Source imaging of seizure onset predicts surgical outcome in pediatric epilepsy

Interictal EEG source connectivity to localize the epileptogenic zone in patients with drug-resistant epilepsy: A machine learning approach

OBJECTIVE

To deconstruct the epileptogenic networks of patients with drug-resistant epilepsy (DRE) using source functional connectivity (FC) analysis; unveil the FC biomarkers of the epileptogenic zone (EZ); and develop machine learning (ML) models to estimate the EZ using brief interictal electroencephalography (EEG) data.

METHODS

We analyzed scalp EEG from 50 patients with DRE who had surgery. We reconstructed the activity (electrical source imaging [ESI]) of virtual sensors (VSs) across the whole cortex and computed FC separately for epileptiform and non-epileptiform EEG epochs (with or without spikes). In patients with good outcome (Engel 1a), four cortical regions were defined: EZ (resection) and three non-epileptogenic zones (NEZs) in the same and opposite hemispheres. Region-specific FC features in six frequency bands and three spatial ranges (long, short, inner) were compared between regions (Wilcoxon sign-rank). We developed ML classifiers to identify the VSs in the EZ using VS-specific FC features. Cross-validation was performed using good outcome data. Performance was compared with poor outcomes and interictal spike localization.

RESULTS

FC differed between EZ and NEZs (p < .05) during non-epileptiform and epileptiform epochs, showing higher FC in the EZ than its homotopic contralateral NEZ. During epileptiform epochs, the NEZ in the epileptogenic hemisphere showed higher FC than its contralateral NEZ. In good outcome patients, the ML classifiers reached 75% accuracy to the resection (91% sensitivity; 74% specificity; distance from EZ: 38 mm) using epileptiform epochs (gamma and beta frequency bands) and 62% accuracy using broadband non-epileptiform epochs, both outperforming spike localization (accuracy = 47%; p < .05; distance from EZ: 57 mm). Lower performance was seen in poor outcomes.

SIGNIFICANCE

We present an FC approach to extract EZ biomarkers from brief EEG data. Increased FC in various frequencies characterized the EZ during epileptiform and non-epileptiform epochs. FC-based ML models identified the resection better in good than poor outcome patients, demonstrating their potential for presurgical use in pediatric DRE.

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.

Sleep Spindle Generation Before and After Epilepsy Surgery: A Source Imaging Study in Children with Drug-Resistant Epilepsy

INTRODUCTION

Literature lacks studies investigating the cortical generation of sleep spindles in drug-resistant epilepsy (DRE) and how they evolve after resection of the epileptogenic zone (EZ). Here, we examined sleep EEGs of children with focal DRE who became seizure-free after focal epilepsy surgery, and aimed to investigate the changes in the spindle generation before and after the surgery using low-density scalp EEG and electrical source imaging (ESI).

METHODS

We analyzed N2-sleep EEGs from 19 children with DRE before and after surgery. We identified slow (8-12 Hz) and fast spindles (13-16 Hz), computed their spectral features and cortical generators through ESI and computed their distance from the EZ and irritative zone (IZ). We performed two-way ANOVA testing the effect of spindle type (slow vs. fast) and surgical phase (pre-surgery vs. post-surgery) on each feature.

RESULTS

Power, frequency and cortical activation of slow spindles increased after surgery (p < 0.005), while this was not seen for fast spindles. Before surgery, the cortical generators of slow spindles were closer to the EZ (57.3 vs. 66.2 mm, p = 0.007) and IZ (41.3 vs. 55.5 mm, p = 0.02) than fast spindle generators.

CONCLUSIONS

Our data indicate alterations in the EEG slow spindles after resective epilepsy surgery. Fast spindle generation on the contrary did not change after surgery. Although the study is limited by its retrospective nature, lack of healthy controls, and reduced cortical spatial sampling, our findings suggest a spatial relationship between the slow spindles and the epileptogenic generators.

EEG electrode localization with 3D iPhone scanning using point-cloud electrode selection (PC-ES)

Objective.Electroencephalography source imaging (ESI) is a valuable tool in clinical evaluation for epilepsy patients but is underutilized in part due to sensitivity to anatomical modeling errors. Accurate localization of scalp electrodes is instrumental to ESI, but existing localization devices are expensive and not portable. As a result, electrode localization challenges further impede access to ESI, particularly in inpatient and intensive care settings.Approach.To address this challenge, we present a portable and affordable electrode digitization method using the 3D scanning feature in modern iPhone models. This technique combines iPhone scanning with semi-automated image processing using point-cloud electrode selection (PC-ES), a custom MATLAB desktop application. We compare iPhone electrode localization to state-of-the-art photogrammetry technology in a human study with over 6000 electrodes labeled using each method. We also characterize the performance of PC-ES with respect to head location and examine the relative impact of different algorithm parameters.Main Results.The median electrode position variation across reviewers was 1.50 mm for PC-ES scanning and 0.53 mm for photogrammetry, and the average median distance between PC-ES and photogrammetry electrodes was 3.4 mm. These metrics demonstrate comparable performance of iPhone/PC-ES scanning to currently available technology and sufficient accuracy for ESI.Significance.Low cost, portable electrode localization using iPhone scanning removes barriers to ESI in inpatient, outpatient, and remote care settings. While PC-ES has current limitations in user bias and processing time, we anticipate these will improve with software automation techniques as well as future developments in iPhone 3D scanning technology.

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.

Source localization of ictal SEEG to predict postoperative seizure outcome

OBJECTIVE

Stereo-electroencephalography (SEEG) is inherently-three-dimensional and can be modeled using source localization. This study aimed to assess the validity of ictal SEEG source localization.

METHODS

The dominant frequency at ictal onset was used for source localization in the time and frequency domains using rotating dipoles and current density maps. Validity was assessed by concordance with the epileptologist-defined seizure onset zone (conventional SOZ) and the surgical treatment volume (TV) of seizure-free versus non-seizure-free patients.

RESULTS

Source localization was performed on 68 seizures from 27 patients. Median distance to nearest contact in the conventional SOZ was 7 (IQR 6-12) mm for time-domain dipoles. Current density predicted ictal activity with up to 86 % (60-87 %) accuracy. Distance from time-domain dipoles to the TV was smaller (P = 0.045) in seizure-free (2 [0-4] mm) versus non-seizure-free (12 [2-17] mm) patients, and predicted surgical outcome with 91 % sensitivity and 63 % specificity. Removing near-field data from contacts within the TV negated outcome prediction (P = 0.51).

CONCLUSIONS

Source localization of SEEG accurately mapped ictal onset compared with conventional interpretation. Proximity of dipoles to the TV predicted seizure outcome when near-field recordings were analyzed.

SIGNIFICANCE

Ictal SEEG source localization is useful in corroborating the epileptogenic zone, assuming near-field recordings are obtained.

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.

SEEG in 3D: Interictal Source Localization From Intracerebral Recordings

BACKGROUND

Stereo-electroencephalography (SEEG) uses a three-dimensional configuration of depth electrodes to localize epileptiform activity, but traditional analysis of SEEG is spatially restricted to the point locations of the electrode contacts. Interpolation of brain activity between contacts might allow for three-dimensional representation of epileptiform activity and avoid pitfalls of SEEG interpretation.

OBJECTIVE

The goal of this study was to validate SEEG-based interictal source localization and assess the ability of this technique to monitor far-field activity in non-implanted brain regions.

METHODS

Interictal epileptiform discharges were identified on SEEG in 26 patients who underwent resection, ablation, or disconnection of the suspected epileptogenic zone. Dipoles without (free) and with (scan) gray matter restriction, and current density (sLORETA and SWARM methods), were calculated using a finite element head model. Source localization results were compared to the conventional irritative zone (IZ) and the surgical treatment volumes (TV) of seizure-free vs. non-seizure-free patients.

RESULTS

The median distance from dipole solutions to the nearest contact in the conventional IZ was 7 mm (interquartile range 4-15 mm for free dipoles and 4-14 mm for scan dipoles). The IZ modeled with SWARM predicted contacts within the conventional IZ with 83% (75-100%) sensitivity and 94% (88-100%) specificity. The proportion of current within the TV was greater in seizure-free patients (P = 0.04) and predicted surgical outcome with 45% sensitivity and 93% specificity. Dipole solutions and sLORETA results did not correlate with seizure outcome. Addition of scalp EEG led to more superficial modeled sources (P = 0.03) and negated the ability to predict seizure outcome (P = 0.23). Removal of near-field data from contacts within the TV resulted in smearing of the current distribution (P = 0.007) and precluded prediction of seizure freedom (P = 0.20).

CONCLUSIONS

Source localization accurately represented interictal discharges from SEEG. The proportion of current within the TV distinguished between seizure-free and non-seizure-free patients when near-field recordings were obtained from the surgical target. The high prevalence of deep sources in this cohort likely obscured any benefit of concurrent scalp EEG. SEEG-based interictal source localization is useful in illustrating and corroborating the epileptogenic zone. Additional techniques are needed to localize far-field epileptiform activity from non-implanted brain regions.

Case Report: Laser Ablation Guided by State of the Art Source Imaging Ends an Adolescent's 16-Year Quest for Seizure Freedom

Epilepsy surgery is the most effective therapeutic approach for children with drug resistant epilepsy (DRE). Recent advances in neurosurgery, such as the Laser Interstitial Thermal Therapy (LITT), improved the safety and non-invasiveness of this method. Electric and magnetic source imaging (ESI/MSI) plays critical role in the delineation of the epileptogenic focus during the presurgical evaluation of children with DRE. Yet, they are currently underutilized even in tertiary epilepsy centers. Here, we present a case of an adolescent who suffered from DRE for 16 years and underwent surgery at Cook Children's Medical Center (CCMC). The patient was previously evaluated in a level 4 epilepsy center and treated with multiple antiseizure medications for several years. Presurgical evaluation at CCMC included long-term video electroencephalography (EEG), magnetoencephalography (MEG) with simultaneous conventional EEG (19 channels) and high-density EEG (256 channels) in two consecutive sessions, MRI, and fluorodeoxyglucose - positron emission tomography (FDG-PET). Video long-term EEG captured nine focal-onset clinical seizures with a maximal evolution over the right frontal/frontal midline areas. MRI was initially interpreted as non-lesional. FDG-PET revealed a small region of hypometabolism at the anterior right superior temporal gyrus. ESI and MSI performed with dipole clustering showed a tight cluster of dipoles in the right anterior insula. The patient underwent intracranial EEG which indicated the right anterior insular as seizure onset zone. Eventually LITT rendered the patient seizure free (Engel 1; 12 months after surgery). Retrospective analysis of ESI and MSI clustered dipoles found a mean distance of dipoles from the ablated volume ranging from 10 to 25 mm. Our findings highlight the importance of recent technological advances in the presurgical evaluation and surgical treatment of children with DRE, and the underutilization of epilepsy surgery in children with DRE.

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.

Localizing the Epileptogenic Zone with Novel Biomarkers

Several noninvasive methods, such as high-density EEG or magnetoencephalography, are currently used to delineate the epileptogenic zone (EZ) during the presurgical evaluation of patients with drug resistant epilepsy (DRE). Yet, none of these methods can reliably identify the EZ by their own. In most cases a multimodal approach is needed. Challenging cases often require the implantation of intracranial electrodes, either through stereo-taxic EEG or electro-corticography. Recently, a growing body of literature introduces novel biomarkers of epilepsy that can be used for analyzing both invasive as well as noninvasive electrophysiological data. Some of these biomarkers are able to delineate the EZ with high precision, augment the presurgical evaluation, and predict the surgical outcome of patients with DRE undergoing surgery. However, the use of these epilepsy biomarkers in clinical practice is limited. Here, we summarize and discuss the latest technological advances in the presurgical neurophysiological evaluation of children with DRE with emphasis on electric and magnetic source imaging, high frequency oscillations, and functional connectivity.

Changes in the Functional Brain Network of Children Undergoing Repeated Epilepsy Surgery: An EEG Source Connectivity Study

About 30% of children with drug-resistant epilepsy (DRE) continue to have seizures after epilepsy surgery. Since epilepsy is increasingly conceptualized as a network disorder, understanding how brain regions interact may be critical for planning re-operation in these patients. We aimed to estimate functional brain connectivity using scalp EEG and its evolution over time in patients who had repeated surgery (RS-group, n = 9) and patients who had one successful surgery (seizure-free, SF-group, n = 12). We analyzed EEGs without epileptiform activity at varying time points (before and after each surgery). We estimated functional connectivity between cortical regions and their relative centrality within the network. We compared the pre- and post-surgical centrality of all the non-resected (untouched) regions (far or adjacent to resection) for each group (using the Wilcoxon signed rank test). In alpha, theta, and beta frequency bands, the post-surgical centrality of the untouched cortical regions increased in the SF group (p < 0.001) whereas they decreased (p < 0.05) or did not change (p > 0.05) in the RS group after failed surgeries; when re-operation was successful, the post-surgical centrality of far regions increased (p < 0.05). Our data suggest that removal of the epileptogenic focus in children with DRE leads to a gain in the network centrality of the untouched areas. In contrast, unaltered or decreased connectivity is seen when seizures persist after surgery.