Regional differences in the sensitivity of MEG for interictal spikes in epilepsy

Cortical control of posture in fine motor skills: evidence from inter-utterance rest position

The vocal tract continuously employs tonic muscle activity in the maintenance of postural configurations. Gamma-band activity in the sensorimotor cortex underlies transient movements during speech production, yet little is known about the neural control of postural states in the vocal tract. Simultaneously, there is evidence that sensorimotor beta-band activations contribute to a system of inhibition and state maintenance that is integral to postural control in the body. Here we use electrocorticography to assess the contribution of sensorimotor beta-band activity during speech articulation and postural maintenance, and demonstrate that beta-band activity corresponds to the inhibition of discrete speech movements and the maintenance of tonic postural states in the vocal tract. Our findings identify consistencies between the neural control of posture in speech and what is previously reported in gross motor contexts, providing support for a unified theory of postural control across gross and fine motor skills.

Data-driven approach for the delineation of the irritative zone in epilepsy in MEG

The reliable identification of the irritative zone (IZ) is a prerequisite for the correct clinical evaluation of medically refractory patients affected by epilepsy. Given the complexity of MEG data, visual analysis of epileptiform neurophysiological activity is highly time consuming and might leave clinically relevant information undetected. We recorded and analyzed the interictal activity from seven patients affected by epilepsy (Vectorview Neuromag), who successfully underwent epilepsy surgery (Engel > = II). We visually marked and localized characteristic epileptiform activity (VIS). We implemented a two-stage pipeline for the detection of interictal spikes and the delineation of the IZ. First, we detected candidate events from peaky ICA components, and then clustered events around spatio-temporal patterns identified by convolutional sparse coding. We used the average of clustered events to create IZ maps computed at the amplitude peak (PEAK), and at the 50% of the peak ascending slope (SLOPE). We validated our approach by computing the distance of the estimated IZ (VIS, SLOPE and PEAK) from the border of the surgically resected area (RA). We identified 25 spatiotemporal patterns mimicking the underlying interictal activity (3.6 clusters/patient). Each cluster was populated on average by 22.1 [15.0–31.0] spikes. The predicted IZ maps had an average distance from the resection margin of 8.4 ± 9.3 mm for visual analysis, 12.0 ± 16.5 mm for SLOPE and 22.7 ±. 16.4 mm for PEAK. The consideration of the source spread at the ascending slope provided an IZ closer to RA and resembled the analysis of an expert observer. We validated here the performance of a data-driven approach for the automated detection of interictal spikes and delineation of the IZ. This computational framework provides the basis for reproducible and bias-free analysis of MEG recordings in epilepsy.

Increased delta power as a scalp marker of epileptic activity: a simultaneous scalp and intracranial electroencephalography study

BACKGROUND AND PURPOSE

The purpose was to evaluate whether intracranial interictal epileptiform discharges (IEDs) that are not visible on the scalp are associated with changes in the frequency spectrum on scalp electroencephalograms (EEGs).

METHODS

Simultaneous scalp high-density EEG and intracranial EEG recordings were recorded in nine patients undergoing pre-surgical invasive recordings for pharmaco-resistant temporal lobe epilepsy. Epochs with hippocampal IED visible on intracranial EEG (ic-IED) but not on scalp EEG were selected, as well as control epochs without ic-IED. Welch's power spectral density was computed for each scalp electrode and for each subject; the power spectral density was further averaged across the canonical frequency bands and compared between the two conditions with and without ic-IED. For each patient the peak frequency in the delta band (the significantly strongest frequency band in all patients) was determined during periods of ic-IED. The five electrodes showing strongest power at the peak frequency were also determined.

RESULTS

It was found that intracranial IEDs are associated with an increase in delta power on scalp EEGs, in particular at a frequency ≥1.4 Hz. Electrodes showing slow frequency power changes associated with IEDs were consistent with the hemispheric lateralization of IEDs. Electrodes with maximum power of slow activity were not limited to temporal regions but also involved frontal (bilateral or unilateral) regions.

CONCLUSIONS

In patients with a clinical picture suggestive of temporal lobe epilepsy, the presence of delta slowing ≥1.4 Hz in anterior temporal regions can represent a scalp marker of hippocampal IEDs. To our best knowledge this is the first study that demonstrates the co-occurrence of ic-IED and increased delta power.

The 10 Common Evidence-Supported Indications for MEG in Epilepsy Surgery: An Illustrated Compendium

Unfamiliarity with the indications for and benefits of magnetoencephalography (MEG) persists, even in the epilepsy community, and hinders its acceptance to clinical practice, despite the evidence. The wide treatment gap for patients with drug-resistant epilepsy and immense underutilization of epilepsy surgery had similar effects. Thus, educating referring physicians (epileptologists, neurologists, and neurosurgeons) both about the value of epilepsy surgery and about the potential benefits of MEG can achieve synergy and greatly improve the process of selecting surgical candidates. As a practical step toward a comprehensive educational process to benefit potential MEG users, current MEG referrers, and newcomers to MEG, the authors have elected to provide an illustrated guide to 10 everyday situations where MEG can help in the evaluation of people with drug-resistant epilepsy. They are as follows: (1) lacking or imprecise hypothesis regarding a seizure onset; (2) negative MRI with a mesial temporal onset suspected; (3) multiple lesions on MRI; (4) large lesion on MRI; (5) diagnostic or therapeutic reoperation; (6) ambiguous EEG findings suggestive of "bilateral" or "generalized" pattern; (7) intrasylvian onset suspected; (8) interhemispheric onset suspected; (9) insular onset suspected; and (10) negative (i.e., spikeless) EEG. Only their practical implementation and furtherance of personal and collective education will lead to the potentially impactful synergy of the two-MEG and epilepsy surgery. Thus, while fulfilling our mission as physicians, we must not forget that ignoring the wealth of evidence about the vast underutilization of epilepsy surgery - and about the usefulness and value of MEG in selecting surgical candidates - is far from benign neglect.

Contribution of Ictal Source Imaging for Localizing Seizure Onset Zone in Patients With Focal Epilepsy

OBJECTIVE

To determine whether seizure onset zone (SOZ) can be localized accurately prior to surgical planning in patients with focal epilepsy, we performed noninvasive EEG recordings and source localization analyses on 39 patients.

METHODS

In 39 patients with focal epilepsy, we recorded and extracted 138 seizures and 1,325 interictal epileptic discharges using high-density EEG. We investigated a novel approach for directly imaging sources of seizures and interictal spikes from high-density EEG recordings, and rigorously validated it for noninvasive localization of SOZ determined from intracranial EEG findings and surgical resection volume. Conventional source imaging analyses were also performed for comparison.

RESULTS

Ictal source imaging showed a concordance rate of 95% when compared to intracranial EEG or resection results. The average distance from estimation to seizure onset (intracranial) electrodes is 1.35 cm in patients with concordant results, and 0.74 cm to surgical resection boundary in patients with successful surgery. About 41% of the patients were found to have multiple types of interictal activities; coincidentally, a lower concordance rate and a significantly worse performance in localizing SOZ were observed in these patients.

CONCLUSION

Noninvasive ictal source imaging with high-density EEG recording can provide highly concordant results with clinical decisions obtained by invasive monitoring or confirmed by resective surgery. By means of direct seizure imaging using high-density scalp EEG recordings, the added value of ictal source imaging is particularly high in patients with complex interictal activity patterns, who may represent the most challenging cases with poor prognosis.

Assessing the localization accuracy and clinical utility of electric and magnetic source imaging in children with epilepsy

OBJECTIVE

To evaluate the accuracy and clinical utility of conventional 21-channel EEG (conv-EEG), 72-channel high-density EEG (HD-EEG) and 306-channel MEG in localizing interictal epileptiform discharges (IEDs).

METHODS

Twenty-four children who underwent epilepsy surgery were studied. IEDs on conv-EEG, HD-EEG, MEG and intracranial EEG (iEEG) were localized using equivalent current dipoles and dynamical statistical parametric mapping (dSPM). We compared the localization error (E_Loc) with respect to the ground-truth Irritative Zone (IZ), defined by iEEG sources, between non-invasive modalities and the distance from resection (D_res) between good- (Engel 1) and poor-outcomes. For each patient, we estimated the resection percentage of IED sources and tested whether it predicted outcome.

RESULTS

MEG presented lower E_Loc than HD-EEG and conv-EEG. For all modalities, D_res was shorter in good-outcome than poor-outcome patients, but only the resection percentage of the ground-truth IZ and MEG-IZ predicted surgical outcome.

CONCLUSIONS

MEG localizes the IZ more accurately than conv-EEG and HD-EEG. MSI may help the presurgical evaluation in terms of patient's outcome prediction. The promising clinical value of ESI for both conv-EEG and HD-EEG prompts the use of higher-density EEG-systems to possibly achieve MEG performance.

SIGNIFICANCE

Localizing the IZ non-invasively with MSI/ESI facilitates presurgical evaluation and surgical prognosis assessment.

Bayesian Electromagnetic Spatio-Temporal Imaging of Extended Sources Based on Matrix Factorization

Accurate estimation of the locations and extents of neural sources from electroencephalography and magnetoencephalography (E/MEG) is challenging, especially for deep and highly correlated neural activities. In this study, we proposed a new fully data-driven source imaging method, source imaging based on spatio-temporal basis function (SI-STBF), which is built upon a Bayesian framework, to address this issue. The SI-STBF is based on the factorization of a source matrix as a product of a sparse coding matrix and a temporal basis function (TBF) matrix, which includes a few TBFs. The prior of the TBF is set in the empirical Bayesian manner. Similarly, for the spatial constraint, the SI-STBF assumes the prior covariance of the coding matrix as a weighted sum of several spatial covariance components. Both the TBFs and the coding matrix are learned from E/MEG simultaneously through variational Bayesian inference. To enable inference on high-resolution source space, we derived a scalable algorithm using convex analysis. The performance of the SI-STBF was assessed using both simulated and experimental E/MEG recordings. Compared with L₂-norm constrained methods, the SI-STBF is superior in reconstructing extended sources with less spatial diffusion and less localization error. By virtue of the spatio-temporal factorization of source matrix, the SI-STBF also produces more accurate estimations than spatial-only constraint method for high correlated and deep sources.

Magnetoencephalographic Mapping of Epileptic Spike Population Using Distributed Source Analysis: Comparison With Intracranial Electroencephalographic Spikes

INTRODUCTION

This study evaluates magnetoencephalographic (MEG) spike population as compared with intracranial electroencephalographic (IEEG) spikes using a quantitative method based on distributed source analysis.

METHODS

We retrospectively studied eight patients with medically intractable epilepsy who had an MEG and subsequent IEEG monitoring. Fifty MEG spikes were analyzed in each patient using minimum norm estimate. For individual spikes, each vertex in the source space was considered activated when its source amplitude at the peak latency was higher than a threshold, which was set at 50% of the maximum amplitude over all vertices. We mapped the total count of activation at each vertex. We also analyzed 50 IEEG spikes in the same manner over the intracranial electrodes and created the activation count map. The location of the electrodes was obtained in the MEG source space by coregistering postimplantation computed tomography to MRI. We estimated the MEG- and IEEG-active regions associated with the spike populations using the vertices/electrodes with a count over 25.

RESULTS

The activation count maps of MEG spikes demonstrated the localization associated with the spike population by variable count values at each vertex. The MEG-active region overlapped with 65 to 85% of the IEEG-active region in our patient group.

CONCLUSIONS

Mapping the MEG spike population is valid for demonstrating the trend of spikes clustering in patients with epilepsy. In addition, comparison of MEG and IEEG spikes quantitatively may be informative for understanding their relationship.

Automated detection of epileptic ripples in MEG using beamformer-based virtual sensors

OBJECTIVE

In epilepsy, high-frequency oscillations (HFOs) are expressively linked to the seizure onset zone (SOZ). The detection of HFOs in the noninvasive signals from scalp electroencephalography (EEG) and magnetoencephalography (MEG) is still a challenging task. The aim of this study was to automate the detection of ripples in MEG signals by reducing the high-frequency noise using beamformer-based virtual sensors (VSs) and applying an automatic procedure for exploring the time-frequency content of the detected events.

APPROACH

Two-hundred seconds of MEG signal and simultaneous iEEG were selected from nine patients with refractory epilepsy. A two-stage algorithm was implemented. Firstly, beamforming was applied to the whole head to delimitate the region of interest (ROI) within a coarse grid of MEG-VS. Secondly, a beamformer using a finer grid in the ROI was computed. The automatic detection of ripples was performed using the time-frequency response provided by the Stockwell transform. Performance was evaluated through comparisons with simultaneous iEEG signals.

MAIN RESULTS

ROIs were located within the seizure-generating lobes in the nine subjects. Precision and sensitivity values were 79.18% and 68.88%, respectively, by considering iEEG-detected events as benchmarks. A higher number of ripples were detected inside the ROI compared to the same region in the contralateral lobe.

SIGNIFICANCE

The evaluation of interictal ripples using non-invasive techniques can help in the delimitation of the epileptogenic zone and guide placement of intracranial electrodes. This is the first study that automatically detects ripples in MEG in the time domain located within the clinically expected epileptic area taking into account the time-frequency characteristics of the events through the whole signal spectrum. The algorithm was tested against intracranial recordings, the current gold standard. Further studies should explore this approach to enable the localization of noninvasively recorded HFOs to help during pre-surgical planning and to reduce the need for invasive diagnostics.

Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy

Fusion of electroencephalography (EEG) and magnetoencephalography (MEG) data using maximum entropy on the mean method (MEM-fusion) takes advantage of the complementarities between EEG and MEG to improve localization accuracy. Simulation studies demonstrated MEM-fusion to be robust especially in noisy conditions such as single spike source localizations (SSSL). Our objective was to assess the reliability of SSSL using MEM-fusion on clinical data. We proposed to cluster SSSL results to find the most reliable and consistent source map from the reconstructed sources, the so-called consensus map. Thirty-four types of interictal epileptic discharges (IEDs) were analyzed from 26 patients with well-defined epileptogenic focus. SSSLs were performed on EEG, MEG, and fusion data and consensus maps were estimated using hierarchical clustering. Qualitative (spike-to-spike reproducibility rate, SSR) and quantitative (localization error and spatial dispersion) assessments were performed using the epileptogenic focus as clinical reference. Fusion SSSL provided significantly better results than EEG or MEG alone. Fusion found at least one cluster concordant with the clinical reference in all cases. This concordant cluster was always the one involving the highest number of spikes. Fusion yielded highest reproducibility (SSR EEG = 55%, MEG = 71%, fusion = 90%) and lowest localization error. Also, using only few channels from either modality (21EEG + 272MEG or 54EEG + 25MEG) was sufficient to reach accurate fusion. MEM-fusion with consensus map approach provides an objective way of finding the most reliable and concordant generators of IEDs. We, therefore, suggest the pertinence of SSSL using MEM-fusion as a valuable clinical tool for presurgical evaluation of epilepsy.

Magnetoencephalographic and functional MRI connectomics in schizophrenia via intra- and inter-network connectivity

Examination of intrinsic functional connectivity using functional MRI (fMRI) has provided important findings regarding dysconnectivity in schizophrenia. Extending these results using a complementary neuroimaging modality, magnetoencephalography (MEG), we present the first direct comparison of functional connectivity between schizophrenia patients and controls, using these two modalities combined. We developed a novel MEG approach for estimation of networks using MEG that incorporates spatial independent component analysis (ICA) and pairwise correlations between independent component timecourses, to estimate intra- and intern-network connectivity. This analysis enables group-level inference and testing of between-group differences. Resting state MEG and fMRI data were acquired from a large sample of healthy controls (n=45) and schizophrenia patients (n=46). Group spatial ICA was performed on fMRI and MEG data to extract intrinsic fMRI and MEG networks and to compensate for signal leakage in MEG. Similar, but not identical spatial independent components were detected for MEG and fMRI. Analysis of functional network connectivity (FNC; i.e., pairwise correlations in network (ICA component) timecourses) revealed a differential between-modalities pattern, with greater connectivity among occipital networks in fMRI and among frontal networks in MEG. Most importantly, significant differences between controls and patients were observed in both modalities. MEG FNC results in particular indicated dysfunctional hyperconnectivity within frontal and temporal networks in patients, while in fMRI FNC was always greater for controls than for patients. This is the first study to apply group spatial ICA as an approach to leakage correction, and as such our results may be biased by spatial leakage effects. Results suggest that combining these two neuroimaging modalities reveals additional disease-relevant patterns of connectivity that were not detectable with fMRI or MEG alone.

Accuracy of MEG in localizing irritative zone and seizure onset zone: Quantitative comparison between MEG and intracranial EEG

BACKGROUND

We conducted the study to examine accuracy of the magnetoencephalography (MEG) spike source localization in presurgical evaluation of patients with medically refractory focal epilepsy.

METHODS

Ten consecutive patients with refractory focal epilepsy who were candidates for two-stage surgery with long-term intracranial electroencephalography (ICEEG) monitoring were enrolled. Interictal MEG recordings with simultaneous scalp EEG were obtained within 7days before the ICEEG electrode implantation. The location of each MEG spike source was quantitatively compared with ICEEG spike foci (focal area of interictal spikes) and ICEEG ictal foci (earliest cortical origin of seizures). Gyral-width concordance and sublobar concordance were also determined for all MEG spike sources. Gyral-width concordance was defined by distance of 15mm or less between MEG spike sources and ICEEG spike foci or ICEEG ictal foci.

RESULTS

Visual analyses of the MEG traces of all 10 patients revealed 292 spikes (29.2±24.0 per patient). Spike yield of the MEG was similar to the simultaneously recorded scalp EEG. MEG spike sources were closely located with ICEEG spike foci (distance: 9.3±10.8mm). Clustered MEG spike sources were even closer to ICEEG spike foci (distance: 7.3±6.4mm). MEG spike sources, even clustered ones, were less concordant with ICEEG ictal foci and had significant longer distance from ICEEG ictal foci (distance: 21.5±15.6mm for all sources, 19.7±13.7mm for clustered sources). Gyral-width concordance rate and sublobar concordance rate were also higher with ICEEG interictal spike foci than with ICEEG ictal foci. On the other hand, 53.4% of interictal spike foci from ICEEG were not detected by interictal MEG recordings.

CONCLUSIONS

MEG spike sources, especially clustered ones, from interictal recording could localize the irritative zone of ICEEG with a high accuracy. However, MEG spike sources have relatively poor correlation with seizure onset zone and lower sensitivity in identifying all irritative zones of ICEEG. This limitation should be considered in the interpretation of MEG results.

Preoperative evaluation and surgical decision-making in pediatric epilepsy surgery

Epilepsy is a common disease in the pediatric population, and the majority of cases are controlled with medications and lifestyle modification. For the children whose seizures are pharmacoresistant, continued epileptic activity can have a severely detrimental impact on cognitive development. Early referral of children with drug-resistant seizures to a pediatric epilepsy surgery center for evaluation is critical to achieving optimal patient outcomes. There are several components to a thorough presurgical evaluation, including a detailed medical history and physical examination, noninvasive testing including electroencephalogram, magnetic resonance imaging (MRI) of the brain, and often metabolic imaging. When necessary, invasive diagnostic testing using intracranial monitoring can be used. The identification of an epileptic focus may allow resection or disconnection from normal brain structures, with the ultimate goal of complete seizure remission. Additional operative measures can decrease seizure frequency and/or intensity if a clear epileptic focus cannot be identified. In this review, we will discuss the nuances of presurgical evaluation and decision-making in the management of children with drug-resistant epilepsy (DRE).

Preoperative evaluation using magnetoencephalography: Experience in 382 epilepsy patients

OBJECTIVE

Identifying epilepsy patients for whom clinical MEG is likely to be beneficial avoids or optimizes burdensome ancillary investigations. We determined whether it could be predicted upfront if MEG would be able to generate a hypothesis about the location of the epileptogenic zone (EZ), and in which patients MEG fails to do so.

METHODS

MEG recordings of 382 epilepsy patients with inconclusive findings regarding EZ localization prior to MEG were acquired for preoperative evaluation. MEG reports were categorized for several demographic, clinical and MEG variables. First, demographic and clinical variables were associated with MEG localization ability for upfront prediction. Second, all variables were compared between patients with and without MEG location in order to characterize patients without MEG location.

RESULTS

Our patient group had often complex etiology and did not contain the (by other means) straightforward and well-localized cases, such as those with concordant tumor and EEG location. For our highly-selected patient group, MEG localization ability cannot be predicted upfront, although the odds of a recording with MEG location were significantly higher in the absence of a tumor and in the presence of widespread MRI abnormalities. Compared to the patients with MEG location, patients without MEG location more often had a tumor, widespread EEG abnormalities, non-lateralizing MEG abnormalities, non-concordant MEG/EEG abnormalities and less often widespread MRI abnormalities or epileptiform MEG activity. In a subgroup of 48 patients with known surgery outcome, more patients with concordant MEG and resection area were seizure-free than patients with discordant results.

CONCLUSIONS

MEG potentially adds information about the location of the EZ even in patients with a complex etiology, and the clinical advice is to not withhold MEG in epilepsy surgery candidates. Providing a hypothesis about the location of the EZ using MEG is difficult in patients with inconclusive EEG and MRI findings, and in the absence of specific epileptiform activity. More refined methods are needed for patients where MEG currently does not contribute to the hypothesis about the location of the EZ.

Source localization of the seizure onset zone from ictal EEG/MEG data

INTRODUCTION

Surgical treatment of drug-resistant epilepsy relies on the identification of the seizure onset zone (SOZ) and often requires intracranial EEG (iEEG). We have developed a new approach for non-invasive magnetic and electric source imaging of the SOZ (MSI-SOZ and ESI-SOZ) from ictal magnetoencephalography (MEG) and EEG recordings, using wavelet-based Maximum Entropy on the Mean (wMEM) method. We compared the performance of MSI-SOZ and ESI-SOZ with interictal spike source localization (MSI-spikes and ESI-spikes) and clinical localization of the SOZ (i.e., based on iEEG or lesion topography, denoted as clinical-SOZ).

METHODS

A total of 46 MEG or EEG seizures from 13 patients were analyzed. wMEM was applied around seizure onset, centered on the frequency band showing the strongest power change. Principal component analysis applied to spatiotemporal reconstructed wMEM sources (0.4-1 s around seizure onset) identified the main spatial pattern of ictal oscillations. Qualitative sublobar concordance and quantitative measures of distance and spatial overlaps were estimated to compare MSI/ESI-SOZ with MSI/ESI-Spikes and clinical-SOZ.

RESULTS

MSI/ESI-SOZ were concordant with clinical-SOZ in 81% of seizures (MSI 90%, ESI 64%). MSI-SOZ was more accurate and identified sources closer to the clinical-SOZ (P = 0.012) and to MSI-Spikes (P = 0.040) as compared with ESI-SOZ. MSI/ESI-SOZ and MSI/ESI-Spikes did not differ in terms of concordance and distance from the clinical-SOZ.

CONCLUSIONS

wMEM allows non-invasive localization of the SOZ from ictal MEG and EEG. MSI-SOZ performs better than ESI-SOZ. MSI/ESI-SOZ can provide important additional information to MSI/ESI-Spikes during presurgical evaluation. Hum Brain Mapp 37:2528-2546, 2016. © 2016 Wiley Periodicals, Inc.

Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy

Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc.

Ictal Magnetic Source Imaging in Presurgical Assessment

Ictal MEG recordings constitute rare data. The objective of this study was to evaluate ictal magnetic source localization (MSI), using two algorithms: linearly constrained minimum variance (LCMV), a beamforming technique and equivalent current dipole (ECD). Ictal MSI was studied in six patients. Three of them were undergoing post-operative re-evaluation. For all patients, results were validated by the stereoelectroencephalographic (SEEG) definition of the epileptogenic zone (EZ). EZ was quantified using the epileptogenicity index (EI) method, which accounts for both the propensity of a brain area to generate rapid discharges and the time for this area to become involved in the seizure. EI values range from 0 (no epileptogenicity) to 1 (maximal epileptogenicity). Levels of concordance between ictal MSI and EZ were determined as follows: A: ictal MSI localized the site whose value EI = 1, B: MSI localized a part of the EZ (not corresponding to the maximal value of EI = 1), C: a region could be identified on ictal MSI but not on SEEG, D: a region could be identified on SEEG but not on MSI, E: different regions were localized on MSI and SEEG. Ictal MEG pattern consisted of rhythmic activities between 10 and 20 Hz for all patients. For LCMV (first maxima), levels of concordance were A (two cases), B (two cases) and E (two cases). For ECD fitted on each time point separately (location characterized by the best goodness-of-fit value), levels of concordance were A (one case), B (one case), D (three cases) and E (one case). For ECD calculated for the whole time window, levels of concordance were A (two cases) and D (four cases). Source localization methods performed on rhythmic patterns can localize the EZ as validated by SEEG. In terms of concordance, LCMV was superior to ECD. In some cases, LCMV allows extraction of several maxima that could reflect ictal dynamics. In a medial temporal lobe epilepsy case, ictal MSI indicated an area of delayed propagation and was non-contributory to the presurgical assessment.

MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy

The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG–MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion.

Magnetoencephalography in the presurgical evaluation of epilepsy

Magnetoencephalography (MEG) is an important tool in the presurgical evaluation of patients with medically refractory epilepsy. The appropriate utilization and interpretation of MEG studies can increase the proportion of patients who may be able to further pursue surgical evaluation, refine surgical planning, and potentially increase the probability of seizure freedom after surgery. The aim of this paper is to provide the reader with a comprehensive but accessible guide to MEG, with particular emphasis on acquiring a working knowledge of MEG analysis, identifying patient groups that are most likely to benefit, and clarifying the limitations of this technology.

The role of functional neuroimaging in pre-surgical epilepsy evaluation

The prevalence of epilepsy is about 1% and one-third of cases do not respond to medical treatment. In an eligible subset of patients with drug-resistant epilepsy, surgical resection of the epileptogenic zone is the only treatment that can possibly cure the disease. Non-invasive techniques provide information for the localization of the epileptic focus in the majority of cases, whereas in others invasive procedures are required. In the last years, non-invasive neuroimaging techniques, such as simultaneous recording of functional magnetic resonance imaging and electroencephalogram (EEG-fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), electric and magnetic source imaging (MSI, ESI), spectroscopy (MRS), have proved their usefulness in defining the epileptic focus. The combination of these functional techniques can yield complementary information and their concordance is crucial for guiding clinical decision, namely the planning of invasive EEG recordings or respective surgery. The aim of this review is to present these non-invasive neuroimaging techniques, their potential combination, and their role in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy.

The role of functional neuroimaging in pre-surgical epilepsy evaluation

The prevalence of epilepsy is about 1% and one-third of cases do not respond to medical treatment. In an eligible subset of patients with drug-resistant epilepsy, surgical resection of the epileptogenic zone is the only treatment that can possibly cure the disease. Non-invasive techniques provide information for the localization of the epileptic focus in the majority of cases, whereas in others invasive procedures are required. In the last years, non-invasive neuroimaging techniques, such as simultaneous recording of functional magnetic resonance imaging and electroencephalogram (EEG-fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), electric and magnetic source imaging (MSI, ESI), spectroscopy (MRS), have proved their usefulness in defining the epileptic focus. The combination of these functional techniques can yield complementary information and their concordance is crucial for guiding clinical decision, namely the planning of invasive EEG recordings or respective surgery. The aim of this review is to present these non-invasive neuroimaging techniques, their potential combination, and their role in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy.

Magnetoencephalography in the study of epilepsy and consciousness

The neural bases of altered consciousness in patients with epilepsy during seizures and at rest have raised significant interest in the last decade. This exponential growth has been supported by the parallel development of techniques and methods to investigate brain function noninvasively with unprecedented spatial and temporal resolution. In this article, we review the contribution of magnetoencephalography to deconvolve the bioelectrical changes associated with impaired consciousness during seizures. We use data collected from a patient with refractory absence seizures to discuss how spike-wave discharges are associated with perturbations in optimal connectivity within and between brain regions and discuss indirect evidence to suggest that this phenomenon might explain the cognitive deficits experienced during prolonged 3/s spike-wave discharges.

The value of Magnetoencephalography to guide electrode implantation in epilepsy

To investigate if Magnetoencephalography (MEG) can add non-redundant information to guide implantation sites for intracranial recordings (IR). The contribution of MEG to intracranial recording planning was evaluated in 12 consecutive patients assessed pre-surgically with MEG followed by IR. Primary outcome measures were the identification of focal seizure onset in IR and favorable surgical outcome. Outcome measures were compared to those of 12 patients matched for implantation type in whom non-invasive pre-surgical assessment suggested clear hypotheses for implantation (non-MEG group). In the MEG group, non-invasive assessment without MEG was inconclusive, and MEG was then used to further help identify implantation sites. In all MEG patients, at least one virtual MEG electrode generated suitable hypotheses for the location of implantations. No differences in outcome measures were found between non-MEG and MEG groups. Although the MEG group included more complex patients, it showed similar percentage of successful implantations as the non-MEG group. This suggests that MEG can contribute to identify implantation sites where standard methods failed.

Reliability of MEG source imaging of anterior temporal spikes: analysis of an intracranially characterized spike focus

OBJECTIVE

To assess the reliability of MEG source imaging (MSI) of anterior temporal spikes through detailed analysis of the localization and orientation of source solutions obtained for a large number of spikes that were separately confirmed by intracranial EEG to be focally generated within a single, well-characterized spike focus.

METHODS

MSI was performed on 64 identical right anterior temporal spikes from an anterolateral temporal neocortical spike focus. The effects of different volume conductors (sphere and realistic head model), removal of noise with low frequency filters (LFFs) and averaging multiple spikes were assessed in terms of the reliability of the source solutions.

RESULTS

MSI of single spikes resulted in scattered dipole source solutions that showed reasonable reliability for localization at the lobar level, but only for solutions with a goodness-of-fit exceeding 80% using a LFF of 3 Hz. Reliability at a finer level of intralobar localization was limited. Spike averaging significantly improved the reliability of source solutions and averaging 8 or more spikes reduced dependency on goodness-of-fit and data filtering.

CONCLUSIONS

MSI performed on topographically identical individual spikes from an intracranially defined classical anterior temporal lobe spike focus was limited by low reliability (i.e., scattered source solutions) in terms of fine, sublobar localization within the ipsilateral temporal lobe. Spike averaging significantly improved reliability.

SIGNIFICANCE

MSI performed on individual anterior temporal spikes is limited by low reliability. Reduction of background noise through spike averaging significantly improves the reliability of MSI solutions.

Dense array EEG source estimation in neocortical epilepsy

RATIONALE

Dense array EEG (dEEG) evenly covers the whole head surface with over 100 channels contributing to more accurate electrical source imaging due to the higher spatial and temporal resolution. Several studies have shown the clinical utility of dEEG in presurgical clinical evaluation of epilepsy. However validation studies measuring the accuracy of dEEG source imaging are still needed. This can be achieved through simultaneously recording both scalp dEEG with intracranial electrodes (icEEG), which is considered as the true measure of cortical activity at the source. The purpose of this study is to evaluate the accuracy of 256-channel dEEG electrical source estimation for interictal spikes.

METHODS

Four patients with medically refractory neocortical epilepsy, all surgical candidates, underwent subdural electrode implantation to determine ictal onset and define functional areas. One patient showed a lesion on the magnetic resonance imaging in the right parietal lobe. The patient underwent simultaneous recording of interictal spikes by both scalp 256-channelsvdEEG and icEEG. The dEEG was used to non-invasively estimate the source of the interictal spikes detected by the 256-channel dEEG array, which was then compared to the activity measured directly at the source by the icEEG.

RESULTS

From the four patients, a total of 287 interictal spikes were measured with the icEEG. One hundred fifty-five of the 287 spikes (54%) were visually detected by the dEEG upon examination of the 256 channel head surface array. The spike amplitudes detected by the 256-channel dEEG correlated with icEEG spike amplitudes (p < 0.01). All spikes detected in dEEG were localized to the same lobe correctly.

CONCLUSION

Our study demonstrates that 256-channel dEEG can reliably detect interictal spikes and localize them with reasonable accuracy. Two hundred fifty-six-channel dEEG may be clinically useful in the presurgical workup for epilepsy and also reduce the need for invasive EEG evaluation.

MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches

Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm² to 30 cm², whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered.

Integrating dense array EEG in the presurgical evaluation of temporal lobe epilepsy

Purpose. To evaluate the clinical utility of dense array electroencephalography (dEEG) for detecting and localizing interictal spikes in temporal lobe epilepsy. Methods. Simultaneous invasive and noninvasive recordings were performed across two different groups. (1) The first group underwent both noninvasive recording with 128 channels of (scalp) dEEG and invasive sphenoidal electrode recording. (2) The second group underwent both noninvasive recording with 256 channels of (scalp) dEEG and invasive intracranial EEG (icEEG) involving coverage with grids and strips over the lateral and mesial temporal lobe. A noninvasive to noninvasive comparison was made comparing the overall spike detection rate of the dEEG to that of conventional 10/20 EEG. A noninvasive to invasive comparison was made comparing the spike detection rate of dEEG to that of conventional 10/20 EEG plus sphenoidal electrodes. And finally, a noninvasive to invasive evaluation measuring the source localization ability of the dEEG using the icEEG as validation. Results. In the 128-channel dEEG study (1), 90.4% of the interictal spikes detected by the dEEG were not detected in the 10/20 montage. 91% of the dEEG-detected spikes were accurately localized to the medial temporal lobe. In the 256-channel dEEG study (2), 218 of 519 interictal spikes (42%) were detected by dEEG. 85% of these spikes were accurately localized to the medial temporal lobe, close to the position confirmed by subdural electrodes. Conclusion. Dense array EEG may provide more precise information than conventional EEG and has a potential for providing an alternative to sphenoidal electrode monitoring in patients with temporal lobe epilepsy.

Inverse modeling in magnetic source imaging: Comparison of MUSIC, SAM(g2), and sLORETA to interictal intracranial EEG

Magnetoencephalography (MEG) is used in the presurgical work-up of patients with focal epilepsy. In particular, localization of MEG interictal spikes may guide or replace invasive electroencephalography monitoring that is required in difficult cases. From literature, it is not clear which MEG source localization method performs best in this clinical setting. Therefore, we applied three source localization methods to the same data from a large patient group for which a gold standard, interictal spikes as identified in electrocorticography (ECoG), was available. The methods used were multiple signal classification (MUSIC), Synthetic Aperture Magnetometry kurtosis [SAM(g2)], and standardized low-resolution electromagnetic tomography. MEG and ECoG data from 38 patients with refractory focal epilepsy were obtained. Results of the three source localization methods applied to the interictal MEG data were assigned to predefined anatomical regions. Interictal spikes as identified in ECoG were also assigned to these regions. Identified regions by each MEG method were compared to ECoG. Sensitivity and positive predictive value (PPV) of each MEG method were calculated. All three MEG methods showed a similar overall correlate with ECoG spikes, but the methods differ in which regions they detect. The choice of the inverse model thus has an unexpected influence on the results of magnetic source imaging. Combining inverse methods and seeking consensus can be used to improve specificity at the cost of some sensitivity. Combining MUSIC with SAM(g2) gives the best results (sensitivity = 38% and PPV = 82%).

Sensitivity of MEG and EEG to source orientation

An important difference between magnetoencephalography (MEG) and electroencephalography (EEG) is that MEG is insensitive to radially oriented sources. We quantified computationally the dependency of MEG and EEG on the source orientation using a forward model with realistic tissue boundaries. Similar to the simpler case of a spherical head model, in which MEG cannot see radial sources at all, for most cortical locations there was a source orientation to which MEG was insensitive. The median value for the ratio of the signal magnitude for the source orientation of the lowest and the highest sensitivity was 0.06 for MEG and 0.63 for EEG. The difference in the sensitivity to the source orientation is expected to contribute to systematic differences in the signal-to-noise ratio between MEG and EEG.