Ictal and interictal electric source imaging in pre-surgical evaluation: a prospective study

Introducing the Concept of Error Vectors to Improve Source Localization Results of Epileptic Discharges

PURPOSE

To improve EEG source localization results of interictal epileptic discharges (IED) by applying postprocessing step to electrical source imaging (ESI).

METHODS

Localization error of ESI was evaluated in comparison to known sources of stimulation potentials (ESP) by recording simultaneous stereo-EEG/scalp EEG. Error vectors were defined as the offset of the ESI-dipole of ESP to the stereo-EEG contacts used for stimulation. The inverted error vector was applied to the ESI-dipole of IED (IED-dipole).

RESULTS

Seven IED clusters were evaluated. Corrected IED-dipoles were located closer to IED-onset contacts on stereo-EEG than uncorrected IED-dipoles (median [IQR]: 7.8 [2.5] versus 18.7 [10.7] mm, P = 0.02). Anatomically, for high skull conductivities, all corrected IED-dipoles were located in cortical structures or adjacent to epileptogenic lesion, whereas uncorrected IED-dipoles were located in white matter or CSF (P = 0.02). Physiologically, cortical extent of IED generators estimated from corrected IED-dipoles was 16.5 cm2 (IQR = 10.4 cm2) and 7.4 cm2 (range 5.8-9.2 cm2) in the group of anterior temporal IED and prefrontal IED, respectively; the former was concordant with the extent estimated by subdural electrodes. In addition, the relationship of stereo-EEG IED amplitude (a) drop with increasing distance (d) from corrected IED-dipole could be modeled as a negative power equation a(d)∝1/db (R2 = 0.87, P < 0.01), with b ranging from 0.79 to 2.3, median: 1.57, consistent with a simulation model of the sensitivity of intracerebral electrode.

CONCLUSIONS

Application of inverted error vector reduces localization error and shifts IED-dipole to an anatomically and physiologically plausible location.

Ictal electrical source imaging for localizing the epileptogenic zone in drug-resistant epilepsy: A retrospective study

PURPOSE

This study aims to analyze the clinical utility of electrical source imaging (ESI) of ictal rhythms in epilepsy surgery.

METHODS

Medical records of 42 patients who underwent resective epilepsy surgery at Asan Medical Center (2000-2021) were reviewed. All patients underwent long-term video-EEG monitoring. EEG data were analyzed for ictal onset, rhythm patterns, and dominant frequency. Ictal ESI (IC-ESI) findings were compared with 18-fluorodeoxyglucose positron emission tomography (18-FDG-PET), ictal single-photon emission computed tomography (SPECT), and intracranial EEG to assess concordance, with surgical outcomes in Engel classification.

RESULTS

Among 223 analyzed seizures, the overall localization accuracy of IC-ESI was 48.0 % (95 % CI: 41.5-54.5 %). Localization to the deep temporal region showed significantly higher accuracy (64.7 %, 95 % CI: 54.1-74.0 %) and sensitivity (86.4 %, 95 % CI: 75.5-93.0 %) than those outside this region (accuracy: 35.2 %, 95 % CI: 27.4-43.9 %; sensitivity: 17.4 %, 95 % CI: 11.0-26.7 %; p < 0.001 for both). At the patient level, IC-ESI demonstrated a 59.5 % accuracy (95 % CI: 44.5-73.0 %) and 76.7 % sensitivity (95 % CI: 59.1-88.2 %). Accuracy differences between IC-ESI and 18-FDG-PET and ictal SPECT were not significant (p = 0.15). Dye injection within 15.5 s of ictal EEG onset was associated with concordant SPECT and IC-ESI findings (p = 0.03). IC-ESI accuracy was independent of MRI (p = 0.60) or intracranial EEG findings (p = 0.18; 95 % CI: 0.02-1.94).

CONCLUSION

IC-ESI achieves accuracy comparable to that of ictal SPECT and 18-FDG-PET, supporting its reliability for identifying epileptogenic zones, particularly in temporal lobe epilepsy. Despite challenges in detecting ictal rhythms, IC-ESI adds clinical value to presurgical evaluations.

On the concordance between electrical source imaging, anatomical and functional neuroimaging in patients with focal epilepsy

OBJECTIVE

Limited knowledge exists regarding how electrical source imaging (ESI) of interictal epileptiform discharges (IEDs) aligns with findings from other neuroimaging modalities. This study investigates the relationships of interictal ESI with MRI, 18FDG PET, SISCOM, and voxel-based morphometry (VBM) during presurgical evaluation of drug-resistant epilepsy (DRE).

METHODS

A cross-sectional study evaluated the concordance of IED locations from ESI using various inverse solutions (CLARA, LAURA, LORETA, SLORETA, SWLORETA, SSLOFO) with MRI lesions, 18FDG PET, SISCOM, and VBM grey matter abnormalities. The role of ESI in presurgical evaluation of DRE was assessed.

RESULTS

Significant relationships were identified between the localization and distribution of IEDs identified by ESI and the various sets of neuroimages. SLORETA and SWLORETA exhibited the highest concordance and interlobar associations with MRI, 18FDG PET and SISCOM. The main cluster of IEDs proved helpful in locating the epileptogenic zone (EZ).

CONCLUSIONS

The distribution of IEDs identified by the ESI technique exhibited a high degree of significant relationships with other neuroimaging sources. Its use may prove valuable in defining the epileptogenic zone.

SIGNIFICANCE

Combining ESI of IEDs with other neuroimaging techniques may be useful in the presurgical evaluation of DRE.

Increase in EEG functional connectivity and power during wakefulness in self-limited epilepsy with centrotemporal spikes

OBJECTIVE

Examine power and functional connectivity (FC) in children with Self-limited Epilepsy with Centrotemporal Spikes (SeLECTS) during resting-state.

METHODS

We retrospectively analyzed 37 children with SeLECTS and 34 matched controls. Fifty seconds of awake resting-state source-reconstructed EEG per subject were selected to compare groups using power and weighted phase lag index (wPLI). We compared patients' epochs with and without interictal epileptiform discharges (IEDs) between each other and to controls' epochs. Additionally, we compared epochs without IEDs from recent-onset SeLECTS and longer-duration SeLECTS patients between each other and to controls' epochs.

RESULTS

SeLECTS patients demonstrated widespread and significant power increases compared to controls. FC analyses of epochs without IEDs revealed predominantly left-sided increases in the beta band and decreases in theta band compared to controls. In epochs with IEDs, there were further FC increases in the delta band compared to epochs without IEDs located in bilateral fronto-centrotemporal regions. Patients with recent-onset SeLECTS had significant bilateral temporo-parietal FC increases in beta1 relative to controls. Patients with longer-duration SeLECTS showed significant left centrotemporal FC increases in beta and bilateral centrotemporal decreases in delta compared to controls.

CONCLUSIONS

SeLECTS patients exhibit atypical power and FC patterns during wakefulness, even in epochs without IEDs. These were more pronounced in recent-onset cases and epochs with IEDs, suggesting an association between IEDs frequency and the disease course.

SIGNIFICANCE

Studying power and FC abnormalities in children with SeLECTS provides insight into disease evolution and the influence of IEDs on brain networks.

Detectability in Scalp EEGs of Epileptic Spikes Emitted from Brain Electrical Sources of Different Sizes and Locations: A Simulation Study Using Realistic Head Models of Elderly Adults

Background. Epilepsy is prevalent in the elderly, whose brain morphologies and skull electrical characteristics differ from those of younger adults. Here, using a multivariate definition of signal-to-noise ratio (SNR), we explored the detectability of epileptic spikes in scalp EEG measurements in elderly by forward simulations of hypersynchronous spikes generated at 78 cortical regions of interest (ROIs) in the presence of background noise. Methods. Simulated electric potentials were measured at 18, 35, and 70 standard 10-20 electrode positions using three reference methods: infinity reference (INF), common average reference (CAR), and average mastoid reference (M1M2). MRIs of six elderly subjects were used to construct finite element method (FEM) models with age-adjusted skull conductivities. Results. SNRs of epileptic spikes increased with increasing sizes of the brain electrical source areas, although medial and deep brain regions such as the hippocampus showed lower SNRs, consistent with clinical findings. The SNRs were greater in the 70-channel dataset than in the 18-channel and 35-channel datasets, especially for ROIs located closer to the head surface. In addition, the SNRs were lower for the CAR and M1M2 references than for the ideal INF reference. Moreover, we found comparable results in the standard FEM heads with age-adjusted skull conductivities. Conclusions. The results provide insights for evaluating scalp EEG data in elderly patients with suspected epilepsy, and suggest that age-adjusted skull conductivity is an important factor for forward models in elderly adults, and that the standard FEM head with age-adjusted skull conductivity can be used when MRIs are not available.

Accuracy of SEEG Source Localization: A Pilot Study Using Corticocortical Evoked Potentials

INTRODUCTION

EEG source localization is an established technique for localizing scalp EEG in medically refractory epilepsy but has not been adequately studied with intracranial EEG (iEEG). Differences in sensor location and spatial sampling may affect the accuracy of EEG source localization with iEEG. Corticocortical evoked potentials can be used to evaluate EEG source localization algorithms for iEEG given the known source location.

METHODS

We recorded 205 sets of corticocortical evoked potentials using low-frequency single-pulse electrical stimulation in four patients with iEEG. Averaged corticocortical evoked potentials were analyzed using 11 distributed source algorithms and compared using the Wilcoxon signed-rank test ( P < 0.05). We measured the localization error from stimulated electrodes and the spatial dispersion of each solution.

RESULTS

Minimum norm, standard low-resolution electromagnetic tomography (sLORETA), LP Norm, sLORETA-weighted accurate minimum norm (SWARM), exact LORETA (eLORETA), standardized weighted LORETA (swLORETA), and standardized shrinking LORETA-FOCUSS (ssLOFO) had the least localization error (13.3-15.7 mm) and were superior to focal underdetermined system solver (FOCUSS), logistic autoregressive average (LAURA, and LORETA, 17.9-21.7, P < 0.001). The FOCUSS solution had the smallest spatial dispersion (7.4 mm), followed by minimum norm, L1 norm, LP norm, and SWARM (20.8-28.3 mm). Gray matter stimulations had less localization error than white matter (median differences 3.1-6.1 mm) across all algorithms except SWARM, LORETA, and logistic autoregressive average. A multivariate linear regression showed that distance from the source to sensors and gray/white matter stimulation had a significant effect on localization error for some algorithms but not SWARM, minimum norm, focal underdetermined system solver, logistic autoregressive average, and LORETA.

CONCLUSIONS

Our study demonstrated that minimum norm, L1 norm, LP norm, and SWARM localize iEEG corticocortical evoked potentials well with lower localization error and spatial dispersion. Larger studies are needed to confirm these findings.

Seizure Sources Can Be Imaged from Scalp EEG by Means of Biophysically Constrained Deep Neural Networks

Seizure localization is important for managing drug-resistant focal epilepsy. Here, the capability of a novel deep learning-based source imaging framework (DeepSIF) for imaging seizure activities from electroencephalogram (EEG) recordings in drug-resistant focal epilepsy patients is investigated. The neural mass model of ictal oscillations is adopted to generate synthetic training data with spatio-temporal-spectra features similar to ictal dynamics. The trained DeepSIF model is rigorously validated using computer simulations and in a cohort of 33 drug-resistant focal epilepsy patients with high-density (76-channel) EEG seizure recordings, by comparing DeepSIF estimates with surgical resection outcome and seizure onset zone (SOZ). These findings show that the trained DeepSIF model outperforms other methods in estimating the spatial and temporal information of origins of ictal activities. It achieves a high spatial specificity of 96% and a low spatial dispersion of 3.80 ± 5.74 mm when compared to the resection region. The source imaging results also demonstrate good coverage of SOZ, with an average distance of 10.89 ± 10.14 mm (from the SOZ to the reconstruction). These promising results suggest that DeepSIF has significant potential for advancing noninvasive imaging of the origins of ictal activities in patients with focal epilepsy, aiding management of intractable epilepsy.

Deep source transfer learning for the estimation of internal brain dynamics using scalp EEG

Electroencephalography (EEG) provides high temporal resolution neural data for brain-computer interfacing via noninvasive electrophysiological recording. Estimating the internal brain activity by means of source imaging techniques can further improve the spatial resolution of EEG and enhance the reliability of neural decoding and brain-computer interaction. In this work, we propose a novel EEG data-driven source imaging scheme for precise and efficient estimation of macroscale spatiotemporal brain dynamics across thalamus and cortical regions with deep learning methods. A deep source imaging framework with a convolutional-recurrent neural network is designed to estimate the internal brain dynamics from high-density EEG recordings. Moreover, a brain model including 210 cortical regions and 16 thalamic nuclei is established based on human brain connectome to provide synthetic training data, which manifests intrinsic characteristics of underlying brain dynamics in spontaneous, stimulation-evoked, and pathological states. Transfer learning algorithm is further applied to the trained network to reduce the dynamical differences between synthetic and realistic EEG. Extensive experiments exhibit that the proposed deep-learning method can accurately estimate the spatial and temporal activity of brain sources and achieves superior performance compared to the state-of-the-art approaches. Moreover, the EEG data-driven source imaging framework is effective in the location of seizure onset zone in epilepsy and reconstruction of dynamical thalamocortical interactions during sensory processing of acupuncture stimulation, implying its applicability in brain-computer interfacing for neuroscience research and clinical applications.

Ictal EEG Source Imaging With Supplemental Electrodes

INTRODUCTION

Noninvasive brain imaging tests play a major role in guiding decision-making and the usage of invasive, costly intracranial electroencephalogram (ICEEG) in the presurgical epilepsy evaluation. This study prospectively examined the concordance in localization between ictal EEG source imaging (ESI) and ICEEG as a reference standard.

METHODS

Between August 2014 and April 2019, patients during video monitoring with scalp EEG were screened for those with intractable focal epilepsy believed to be amenable to surgical treatment. Additional 10-10 electrodes (total = 31-38 per patient, "31+") were placed over suspected regions of seizure onset in 104 patients. Of 42 patients requiring ICEEG, 30 (mean age 30, range 19-59) had sufficiently localized subsequent intracranial studies to allow comparison of localization between tests. ESI was performed using realistic forward boundary element models used in dipole and distributed source analyses.

RESULTS

At least partial sublobar concordance between ESI and ICEEG solutions was obtained in 97% of cases, with 73% achieving complete agreement. Median Euclidean distances between ESI and ICEEG solutions ranged from 25 to 30 mm (dipole) and 23 to 38 mm (distributed source). The latter was significantly more accurate with 31+ compared with 21 electrodes ( P < 0.01). A difference of ≤25 mm was present in two thirds of the cases. No significant difference was found between dipole and distributed source analyses.

CONCLUSIONS

A practical method of ictal ESI (nonuniform placement of 31-38 electrodes) yields high accuracy for seizure localization in epilepsy surgery candidates. These results support routine clinical application of ESI in the presurgical evaluation.

EEG Source Localization in Temporal Encephaloceles: Concordance With Surgical Resection and Clinical Outcomes

PURPOSE

Temporal encephaloceles are a cause of drug-resistant temporal lobe epilepsy; however, their relationship with epileptogenesis is unclear, and optimal surgical resection is uncertain. EEG source localization (ESL) may guide surgical decision-making.

METHODS

We reviewed patients at Mayo Clinic Rochester with drug-resistant temporal lobe epilepsy and temporal encephaloceles, who underwent limited resection and had 1-year outcomes. EEG source localization was performed using standard density scalp EEG of ictal and interictal activity. Distance from dipole and standardized low-resolution brain electromagnetic tomography (sLORETA) solutions to the encephalocele were measured. Concordance of ESL with encephalocele and surgical resection was compared with 1-year surgical outcomes.

RESULTS

Seventeen patients met criteria. The mean distances from ESL results to encephalocele center for dipole and sLORETA analyses were 23 mm (SD 9) and 22 mm (SD 11), respectively. Ten patients (55.6%) had Engel I outcomes at 1 year. Dipole-encephalocele distance and sLORETA-encephalocele distance were significantly longer in patients with Engel I outcome and patients whose encephalocele was contained by sLORETA had worse outcome as well; however, multiple logistic regression analysis found that only containment of encephalocele by the sLORETA current density was significant ( P < 0.05), odds ratio 0.12 (95% confidence interval [0.021, 0.71]).

CONCLUSIONS

EEG source localization of scalp EEG localizes near encephaloceles, however, typically not in the encephalocele itself; this may be due to scalp EEG sampling propagated activity or alternatively that the seizure onset zone extends beyond the herniated cortex. Surprisingly, we observed increased ESL to encephalocele distances in patients with excellent surgical outcomes. Larger cohort studies including intracranial EEG data are needed to further explore this finding.

Semiautomated electric source imaging determines epileptogenicity of encephaloceles in temporal lobe epilepsy

OBJECTIVE

We aimed to assess the ability of semiautomated electric source imaging (ESI) from long-term video-electroencephalographic (EEG) monitoring (LTM) to determine the epileptogenicity of temporopolar encephaloceles (TEs) in patients with temporal lobe epilepsy.

METHODS

We conducted a retrospective study involving 32 temporal lobe epilepsy patients with TEs as potentially epileptogenic lesions in structural magnetic resonance imaging scans. Findings were validated through invasive intracerebral stereo-EEG in six of 32 patients and postsurgical outcome after tailored resection of the TE in 17 of 32 patients. LTM (mean duration = 6 days) was performed using the 10/20 system with additional T1/T2 for all patients and sphenoidal electrodes in 23 of 32 patients. Semiautomated detection and clustering of interictal epileptiform discharges (IEDs) were carried out to create IED types. ESI was performed on the averages of the two most frequent IED types per patient, utilizing individual head models, and two independent inverse methods (sLORETA [standardized low-resolution brain electromagnetic tomography], MUSIC [multiple signal classification]). ESI maxima concordance and propagation in spatial relation to TEs were quantified for sources with good signal quality (signal-to-noise ratio > 2, explained signal > 60%).

RESULTS

ESI maxima correctly colocalized with a TE in 20 of 32 patients (62.5%) either at the onset or half-rising flank of at least one IED type per patient. ESI maxima showed propagation from the temporal pole to other temporal or extratemporal regions in 14 of 32 patients (44%), confirming propagation originating in the area of the TE. The findings from both inverse methods validated each other in 14 of 20 patients (70%), and sphenoidal electrodes exhibited the highest signal amplitudes in 17 of 23 patients (74%). The concordance of ESI with the TE predicted a seizure-free postsurgical outcome (Engel I vs. >I) with a diagnostic odds ratio of 2.1.

SIGNIFICANCE

Semiautomated ESI from LTM often successfully identifies the epileptogenicity of TEs and the IED onset zone within the area of the TEs. Additionally, it shows potential predictive power for postsurgical outcomes in these patients.

Ictal EEG Source Imaging

SUMMARY

Ictal EEG source imaging (ESI) is an advancing and growing application for presurgical epilepsy evaluation. For far too long, localization of seizures with scalp EEG has continued to rely on visual inspection of tracings arranged in a variety of montages allowing, at best, rough estimates of seizure onset regions. This most critical step is arguably the weakest point in epilepsy localization for surgical decision-making in clinical practice today. This review covers the methods and strategies that have been developed and tested for the performance of ictal ESI. It highlights practical issues and solutions toward sound implementation while covering differing methods to tackle the challenges specific to ictal ESI-noise and artifact reduction, component analysis, and other tools to increase seizure-specific signal for analysis. Further, validation studies to date-those with both high and low density numbers of electrodes-are summarized, providing a glimpse at the relative accuracy of ictal ESI in all types of focal epilepsy patients. Finally, given the added noninvasive information (greater degree of spatial resolution compared with standard ictal EEG review), the role of ictal ESI and its clinical utility in the presurgical evaluation is discussed.

Setting up EEG Source Imaging in Practice

SUMMARY

Adding EEG source imaging to a clinical practice has clear advantages over visual inspection of EEG. This article offers insight on incorporating EEG source imaging into an EEG laboratory and the best practices for producing optimal source analysis results.

Technical Considerations in EEG Source Imaging

SUMMARY

EEG source imaging is an established technique for identifying the origin of interictal and ictal epileptiform discharges in patients with epilepsy, and it is an important tool in neurophysiology research. Accurate and reliable EEG source imaging requires appropriate choices of how the head, skull, and scalp are modeled, and understanding of the different approaches to modeling is important to guide these choices. Similarly, numerous different approaches to modeling the electrical sources within the brain exist, and appropriate understanding of the strengths and limitations of each are essential to obtaining accurate, reliable, and interpretable solutions. This review aims to describe the essential theoretical basis for these head and source models while also discussing the practical implications of each in clinical or research applications.

EEG Source Imaging in Presurgical Evaluations

SUMMARY

Presurgical evaluations to plan intracranial EEG implantations or surgical therapies at most epilepsy centers in the United States currently depend on the visual inspection of EEG traces. Such analysis is inadequate and does not exploit all the localizing information contained in scalp EEG. Various types of EEG source modeling or imaging can provide sublobar localization of spike and seizure sources in the brain, and the software to do this with typical long-term monitoring EEG data are available to all epilepsy centers. This article reviews the fundamentals of EEG voltage fields that are used in EEG source imaging, the strengths and weakness of dipole and current density source models, the clinical situations where EEG source imaging is most useful, and the particular strengths of EEG source imaging for various cortical areas where spike/seizure sources are likely.

Targeted density electrode placement achieves high concordance with traditional high-density EEG for electrical source imaging in epilepsy

OBJECTIVE

High-density (HD) electroencephalography (EEG) is increasingly used in presurgical epilepsy evaluation, but it is demanding in time and resources. To overcome these issues, we compared EEG source imaging (ESI) solutions with a targeted density and HD-EEG montage.

METHODS

HD-EEGs from patients undergoing presurgical evaluation were analyzed. A low-density recording was created by selecting the 25 electrodes of a standard montage from the 83 electrodes of the HD-EEG and adding 8-11 electrodes around the electrode with the highest amplitude interictal epileptiform discharges. The ESI solution from this "targeted" montage was compared to that from the HD-EEG using the distance between peak vertices, sublobar concordance and a qualitative similarity measure.

RESULTS

Fifty-eight foci of forty-three patients were included. The median distance between the peak vertices of the two montages was 13.2 mm, irrespective of focus' location. Tangential generators (n = 5/58) showed a higher distance than radial generators (p = 0.04). We found sublobar concordance in 54/58 of the foci (93%). Map similarity, assessed by an epileptologist, had a median score of 4/5.

CONCLUSIONS

ESI solutions obtained from a targeted density montage show high concordance with those calculated from HD-EEG.

SIGNIFICANCE

Requiring significantly fewer electrodes, targeted density EEG allows obtaining similar ESI solutions as traditional HD-EEG montage.

Spatiotemporal Rhythmic Seizure Sources Can be Imaged by means of Biophysically Constrained Deep Neural Networks

Noninvasive dynamic brain imaging of neural oscillations provides valuable insights into both physiological and pathological brain states. Yet, challenges remain due to the ill-posed nature of the problem and high complexity of the solution space, which can be alleviated by advanced computational models. Here, we investigated the capability of a novel deep learning-based source imaging framework (DeepSIF) for imaging ictal activities from high-density electroencephalogram (EEG) recordings in drug-resistant focal epilepsy patients. The neural mass model of ictal oscillations was adopted to generate synthetic training data with spatio-temporal-spectra features similar to ictal dynamics. We rigorously validated the trained DeepSIF model using computer simulations and in a cohort of 33 drug-resistant focal epilepsy patients. The DeepSIF ictal source imaging was compared with interictal source imaging and three conventional imaging methods as benchmark comparisons. Our findings show that the trained DeepSIF model outperforms other methods in estimating the spatial and temporal information of ictal sources. It achieves a high spatial specificity of 96% and a low spatial dispersion of 3.80 ± 5.74 mm when compared to the resection region. The noninvasive source imaging results also demonstrate good coverage of seizure-onset-zone (SOZ), with an average distance of 10.89 ± 10.14 mm (from the SOZ to the reconstruction). These promising results suggest that DeepSIF has significant potential for advancing noninvasive imaging of ictal activities in patients with focal epilepsy. By providing valuable insights into the spatiotemporal dynamics of seizure activity, DeepSIF promises to help guide clinical decisions and improve treatment outcomes for epilepsy patients.

Deep-learning predicted PET can be subtracted from the true clinical fluorodeoxyglucose PET co-registered to MRI to identify the epileptogenic zone in focal epilepsy

OBJECTIVE

Normal interictal [18 F]FDG-PET can be predicted from the corresponding T1w MRI with Generative Adversarial Networks (GANs). A technique we call SIPCOM (Subtraction Interictal PET Co-registered to MRI) can then be used to compare epilepsy patients' predicted and clinical PET. We assessed the ability of SIPCOM to identify the Resection Zone (RZ) in patients with drug-resistant epilepsy (DRE) with reference to visual and statistical parametric mapping (SPM) analysis.

METHODS

Patients with complete presurgical work-up and subsequent SEEG and cortectomy were included. RZ localisation, the reference region, was assigned to one of eighteen anatomical brain regions. SIPCOM was implemented using healthy controls to train a GAN. To compare, the clinical PET coregistered to MRI was visually assessed by two trained readers, and a standard SPM analysis was performed.

RESULTS

Twenty patients aged 17-50 (32 ± 7.8) years were included, 14 (70%) with temporal lobe epilepsy (TLE). Eight (40%) were MRI-negative. After surgery, 14 patients (70%) had a good outcome (Engel I-II). RZ localisation rate was 60% with SIPCOM vs 35% using SPM (P = 0.015) and vs 85% using visual analysis (P = 0.54). Results were similar for Engel I-II patients, the RZ localisation rate was 64% with SIPCOM vs 36% with SPM. With SIPCOM localisation was correct in 67% in MRI-positive vs 50% in MRI-negative patients, and 64% in TLE vs 43% in extra-TLE. The average number of false-positive clusters was 2.2 ± 1.3 using SIPCOM vs 2.3 ± 3.1 using SPM. All RZs localized with SPM were correctly localized with SIPCOM. In one case, PET and MRI were visually reported as negative, but both SIPCOM and SPM localized the RZ.

SIGNIFICANCE

SIPCOM performed better than the reference computer-assisted method (SPM) for RZ detection in a group of operated DRE patients. SIPCOM's impact on epilepsy management needs to be prospectively validated.

Electromagnetic source imaging predicts surgical outcome in children with focal cortical dysplasia

OBJECTIVE

To evaluate the diagnostic accuracy of electromagnetic source imaging (EMSI) in localizing spikes and predict surgical outcome in children with drug resistant epilepsy (DRE) due to focal cortical dysplasia (FCD).

METHODS

We retrospectively analyzed magnetoencephalography (MEG) and high-density (HD-EEG) data from 23 children with FCD-associated DRE who underwent intracranial EEG and surgery. We localized spikes using equivalent current dipole (ECD) fitting, dipole clustering, and dynamical statistical parametric mapping (dSPM) on EMSI, electric source imaging (ESI), and magnetic source imaging (MSI). We calculated the distance from the seizure onset zone (DSOZ) and resection (DRES). We estimated receiver operating characteristic (ROC) curves with Youden's index (J) to predict outcome.

RESULTS

EMSI presented shorter DSOZ (15.18 ± 9.06 mm) and DRES (8.56 ± 6.24 mm) compared to ESI (DSOZ: 25.04 ± 16.20 mm, p < 0.009; DRES: 18.88 ± 17.30 mm, p < 0.03) and MSI (DSOZ: 23.37 ± 8.98 mm, p < 0.03; DRES: 15.51 ± 10.11 mm, p < 0.02) for clustering in patients with good outcome. Clustering showed shorter DSOZ and DRES compared to ECD fitting and dSPM (p < 0.05). EMSI had higher performance as outcome predictor (J = 70.63%) compared to ESI (J = 41.27%) and MSI (J = 33.33%) for clustering.

CONCLUSIONS

EMSI provides superior localization and improved predictive performance than individual modalities.

SIGNIFICANCE

EMSI can help the surgical planning and facilitate the localization of epileptogenic foci.

Source localization using recursively applied and projected MUSIC with flexible extent estimation

Magneto- and electroencephalography (M/EEG) are widespread techniques to measure neural activity in-vivo at a high temporal resolution but low spatial resolution. Locating the neural sources underlying the M/EEG poses an inverse problem, which is ill-posed. We developed a new method based on Recursive Application of Multiple Signal Classification (MUSIC). Our proposed method is able to recover not only the locations but, in contrast to other inverse solutions, also the extent of active brain regions flexibly (FLEX-MUSIC). This is achieved by allowing it to search not only for single dipoles but also dipole clusters of increasing extent to find the best fit during each recursion. FLEX-MUSIC achieved the highest accuracy for both single dipole and extended sources compared to all other methods tested. Remarkably, FLEX-MUSIC was capable to accurately estimate the level of sparsity in the source space (r = 0.82), whereas all other approaches tested failed to do so (r ≤ 0.18). The average computation time of FLEX-MUSIC was considerably lower compared to a popular Bayesian approach and comparable to that of another recursive MUSIC approach and eLORETA. FLEX-MUSIC produces only few errors and was capable to reliably estimate the extent of sources. The accuracy and low computation time of FLEX-MUSIC renders it an improved technique to solve M/EEG inverse problems both in neuroscience research and potentially in pre-surgery diagnostic in epilepsy.

Clinical added value of interictal automated electrical source imaging in the presurgical evaluation of MRI-negative epilepsy: A real-life experience in 29 consecutive patients

OBJECTIVE

During the presurgical evaluation, manual electrical source imaging (ESI) provides clinically useful information in one-third of the patients but it is time-consuming and requires specific expertise. This prospective study aims to assess the clinical added value of a fully automated ESI analysis in a cohort of patients with MRI-negative epilepsy and describe its diagnostic performance, by evaluating sublobar concordance with stereo-electroencephalography (SEEG) results and surgical resection and outcome.

METHODS

All consecutive patients referred to the Center for Refractory Epilepsy (CRE) of St-Luc University Hospital (Brussels, Belgium) for presurgical evaluation between 15/01/2019 and 31/12/2020 meeting the inclusion criteria, were recruited to the study. Interictal ESI was realized on low-density long-term EEG monitoring (LD-ESI) and, whenever available, high-density EEG (HD-ESI), using a fully automated analysis (Epilog PreOp, Epilog NV, Ghent, Belgium). The multidisciplinary team (MDT) was asked to formulate hypotheses about the epileptogenic zone (EZ) location at sublobar level and make a decision on further management for each patient at two distinct moments: i) blinded to ESI and ii) after the presentation and clinical interpretation of ESI. Results leading to a change in clinical management were considered contributive. Patients were followed up to assess whether these changes lead to concordant results on stereo-EEG (SEEG) or successful epilepsy surgery.

RESULTS

Data from all included 29 patients were analyzed. ESI led to a change in the management plan in 12/29 patients (41%). In 9/12 (75%), modifications were related to a change in the plan of the invasive recording. In 8/9 patients, invasive recording was performed. In 6/8 (75%), the intracranial EEG recording confirmed the localization of the ESI at a sublobar level. So far, 5/12 patients, for whom the management plan was changed after ESI, were operated on and have at least one-year postoperative follow-up. In all cases, the EZ identified by ESI was included in the resection zone. Among these patients, 4/5 (80%) are seizure-free (ILAE 1) and one patient experienced a seizure reduction of more than 50% (ILAE 4).

CONCLUSIONS

In this single-center prospective study, we demonstrated the added value of automated ESI in the presurgical evaluation of MRI-negative cases, especially in helping to plan the implantation of depth electrodes for SEEG, provided that ESI results are integrated into the whole multimodal evaluation and clinically interpreted.

Accuracy of predicting surgical outcomes using interictal electrical source imaging in patients with MRI-negative intractable epilepsy

OBJECTIVE

We investigated the accuracy of interictal electrical source imaging (II-ESI) in localizing the epileptogenic zone in MRI-negative epilepsy patients who underwent epilepsy surgery. We also aimed to compare II-ESI's utility with other presurgical investigations and its role in guiding intracranial electroencephalography (iEEG) planning.

METHODS

We retrospectively reviewed the medical records of patients with operated MRI-negative intractable epilepsy at our center between 2010 and 2016. All patients underwent video electroencephalography (EEG) monitoring, high-resolution MRI, ¹⁸ fluorodeoxyglucose positron emission tomography (FDG-PET) scans, ictal single-photon emission computed tomography (SPECT) and intracranial EEG (iEEG) monitoring. We computed II-ESI following the visual identification of interictal spikes, and outcomes were determined using Engel's classification at 6 months after surgery.

RESULTS

Among 21 operated MRI-negative intractable epilepsy patients, 15 had sufficient data for II-ESI analysis. Of these, nine patients (60%) showed favorable outcomes corresponding to Engle's classification I and II. The localization accuracy of II-ESI was 53%, which was not significantly different from those of FDG-PET and ictal SPECT (47% and 45%, respectively). Among the patients, iEEG did not cover the areas suggested by II-ESIs in seven cases (47%). In two of those patients (29%), the regions indicated by II-ESIs were not resected, resulting in poor surgical outcomes.

CONCLUSION

This study demonstrates that the localization accuracy of II-ESI was comparable to ictal SPECT and the brain FDG-PET scan. II-ESI is a simple, noninvasive method for evaluating the epileptogenic zone and guiding iEEG planning in patients with MRI-negative epilepsy.

EEG Beta functional connectivity decrease in the left amygdala correlates with the affective pain in fibromyalgia: A pilot study

Fibromyalgia (FM) is a major chronic pain disease with prominent affective disturbances, and pain-associated changes in neurotransmitters activity and in brain connectivity. However, correlates of affective pain dimension lack. The primary goal of this correlational cross-sectional case-control pilot study was to find electrophysiological correlates of the affective pain component in FM. We examined the resting-state EEG spectral power and imaginary coherence in the beta (β) band (supposedly indexing the GABAergic neurotransmission) in 16 female patients with FM and 11 age-adjusted female controls. FM patients displayed lower functional connectivity in the High β (Hβ, 20-30 Hz) sub-band than controls (p = 0.039) in the left basolateral complex of the amygdala (p = 0.039) within the left mesiotemporal area, in particular, in correlation with a higher affective pain component level (r = 0.50, p = 0.049). Patients showed higher Low β (Lβ, 13-20 Hz) relative power than controls in the left prefrontal cortex (p = 0.001), correlated with ongoing pain intensity (r = 0.54, p = 0.032). For the first time, GABA-related connectivity changes correlated with the affective pain component are shown in the amygdala, a region highly involved in the affective regulation of pain. The β power increase in the prefrontal cortex could be compensatory to pain-related GABAergic dysfunction.

Semiautomatic interictal electric source localization based on long-term electroencephalographic monitoring: A prospective study

OBJECTIVE

Electric source imaging (ESI) of interictal epileptiform discharges (IEDs) has shown significant yield in numerous studies; however, its implementation at most centers is labor- and cost-intensive. Semiautomatic ESI analysis (SAEA) has been proposed as an alternative and has previously shown benefit. Computer-assisted automatic spike cluster retrieval, averaging, and source localization are carried out for each cluster and are then reviewed by an expert neurophysiologist, to determine their relevance for the individual case. Here, we examine its yield in a prospective single center study.

METHOD

Between 2017 and 2022, 122 patients underwent SAEA. Inclusion criteria for the current study were unifocal epilepsy disorder, epilepsy surgery with curative purpose, and postoperative follow-up of 2 years or more. All patients (N=40) had continuous video-electroencephalographic (EEG) monitoring with 37 scalp electrodes, which underwent SAEA. Forty patients matched our inclusion criteria.

RESULTS

Twenty patients required intracranial monitoring; 13 were magnetic resonance imaging (MRI)-negative. Mean duration of analyzed EEG was 4.3 days (±3.1 days), containing a mean of 12 749 detected IEDs (±22 324). The sensitivity, specificity, and accuracy of SAEA for localizing the epileptogenic focus of the entire group were 74.3%, 80%, and 75%, respectively, leading to an odds ratio (OR) of 11.5 to become seizure-free if the source was included in the resection volume (p < .05). In patients with extratemporal lobe epilepsy, our results indicated an accuracy of 68% (OR=11.7). For MRI-negative patients (n = 13) and patients requiring intracranial EEG (n = 20), we found a similarly high accuracy of 84.6% (OR=19) and 75% (OR = 15.9), respectively.

SIGNIFICANCE

In this prospective study of SAEA of long-term video-EEG, spanning several days, we found excellent localizing information and a high yield, even in difficult patient groups. This compares favorably to high-density ESI, most likely due to marked improved signal-to-noise ratio of the averaged IEDs. We propose including ESI, or SAEA, in the workup of all patients who are referred for epilepsy surgery.

Decision-making in stereotactic epilepsy surgery

Surgery can cure or significantly improve both the frequency and the intensity of seizures in patients with medication-refractory epilepsy. The set of diagnostic and therapeutic interventions involved in the path from initial consultation to definitive surgery is complex and includes a multidisciplinary team of neurologists, neurosurgeons, neuroradiologists, and neuropsychologists, supported by a very large epilepsy-dedicated clinical architecture. In recent years, new practices and technologies have emerged that dramatically expand the scope of interventions performed. Stereoelectroencephalography has become widely adopted for seizure localization; stereotactic laser ablation has enabled more focal, less invasive, and less destructive interventions; and new brain stimulation devices have unlocked treatment of eloquent foci and multifocal onset etiologies. This article articulates and illustrates the full framework for how epilepsy patients are considered for surgical intervention, with particular attention given to stereotactic approaches.

Electric Source Imaging in Presurgical Evaluation of Epilepsy: An Inter-Analyser Agreement Study

Electric source imaging (ESI) estimates the cortical generator of the electroencephalography (EEG) signals recorded with scalp electrodes. ESI has gained increasing interest for the presurgical evaluation of patients with drug-resistant focal epilepsy. In spite of a standardised analysis pipeline, several aspects tailored to the individual patient involve subjective decisions of the expert performing the analysis, such as the selection of the analysed signals (interictal epileptiform discharges and seizures, identification of the onset epoch and time-point of the analysis). Our goal was to investigate the inter-analyser agreement of ESI in presurgical evaluations of epilepsy, using the same software and analysis pipeline. Six experts, of whom five had no previous experience in ESI, independently performed interictal and ictal ESI of 25 consecutive patients (17 temporal, 8 extratemporal) who underwent presurgical evaluation. The overall agreement among experts for the ESI methods was substantial (AC1 = 0.65; 95% CI: 0.59–0.71), and there was no significant difference between the methods. Our results suggest that using a standardised analysis pipeline, newly trained experts reach similar ESI solutions, calling for more standardisation in this emerging clinical application in neuroimaging.

Expedited epilepsy surgery prior to drug resistance in children: a frontier worth crossing?

Epilepsy surgery is an established safe and effective treatment for selected candidates with drug-resistant epilepsy. In this opinion piece, we outline the clinical and experimental evidence for selectively considering epilepsy surgery prior to drug resistance. Our rationale for expedited surgery is based on the observations that, 1) a high proportion of patients with lesional epilepsies (e.g. focal cortical dysplasia, epilepsy associated tumours) will progress to drug-resistance, 2) surgical treatment of these lesions, especially in non-eloquent areas of brain, is safe, and 3) earlier surgery may be associated with better seizure outcomes. Potential benefits beyond seizure reduction or elimination include less exposure to anti-seizure medications (ASM), which may lead to improved developmental trajectories in children and optimize long-term neurocognitive outcomes and quality of life. Further, there exists emerging experimental evidence that brain network dysfunction exists at the onset of epilepsy, where continuing dysfunctional activity could exacerbate network perturbations. This in turn could lead to expanded seizure foci and contribution to the comorbidities associated with epilepsy. Taken together, we rationalize that epilepsy surgery, in carefully selected cases, may be considered prior to drug resistance. Lastly, we outline the path forward, including the challenges associated with developing the evidence base and implementing this paradigm into clinical care.

Virtual implantation using conventional scalp EEG delineates seizure onset and predicts surgical outcome in children with epilepsy

OBJECTIVE

Delineation of the seizure onset zone (SOZ) is required in children with drug resistant epilepsy (DRE) undergoing neurosurgery. Intracranial EEG (icEEG) serves as gold standard but has limitations. Here, we examine the utility of virtual implantation with electrical source imaging (ESI) on ictal scalp EEG for mapping the SOZ and predict surgical outcome.

METHODS

We retrospectively analyzed EEG data from 35 children with DRE who underwent surgery and dichotomized into seizure-free (SF) and non-seizure-free (NSF). We estimated virtual sensors (VSs) at brain locations that matched icEEG implantation and compared ictal patterns at VSs vs icEEG. We calculated the agreement between VSs SOZ and clinically defined SOZ and built receiver operating characteristic (ROC) curves to test whether it predicted outcome.

RESULTS

Twenty-one patients were SF after surgery. Moderate agreement between virtual and icEEG patterns was observed (kappa = 0.45, p < 0.001). Virtual SOZ agreement with clinically defined SOZ was higher in SF vs NSF patients (66.6% vs 41.6%, p = 0.01). Anatomical concordance of virtual SOZ with clinically defined SOZ predicted outcome (AUC = 0.73; 95% CI: 0.57-0.89; sensitivity = 66.7%; specificity = 78.6%; accuracy = 71.4%).

CONCLUSIONS

Virtual implantation on ictal scalp EEG can approximate the SOZ and predict outcome.

SIGNIFICANCE

SOZ mapping with VSs may contribute to tailoring icEEG implantation and predict outcome.

Detection of interictal epileptiform discharges in an extended scalp EEG array and high-density EEG - A prospective multicenter study

OBJECTIVES

High counts of averaged interictal epileptiform discharges (IEDs) are key components of accurate interictal electric source imaging (ESI) in patients with focal epilepsy. Automated detections may be time-efficient, but they need to identify the correct IED types. Thus, we compared semiautomated and automated detection of IED types in long-term video EEG monitoring (LTM) using an extended scalp EEG array and short-term high-density EEG (hdEEG) with visual detection of IED types and the seizure onset zone (SOZ).

METHODS

We prospectively recruited consecutive patients from four epilepsy centers who underwent both LTM with 40 electrodes scalp EEG and short-term hdEEG with 256 electrodes. Only patients with a single circumscribed SOZ in LTM were included. In LTM and hdEEG, IED types were identified visually, semiautomatically and automatically. Concordances of semiautomated and automated detections in LTM and hdEEG as well as visual detections in hdEEG were compared against visually detected IED types and the SOZ in LTM.

RESULTS

Fifty-two out of 62 patients with LTM and hdEEG were included. The most frequent IED types per patient, detected semiautomatically and automatically in LTM and visually in hdEEG, were significantly concordant with the most frequently visually identified IED type in LTM and the SOZ. Semiautomated and automated detections of IED types in hdEEG were significantly concordant with visually identified IED types in LTM only when IED types with more than 50 detected single IEDs were selected. The threshold of 50 detected IED in hdEEG was reached in half of the patients. For all IED types per patient, agreement between visual and semiautomated detections in LTM was high.

SIGNIFICANCE

Semiautomated and automated detections of IED types in LTM show significant agreement with visually detected IED types and the SOZ. In short-term hdEEG, semiautomated detections of IED types are concordant with visually detected IED types and the SOZ in LTM if high IED counts were detected.

EEG source imaging concordance with intracranial EEG and epileptologist review in focal epilepsy

EEG source imaging is becoming widely used for the evaluation of medically refractory focal epilepsy. The validity of EEG source imaging has been established in several studies comparing source imaging to the surgical resection cavity and subsequent seizure freedom. We present a cohort of 87 patients and compare EEG source imaging of both ictal and interictal scalp EEG to the seizure onset zone on intracranial EEG. Concordance of EEG source imaging with intracranial EEG was determined on a sublobar level and was quantified by measuring the distance between the source imaging result and the centroid of the active seizure onset zone electrodes. The EEG source imaging results of a subgroup of 26 patients with high density 76-channel EEG were compared with the localization of three experienced epileptologists. Of 87 patients, 95% had at least one analysis concordant with intracranial EEG and 74% had complete concordance. There was a higher rate of complete concordance in temporal lobe epilepsy compared to extratemporal (89.3 and 62.8%, respectively, P = 0.015). Of the total 282 analyses performed on this cohort, higher concordance was also seen in temporal discharges (95%) compared to extratemporal (77%) (P = 0.0012), but no difference was seen comparing high-density EEG with standard (32-channel) EEG. Subgroup analysis of ictal waveforms showed greater concordance for ictal spiking, compared with rhythmic activity, paroxysmal fast activity, or obscured onset. Median distances from the dipole and maximum distributed source to a centroid of seizure onset zone electrodes were 30.0 and 32.5 mm, respectively, and the median distances from dipole and maximum distributed source to nearest seizure onset zone electrode were 22.8 and 21.7, respectively. There were significantly shorter distances in ictal spiking. There were shorter distances in patients with Engel Class 1 outcome from surgical resection compared to patients with worse outcomes. For the subgroup of 26 high-density EEG patients, EEG source localization had a significantly higher concordance (92% versus 65%), sensitivity (57% versus 35%) and positive predictive value (60% versus 36%) compared with epileptologist localization. Our study demonstrates good concordance between ictal and interictal source imaging and intracranial EEG. Temporal lobe discharges have higher concordance rates than extratemporal discharges. Importantly, this study shows that source imaging has greater agreement with intracranial EEG than visual review alone, supporting its role in surgical planning.

High-resolution electric source imaging for presurgical evaluation of tuberous sclerosis complex patients

OBJECTIVE

We retrospectively assessed the localizing value of patient-history-based semiology (PHS), video-based semiology (VS), long-term monitoring video electroencephalography (LTM-VEEG) and interictal high resolution electric source imaging (HR-ESI) in the presurgical workup of patients with tuberous sclerosis complex (TSC).

METHODS

Data from 24 consecutive TSC surgical candidates who underwent both HR-ESI and LTM-VEEG was retrospectively collected. PHS and VS were analyzed to hypothesize the symptomatogenic zone localization. LTM-VEEG and HR-ESI localization results were extracted from the diagnostic reports. Localizing value was compared between modalities, taken the resected/disconnected area of surgical patients in consideration. HR-ESI's impact on the epileptogenic zone hypothesis and surgical workup was evaluated.

RESULTS

Semiology, interictal EEG, ictal EEG and HR-ESI were localizing in 25%, 54%, 63% and 79% of patients. Inter-modality concordance ranged between 33-89%. In good surgical outcome patients, PHS, VS, interictal EEG, ictal EEG and HR-ESI showed concordance with resected area in 1/9 (11%), 0/9 (0%), 4/9 (44%), 3/9 (33%) and 6/9 patients (67%). HR-ESI positively impacts clinical management in 50% of patients.

CONCLUSIONS

In presurgical evaluation of TSC patients, semiology often has limited localizing value. Presurgical work-up benefits from HR-ESI.

SIGNIFICANCE

Our findings may advice future presurgical epilepsy workup of TSC patients with the ultimate aim to improve outcome.

Linear distributed inverse solutions for interictal EEG source localisation

OBJECTIVE

To compare the spatial accuracy of 6 linear distributed inverse solutions for EEG source localisation of interictal epileptic discharges: Minimum Norm, Weighted Minimum Norm, Low-Resolution Electromagnetic Tomography (LORETA), Local Autoregressive Average (LAURA), Standardised LORETA, and Exact LORETA.

METHODS

Spatial accuracy was assessed clinically by retrospectively comparing the maximum source of averaged interictal discharges to the resected brain area in 30 patients with successful epilepsy surgery, based on 204-channel EEG. Additionally, localisation errors of the inverse solutions were assessed in computer simulations, with different levels of noise added to the signal in both sensor space and source space.

RESULTS

In the clinical evaluations, the source maximum was located inside the resected brain area in 50-57% of patients when using LORETA or LAURA, while all other inverse solutions performed significantly worse (17-30%; corrected p < 0.01). In the simulation studies, when noise levels exceeded 10%, LORETA and LAURA had substantially smaller localisation errors than the other inverse solutions.

CONCLUSIONS

LORETA and LAURA provided the highest spatial accuracy both in clinical and simulated data, alongside with a comparably high robustness towards noise.

SIGNIFICANCE

Among the different linear inverse solution algorithms tested, LORETA and LAURA might be preferred for interictal EEG source localisation.

Low density electrical source imaging of the ictal onset zone in the surgical evaluation of children with epilepsy

PURPOSE

To investigate the utility of Low Density (LD) Electrical Source Imaging (ESI) to model the ictal onset zone (IOZ) for the surgical work up of children with medically refractory epilepsy.

METHODS

This was a retrospective review of 12 patients from a district and regional pediatric epilepsy center, who underwent focal resections between 2014 and 2019. ESI was generated using the Curry 8 software, incorporating T1 Magnetic Resonance Imaging (MRI) scans and scalp electroencephalogram (EEG) recordings. Concordance of the ictal LD-ESI localizations to the epileptogenic zone was assessed by comparing the location of the ictal LD-ESI to the focal resection margins on neuroimaging and noting the post-operative outcomes at one year. Localizations determined by ictal LD-ESI were also compared to interictal LD-ESI, positron emission tomography (FDG-PET) and interictal magnetoencephalography (MEG).

RESULTS

Ictal ESI correctly localized the ictal onset zone in 4/6 patients, with all four being seizure free at one year. Similarly, interictal ESI localized the irritative zone in 7/9 patients with focal resections, with 6/7 being seizure free at one year. Additionally, we observed ictal ESI to be concordant to interictal ESI in 5/6 patients. Ictal ESI and interictal ESI were concordant to interictal MEG in 3/6 patients. Ictal ESI was concordant with FDG-PET in 6/7 cases.

CONCLUSION

IOZ source localization through LD-ESI is a promising complementary method of assessing the epileptogenic focus in children. These findings may support the inclusion of ictal LD-ESI within the pre-surgical evaluation of children to supplement current diagnostic tools.

Automated electrical source imaging with scalp EEG to define the insular irritative zone: Comparison with simultaneous intracranial EEG

OBJECTIVE

To evaluate the accuracy of automatedinterictallow-density electrical source imaging (LD-ESI) to define the insular irritative zone (IZ) by comparing the simultaneous interictal ESI localization with the SEEG interictal activity.

METHODS

Long-term simultaneous scalp electroencephalography (EEG) and stereo-EEG (SEEG) with at least one depth electrode exploring the operculo-insular region(s) were analyzed. Automated interictal ESI was performed on the scalp EEG using standardized low-resolution brain electromagnetic tomography (sLORETA) and individual head models. A two-step analysis was performed: i) sublobar concordance betweencluster-based ESI localization and SEEG-based IZ; ii) time-locked ESI-/SEEG analysis. Diagnostic accuracy values were calculated using SEEG as reference standard. Subgroup analysis wascarried out, based onthe involvement of insular contacts in the seizure onset and patterns of insular interictal activity.

RESULTS

Thirty patients were included in the study. ESI showed an overall accuracy of 53% (C.I. 29-76%). Sensitivity and specificity were calculated as 53% (C.I. 29-76%), 55% (C.I. 23-83%) respectively. Higher accuracy was found in patients with frequent and dominant interictal insular spikes.

CONCLUSIONS

LD-ESI defines with good accuracy the insular implication in the IZ, which is not possible with classical interictalscalpEEG interpretation.

SIGNIFICANCE

Automated LD-ESI may be a valuable additional tool to characterize the epileptogenic zone in epilepsies with suspected insular involvement.

Automated interictal source localisation based on high-density EEG

PURPOSE

To study the accuracy of automated interictal EEG source localisation based on high-density EEG, and to compare it to low-density EEG.

METHODS

Thirty patients operated for pharmacoresistant focal epilepsy were retrospectively examined. Twelve months after resective brain surgery, 18 were seizure-free or had 'auras' only, while 12 had persistence of disabling seizures. Presurgical 257-channel EEG lasting 3-20 h was down-sampled to 25, 40, and 204 channels for separate analyses. For each electrode setup, interictal spikes were detected, clustered, and averaged automatically before validation by an expert reviewer. An individual 6-layer finite difference head model and the standardised low-resolution electromagnetic tomography were used to localise the maximum source activity of the most prevalent spike. Sublobar concordance with the resected brain area was visually assessed and related to favourable vs. unfavourable postsurgical outcome.

RESULTS

Depending on the EEG setup, epileptic spikes were detected in 21-24 patients (70-80%). The median number of single spikes per average was 470 (range 17-15,066). Diagnostic sensitivity of EEG source localisation was 58-75%, specificity was 50-67%, and overall accuracy was 55-71%. There were no significant differences between low- and high-density EEG setups with 25 to 257 electrodes.

CONCLUSION

Automated high-density EEG source localisation provides meaningful information in the majority of cases. With hundreds of single spikes averaged, diagnostic accuracy is similar in high- and low-density EEG. Therefore, low-density EEG may be sufficient for interictal EEG source localisation if high numbers of spikes are available.

Triphasic Waves Are Generated by Widespread Bilateral Cortical Networks

PURPOSE

Triphasic waves (TWs) have been observed in the EEG recorded in patients with various types of encephalopathy, yet their genesis and significance is still debated. The aim of this study was to elucidate the localization of the cortical generators of TWs using EEG source imaging.

METHODS

In 20 consecutive patients who had encephalopathy with TWs, EEG source imaging of the first negative and the positive phases of the TW was performed. Three different approaches were used: equivalent current dipoles, a distributed source model, and a recently described spatial filtration method for visualizing EEG in source space.

RESULTS

Equivalent current dipole models failed to provide valid solutions. The distributed source model and the spatial filtration method suggested that TWs were generated by large, bilateral cortical networks, invariably involving the anterior frontal and the temporo-polar areas.

CONCLUSIONS

Source imaging localized TWs to anterior frontal and temporo-frontal structures. Involvement of these regions is consistent with the typical pathophysiological changes of altered consciousness and cognitive changes observed in patients with TW encephalopathy.

Advances in Epilepsy Surgery

BACKGROUND

A large number of patients have epilepsy that is intractable and adversely affects a child's lifelong experience with addition societal burden that is disabling and expensive. The last two decades have seen a major explosion of new antiseizure medication options. Despite these advances, children with epilepsy continue to have intractable seizures. An option that has been long available but little used is epilepsy surgery to control intractable epilepsy.

METHODS

This article is a review of the literature as well as published opinions.

RESULTS

Epilepsy surgery in pediatrics is an underused modality to effectively treat children with epilepsy. Adverse effects of medication should be weighed against risks of surgery as well as risks of nonefficacy.

CONCLUSIONS

We discuss an approach to selecting the appropriate pediatric patient for consideration, a detailed evaluation including necessary evaluation, and the creation of an algorithm to approach patients with both generalized and focal epilepsy. We then discuss surgical options available including outcome data. New modalities are also addressed including high-frequency ultrasound and co-registration techniques including magnetic resonance imaging-guided laser therapy.

Improving surgical outcome with electric source imaging and high field magnetic resonance imaging

While most patients with focal epilepsy present with clear structural abnormalities on standard, 1.5 or 3 T MRI, some patients are MRI-negative. For those, quantitative MRI techniques, such as volumetry, voxel-based morphometry, and relaxation time measurements can aid in finding the epileptogenic focus. High-field MRI, just recently approved for clinical use by the FDA, increases the resolution and, in several publications, was shown to improve the detection of focal cortical dysplasias and mild cortical malformations. For those cases without any tissue abnormality in neuroimaging, even at 7 T, scalp EEG alone is insufficient to delimitate the epileptogenic zone. They may benefit from the use of high-density EEG, in which the increased number of electrodes helps improve spatial sampling. The spatial resolution of even low-density EEG can benefit from electric source imaging techniques, which map the source of the recorded abnormal activity, such as interictal epileptiform discharges, focal slowing, and ictal rhythm. These EEG techniques help localize the irritative, functional deficit, and seizure-onset zone, to better estimate the epileptogenic zone. Combining those technologies allows several drug-resistant cases to be submitted to surgery, increasing the odds of seizure freedom and providing a must needed hope for patients with epilepsy.

ConvDip: A Convolutional Neural Network for Better EEG Source Imaging

The electroencephalography (EEG) is a well-established non-invasive method in neuroscientific research and clinical diagnostics. It provides a high temporal but low spatial resolution of brain activity. To gain insight about the spatial dynamics of the EEG, one has to solve the inverse problem, i.e., finding the neural sources that give rise to the recorded EEG activity. The inverse problem is ill-posed, which means that more than one configuration of neural sources can evoke one and the same distribution of EEG activity on the scalp. Artificial neural networks have been previously used successfully to find either one or two dipole sources. These approaches, however, have never solved the inverse problem in a distributed dipole model with more than two dipole sources. We present ConvDip, a novel convolutional neural network (CNN) architecture, that solves the EEG inverse problem in a distributed dipole model based on simulated EEG data. We show that (1) ConvDip learned to produce inverse solutions from a single time point of EEG data and (2) outperforms state-of-the-art methods on all focused performance measures. (3) It is more flexible when dealing with varying number of sources, produces less ghost sources and misses less real sources than the comparison methods. It produces plausible inverse solutions for real EEG recordings from human participants. (4) The trained network needs <40 ms for a single prediction. Our results qualify ConvDip as an efficient and easy-to-apply novel method for source localization in EEG data, with high relevance for clinical applications, e.g., in epileptology and real-time applications.

Source imaging of seizure onset predicts surgical outcome in pediatric epilepsy

Objective:

To assess whether ictal electric source imaging (ESI) on low-density scalp EEG can approximate the seizure onset zone (SOZ) location and predict surgical outcome in children with refractory epilepsy undergoing surgery.

Methods:

We examined 35 children with refractory epilepsy. We dichotomized surgical outcome into seizure- and non-seizure-free. We identified ictal onsets recorded with scalp and intracranial EEG and localized them using equivalent current dipoles and standardized low-resolution magnetic tomography (sLORETA). We estimated the localization accuracy of scalp EEG as distance of scalp dipoles from intracranial dipoles. We also calculated the distances of scalp dipoles from resection, as well as their resection percentage and compared between seizure-free and non-seizure-free patients. We built receiver operating characteristic curves to test whether resection percentage predicted outcome.

Results:

Resection distance was lower in seizure-free patients for both dipoles (p = 0.006) and sLORETA (p = 0.04). Resection percentage predicted outcome with a sensitivity of 57.1% (95% CI, 34–78.2%), a specificity of 85.7% (95% CI, 57.2–98.2%) and an accuracy of 68.6% (95% CI, 50.7–83.5%) (p = 0.01).

Conclusion:

Ictal ESI performed on low-density scalp EEG can delineate the SOZ and predict outcome.

Significance:

Such an application may increase the number of children who are referred for epilepsy surgery and improve their outcome.

Automated ictal EEG source imaging: A retrospective, blinded clinical validation study

OBJECTIVE

EEG source imaging (ESI) is a validated tool in the multimodal workup of patients with drug resistant focal epilepsy. However, it requires special expertise and it is underutilized. To circumvent this, automated analysis pipelines have been developed and validated for the interictal discharges. In this study, we present the clinical validation of an automated ESI for ictal EEG signals.

METHODS

We have developed an automated analysis pipeline of ictal EEG activity, based on spectral analysis in source space, using an individual head model of six tissues. The analysis was done blinded to all other data. As reference standard, we used the concordance with the resected area and one-year postoperative outcome.

RESULTS

We analyzed 50 consecutive patients undergoing epilepsy surgery (34 temporal and 16 extra-temporal). Thirty patients (60%) became seizure-free. The accuracy of the automated ESI was 74% (95% confidence interval: 59.66-85.37%).

CONCLUSIONS

Automated ictal ESI has a high accuracy for localizing the seizure onset zone.

SIGNIFICANCE

Automating the ESI of the ictal EEG signals will facilitate implementation of this tool in the presurgical evaluation.

High-density Electric Source Imaging of interictal epileptic discharges: How many electrodes and which time point?

OBJECTIVE

To assess the value of caudal EEG electrodes over cheeks and neck for high-density electric source imaging (ESI) in presurgical epilepsy evaluation, and to identify the best time point during averaged interictal epileptic discharges (IEDs) for optimal ESI accuracy.

METHODS

We retrospectively examined presurgical 257-channel EEG recordings of 45 patients with pharmacoresistant focal epilepsy. By stepwise removal of cheek and neck electrodes, averaged IEDs were downsampled to 219, 204, and 156 EEG channels. Additionally, ESI at the IED's half-rise was compared to other time points. The respective sources of maximum activity were compared to the resected brain area and postsurgical outcome.

RESULTS

Caudal channels had disproportionately more artefacts. In 30 patients with favourable outcome, the 204-channel array yielded the most accurate results with ESI maxima < 10 mm from the resection in 67% and inside affected sublobes in 83%. Neither in temporal nor in extratemporal cases did the full 257-channel setup improve ESI accuracy. ESI was most accurate at 50% of the IED's rising phase.

CONCLUSION

Information from cheeks and neck electrodes did not improve high-density ESI accuracy, probably due to higher artefact load and suboptimal biophysical modelling.

SIGNIFICANCE

Very caudal EEG electrodes should be used for ESI with caution.

Somatosensory phenomena elicited by electrical stimulation of hippocampus: Insight into the ictal network

Up to 11% of patients with mesial temporal lobe epilepsy experience somatosensory auras, although these structures do not have any somatosensory physiological representation. We present the case of a patient with left mesial temporal lobe epilepsy who had somatosensory auras on the right side of the body. Stereo-EEG recording demonstrated seizure onset in the left mesial temporal structures, with propagation to the sensory cortices, when the patient experienced the somatosensory aura. Direct electrical stimulation of both the left amygdala and the hippocampus elicited the patient's habitual, somatosensory aura, with afterdischarges propagating to sensory cortices. These unusual responses to cortical stimulation suggest that in patients with epilepsy, aberrant neural networks are established, which have an essential role in ictogenesis.

Brain networks involved in generalized periodic discharges (GPD) in post-anoxic-ischemic encephalopathy

AIM

Generalized periodic discharge (GPD) is an EEG pattern of poor neurological outcome, frequently observed in comatose patients after cardiac arrest. The aim of our study was to identify the neuronal network generating ≤2.5 Hz GPD using EEG source localization and connectivity analysis.

METHODS

We analyzed 40 comatose adult patients with anoxic-ischemic encephalopathy, who had 19 channel-EEG recording. We computed electric source analysis based on distributed inverse solution (LAURA) and we estimated cortical activity in 82 atlas-based cortical brain regions. We applied directed connectivity analysis (Partial Directed Coherence) on these sources to estimate the main drivers.

RESULTS

Source analysis suggested that the GPD are generated in the cortex of the limbic system in the majority of patients (87.5%). Connectivity analysis revealed main drivers located in thalamus and hippocampus for the large majority of patients (80%), together with important activation also in amygdala (70%).

CONCLUSIONS

We hypothesize that the anoxic-ischemic dysfunction, leading to hyperactivity of the thalamo-cortical (limbic presumably) circuit, can result in an oscillatory thalamic activity capable of inducing periodic cortical (limbic, mostly medial-temporal and orbitofrontal) discharges, similarly to the case of generalized rhythmic spike-wave discharge in convulsive or non-convulsive status epilepticus.

Ictal EEG source localization in focal epilepsy: Review and future perspectives

Electroencephalographic (EEG) source imaging localizes the generators of neural activity in the brain. During presurgical epilepsy evaluation, EEG source imaging of interictal epileptiform discharges is an established tool to estimate the irritative zone. However, the origin of interictal activity can be partly or fully discordant with the origin of seizures. Therefore, source imaging based on ictal EEG data to determine the seizure onset zone can provide precious clinical information. In this descriptive review, we address the importance of localizing the seizure onset zone based on noninvasive EEG recordings as a complementary analysis that might reduce the burden of the presurgical evaluation. We identify three major challenges (low signal-to-noise ratio of the ictal EEG data, spread of ictal activity in the brain, and validation of the developed methods) and discuss practical solutions. We provide an extensive overview of the existing clinical studies to illustrate the potential clinical utility of EEG-based localization of the seizure onset zone. Finally, we conclude with future perspectives and the needs for translating ictal EEG source imaging into clinical practice.

REM-sleep related hypermotor seizures: Video documentation and ictal source imaging

INTRODUCTION

Rapid eye movement (REM) sleep has an inhibitory effect on epileptiform EEG discharges, and seizures occur extremely rarely in REM sleep.

CASE STUDY

We present the case and video recordings of a 10-year-old boy, with sleep-related hypermotor seizures starting from REM sleep, identified from videoEEG recordings. The semiology comprised intense fear, tachycardia, tachypnea, followed by hypermotor manifestations. Further investigations included brain MRI and source localization of the EEG signals. Multiple antiepileptic drugs were tried, the patient obtaining a good control of the seizures in the last 2.5 years with eslicarbazepine.

DISCUSSION AND CONCLUSION

The ictal EEG source imaging showed seizure onset in the anterior part of the right insula, with propagation to the orbitofrontal area, confirmed by the semiological sequence. Although rare, focal seizures can be triggered by REM sleep and our findings suggest that deficient maturation of brain areas involved in sleep modulation might induce insufficient desynchronization during REM sleep, thus allowing seizure emergence.

Accuracy of Interictal and Ictal Electric and Magnetic Source Imaging: A Systematic Review and Meta-Analysis

Background: Electric and magnetic source imaging methods (ESI, MSI) estimate the location in the brain of the sources generating the interictal epileptiform discharges (II-ESI, II-MSI) and the ictal activity (IC-ESI, IC-MSI). These methods provide potentially valuable clinical information in the presurgical evaluation of patients with drug-resistant focal epilepsy, evaluated for surgical therapy. In spite of the significant technical advances in this field, and the numerous papers published on clinical validation of these methods, ESI and MSI are still underutilized in most epilepsy centers performing a presurgical evaluation. Our goal was to review and summarize the published evidence on the diagnostic accuracy of interictal and ictal ESI and MSI in epilepsy surgery.

Methods: We searched the literature for papers on ESI and MSI that specified the diagnostic reference standard as the site of resection and the postoperative outcome (seizure-freedom). We extracted data from the selected studies, to calculate the diagnostic accuracy measures.

Results: Our search resulted in 797 studies; 48 studies fulfilled the selection criteria (25 ESI and 23 MSI studies), providing data from 1,152 operated patients (515 for II-ESI, 440 for II-MSI, 159 for IC-ESI, and 38 for IC-MSI). The sensitivity of source imaging methods was between 74 and 90% (highest for IC-ESI). The specificity of the source imaging methods was between 20 and 54% (highest for II-MSI). The overall accuracy was between 50 and 75% (highest for IC-ESI). Diagnostic Odds Ratio was between 0.8 (IC-MSI) and 4.02–7.9 (II-ESI < II-MSI < IC-ESI).

Conclusions: Our systematic review and meta-analysis provides evidence for the accuracy of source imaging in presurgical evaluation of patients with drug-resistant focal epilepsy. These methods have high sensitivity (up to 90%) and diagnostic odds ratio (up to 7.9), but the specificity is lower (up to 54%). ESI and MSI should be included in the multimodal presurgical evaluation.