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Objective: A prerequisite for the implementation of interictal electroencephalography-correlated functional magnetic resonance imaging (EEG-fMRI) in the presurgical work-up for epilepsy surgery is straightforward processing. We propose a new semi-automatic method as alternative for the challenging and time-consuming visual spike identification.
Methods: Our method starts from a patient-specific spike-template, built by averaging spikes recorded on the EEG outside the scanner. Spatiotemporal cross-correlations between the template and the EEG measured during fMRI were calculated. To minimize false-positive detections, this time course of cross-correlations was binarized by means of a spike-template-specific threshold determined in healthy controls. To inform our model for statistical parametric mapping, this binarized regressor was convolved with the canonical hemodynamic response function. We validated our "template-based" method in 21 adult patients with refractory focal epilepsy with a well-defined epileptogenic zone and interictal spikes during EEG-fMRI. Sensitivity and specificity for detecting the epileptogenic zone were calculated and represented in receiver operating characteristic (ROC) curves. Our approach was compared with a previously proposed semiautomatic "topography-based" method that used the topographic amplitude distribution of spikes as a starting point for correlation-based fitting.
Results: Good diagnostic performance could be reached with our template-based method. The optimal area under the ROC curve was 0.77. Diagnostic performance of the topography-based method was overall low.
Significance: Our new template-based method is more standardized and time-saving than visual spike identification on intra-scanner EEG recordings, and preserves good diagnostic performance for detecting the epileptogenic zone.
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http://dx.doi.org/10.1111/epi.12841 | DOI Listing |
Epilepsy Behav Rep
September 2025
Department of Neurology and Agnes Ginges Center for Human Neurogenetics, Hadassah Medical Organization, Hadassah Ein Kerem, POB12000 Jerusalem, Israel.
The data obtained from stereo-elecroencephalography (SEEG) in patients with focal epilepsy are crucial for defining the epileptogenic zone and achieving successful resection, but suboptimal electrode placement impairs SEEG results. We demonstrate an approach for concurrent scalp and depth EEG analysis from one patient with successful intracranial workup and one in whom the seizure onset zone was unsampled by SEEG. Intracranial epileptiform discharges were identified and clustered, their scalp correlates were averaged, and electric source imaging (ESI) was applied to the resulting averaged scalp potential - depth-to-scalp ESI (dsESI).
View Article and Find Full Text PDFFront Neurol
August 2025
Department of Neurosurgery, Children's Hospital Affiliated to Shandong University, Jinan, China.
Background And Aim: Neurofibromatosis type 1 (NF1) is an autosomal dominant tumor predisposition syndrome caused by pathogenic variants in the NF1 gene. It exhibits highly variable and unpredictable clinical manifestations involving multiple organ systems, with café-au-lait macules and multiple neurofibromas being hallmark features. Epilepsy represents a common central nervous system complication in NF1, though its underlying mechanisms remain poorly understood.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Breast Surgery, Hangzhou Women's Hospital, Hangzhou, Zhejiang, China.
Objective: This study aims to utilize our hospital's existing Stereo Electroencephalography (SEEG) examination results combined with other clinical data to systematically analyze the risk factors for epilepsy comorbid with depression, and to establish a model for predicting the risk of developing depression in epilepsy patients. Clinically, this model can be used to predict the risk of comorbid depression in epilepsy patients, thereby enhancing the identification of this condition and providing a theoretical basis for proactive intervention in depressive symptoms among epilepsy patients.
Methods: A retrospective analysis was conducted on the clinical data of patients diagnosed with epilepsy in the Department of Neurosurgery at Tongde Hospital Of Zhejiang Province from 01/01/2020-31/12/2024, all of whom underwent Electroencephalography (EEG) examinations.
Stereotact Funct Neurosurg
September 2025
Introduction: Stereoelectroencephalography-guided radio-frequency thermo coagulation (SEEG-RFTC) is a minimally invasive technique whereby radiofrequency-thermocoagulation is performed using SEEG electrodes, following recording and stimulation. It helps to disconnect/disrupt or ablate the epileptogenic networks, and provides both therapeutic and diagnostic abilities.
Methods: Retrospective study (2016-2024).
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
August 2025
School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, P. R. China.
The existing epilepsy seizure detection algorithms have problems such as overfitting and poor generalization ability due to high reliance on manual labeling of electroencephalogram's data and data imbalance between seizure and interictal periods. An unsupervised learning detection method for epileptic seizure that jointed graph attention network (GAT) and Transformer framework (GAT-T) was proposed. In this method, channel correlations were adaptively learned by GAT encoder.
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