy suggest an immune-mediated etiology in some TLE-AE cases.

CASPR2-related epilepsy: A distinctive and unrecognized form of epilepsy in adult and elderly males.

The aim of this study was to describe the clinical features of contactin-associated protein-like 2 (CASPR2)-IgG-associated seizures. Nine patients were retrospectively collected from two epilepsy centers. For each patient we obtained a full clinical, neurophysiological, and MRI study along with detection of antineuronal autoantibodies from serum and CSF. The patients were followed up for 1-6 years. The patients were nine male subjects aged 56-85 years (mean: 66) with a 1- to 14-year (mean: 6,3 median: 6) history of seizures. The seizures were classified as focal onset seizures with impaired awareness, usually preceded by epigastric aura (two), piloerection (two), olfactory hallucinations (two), nausea and dizziness (one). Tonic-clonic seizures were present in five patients. Seizure frequency was high in six cases and sporadic in three. Most patients reported memory impairment (eight) or behavioral/mood changes (four). Interictal EEGs usually showed bilateral or unilateral temporal epileptiform abnormalities. A number of seizures arising from the temporal lobes, with bilateral asynchronous onset, were recorded on long-term video-EEG monitoring in two patients. MRI disclosed nonspecific white matter T2 hyperintensities suggestive of chronic vascular changes in four patients and bilateral T2-FLAIR amygdalo-hippocampal hyperintensity in three cases. Neuropsychological study demonstrated various degrees of cognitive impairment in the majority of cases. Increased titers of CASPR2 autoantibodies were detected in the serum and CSF, which persisted over time in four cases. Drug resistance to common anti-seizure medications was present in seven cases who benefited from immunotherapy. CASPR2-IgG testing should be performed among old male patients with a recent or even not recent onset of focal seizures with impaired awareness particularly when these seizures are accompanied by cognitive impairment or behavioral disturbances. In these cases, anti-seizure medications may be ineffective while immunotherapy may lead to a prompt improvement of seizures and cognitive deficits.

Temporal Lobe Epilepsy with Bitemporal Interictal Epileptiform Discharges: Effects of Sleep and Wakefulness

Introduction. Independent bitemporal interictal discharges are often found in patients with temporal lobe epilepsy. The likelihood of registering epileptiform activity (EA) is higher during sleep. Assessment of bitemporal interictal epileptiform discharges (BIEDs) with various discharge predominance ratio is used for presurgical evaluation of epilepsy patients and prediction of surgical outcomes. Our objective was to determine the predominant side (PS) in patients with bitemporal epilepsy using the incidence of epileptiform discharges for each sleep stage. Materials and methods. We analyzed 45 recordings of 10–24 h long-term video-EEG monitoring (LTM) in patients with bitemporal EA. For each recording, the total incidence of EA (IEA) and EA incidence for wakefulness and for each sleep stage were calculated individually. We also assessed the discharge predominance index (DPI) as a ratio of IEA in the predominant and contralateral sides for the entire recording and for each sleep stage. Results. We observed an IEA increase with sleep deepening, with maximum values observed during N2 and N3 sleep stages. The minimum IEA values were recorded during REM sleep; nevertheless, most of the REM sleep discharges were detected on the PS. DPI values were the highest and the most stable during N2 and N3 stages. Conclusion. The findings of our study demonstrate an increase in DPI values with non-rapid eye movement (NREM) sleep deepening in patients with bitemporal localization of EA. Despite the protective effects of REM sleep (i.e., reducing the likelihood of EA), it may be pivotal in lateralization of EA in patients with BIEDs. The PS is generally determined by a higher DPI during N2 and N3 stages.

Ictal and Postictal Central Apnea in DEPDC5-Related Epilepsy.

DEPDC5-related epilepsy carries an increased risk of sudden unexpected death in epilepsy. We evaluated the occurrence and features of ictal central apnea (ICA) in patients with pathogenic sequence variant in DEPDC5. We reviewed data of 108 patients collected in 2 independent cohorts of patients with focal epilepsy who prospectively underwent long-term video-EEG monitoring (LTVM) with cardiorespiratory polygraphy. All patients underwent (1) at least an overnight polysomnography, (2) a high-field (3T) brain MRI study, and (3) CSF analysis when clinically indicated. Genetic testing (next-generation sequencing [NGS]) was offered for diagnostic purposes to patients with focal epilepsy of unknown etiology. In this cohort, NGS was finally performed in 29 patients, resulting in DEPDC5 pathogenic mutations in 5 patients. According to the presence of ictal apnea events, 5 of 14 patients with ICA showed pathogenic DEPDC5 variants (35%) while none of the 15 patients without ICA showed pathogenic mutation. Notably, DEPDC5 patients showed ICA in all recorded seizures (n = 15) with apnea duration ranging from 20 seconds to more than 1 minute. All seizures were characterized by motor arrest without overt automatic behaviors during ictal apnea. Scalp EEG showed the involvement of temporal lobe leads in all events. Severe oxygen desaturation was observed in 2 cases. In our cohort, ictal central apnea was a common finding in DEPDC5. These results support (1) the need for respiratory polygraphy during LTVM in DEPDC5-related epilepsy and (2) the potential relevance of genetic testing in patients with focal epilepsy of unknown etiology and ictal apnea.

Effect evaluation of outpatient long-term video EEGs for people with seizure disorders – study protocol of the ALVEEG project: a randomized controlled trial in Germany

BackgroundEpilepsy and other seizure disorders account for a high disease burden in Germany. As a timely diagnosis and accurate treatment are crucial, improving the management of these disorders is important. Outside of Germany, outpatient long-term video EEGs (ALVEEGs) have demonstrated the potential to support the diagnosis and management of epilepsy and other seizure disorders. This study aims to evaluate the implementation of ALVEEGs as a new diagnostic pathway in eastern parts of Germany to diagnose epilepsy and other seizure disorders and to assess if ALVEEGs are equally effective as the current inpatient-monitoring gold standard, which is currently only available at a limited number of specialized centers in Germany.MethodsALVEEG is a prospective, multicenter, randomized controlled equivalence trial, involving five epilepsy centers in the eastern states of Germany. Patients will be randomized into either intervention (IG) or control group (CG), using a permuted block randomization. The sample size targeted is 688 patients, continuously recruited over the trial. The IG will complete an ALVEEG in a home setting, including getting access to a smartphone app to document seizure activity. The CG will receive care as usual, i.e., inpatient long-term video-EEG monitoring. The primary outcome is the proportion of clinical questions being solved in the IG compared to the CG. Secondary outcomes include hospital stays, time until video EEG, time until diagnosis and result discussion, patients’ health status, quality of life and health competence, and number and form of epilepsy-related events and epileptiform activity. Alongside the trial, a process implementation and health economic evaluation will be conducted.DiscussionThe extensive evaluation of this study, including an implementation and health economic evaluation, will provide valuable information for health policy decision-makers to optimize future delivery of neurological care to patients affected by epilepsy and other seizure disorders and on the uptake of ALVEEG into standard care in Germany.Trial registrationGerman Clinical Trials Register (DRKS00032220), date registered: December 11, 2023.

The role of long-term video-EEG monitoring in the diagnosis of childhood epilepsies

A videó-elektroencefalográfiás (EEG-) monitorozás kulcsfontosságú eszköz az epilepsziaszindrómák diagnosztizálásában, illetve a különböző paroxysmalis jelenségek differenciáldiagnosztikájában. Az EEG és a videó kombinálása lehetővé teszi a klinikusok számára az agyi elektromos tevékenységben bekövetkező változások és az azokat kísérő klinikai tünetek közötti összefüggés felismerését, az észlelt rohamjelenség evolúciójának és szemiológiájának valós idejű megfigyelését, a pontos diagnózis és az optimális kezelési terv felállítását. A digitális technika fejlődésével párhuzamosan – jobb képi felbontás, hosszabb felvételi időtartam, nagyobb adattároló kapacitás – a videó-EEG-monitorozás érzékenysége és specifikussága is jelentősen nőtt, hozzájárulva a diagnózisok pontosításához és a személyre szabott kezelési stratégiák kidolgozásához az epilepsziás és más paroxysmalis neurológiai tüneteket mutató betegek számára. A jelen összefoglaló áttekintést nyújt a videó-EEG kiemelt jelentőségéről a gyermekkori epilepszia-kórképek diagnosztikájában, az epilepsziás és a nem epilepsziás paroxysmalis jelenségek megkülönböztetésében, valamint az idegsebészeti beavatkozások előtti kivizsgálásban betöltött szerepéről. Tanulmányunkban bemutatjuk a kórházunk videó-EEG-monitorozási egységében a gyermekkori epilepsziák és paroxysmalis jelenségek kivizsgálásában összegyűlt, több mint két évtizedes eredményeket és tapasztalatokat, alátámasztva a módszer jelentőségét a gyermekneurológiában. Orv Hetil. 2024; 165(19): 722–726.

Three Patients of the Early Onset Epileptic Spasms without Hypsarrhythmia.

Epileptic spasms without hypsarrhythmia occur when patients do not display hypsarrhythmia on electroencephalogram (EEG) at the onset and throughout the clinical course. We report three patients of epileptic spasms in patients with early onset, all of whom experienced other types of seizures.We detail three patients (two boys and one girl) of epileptic spasms without hypsarrhythmia, occurring between 1 and 3 months of age, with no abnormalities detected on neurometabolic analysis and brain magnetic resonance imaging. Long-term video-EEG monitoring revealed epileptic spasms with focal onset seizures in two patients, and epileptic spasms followed by generalized tonic-clonic seizures in one patient. Hypsarrhythmia was never observed in repeated EEG examinations. Two patients achieved seizure freedom and improved development through treatment with topiramate alone or in combination with valproate, without requiring hormonal therapies or vigabatrin. The remaining patient achieved seizure freedom following administration of antiseizure medications, including topiramate, after a trial of adrenocorticotropic hormone therapy.We report the cases of three patients with early onset epileptic spasms without hypsarrhythmia. All patients achieved seizure freedom after topiramate treatment. Topiramate may be considered as a relatively effective antiseizure medication for early onset epileptic spasms without hypsarrhythmia.

Artificial intelligence applied for the diagnosis of absence epilepsy with simultaneously tested patient’s consciousness level in ictal event

Background. Given the difficulties in identifying absences and assessing the level of consciousness in epilepsy patients, it is extremely relevant to develop digital programs for automatic registration and testing of this type of epileptic seizures and related electroencephalographic (EEG) patterns, including those based on artificial intelligence.Objective: development of an algorithm for automatic detection of absence seizures to test real time patient's consciousness level during long-term video-EEG monitoring.Material and methods. The work on creating an algorithm was carried out during joint doctor/engineer cooperation. Doctors prepared a set of labeled EEG recordings of patients with verified absence epilepsy. Two independent experts in the generated examinations database mapped typical episodes of absence seizures that allowed to develop training and testing samples for a neural network algorithm to detect EEG absence epiactivity. Next, trained neural network was incorporated into Neuron- Spectrum.NET software to compare its accuracy with similar approaches published elsewhere.Results. A neural network algorithm was developed and trained using a mapped database to detect EEG absence epiactivity. A comparative analysis of the effectiveness for the proposed method vs. other approaches showed that the former is comparable in quality, whereas in some aspects – even superior to the latter. Accuracy was assessed using a publicly available database with mapped epiactivity episodes.Conclusion. A hardware and software system for automated assessment of patient’s consciousness level during absence seizure in continuous video-EEG monitoring was proposed. Potentially, neural networks may be applied not only to assess patient’s consciousness level, but also to stop stimulation-mediated seizure onset in the future.

Idiopathic generalized epilepsies in the epilepsy monitoring unit: Systematic quantification of focal EEG and semiological signs

ObjectiveFocal seizure symptoms (FSS) and focal interictal epileptiform discharges (IEDs) are common in patients with idiopathic generalized epilepsies (IGEs), but dedicated studies systematically quantifying them both are lacking. We used automatic IED detection and localization algorithms and correlated these EEG findings with clinical FSS for the first time in IGE patients. Methods32 patients with IGEs undergoing long-term video EEG monitoring were systematically analyzed regarding focal vs. generalized IEDs using automatic IED detection and localization algorithms. Quantitative EEG findings were correlated with FSS. ResultsWe observed FSS in 75% of patients, without significant differences between IGE subgroups. Mostly varying/shifting lateralizations of FSS across successive recorded seizures were seen. We detected a total of 81,949 IEDs, whereof 19,513 IEDs were focal (23.8%). Focal IEDs occurred in all patients (median 13% focal IEDs per patient, range 1.1 – 51.1%). Focal IED lateralization and localization predominance had no significant effect on FSS. ConclusionsAll included patients with IGE showed focal IEDs and three-quarter had focal seizure symptoms irrespective of the specific IGE subgroup. Focal IED localization had no significant effect on lateralization and localization of FSS. SignificanceOur findings may facilitate diagnostic and treatment decisions in patients with suspected IGE and focal signs.

Alterations in HCN1 expression and distribution during epileptogenesis in rats

BackgroundThe hyperpolarization-activated cyclic nucleotide-gated cation channel (HCN1) is predominantly located in key regions associated with epilepsy, such as the neocortex and hippocampus. Under normal physiological conditions, HCN1 plays a crucial role in the excitatory and inhibitory regulation of neuronal networks. In temporal lobe epilepsy, the expression of HCN1 is decreased in the hippocampi of both animal models and patients. However, whether HCN1 expression changes during epileptogenesis preceding spontaneous seizures remains unclear. ObjectiveThe aim of this study was to determine whether the expression of HCN1 is altered during the epileptic prodromal phase, thereby providing evidence for its role in epileptogenesis. MethodsWe utilized a cobalt wire-induced rat epilepsy model to observe changes in HCN1 during epileptogenesis and epilepsy. Additionally, we also compared HCN1 alterations in epileptogenic tissues between cobalt wire- and pilocarpine-induced epilepsy rat models. Long-term video EEG recordings were used to confirm seizures development. Transcriptional changes, translation, and distribution of HCN1 were assessed using high-throughput transcriptome sequencing, total protein extraction, membrane and cytoplasmic protein fractionation, western blotting, immunohistochemistry, and immunofluorescence techniques. ResultsIn the cobalt wire-induced rat epilepsy model during the epileptogenesis phase, total HCN1 mRNA and protein levels were downregulated. Specifically, the membrane expression of HCN1 was decreased, whereas cytoplasmic HCN1 expression showed no significant change. The distribution of HCN1 in the distal dendrites of neurons decreased. During the epilepsy period, similar HCN1 alterations were observed in the neocortex of rats with cobalt wire-induced epilepsy and hippocampus of rats with lithium pilocarpine-induced epilepsy, including downregulation of mRNA levels, decreased total protein expression, decreased membrane expression, and decreased distal dendrite expression. ConclusionsAlterations in HCN1 expression and distribution are involved in epileptogenesis beyond their association with seizure occurrence. Similarities in HCN1 alterations observed in epileptogenesis-related tissues from different models suggest a shared pathophysiological pathway in epileptogenesis involving HCN1 dysregulation. Therefore, the upregulation of HCN1 expression in neurons, maintenance of the HCN1 membrane, and distal dendrite distribution in neurons may represent promising disease-modifying strategies in epilepsy.

EDeeplepsy: An artificial neural framework to reveal different brain states in children with epileptic spasms

ObjectiveDespite advances, analysis and interpretation of EEG still essentially rely on visual inspection by a super-specialized physician. Considering the vast amount of data that composes the EEG, much of the detail inevitably escapes ordinary human scrutiny. Significant information may not be evident and is missed, and misinterpretation remains a serious problem. Can we develop an artificial intelligence system to accurately and efficiently classify EEG and even reveal novel information? In this study, deep learning techniques and, in particular, Convolutional Neural Networks, have been used to develop a model (which we have named eDeeplepsy) for distinguishing different brain states in children with epilepsy. MethodsA novel EEG database from a homogenous pediatric population with epileptic spasms beyond infancy was constituted by epileptologists, representing a particularly intriguing seizure type and challenging EEG. The analysis was performed on such samples from long-term video-EEG recordings, previously coded as images showing how different parts of the epileptic brain are distinctly activated during varying states within and around this seizure type. ResultsResults show that not only could eDeeplepsy differentiate ictal from interictal states but also discriminate brain activity between spasms within a cluster from activity away from clusters, usually undifferentiated by visual inspection. Accuracies between 86 % and 94 % were obtained for the proposed use cases. SignificanceWe present a model for computer-assisted discrimination that can consistently detect subtle differences in the various brain states of children with epileptic spasms, and which can be used in other settings in epilepsy with the purpose of reducing workload and discrepancies or misinterpretations. The research also reveals previously undisclosed information that allows for a better understanding of the pathophysiology and evolving characteristics of this particular seizure type. It does so by documenting a different state (interspasms) that indicates a potentially non-standard signal with distinctive epileptogenicity at that period.

Detection of seizures with ictal tachycardia, using heart rate variability and patient adaptive logistic regression machine learning methods: A hospital-based validation study.

Automated seizure detection of focal epileptic seizures is needed for objective seizure quantification to optimize the treatment of patients with epilepsy. Heart rate variability (HRV)-based seizure detection using patient-adaptive threshold with logistic regression machine learning (LRML) methods has presented promising performance in a study with a Danish patient cohort. The objective of this study was to assess the generalizability of the novel LRML seizure detection algorithm by validating it in a dataset recorded from long-term video-EEG monitoring (LTM) in a Brazilian patient cohort. Ictal and inter-ictal ECG-data epochs recorded during LTM were analyzed retrospectively. Thirty-four patients had 107 seizures (79 focal, 28 generalized tonic-clonic [GTC] including focal-to-bilateral-tonic-clonic seizures) eligible for analysis, with a total of 185.5 h recording. Because HRV-based seizure detection is only suitable in patients with marked ictal autonomic change, patients with >50 beats/min change in heart rate during seizures were selected as responders. The patient-adaptive LRML seizure detection algorithm was applied to all elected ECG data, and results were computed separately for responders and non-responders. The patient-adaptive LRML seizure detection algorithm yielded a sensitivity of 84.8% (95% CI: 75.6-93.9) with a false alarm rate of .25/24 h in the responder group (22 patients, 59 seizures). Twenty-five of the 26 GTC seizures were detected (96.2%), and 25 of the 33 focal seizures without bilateral convulsions were detected (75.8%). The study confirms in a new, independent external dataset the good performance of seizure detection from a previous study and suggests that the method is generalizable. This method seems useful for detecting both generalized and focal epileptic seizures. The algorithm can be embedded in a wearable seizure detection system to alert patients and caregivers of seizures and generate objective seizure counts helping to optimize the treatment of the patients.

The ENCEVIS algorithm in the EMU and the factors affecting its performance: Our experience

The study's purpose was to assess the seizure detection performance of ENCEVIS 1.7, identify factors that may influence algorithm performance, and explore its potential for implementation and application in long-term video EEG monitoring units. The study included video-EEG recordings containing at least one epileptic seizure. Forty-three recordings, encompassing 112 seizures, were included in the analysis. True positive, false negative, and false positive seizure detections were defined. Factors that may influence algorithm performance were studied. ENCEVIS demonstrated an overall sensitivity of 71.2%, significantly higher (75.1%) in focal compared to generalized seizures (62%). Ictal patterns rhythmicity (rhythmic 59.4 %, arrhythmic 41.7 %), seizure duration (<10 sec 6.3 %, >60 sec. 63.9 % (p < 0.05)) and patient age (<18 years 39.5 %, >18 years 58.1 % (P < 0.05)) influenced ENCEVIS sensitivity. The coexistence of extracerebral signal changes did not influence sensitivity. ENCEVIS with 79.1% accuracy annotates at least one seizure in those recordings containing epileptic seizures. ENCEVIS seizure detection performance was reasonable for generalized/focal to bilateral tonic-clonic seizures and seizures with temporal lobe onset. Rhythmic ictal patterns, longer seizure duration, and adult age positively influenced algorithm performance. ENCEVIS can be a valuable tool for identifying recordings containing seizures and can potentially reduce the workload of neurophysiologists.

The Value of Long-term Video EEG Monitoring to Diagnose and Track Childhood Epilepsy.

Long-term video-EEG monitoring (LTM) is a new technique to assess and track fluctuations, classify seizures, identify epileptic syndromes, and determine the number of seizures and epilepsy-simulating disorders. The present study aims to evaluate the concordance of traditional EEG and LTM in assessing childhood epilepsy. This cross-sectional before-after study was performed on 120 children with epilepsy who were referred to the Epilepsy Monitoring Unit (EMU) at the Children's Medical Center between September 2021 and September 2022 and were monitored for at least eight hours in this unit. The source of the study information collection was the patients' recorded files. A neurologist reviewed the primary EEGs, and two experts blindly reviewed and interpreted the patients' LTMs under a clinical neurophysiologist's supervision. The diagnoses changed after employing LTM in most children with epilepsy. Based on the diagnostic agreement analysis between EEG and LTM, the coefficient value for LTM was calculated at -0.37 (p= 0.229), showing that LTM has significantly expanded patients' diagnoses and care plans. The use of LTM improves the diagnosis, classification, and monitoring of epilepsy in affected children and can be a reliable supplement to EEG in some instances.

Role of glucose level in early termination of epileptic activities: Analysis using long-term video EEG with flash glucose monitoring

Role of glucose level in early termination of epileptic activities: Analysis using long-term video EEG with flash glucose monitoring

Assessing 72 h vs. 24 h of long-term video-EEG monitoring to confirm the diagnosis of epilepsy: a retrospective observational study.

Paroxysmal seizure-like events can be a diagnostic challenge. Inpatient video-electroencephalography (EEG) monitoring (VEM) can be a valuable diagnostic tool, but recommendations for the minimal duration of VEM to confirm or rule out epilepsy are inconsistent. In this study, we aim to determine whether VEM of 48 or 72 h was superior to 24 h. In this monocentric, retrospective study, we included 111 patients with paroxysmal, seizure-like events who underwent at least 72 h of VEM. Inclusion criteria were as follows: (1) Preliminary workup was inconclusive; (2) VEM admission occurred to confirm a diagnosis; (3) At discharge, the diagnosis of epilepsy was conclusively established. We analyzed the VEM recordings to determine the exact time point of the first occurrence of epileptic abnormalities (EAs; defined as interictal epileptiform discharges or electrographic seizures). Subgroup analyses were performed for epilepsy types and treatment status. In our study population, 69.4% (77/111) of patients displayed EAs during VEM. In this group, the first occurrence of EAs was observed within 24 h in 92.2% (71/77) of patients and within 24-72 h in 7.8% (6/77). There was no statistically significant difference in the incidence of EA between medicated and non-medicated patients or between focal, generalized epilepsies and epilepsies of unknown type. Of the 19 recorded spontaneous electroclinical seizures, 6 (31.6%) occurred after 24 h. A VEM of 24 h may be sufficient in the diagnostic workup of paroxysmal seizure-like events under most circumstances. Considering the few cases of first EA in the timeframe between 24 and 72 h, a prolonged VEM may be useful in cases with a high probability of epilepsy or where other strategies like sleep-EEG or ambulatory EEG show inconclusive results. Prolonged VEM increases the chance of recording spontaneous seizures. Our study also highlights a high share of subjects with epilepsy that do not exhibit EAs during 72 h of VEM.

P20.02.B ELECTRO-CLINICAL, NEUROIMAGING FEATURES AND NEUROPATHOLOGICAL CHARACTERIZATION OF POLYMORPHOUS LOW-GRADE NEUROEPITHELIAL TUMOR OF THE YOUNG (PLNTY)

Abstract BACKGROUND Polymorphous low-grade neuroepithelial tumor of the young (PLNTY) has been recently recognized by 2021 WHO Central nervous system classification. It is an epileptogenic tumor type, affecting mostly children and young adults, with peculiar radiological, and pathomolecular features. PLNTY is a very rare tumor, described in only 52 cases up to now. Herein, we describe 13 patients with electro-clinical and neuroimaging findings, associated to histopathological and molecular findings. MATERIAL AND METHODS We selected PLNTY patients from our Cancer Registry (Apr 2017-Dec 2022), and collected electro-clinical, radiological and histo-molecular data. Minimum follow-up was 6 months. Exams included EEG, long-term scalp video-EEG, pre-surgical brain computer tomography and Magnetic Brain Imaging (MRI). Immunohistochemistry included CD34, IDH1-R132H, GFAP, synaptophysin, ATRX, p53 and FGFR3. IDH1-2, BRAF (V600E) sequencing, Kiaa1549:BRAF, FGFR3:TACC3, FGFR2:kii1598 and FGFR2:CTNNA3 fusion analyses will be performed. RESULTS We describe 13 patients, median age 20.6 years (range 12.3-46.4). Most patients showed memory/executive impairment and had epilepsy, with an onset from 5 months-21 years before surgery. The main feature of seizures was a difficult localization and even lateralization, both semiologically and electrographically. Post-surgical seizure control was excellent.The tumors (n=11/13 temporal) presented as solid or solid-cystic cortical mass with no mass effect and unclear hedges. Calcifications were present in 4, and cysts in 6 cases. Microscopically the tumors showed infiltrative growth pattern, oligodendroglial-like cells, strong and often diffuse CD34 immunostaining, and frequent intra-tumoral calcifications. Malformation of cortical development, namely FCD type IIIB, was associated to PLNTY in 2 cases. Proliferation activity (MIB-1 LI) was very low (1%) in all cases except one (MIB-1 LI which reached 3%). CONCLUSION This study significantly extends the number of reported PLNTY associated to epilepsy, mostly characterized by bilateral interictal epileptiform discharges and difficult to lateralize seizures.The MRI features were heterogeneous and the differential diagnosis should include also dysplasia and glioneuronal tumors. PLNTY, despite its name, occurs also in adults, and electro-clinical and radiological diagnosis can be challenging. As recently described, PLNTY can show the MAPK pathway activating alterations, that are under investigation in our cohort to eventually clarify their role in the evolution of the disease. SUPPORT the study is partially supported by the Health Italian Minister (RC).

Classification of Epileptic and Psychogenic Nonepileptic Seizures via Time-Frequency Features of EEG Data.

The majority of psychogenic nonepileptic seizures (PNESs) are brought on by psychogenic causes, but because their symptoms resemble those of epilepsy, they are frequently misdiagnosed. Although EEG signals are normal in PNES cases, electroencephalography (EEG) recordings alone are not sufficient to identify the illness. Hence, accurate diagnosis and effective treatment depend on long-term video EEG data and a complete patient history. Video EEG setup, however, is more expensive than using standard EEG equipment. To distinguish PNES signals from conventional epileptic seizure (ES) signals, it is crucial to develop methods solely based on EEG recordings. The proposed study presents a technique utilizing short-term EEG data for the classification of inter-PNES, PNES, and ES segments using time-frequency methods such as the Continuous Wavelet transform (CWT), Short-Time Fourier transform (STFT), CWT-based synchrosqueezed transform (WSST), and STFT-based SST (FSST), which provide high-resolution time-frequency representations (TFRs). TFRs of EEG segments are utilized to generate 13 joint TF (J-TF)-based features, four gray-level co-occurrence matrix (GLCM)-based features, and 16 higher-order joint TF moment (HOJ-Mom)-based features. These features are then employed in the classification procedure. Both three-class (inter-PNES versus PNES versus ES: ACC: 80.9%, SEN: 81.8%, and PRE: 84.7%) and two-class (Inter-PNES versus PNES: ACC: 88.2%, SEN: 87.2%, and PRE: 86.1%; PNES versus ES: ACC: 98.5%, SEN: 99.3%, and PRE: 98.9%) classification algorithms performed well, according to the experimental results. The STFT and FSST strategies surpass the CWT and WSST strategies in terms of classification accuracy, sensitivity, and precision. Moreover, the J-TF-based feature sets often perform better than the other two.

Peri-ictal heart rate changes in patients with epilepsy.

Heart rate (HR) changes associated with seizures are promising biomarkers in epilepsy. The aim of our study is to reveal possible HR changes in the peri-ictal period. Long-term video-EEG monitorization records of generalized and focal epilepsy patients were reviewed. HRs were calculated in the pre-ictal (2 min before the first seizure activity in EEG), ictal (the time from the first seizure activity on the EEG to the end of the seizure), and in the interictal period (at least 2 h before or 12 h after the seizure). Interictal, pre-ictal, and ictal HRs were compared with each other. In addition, it was investigated whether peri-ictal HR changes differ between generalized and focal seizure patients. Focal motor seizures were observed in 21, and generalized tonic-clonic seizures were observed in 18 of 39 (22 female and 17 male) patients studied. HRs in the pre-ictal and ictal periods were significantly higher than in the interictal period. This significant increase in HR was validated separately in both focal and generalized seizure groups and was not different between the two groups. Our study supports previous studies showing the presence of increased peri-ictal HR and also provides new insights by comparing focal and generalized motor seizures. We think that our findings may contribute to the development of early warning signs in epilepsy patients.

Safety and efficacy of rapid withdrawal of anti-seizure medication during long-term video-EEG monitoring.

Anti-seizure medications (ASMs) are often withdrawn during long-term video-EEG monitoring (LTM) to allow pre-surgical evaluation. Herein, we evaluated the safety and efficacy of ultra-rapid withdrawal (URW) and rapid withdrawal (RW) of ASMs in an epilepsy monitoring unit (EMU). This retrospective study examined all consecutive patients admitted to our EMU between May 2021 and October 2022. Patients were classified into the URW and RW groups according to the way ASMs were withdrawn. We compared the efficacy and safety of the procedures used in the groups in terms of duration of LTM, latency to the first seizure, and incidence of focal to bilateral tonic-clonic seizures (FBTCS), seizure clusters (SC), and status epilepticus (SE). Overall, 110 patients (38 women) were included. The mean age of patients at the time of LTM was 29 years. All medications were stopped on admission for monitoring in the URW group (n = 75), while in the RW group (n = 35) ASMs were withdrawn within 1 day. In both groups, the duration of LTM was approximately 3 days: URW group (2.9 ± 0.5 days) and RW group (3.1 ± 0.8 days). The latency to the first seizure was significantly different between the two groups; however, there were no differences between the two groups in terms of the distribution of FBTCS, SC, or SE, number of seizures, and the requirement for intravenous rescue medication was low. The rapid withdrawal of ASMs to provoke seizures during monitoring for pre-surgical evaluation following the URW protocol was as effective and safe as with RW. Ultra-rapid ASM withdrawal has the benefits of reducing LTM duration and shortening the time to first seizure compared to rapid medication tapering.