Rüdiger Hopfengärtner

Lobar localization information in epilepsy patients: MEG—A useful tool in routine presurgical diagnosis

Epilepsy surgery is an established therapy for pharmacoresistant focal epilepsy. This study investigated the contribution of routinely used magnetoencepahlography (MEG) in addition to long term video-EEG-monitoring in presurgical evaluation. The distribution of localization results to anatomical lobes was compared with special focus to MEG spike localization results in cases without or with ambiguous EEG findings. A total of 105 consecutive patients with intractable focal epilepsy and epilepsy surgery after investigation by video-EEG-monitoring and MEG were included. The percentages of monolobar results were analysed and compared, especially with respect to the resection lobe. Postoperative outcome was used for further validation. No spikes were recorded on MEG in 30% (32 of 105). In cases with a diagnostic finding by the respective method, MEG localized in 82% (60 of 73 patients) within one anatomical lobe. Ictal EEG localized within one lobe in 72% (66 of 92 patients), interictal EEG in 60% (59 of 98 patients). In 25 of 105 patients (24%) no clear localization within one lobe was found either in interictal or in ictal EEG. In 11 of these cases MEG localized within the resection lobe. Six patients of these became seizure free, the other five had at least 50% reduction of their seizure rate 1 year after surgery. In summary MEG is a useful tool in the routine workup for epilepsy surgery contributing information to focus hypothesis in addition to video-EEG.

An efficient, robust and fast method for the offline detection of epileptic seizures in long-term scalp EEG recordings

OBJECTIVE A robust and fast algorithm for the offline detection of epileptic seizures in scalp EEG is described. It is aimed for seizure detection with high sensitivity and low number of false detections in long-term EEG data without a priori information. METHODS To capture the characteristic electrographic changes of seizures, we developed an efficient method based on power spectral analysis techniques. The integrated power is calculated in two frequency bands for three multi-channel seizure detection montages (referenced against the average of Fz-Cz-Pz, common average, bipolar) using the same parameters for all montages and all patients taking into account an appropriate artifact rejection. RESULTS A total of 3248 h of scalp recordings containing 148 seizures from 19 patients were examined. The averaged sensitivity was 90.9% and selectivity (false-positive errors/h, FPH) was 0.29/h of the Fz-Cz-Pz montage; the other montages yielded lower sensitivities but even better selectivity values. CONCLUSIONS Taking into account that the method has been performed in a standardized way with fixed parameters for all patients and montages the obtained values for sensitivity are quite high while the selectivity is acceptably low. The parameters can additionally be tuned to patient specific seizures. It is assumed that this may further improve the seizure detection performance. SIGNIFICANCE The proposed method may enhance the clinical use for the detection of seizures in scalp EEG long-term monitoring during presurgical evaluation.

Standardized computer-based organized reporting of EEG: SCORE.

The electroencephalography (EEG) signal has a high complexity, and the process of extracting clinically relevant features is achieved by visual analysis of the recordings. The interobserver agreement in EEG interpretation is only moderate. This is partly due to the method of reporting the findings in free‐text format. The purpose of our endeavor was to create a computer‐based system for EEG assessment and reporting, where the physicians would construct the reports by choosing from predefined elements for each relevant EEG feature, as well as the clinical phenomena (for video‐EEG recordings). A working group of EEG experts took part in consensus workshops in Dianalund, Denmark, in 2010 and 2011. The faculty was approved by the Commission on European Affairs of the International League Against Epilepsy (ILAE). The working group produced a consensus proposal that went through a pan‐European review process, organized by the European Chapter of the International Federation of Clinical Neurophysiology. The Standardised Computer‐based Organised Reporting of EEG (SCORE) software was constructed based on the terms and features of the consensus statement and it was tested in the clinical practice. The main elements of SCORE are the following: personal data of the patient, referral data, recording conditions, modulators, background activity, drowsiness and sleep, interictal findings, “episodes” (clinical or subclinical events), physiologic patterns, patterns of uncertain significance, artifacts, polygraphic channels, and diagnostic significance. The following specific aspects of the neonatal EEGs are scored: alertness, temporal organization, and spatial organization. For each EEG finding, relevant features are scored using predefined terms. Definitions are provided for all EEG terms and features. SCORE can potentially improve the quality of EEG assessment and reporting; it will help incorporate the results of computer‐assisted analysis into the report, it will make possible the build‐up of a multinational database, and it will help in training young neurophysiologists.

Periventricular nodular heterotopia: A challenge for epilepsy surgery

Pharmacoresistant focal epilepsies due to periventricular nodular heterotopia are a diagnostic and therapeutic challenge because of the need of invasive presurgical diagnostics and the selection of an optimal surgical approach. Invasive investigations in previous studies showed that focal epileptic activity can be correlated predominantly either with one of the nodular heterotopia or with neocortical epileptogenic zones distant to the periventricular nodules. Up to now, invasive recordings were required for localization of epileptic activity and its correlation to heterotopia. The following case presentation reports on a non-invasive approach using magnetic source imaging (MSI) combined with intraoperative ECoG. MSI combines preoperative data from magnetic resonance imaging (MRI) with magnetoencephalography (MEG). The MSI data for definition of the localization of the epileptic activity and functional important areas were coregistered with the intraoperative high-field-MRI and diffusion tensor imaging-based fiber tracking (DTI) of the visual pathway using a neuronavigational system. A neuronavigation-guided surgical resection of the epileptogenic area was performed leaving the heterotopia and the visual tract fibers intact. Postoperatively preservation of the visual fields was documented and the frequency of seizures was markedly reduced.

Automatic seizure detection in long-term scalp EEG using an adaptive thresholding technique: A validation study for clinical routine

OBJECTIVE In a previous study we proposed a robust method for automatic seizure detection in scalp EEG recordings. The goal of the current study was to validate an improved algorithm in a much larger group of patients in order to show its general applicability in clinical routine. METHODS For the detection of seizures we developed an algorithm based on Short Time Fourier Transform, calculating the integrated power in the frequency band 2.5-12 Hz for a multi-channel seizure detection montage referenced against the average of Fz-Cz-Pz. For identification of seizures an adaptive thresholding technique was applied. Complete data sets of each patient were used for analyses for a fixed set of parameters. RESULTS 159 patients (117 temporal-lobe epilepsies (TLE), 35 extra-temporal lobe epilepsies (ETLE), 7 other) were included with a total of 25,278 h of EEG data, 794 seizures were analyzed. The sensitivity was 87.3% and number of false detections per hour (FpH) was 0.22/h. The sensitivity for TLE patients was 89.9% and FpH=0.19/h; for ETLE patients sensitivity was 77.4% and FpH=0.25/h. CONCLUSIONS The seizure detection algorithm provided high values for sensitivity and selectivity for unselected large EEG data sets without a priori assumptions of seizure patterns. SIGNIFICANCE The algorithm is a valuable tool for fast and effective screening of long-term scalp EEG recordings.

Spatial relationship of source localizations in patients with focal epilepsy: Comparison of MEG and EEG with a three spherical shells and a boundary element volume conductor model

Epilepsy surgery is an option for patients with pharmacoresistant focal epilepsies, but it requires a precise focus localization procedure. Magnetoencephalography (MEG) and electroencephalography (EEG) can be used for analysis of interictal activity. The aim of this prospective study was to compare clusters of source localization results with MEG and EEG using a three spherical shells (3SS) and a boundary element method (BEM) volume conductor model. The study was closed when 100 patients met the inclusion criteria. Simultaneous MEG and EEG were recorded during presurgical evaluation. Epileptiform signals were analyzed using an equivalent current dipole model. Centroids of source localizations from MEG, EEG, 3SS, and BEM in their respective combinations were compared. In a 3SS model, MEG source localizations were 5.6 mm inferior to those obtained by EEG, while in a BEM model MEG source localizations were 6.3 mm anterior and 4.8 mm superior. The mean scattering of source localizations between both volume conductor models was 19.5 mm for EEG and 9.6 mm for MEG. For MEG no systematic difference between BEM and 3SS source localizations was found. For EEG, source localizations with BEM were 5.9 mm posterior and 11.7 mm inferior to those determined using 3SS. No differences were found between the 46 temporal and the 54 extratemporal lobe epilepsy patients. The observed systematic differences of source localizations of epileptic spikes due to the applied source signal modality and volume conductor model should be considered in presurgical evaluation when only one source signal and volume conductor model is available. Hum Brain Mapp, 2007.

MEG in frontal lobe epilepsies: Localization and postoperative outcome

Purpose:  This study aimed to analyze magnetoencephalography (MEG) localizations of epileptic clusters in different cortical regions of the frontal lobe and relate these findings to postoperative outcomes associated with frontal lobe epilepsy (FLE).

Interictal triple ECoG characteristics of temporal lobe epilepsies: An intraoperative ECoG analysis correlated with surgical outcome.

OBJECTIVE Recent reports showed that intraoperative ECoG activities can be analysed with respect to more complex spike patterns. We have systematically investigated different characteristic epileptiform activities in intraoperative ECoG and correlated them to postoperative outcome. METHODS Intraoperative ECoG findings of patients with non-tumorous epilepsies (20 patients with Engel outcome 1a, 20 patients with Engel outcome 2-4) were analysed in order to differentiate ECoG characteristics in temporal lobe epilepsies (TLE). RESULTS In addition to focal spiking with or without propagation, focal slowing in the theta or delta range and so-called ictaform ECoG patterns were found. These ictaform patterns occurred in 40% of the patients with TLE. CONCLUSIONS Leading spikes in combination with focal slowing and ictaform patterns can contribute to a better delineation of mesial temporal epileptic activity in the anterior-posterior alignment. They provide an additional information which can be used for the extent of resection. SIGNIFICANCE If the resected area included the anterior mesial regions, where interictal spikes, ictaform activity and slowing were localized, the postoperative outcome was good.

Objective quantification of seizure frequency and treatment success via long-term outpatient video-EEG monitoring: A feasibility study

A reliable method for the estimation of seizure frequency and severity is indispensable in assessing the efficacy of drug treatment in epilepsies. These quantities are usually deduced from subjective patient reports, which may cause considerable problems due to insufficient or false descriptions of seizures and their frequency. We present data from two difficult-to-treat patients with intractable epilepsy. Pat. 1 has had an unknown number of CP seizures. Here, a prolonged outpatient video-EEG monitoring over 160 h and 137 h (over an interval of three months) was performed with an automated seizure detection method. Pat. 2 suffered exclusively from nocturnal seizures originating from the frontal lobe. In this case, an objective quantification of the efficacy of drug treatment over a time period of 22 weeks was established. For the reliable quantification of seizures, a prolonged outpatient video/video-EEG monitoring was appended after a short-term inpatient monitoring period. Patient 1: The seizure detection algorithm was capable of detecting 10 out of 11 seizures. The number of false-positive events was <0.03/h. It was clearly demonstrated that the patient showed more seizures than originally reported. Patient 2: The add-on medication of lacosamide led to a significant reduction in seizure frequency and to a marked decrease in the mean duration of seizures. The severity of seizures was reduced from numerous hypermotoric seizures to few mild, head-turning seizures. Outpatient monitoring may be helpful to guide treatment for severe epilepsies and offers the possibility to more reliably quantify the efficacy of treatment in the long-term, even over several months.

Using wearable sensors for semiology-independent seizure detection - towards ambulatory monitoring of epilepsy

Epilepsy is a disease of the central nervous system. Nearly 70% of people with epilepsy respond to a proper treatment, but for a successful therapy of epilepsy, physicians need to know if and when seizures occur. The gold standard diagnosis tool video-electroencephalography (vEEG) requires patients to stay at hospital for several days. A wearable sensor system, e.g. a wristband, serving as diagnostic tool or event monitor, would allow unobtrusive ambulatory long-term monitoring while reducing costs. Previous studies showed that seizures with motor symptoms such as generalized tonic-clonic seizures can be detected by measuring the electrodermal activity (EDA) and motion measuring acceleration (ACC). In this study, EDA and ACC from 8 patients were analyzed. In extension to previous studies, different types of seizures, including seizures without motor activity, were taken into account. A hierarchical classification approach was implemented in order to detect different types of epileptic seizures using data from wearable sensors. Using a k-nearest neighbor (kNN) classifier an overall sensitivity of 89.1% and an overall specificity of 93.1% were achieved, for seizures without motor activity the sensitivity was 97.1% and the specificity was 92.9%. The presented method is a first step towards a reliable ambulatory monitoring system for epileptic seizures with and without motor activity.