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Diagnostic Accuracy of Epilepsy-dedicated MRI with Post-processing
Abstract: Purpose To evaluate the diagnostic accuracy of epilepsy-dedicated 3 Tesla MRI including post-processing by correlating MRI, histopathology, and postsurgical seizure outcomes. Methods 3 Tesla-MRI including a magnetization-prepared two rapid acquisition gradient echo (MP2RAGE) sequence for post-processing using the morphometric analysis program MAP was acquired in 116 consecutive patients with drug-resistant focal epilepsy undergoing resection surgery. The MRI, histopathology reports and postsurgical seizure outcomes were recorded from the patient's charts. Results The MRI and histopathology were concordant in 101 and discordant in 15 patients, 3 no hippocampal sclerosis/gliosis only...
A Survey of the European Reference Network EpiCARE on Clinical Practice for Selected Rare Epilepsies
Abstract: Objective Clinical care of rare and complex epilepsies is challenging, because evidence-based treatment guidelines are scarce, the experience of many physicians is limited, and interdisciplinary treatment of comorbidities is required. The pathomechanisms of rare epilepsies are, however, increasingly understood, which potentially fosters novel targeted therapies. The objectives of our survey were to obtain an overview of the clinical practice in European tertiary epilepsy centers treating patients with 5 arbitrarily selected rare epilepsies and to get an estimate of potentially available patients for future studies. Methods Members of the European Reference Network for rare and comp...
SGM: a Novel Time-frequency Algorithm Based on Unsupervised Learning Improves High-frequency Oscillation Detection in Epilepsy
Abstract: Objective. We propose a novel automated method called the S-Transform Gaussian Mixture detection algorithm (SGM) to detect high-frequency oscillations (HFO) combining the strengths of different families of previously published detectors. Approach. This algorithm does not depend on parameter tuning on a subject (or database) basis, uses time-frequency characteristics, and relies on non-supervised classification to determine if the events standing out from the baseline activity are HFO or not. SGM consists of three steps: the first stage computes the signal baseline using the entropy of the autocorrelation; the second uses the S-Transform to obtain several time-frequency features (ar...
Epilepsy Surgery in Early Infancy
Abstract: Although epilepsy surgery is the only curative therapeutic approach for lesional drug-resistant epilepsy (DRE), there is reluctance to operate on infants due to a fear of complications. A recent meta-analysis showed that epilepsy surgery in the first 6 months of life can achieve seizure control in about two thirds of children. However, robust data on surgical complications and postoperative cognitive development are lacking. We performed a retrospective multicenter study of infants who underwent epilepsy surgery in the first 6 months of life. 15 infants underwent epilepsy surgery at a median age of 134 days (IQR: 58) at four centers. The most common cause was malformation of cortic...
Cyclical Underreporting of Seizures in Patient-based Seizure Documentation
Abstract: Objective Circadian and multidien cycles of seizure occurrence are increasingly discussed as to their biological underpinnings and in the context of seizure forecasting. This study analyzes if patient reported seizures provide valid data on such cyclical occurrence. Methods We retrospectively studied if circadian cycles derived from patient-based reporting reflect the objective seizure documentation in 2003 patients undergoing in-patient video-EEG monitoring. Results Only 24.1% of more than 29000 seizures documented were accompanied by patient notifications. There was cyclical underreporting of seizures with a maximum during nighttime, leading to significant deviations in the circa...
Modelling and Analysis of Active Biopotential Signals in Healthcare, Volume 1
This book focuses on analysis and modelling of active bio potential signals addressing the real time challenges in biomedical signal processing used in a variety of applications such as analysis, classification and identification of different disorders in healthcare systems.
