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Abstract The value of stimulation-induced seizures for multimodal determination of the epileptogenic zone in preoperative epilepsy diagnostics has not yet been sufficiently investigated. Patients with focal pharmacorefractory epilepsy who underwent invasive electroencephalography with cortical 50 Hz stimulation at the Epilepsy Center Erlangen between 2018 and 2023, had at least one stimulation-induced seizure, underwent resective epilepsy surgery, and had a postoperative follow-up ≥ 1 year were analyzed. 20 patients were included, 11 (55.0%) with temporal, 7 (35.0%) with frontal and 2 (10.0%) with parietal lobe epilepsy. 12 patients (60.0%) had a good Engel outcome (Engel 1A). Associated with a good vs. poor (Engel 1B-4) surgical outcome were not only the percentage of resected electrode contacts of the spontaneous seizure onset zone, SOZ (p = 0.005), but also the stimulation SOZ (p = 0.022), as well as stimulation-induced seizure with a typical seizure semiology (p = 0.033), the electrodes inducing a stimulation-induced seizure (p = 0.014), electrodes with an identical seizure onset pattern (p = 0.035), and the occurrence of low voltage fast seizure onset pattern, LVFA (p = 0.015). ROC analyses showed that the AUC for the predictors of the spontaneous SOZ were greatest for the stimulation SOZ (AUC 0.876) and stimulation-induced seizures with LVFA (0.860). Analysis of combined predictors showed higher odds of predicting SOZ for combinations including LVFA. Electroclinical stimulation seizures have prognostic value in determining the epileptogenic zone. Characteristics such as the seizure onset zone, seizure pattern and stimulation seizure semiology predict seizure freedom in case of resection of electrode contacts. Electrodes should be resected where both stimulation seizures have been induced or the seizure pattern has been localized and low voltage fast seizure pattern has occurred.

Background: Interictal epileptiform discharges (IEDs) are an electrographic biomarker of epilepsy. Despite their crucial role in diagnosing epilepsy, heterogeneous findings exist on the mechanisms underlying their occurrence and the effects of anti-seizure medications (ASMs) on IEDs. Methods: We conducted a study to investigate the association between IED frequency and the serum concentration of two commonly used ASMs, levetiracetam (LEV) and lamotrigine (LTG). We included 56 patients undergoing a continuous video EEG monitoring in our center with tapering of ASM. IED frequency was analyzed using automated and semiautomated methods and serum samples were collected sequentially throughout the stay. Results: The cohort consisted of 41 patients (23 female, 18 male), between 19 and 64 years (mean 37.42 years), most of which were diagnosed with focal epilepsy (93%). IED frequency increased after ASM reduction revealing a negative correlation similarly with LEV and LTG serum concentrations (p = 0.0057 and p = 0.0426, respectively). Discussion: Notably, we observed a significant increase in IED frequency following dose reduction or discontinuation of both medications. This effect was reversed after ASM were re-dosed. This may indicate the suppressive properties of LEV and LTG against epileptic seizures. Furthermore, our study highlights the importance of ASM discontinuation, which may be required for capturing IEDs during diagnostic continuous EEG monitoring, and not be fully explained by circadian or ultradian rhythms alone. Conclusion: Our findings contribute to the understanding of ASM effects on IED frequency dynamics and suggest seizure suppressive properties of LEV and LTG. [ABSTRACT FROM AUTHOR]

Objective: In the neurological emergency room (nER), timely electroencephalography (EEG) diagnostic is often crucial in patients with altered state of consciousness as well as in patients presenting with a first seizure. Yet, routine-EEG (rEEG) is often not available, especially during off-hours. Methods: We analyzed the value of a commercially available, simplified wireless eight-channel EEG recording (swEEG, CerebAir® EEG headset, Nihon Kohden), applied by non-EEG-specialized medical students, in patients presenting in our nER with (suspicion of) epileptic seizures and/or loss of or altered state of consciousness between 08/2019 and 08/2022. We evaluated the feasibility and validity compared to a standard rEEG (21 electrodes according to the international 10/20 system) and also included the clinical follow-up of the patients. Results: 100 patients were included in our analysis (mean age 57.6 ± 20.4 years; 61 male). Median time of electrode application was 7 minutes (range 4–20 minutes), with significantly longer duration in patients with altered level of consciousness (median 8 minutes, p = 0.035). Electrode impedances also differed according to state of consciousness (p = 0.032), and were higher in females (p<0.001). 55 patients received additional rEEG, either during their acute nER stay (25) and/or during the next days (38). Considering normal EEG findings vs. pathological slowing vs. epileptiform activity, swEEG matched first rEEG results in 48/55 cases (87.3%). Overall, swEEG detected the same or additional pathological EEG patterns in 52/55 cases (94.5%). In 7/75 patients (9.3%) who did not receive rEEG, or had their rEEG scheduled to a later time point during their hospital stay, swEEG revealed important additional pathological findings (e.g. status epilepticus, interictal epileptiform discharges), which would have triggered acute therapeutic consequences or led to further diagnostics and investigations. Conclusion: The introduced swEEG represents a practicable, valuable technique to be quickly applied by non-EEG-specialized ER staff to initiate timely diagnostic and guide further investigations and treatment in the nER. Moreover, it may help to avoid under-diagnostic with potentially harmful consequences caused by skipped or postponed regular 10/20 EEG examinations, and ultimately improve the outcome of patients. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to re‐evaluate risk factors for post‐ICH epilepsy (PICHE) and examine the impact of surgical hematoma evacuation on epilepsy development after ICH. Background and purpose: Epilepsy is a common complication after intracerebral hemorrhage (ICH). Information on risk factors is still scarce and the role of ICH evacuation remains uncertain. Methods: We retrospectively included patients with spontaneous ICH treated in our hospital in 2006–2019. Patients' medical records were analyzed. In addition, mailed questionnaires and telephone interviews were used to complete the dataset. Uni‐ and multivariable hazard ratios (HRs) were applied to investigate risk factors for PICHE and the impact of surgical ICH evacuation. Results: Among 587 ICH patients available for analyses, 139 (23.7%) developed PICHE (mean follow‐up 1795 ± 1378 days). The median time of epilepsy onset was 7 months after ICH (range 1–132 months). Risk factors associated with PICHE were cortical hemorrhage (multivariable HR 1.65 [95% CI 1.14–2.37]; p = 0.008), ICH volume > 10 ml (multivariable HR 1.91 [95% CI 1.33–2.73]; p < 0.001) and acute symptomatic seizures (multivariable HR 1.81 [95% CI 1.20–2.75]; p = 0.005). Patients with cortical ICH > 10 ml who underwent surgical hematoma evacuation were less likely to develop epilepsy than those with conservative treatment alone (multivariable HR 0.26 [95% CI 0.08–0.84]; p = 0.025). Conclusions: Post‐ICH epilepsy is frequent and predicted by large cortical ICH and acute symptomatic seizures. Hematoma evacuation reduced the risk of PICHE by more than 70% in patients with large cortical ICH. This finding could be considered in the clinical decision making on the acute treatment of ICH. [ABSTRACT FROM AUTHOR]

Background: Deterioration in naming function is a common sequelae after epilepsy surgery in the language-dominant temporal lobe but information on recovery and long-term outcome is scarce. We, therefore, assessed short-term and long-term outcome of object naming in patients undergoing surgery in the temporal lobe and determined factors affecting deterioration and recovery of naming function., Method: Object naming (Boston naming test) before surgery, at early follow-up (FU, 6-12 months) and late FU (≥2 years) was assessed in people with epilepsy (PWE) undergoing resections in the language-dominant left and non-dominant right temporal lobe., Results: Sixty-six patients with left temporal lobe epilepsy (LTLE) and 87 control patients with right temporal lobe epilepsy (RLTE) were included. At early FU, 28 patients with LTLE (42%) and three patients with RTLE (3%) showed a significant naming decline. In patients with LTLE, risk for deterioration increased with lower verbal memory before surgery, older age at seizure onset and was particularly high with posterior temporal resections (≥40 mm from the temporal pole) and seizure onset >16 years. Of the patients with LTLE with early naming decline, 11 patients (39%) recovered fully in their naming abilities at late FU, averaging almost 10 years. Recovery was associated with the degree of postoperative naming decline at early FU. PWE with a decline of less than 10 items (<20%) had a good prognosis of recovery at late FU. Postoperative seizure control had no significant effect on recovery., Conclusions: In our cohort, less than 50% of PWE showed significantly deteriorated naming function after resection of the dominant temporal lobe. If a decline occurred, it appeared to recover to a certain degree and remained as a permanent deficit in 26% of the patients. Long-term outcome of visual object naming can be predicted by the degree of early postoperative decline., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ Group.)

Background: This research aims to improve glioblastoma survival prediction by integrating MR images, clinical, and molecular-pathologic data in a transformer-based deep learning model, addressing data heterogeneity and performance generalizability., Methods: We propose and evaluate a transformer-based nonlinear and nonproportional survival prediction model. The model employs self-supervised learning techniques to effectively encode the high-dimensional MRI input for integration with nonimaging data using cross-attention. To demonstrate model generalizability, the model is assessed with the time-dependent concordance index (Cdt) in 2 training setups using 3 independent public test sets: UPenn-GBM, UCSF-PDGM, and Rio Hortega University Hospital (RHUH)-GBM, each comprising 378, 366, and 36 cases, respectively., Results: The proposed transformer model achieved a promising performance for imaging as well as nonimaging data, effectively integrating both modalities for enhanced performance (UCSF-PDGM test-set, imaging Cdt 0.578, multimodal Cdt 0.672) while outperforming state-of-the-art late-fusion 3D-CNN-based models. Consistent performance was observed across the 3 independent multicenter test sets with Cdt values of 0.707 (UPenn-GBM, internal test set), 0.672 (UCSF-PDGM, first external test set), and 0.618 (RHUH-GBM, second external test set). The model achieved significant discrimination between patients with favorable and unfavorable survival for all 3 datasets (log-rank P 1.9 × 10 -8 , 9.7 × 10 -3 , and 1.2 × 10 -2 ). Comparable results were obtained in the second setup using UCSF-PDGM for training/internal testing and UPenn-GBM and RHUH-GBM for external testing (Cdt 0.670, 0.638, and 0.621)., Conclusions: The proposed transformer-based survival prediction model integrates complementary information from diverse input modalities, contributing to improved glioblastoma survival prediction compared to state-of-the-art methods. Consistent performance was observed across institutions supporting model generalizability., Competing Interests: The authors declare no conflict of interest in this work., (© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)