Evaluation of MEG vs EEG after sleep deprivation in epilepsy.

OBJECTIVE: MEG and EEG after sleep deprivation (EEG-SD) are applied as diagnostic tools in the evaluation of patients with possible epilepsy. There is no gold standard to check whether the diagnosis based on these two modalities is correct. The best standard available is the long-term follow-up of patients. As follow-up of an earlier study in which the additional value of MEG vs EEG-SD diagnosis was evaluated, we investigated the long-term validity of MEG-based and EEG-SD-based diagnosis. MATERIALS AND METHODS: Data collected from 46 patients were used in a comparative study of the last known diagnosis against the original one of 8 years ago. RESULTS: Long-term (3-8 years) sensitivity of sharp phenomena (combining spikes and sharp waves) in routine MEG and in EEG-SD for the diagnosis epilepsy is 71% and 62%, respectively. When compared to the original study, this hardly changed. Over time, uncertainty on diagnosis diminishes. CONCLUSION: MEG as well as EEG-SD are robust long-term predictors for epilepsy.

Eliciting patients' preferences for epilepsy diagnostics: a discrete choice experiment.

BACKGROUND: Diagnosing epilepsy is a lengthy and burdensome process for patients and their family. Although the need for a more patient-centered approach in clinical practice is widely acknowledged, empirical evidence regarding patient preferences for diagnostic modalities in epilepsy is missing. The objectives of this study were 1) to identify to what extent important attributes of diagnostic procedures in epilepsy affect preferences for a procedure, 2) to determine the relative importance of these attributes, and 3) to calculate overall utility scores for routine electroencephalography (EEG) and magnetoencephalography (MEG) recordings. METHODS: A discrete choice experiment was performed to determine patients' preferences, which involved presentation of pairwise choice tasks regarding hypothetical scenarios. Scenarios varied along six attributes: "way of measuring brain activity", "duration", "freedom of movement", "travel time", "type of additional examination", and "chance of additional examination". Choice tasks were constructed using a statistically efficient design, and the questionnaire contained 15 unique unlabeled choice tasks. Mixed multinomial logistic regression was used to estimate patients' preferences. RESULTS: A total of 289 questionnaires were included in the analysis. McFadden's pseudo R(2) showed a model fit of 0.28, and all attributes were statistically significant. Heterogeneity in preferences was present for all attributes. "Freedom of movement" and "Chance of additional examination" were perceived as the most important attributes. Overall utility scores did not substantially differ between routine EEG and MEG. CONCLUSION: This study suggests that the identified attributes are important in determining patients' preference for epilepsy diagnostics. It can be concluded that MEG is not necessarily more patient-friendly than a routine EEG in primary diagnostics and, regarding additional diagnostics, patients have a strong preference for long-term 24-h EEG over EEG after sleep deprivation. Furthermore, barring substantial heterogeneity within the parameters in mind, our study suggests that it is important to take individual preferences into account in medical decision-making.

A framework to integrate EEG-correlated fMRI and intracerebral recordings.

EEG-correlated functional MRI (EEG-fMRI) has been used to indicate brain regions associated with interictal epileptiform discharges (IEDs). This technique enables the delineation of the complete epileptiform network, including multifocal and deeply situated cortical areas. Before EEG-fMRI can be used as an additional diagnostic tool in the preoperative work-up, its added value should be assessed in relation to intracranial EEG recorded from depth electrodes (SEEG) or from the cortex (ECoG), currently the clinical standard. In this study, we propose a framework for the analysis of the SEEG data to investigate in a quantitative way whether EEG-fMRI reflects the same cortical areas as identified by the IEDs present in SEEG recordings. For that purpose, the data of both modalities were analyzed with a general linear model at the same time scale and within the same spatial domain. The IEDs were used as predictors in the model, yielding for EEG-fMRI the brain voxels that were related to the IEDs and, similarly for SEEG, the electrodes that were involved. Finally, the results of the regression analysis were projected on the anatomical MRI of the patients. To explore the usefulness of this quantitative approach, a sample of five patients was studied who both underwent EEG-fMRI and SEEG recordings. For clinical validation, the results of the SEEG analysis were compared to the standard visual review of IEDs in SEEG and to the identified seizure onset zone, the resected area, and outcome of surgery. SEEG analysis revealed a spatial pattern for the most frequent and dominant IEDs present in the data of all patients. The electrodes with the highest correlation values were in good concordance with the electrodes that showed maximal amplitude during those events in the SEEG recordings. These results indicate that the analysis of SEEG data at the time scale of EEG-fMRI, using the same type of regression model, is a promising way to validate EEG-fMRI data. In fact, the BOLD areas with a positive hemodynamic response function were closely related to the spatial pattern of IEDs in the SEEG recordings in four of the five patients. The areas of significant BOLD that were not located in the vicinity of depth electrodes, were mainly characterized by negative hemodynamic responses. Furthermore, the area with a positive hemodynamic response function overlapped with the resected area in three patients, while it was located at the edge of the resection area for one. To conclude, the results of this study encourage the application of EEG-fMRI to guide the implantation of depth electrodes as prerequisite for successful epilepsy surgery.

MEG-guided analysis of 7T-MRI in patients with epilepsy.

PURPOSE: To study possible detection of structural abnormalities on 7T MRI that were not detected on 3T MRI and estimate the added value of MEG-guidance. For abnormalities found, analysis of convergence between clinical, MEG and 7T MRI localization of suspected epileptogenic foci. METHODS: In adult patients with well-documented localization-related epilepsy in whom a previous 3T MRI did not demonstrate an epileptogenic lesion but MEG indicated a plausible epileptogenic focus, 7T MRI was performed. Based on semiologic data, visual analysis of the 7T images was performed as well as based on prior MEG results. Correlation with other data from the patient charts, for as far as these were available, was analysed. To establish the level of concordance between the three observers the generalized or Fleiss kappa was calculated. RESULTS: In 3/19 patients abnormalities that, based on semiology, could plausibly represent an epileptogenic lesion were detected using 7T MRI. In an additional 3/19 an abnormality was detected after MEG-guidance. However, in these later cases there was no concordance among the three observers with regard to the presence of a structural abnormality. In one of these three cases intracranial recording was performed, proving the possible abnormality on 7T MRI to be the epileptogenic focus. CONCLUSIONS: In 32% of patients 7T MRI showed abnormalities that could indicate an epileptogenic lesion whereas previous 3T MRI did not, especially when visual inspection was guided by the presence of focal interictal MEG abnormalities.

Prospective multi-center study of an automatic online seizure detection system for epilepsy monitoring units.

OBJECTIVE: A method for automatic detection of epileptic seizures in long-term scalp-EEG recordings called EpiScan will be presented. EpiScan is used as alarm device to notify medical staff of epilepsy monitoring units (EMUs) in case of a seizure. METHODS: A prospective multi-center study was performed in three EMUs including 205 patients. A comparison between EpiScan and the Persyst seizure detector on the prospective data will be presented. In addition, the detection results of EpiScan on retrospective EEG data of 310 patients and the public available CHB-MIT dataset will be shown. RESULTS: A detection sensitivity of 81% was reached for unequivocal electrographic seizures with false alarm rate of only 7 per day. No statistical significant differences in the detection sensitivities could be found between the centers. The comparison to the Persyst seizure detector showed a lower false alarm rate of EpiScan but the difference was not of statistical significance. CONCLUSIONS: The automatic seizure detection method EpiScan showed high sensitivity and low false alarm rate in a prospective multi-center study on a large number of patients. SIGNIFICANCE: The application as seizure alarm device in EMUs becomes feasible and will raise the efficiency of video-EEG monitoring and the safety levels of patients.

Spike cluster analysis in neocortical localization related epilepsy yields clinically significant equivalent source localization results in magnetoencephalogram (MEG).

OBJECTIVE: In magnetoencephalogram (MEG) recordings of patients with epilepsy several types of sharp transients with different spatiotemporal distributions are commonly present. Our objective was to develop a computer based method to identify and classify groups of epileptiform spikes, as well as other transients, in order to improve the characterization of irritative areas in the brain of epileptic patients. METHODS: MEG data centered on selected spikes were stored in signal matrices of C channels by T time samples. The matrices were normalized and euclidean distances between spike representations in vector space R(CxT) were input to a Ward's hierarchical clustering algorithm. RESULTS: The method was applied to MEG data from 4 patients with localization-related epilepsy. For each patient, distinct spike subpopulations were found with clearly different topographical field maps. Inverse computations to selected spike subaverages yielded source solutions in agreement with seizure classification and location of structural lesions, if present, on magnetic resonance images. CONCLUSIONS: With the proposed method a reliable categorization of epileptiform spikes is obtained, that can be applied in an automatic way. Computation of subaverages of similar spikes enhances the signal-to-noise ratio of spike field maps and allows for more accurate reconstruction of sources generating the epileptiform discharges.

Magnetic source imaging contributes to the presurgical identification of sensorimotor cortex in patients with frontal lobe epilepsy.

OBJECTIVE: One of the primary goals of preoperative evaluation of patients considered to be candidates for epilepsy surgery is the delineation of eloquent cortex adjacent to the area of resection. The aim of this study is the functional localization of the sensorimotor cortex in relation to an epileptogenic frontal lobe lesion, thus enabling a more complete resection in these patients while minimizing the risk of postoperative neurological deficits. METHODS: Participating in this study were patients with epilepsy, diagnosed as being related to a left or right frontal lobe lesion. Magnetoencephalographic responses evoked by electrical stimulation of the left and right hand median nerve were localized using single time-point equivalent dipole (ED) modeling, taking into account the realistic shape of the head. Instead of relying on the primary component (N/P 20) of the somatosensory evoked magnetic fields (SEFs) in this study ED fits were obtained for each time-point of the somatosensory evoked responses. On a cortical rendering, the reconstructed dipoles were depicted relative to the anatomy obtained from 3D-magnetic resonance imaging. RESULTS: The results of single time-point ED analysis including all the components of the responses indicated that the sources underlying the SEFs are located at the borders of the central sulcus (CS). The opposite direction of the sources underlying, respectively, the primary and subsequent late component of the SEFs indicated distinct sources located at the opposite banks of the CS. These sources, therefore, might correspond to the sensory hand projection area and the primary motor area of the sensorimotor cortex. It appeared that the location of the EDs obtained for the SEFs of 4 of the 7 patients studied were asymmetric for the left and right hemisphere, probably because of a displacement of the sensorimotor areas relative to the CS. The systematic assessment of the dipole fits compared to brain anatomy confirmed that volume conduction changes due to the lesion were not responsible for these observed deviations, thus leaving as explanation space-occupying and neurophysiological changes due to the lesion.

Analysis of striate activity underlying the pattern onset EP of children.

The checkerboard onset Evoked Potential (EP) does not obtain its adult form before puberty. To determine the site of origin of these processes we studied the origin of the checkerboard onset EP in a group of 10 children between the ages of 6 and 16 years. Since the development of the waveform of the pattern onset EP varies with check size we also studied the dependence of these EPs on check size. The child checkerboard onset EPs described in this paper are dominated by a single source. Following an equivalent dipole source localization approach, the position, orientation and variation in strength of the equivalent dipole is estimated. The position and orientation of this dipole indicates an origin in the primary visual cortex (area 17). The variation in strength of the dipole changes from a single positive deflection, specific for children of 8 years and younger, into a negative-positive complex for the children studied between the age of 9 and 16 years. These changes in waveform must be due to changes in the activity pattern of the striate cortex.

Hemispheric asymmetry in the maturation of the extrastriate checkerboard onset evoked potential.

Recently we have shown that the single positive deflection in the checkerboard onset evoked potential (EP) of young children of striate origin develops into a negative-positive complex. However, also an early positive peak becomes apparent in the checkerboard onset EP. To determine the origin and development of the activity underlying this early positive deflection we studied the checkerboard onset EPs in children of 9-16 years of age. It was found that for the children in this age group two different dipole sources are responsible for the activity underlying the pattern onset EP. One of the dipoles corresponds to the activity generated in the striate cortex, whereas a second dipole of extrastriate origin is responsible for the appearance of the early positive deflection. This extrastriate activity shows hemispheric asymmetry, i.e. the strength of the right hemispheric extrastriate source exceeds the strength of the left hemispheric source. These results are in accordance with histological studies of Conel (1939-1963) [The postnatal development of the human cerebral cortex (Vols 1-8). Cambridge, Mass.: Harvard Univ. Press] which show that the maturation of the extrastriate areas of the left hemisphere is delayed with respect to the right hemisphere.

Automatic detection of the seizure onset zone based on ictal EEG.

In this paper we show a proof of concept for novel automatic seizure onset zone detector. The proposed approach utilizes the Austrian Institute of Technology (AIT) seizure detection system EpiScan extended by a frequency domain source localization module. EpiScan was proven to detect rhythmic epileptoform seizure activity often seen during the early phase of epileptic seizures with reasonable high sensitivity and specificity. Additionally, the core module of EpiScan provides complex coefficients and fundamental frequencies representing the rhythmic activity of the ictal EEG signal. These parameters serve as input to a frequency domain version of the Minimum Variance Beamformer to estimate the most dominant source. The position of this source is the detected seizure onset zone. The results are compared to a state of the art wavelet transformation approach based on a manually chosen frequency band. Our first results are encouraging since they coincide with those obtained with the wavelet approach and furthermore show excellent accordance with the medical report for the majority of analyzed seizures. In contrast to the wavelet approach our method has the advantage that it does not rely on a manual selection of the frequency band.

Automatic breath-to-breath analysis of nocturnal polysomnographic recordings.

Diagnosis of sleep-disordered breathing is based on the presence of an abnormal breathing pattern during sleep. In this study, an algorithm was developed for the offline breath-to-breath analysis of the nocturnal respiratory recordings. For that purpose, respiratory signals (nasal airway pressure, thoracic and abdominal movements) were divided into half waves using period amplitude analysis. Individual breaths were characterized by the parameters of the half waves (duration, amplitude, and slope). These values can be used to discriminate between normal and abnormal breaths. This algorithm was applied to six polysomnographic recordings to distinguish abnormal breathing events (apneas and hypopneas). The algorithm was robust for the identification of breaths (sensitivity = 96.8%, positive prediction value (PPV) = 99.5%). The detection of apneas and hypopneas was compared to the manual scoring of two experienced sleep technicians: sensitivity was, respectively, 89.2 and 88.9%, PPV was 54.1 and 59.3%. The classification of apneas into central, obstructive, or mixed was in concordance with the observers in 68% of the apneas. Although the algorithm tended to detect more hypopneas than the clinical standard, this study shows that the extraction of breath-to-breath parameters is useful for detection of abnormal respiratory events and provides a basis for further characterization of these events.

MRS-lateralisation index in patients with epilepsy and focal cortical dysplasia or a MEG-focus using bilateral single voxels.

PURPOSE: To evaluate if single voxel proton magnetic resonance spectroscopy (SV-MRS) can help in lateralising and sometimes in localizing an epileptogenic focus. The assumption is that in MRI negative patients the underlying pathology most often is focal cortical dysplasia (FCD). Several studies have shown that in the presence of FCD there are also (1)H-MRS abnormalities on the contralateral side. However, in most cases the studied group was not homogeneous and included different forms of dysplasias, including band heterotopias and polymicrogyria, and the studies used different spectroscopy protocols. In the present study, using bilateral SV-MRS we investigated the presence of a lateralisation index in two groups of patients with localisation related epilepsy: patients with focal cortical dysplasia on MRI and patients without MRI abnormalities with a focus identified by MEG. Aim of the study was to show that in both groups the expected epileptogenic side shows more pronounced metabolic alterations, making MRS a possible screening tool for clarifying lateralisation questions in patients with cryptogenic localisation related epilepsy. METHODS: In ten patients a single voxel was placed over the FCD and in nine patients over the region of interest (ROI) as indicated by MEG. In all patients a voxel was also placed in the contralateral homologus location. We used metabolite concentrations as peak ratios relative to the creatine (Cr) peak to calculate a lateralisation index. RESULTS: In both groups NAA/Cr was significantly lower on the affected side whereas the results for Cho/Cr were more diverse. There were no significant differences between the two groups. The limitations of the used methods and the implications of the findings are discussed.

The extrastriate generators of the EP to checkerboard onset. A source localization approach.

The cortical origin of the pattern onset EP has been investigated over a time window which covers the entire positive-negative-positive complex of the pattern onset EP. On the basis of a dipole source localization approach, the position, orientation and strength of the underlying sources of the pattern onset EP were estimated. For large check stimuli, chosen to have a weak edge specific component in the response, still two components are needed to account for the variance of the responses. Each component corresponds to a single dipole source, and both originate in the extrastriate cortex. These components dominate, respectively, the initial and the late positive peaks of the pattern onset EP. The equivalent dipole sources of the two components show different behaviors with respect to the position of the stimulus in the visual field. The topography and behavior of the equivalent dipole source underlying the early positive component suggest an origin in area 18. The invariance with stimulus location of the dipole source underlying the late positive component suggests an origin beyond area 18. The different topographies of the components also account for the differences in surface distribution of the pattern onset EP to large check stimulation of the upper and lower sectors of the visual field.

Check size dependency of the sources of the hemifield-onset evoked potential.

The checkerboard-onset evoked potential does not obtain its adult waveform until late puberty. The changing waveform results from the development of the underlying sources originating in distinct areas of the visual cortex. Since the waveform of checkerboard-onset evoked potential also varies with check size, we studied the dependency of the activity of these sources on check size. A dipole source localization procedure yielded the position and orientation of the equivalent dipoles and the constituent components of the pattern-onset evoked potential, each corresponding to one of these dipoles. For every check size used, the checkerboard-onset evoked potential could be described by a summation of the relative amplitudes of these components. Since the relative amplitude versus check size curves showed a different behavior for each source, they provided evidence of functionally distinct cortical generators. The strength of the striate source was especially sensitive to the fine structure of a pattern, whereas the extrastriate sources contributed mainly for coarse pattern elements.