Intralesional epileptiform activity in a fourth ventricular hamartoma associated with epileptic hemifacial spasm in a toddler: illustrative case.

BACKGROUND: Focal epilepsy caused by a posterior fossa lesion is a rare phenomenon. In these cases, seizure onset typically occurs during the first few months of life, with episodes of epileptic hemifacial spasms and abnormal eye movements. Patients often present with drug-resistant epilepsy and often require resection for the best chance of seizure freedom. OBSERVATIONS: The authors present the case of a 19-month-old male with intractable epileptic hemifacial spasms and a dorsally exophytic right brainstem and middle cerebellar peduncle hamartoma, following 2 prior subtotal resections. The authors recommended a third suboccipital craniotomy with intraoperative electrocorticography, which revealed interictal spiking from an intralesional depth electrode. Near-total resection led to durable seizure freedom. LESSONS: Although posterior fossa lesions are rarely associated with epileptiform activity, this case demonstrates that pediatric patients with epileptic hemifacial spasms associated with a posterior fossa lesion may respond favorably to resection. Furthermore, this case demonstrates that intralesional electrocorticography can detect epileptic activity in posterior fossa lesions, which may predict postoperative seizure outcomes. https://thejns.org/doi/10.3171/CASE2452.

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.

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.

Machine learning models for predicting seizure outcome after MR-guided laser interstitial thermal therapy in children.

OBJECTIVE: MR-guided laser interstitial thermal therapy (MRgLITT) is associated with lower seizure-free outcome but better safety profile compared to open surgery. However, the predictors of seizure freedom following MRgLITT remain uncertain. This study aimed to use machine learning to predict seizure-free outcome following MRgLITT and to identify important predictors of seizure freedom in children with drug-resistant epilepsy. METHODS: This multicenter study included children treated with MRgLITT for drug-resistant epilepsy at 13 epilepsy centers. The authors used clinical data, diagnostic investigations, and ablation features to predict seizure-free outcome at 1 year post-MRgLITT. Patients from 12 centers formed the training cohort, and patients in the remaining center formed the testing cohort. Five machine learning algorithms were developed on the training data by using 10-fold cross-validation, and model performance was measured on the testing cohort. The models were developed and tested on the complete feature set. Subsequently, 3 feature selection methods were used to identify important predictors. The authors then assessed performance of the parsimonious models based on these important variables. RESULTS: This study included 268 patients who underwent MRgLITT, of whom 44.4% had achieved seizure freedom at 1 year post-MRgLITT. A gradient-boosting machine algorithm using the complete feature set yielded the highest area under the curve (AUC) on the testing set (AUC 0.67 [95% CI 0.50-0.82], sensitivity 0.71 [95% CI 0.47-0.88], and specificity 0.66 [95% CI 0.50-0.81]). Logistic regression, random forest, support vector machine, and neural network yielded lower AUCs (0.58-0.63) compared to the gradient-boosting machine but the findings were not statistically significant (all p > 0.05). The 3 feature selection methods identified video-EEG concordance, lesion size, preoperative seizure frequency, and number of antiseizure medications as good prognostic features for predicting seizure freedom. The parsimonious models based on important features identified by univariate feature selection slightly improved model performance compared to the complete feature set. CONCLUSIONS: Understanding the predictors of seizure freedom after MRgLITT will assist with prognostication.

Influence of extent and age at corpus callosotomy on seizure outcomes. A single center experience.

Corpus callosotomy (CC) is a palliative treatment for drop seizures in patients with drug-resistant nonlocalizable epilepsy. We compared drop seizure outcomes between patients undergoing anterior CC versus complete CC and examined factors impacting outcomes for drop seizures including age at CC and duration of epilepsy. A retrospective review of patients who underwent CC between 2003 and 2022 with a minimum of 6 months postsurgical follow-up was included. Outcome measure for drop seizures included seizure reduction ≥50% from baseline as well as elimination of drop seizures. Thirty-eight patients were included. Overall, ≥50% reduction in drop seizures occurred in nearly 70% (23 out of 33) patients with complete elimination in 58% (19 out of 33). Compared with anterior CC (n = 13), patients undergoing complete CC (n = 25) had increased likelihood of ≥50% reduction (p = 0.006) or elimination (p = 0.024) of drop seizures. Regression analysis showed that complete CC was the primary predictor for improved drop seizure outcomes (elimination, p = 0.014 or ≥50% reduction, p = 0.006), while age at CC and duration of epilepsy did not impact the outcomes. Compared to anterior CC, complete CC was significantly more likely to lead to improvement/freedom from drop seizures. Age at CC or duration of epilepsy did not influence drop seizure outcomes.

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.

Focal drug-resistant temporal lobe epilepsy associated with an ipsilateral anterior choroidal artery aneurysm: illustrative case.

BACKGROUND: The occurrence of both an intracranial aneurysm and epilepsy, especially drug-resistant epilepsy (DRE), is rare. Although the overall incidence of aneurysms associated with DRE is unclear, it is thought to be particularly infrequent in the pediatric population. Surgical ligation of the offending aneurysm has been reported in conjunction with resolving seizure activity, although few cases have cited a combined approach of aneurysm ligation and resection of an epileptogenic focus. OBSERVATIONS: We present the case of a 14-year-old female patient with drug-resistant temporal lobe epilepsy and an ipsilateral supraclinoid internal carotid artery aneurysm. Seizure semiology, electroencephalography monitoring, and magnetic resonance imaging all indicated a left temporal epileptogenic focus, in addition to an incidental aneurysm. The authors recommended a combined surgery involving resection of the temporal lesion and surgical clip ligation of the aneurysm. Near-total resection and successful ligation were achieved, and the patient has remained seizure free since surgery at 1 year postoperatively. LESSONS: In patients with focal DRE and an adjacent intracranial aneurysm, a combined surgical approach involving both resection and surgical ligation can be used. Several surgical timing and neuroanesthetic considerations should be made to ensure the overall safety and efficacy of this procedure.

Functional connectivity discriminates epileptogenic states and predicts surgical outcome in children with drug resistant epilepsy.

Normal brain functioning emerges from a complex interplay among regions forming networks. In epilepsy, these networks are disrupted causing seizures. Highly connected nodes in these networks are epilepsy surgery targets. Here, we assess whether functional connectivity (FC) using intracranial electroencephalography can quantify brain regions epileptogenicity and predict surgical outcome in children with drug resistant epilepsy (DRE). We computed FC between electrodes on different states (i.e. interictal without spikes, interictal with spikes, pre-ictal, ictal, and post-ictal) and frequency bands. We then estimated the electrodes' nodal strength. We compared nodal strength between states, inside and outside resection for good- (n = 22, Engel I) and poor-outcome (n = 9, Engel II-IV) patients, respectively, and tested their utility to predict the epileptogenic zone and outcome. We observed a hierarchical epileptogenic organization among states for nodal strength: lower FC during interictal and pre-ictal states followed by higher FC during ictal and post-ictal states (p < 0.05). We further observed higher FC inside resection (p < 0.05) for good-outcome patients on different states and bands, and no differences for poor-outcome patients. Resection of nodes with high FC was predictive of outcome (positive and negative predictive values: 47-100%). Our findings suggest that FC can discriminate epileptogenic states and predict outcome in patients with DRE.

Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy.

Neurosurgical intervention is the best available treatment for selected patients with drug resistant epilepsy. For these patients, surgical planning requires biomarkers that delineate the epileptogenic zone, the brain area that is indispensable for the generation of seizures. Interictal spikes recorded with electrophysiological techniques are considered key biomarkers of epilepsy. Yet, they lack specificity, mostly because they propagate across brain areas forming networks. Understanding the relationship between interictal spike propagation and functional connections among the involved brain areas may help develop novel biomarkers that can delineate the epileptogenic zone with high precision. Here, we reveal the relationship between spike propagation and effective connectivity among onset and areas of spread and assess the prognostic value of resecting these areas. We analysed intracranial EEG data from 43 children with drug resistant epilepsy who underwent invasive monitoring for neurosurgical planning. Using electric source imaging, we mapped spike propagation in the source domain and identified three zones: onset, early-spread and late-spread. For each zone, we calculated the overlap and distance from surgical resection. We then estimated a virtual sensor for each zone and the direction of information flow among them via Granger causality. Finally, we compared the prognostic value of resecting these zones, the clinically-defined seizure onset zone and the spike onset on intracranial EEG channels by estimating their overlap with resection. We observed a spike propagation in source space for 37 patients with a median duration of 95 ms (interquartile range: 34-206), a spatial displacement of 14 cm (7.5-22 cm) and a velocity of 0.5 m/s (0.3-0.8 m/s). In patients with good surgical outcome (25 patients, Engel I), the onset had higher overlap with resection [96% (40-100%)] than early-spread [86% (34-100%), P = 0.01] and late-spread [59% (12-100%), P = 0.002], and it was also closer to resection than late-spread [5 mm versus 9 mm, P = 0.007]. We found an information flow from onset to early-spread in 66% of patients with good outcomes, and from early-spread to onset in 50% of patients with poor outcome. Finally, resection of spike onset, but not area of spike spread or the seizure onset zone, predicted outcome with positive predictive value of 79% and negative predictive value of 56% (P = 0.04). Spatiotemporal mapping of spike propagation reveals information flow from onset to areas of spread in epilepsy brain. Surgical resection of the spike onset disrupts the epileptogenic network and may render patients with drug resistant epilepsy seizure-free without having to wait for a seizure to occur during intracranial monitoring.

Stereoelectroencephalography followed by combined electrode removal and MRI-guided laser interstitial thermal therapy or open resection: a single-center series in pediatric patients with medically refractory epilepsy.

OBJECTIVE: Stereoelectroencephalography (SEEG) and MRI-guided laser interstitial thermal therapy (MRgLITT) have emerged as safe, effective, and less invasive alternatives to subdural grid placement and open resection, respectively, for the localization and treatment of medically refractory epilepsy (MRE) in children. Reported pediatric experience combining these complementary techniques is limited, with traditional workflows separating electrode removal and ablation/resection. The authors describe the largest reported series of pediatric epilepsy patients who underwent MRgLITT following SEEG contrasted with a cohort that underwent craniotomy following SEEG, combining ablation/resection with electrode explantation as standard practice. METHODS: The medical records of all patients with MRE who had undergone SEEG followed by MRgLITT or open resection/disconnection at Boston Children's Hospital between November 2015 and December 2020 were retrospectively reviewed. Primary outcome variables included surgical complication rates, length of hospital stay following treatment, and Engel classification at the last follow-up. RESULTS: Of 74 SEEG patients, 27 (median age 12.1 years, 63% female) underwent MRgLITT and 47 (median age 12.1 years, 49% female) underwent craniotomy. Seventy patients (95%) underwent SEEG followed by combined electrode removal and treatment. Eight MRgLITT cases (30%) and no open cases targeted the insula (p < 0.001). Complication rates did not differ, although trends toward more subdural/epidural hematomas, infarcts, and permanent unanticipated neurological deficits were evident following craniotomy, whereas a trend toward more temporary unanticipated neurological deficits was seen following MRgLITT. The median duration of hospitalization after treatment was 3 and 5 days for MRgLITT and open cases, respectively (p = 0.078). Seizure outcomes were similar between the cohorts, with 74% of MRgLITT and craniotomy patients attaining Engel class I or II outcomes (p = 0.386) at the last follow-up (median 1.1 and 1.9 years, respectively). CONCLUSIONS: MRgLITT and open resection following SEEG can both effectively treat MRE in pediatric patients and generally can be performed in a two-surgery workflow during a single hospitalization. In appropriately selected patients, MRgLITT tended to be associated with shorter hospitalizations and fewer complications following treatment and may be best suited for focal deep-seated targets associated with relatively challenging open surgical approaches.

Limited utility of structural MRI to identify the epileptogenic zone in young children with tuberous sclerosis.

BACKGROUND AND PURPOSE: The success of epilepsy surgery in children with tuberous sclerosis complex (TSC) hinges on identification of the epileptogenic zone (EZ). We studied structural MRI markers of epileptogenic lesions in young children with TSC. METHODS: We included 26 children with TSC who underwent epilepsy surgery before the age of 3 years at five sites, with 12 months or more follow-up. Two neuroradiologists, blinded to surgical outcome data, reviewed 10 candidate lesions on preoperative MRI for characteristics of the tuber (large affected area, calcification, cyst-like properties) and of focal cortical dysplasia (FCD) features (cortical malformation, gray-white matter junction blurring, transmantle sign). They selected lesions suspect for the EZ based on structural MRI, and reselected after unblinding to seizure onset location on electroencephalography (EEG). RESULTS: None of the tuber characteristics and FCD features were distinctive for the EZ, indicated by resected lesions in seizure-free children. With structural MRI alone, the EZ was identified out of 10 lesions in 31%, and with addition of EEG data, this increased to 48%. However, rates of identification of resected lesions in non-seizure-free children were similar. Across 251 lesions, interrater agreement was moderate for large size (κ = .60), and fair (κ = .24) for all other features. CONCLUSIONS: In young children with TSC, the utility of structural MRI features is limited in the identification of the epileptogenic tuber, but improves when combined with EEG data.

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.

Complete Corpus Callosotomy for Refractory Epilepsy in Children.

Corpus callosotomy is an interhemispheric disconnection by callosal commissural fiber ablation. Its rationale is the disruption of ictal spread to prevent seizure generalization. The objective pursued is alleviation of intractable, debilitating, and injurious manifestations of generalized epilepsy.1 Eight decades of experience support this procedure's safety and effectiveness for appropriately selected patients with drug-resistant epilepsy not amenable to optimal resection; particularly, favorable outcomes for tonic or atonic seizures with drop attacks have been reported.2,3 Children may benefit more than adults from callosotomy for improved daily function, psychosocial adjustment, and family satisfaction.4 A meta-analysis found a better seizure reduction from total than partial callosotomy (88.2% vs. 58.6% of worthwhile reduction) comprising drop-attacks (77.8% vs. 45.4%) with an increased but transient (i.e., resolution within 6 weeks) risk of significant disconnection syndromes (12.5% vs. none).5 Here, we present the illustrative case of a 4-year-old boy with Lennox-Gastaut syndrome who underwent open single-stage complete callosotomy. Video 1 shows the microscope-assisted interhemispheric approach aided by stereotactic navigation. We showcase critical steps such as dissection of cingulate gyri and anterior and then posterior callosotomy while highlighting crucial anatomic landmarks. This procedure may be accessible for epilepsy surgeons worldwide in resource-constrained environments6 while serving as a basis for promising high-technology development (e.g., endoscopic, radiosurgical, laser interstitial thermal therapy, or magnetic resonance-guided focused ultrasound callosotomies). In this video article, we aim to provide a streamlined and stepwise approach to this rare but important epilepsy surgery.

Posterior quadrant disconnection for refractory epilepsy: how I do it.

BACKGROUND: Posterior quadrant disconnection (PQD) is intended to interrupt the propagation of intractable unilateral temporo-parieto-occipital epilepsy. METHOD: An enhanced operative video presents the illustrative case of a total PQD indicated for a 15-year-old boy with Sturge-Weber syndrome suffering from seizure recurrence after a partial PQD. We describe the surgical procedure with emphasis on relevant anatomy and multimodal intraoperative guidance in three steps: (i) parieto-occipital disconnection, (ii) posterior callosotomy, and (iii) temporal disconnection/resection. Pearls and pitfalls of surgical management are discussed. CONCLUSION: PQD is a less invasive surgical option to typical hemispherotomy and hemispherectomy for selected indications of posterior multilobar epilepsy.

Novel User-Friendly Application for MRI Segmentation of Brain Resection following Epilepsy Surgery.

Delineation of resected brain cavities on magnetic resonance images (MRIs) of epilepsy surgery patients is essential for neuroimaging/neurophysiology studies investigating biomarkers of the epileptogenic zone. The gold standard to delineate the resection on MRI remains manual slice-by-slice tracing by experts. Here, we proposed and validated a semiautomated MRI segmentation pipeline, generating an accurate model of the resection and its anatomical labeling, and developed a graphical user interface (GUI) for user-friendly usage. We retrieved pre- and postoperative MRIs from 35 patients who had focal epilepsy surgery, implemented a region-growing algorithm to delineate the resection on postoperative MRIs and tested its performance while varying different tuning parameters. Similarity between our output and hand-drawn gold standards was evaluated via dice similarity coefficient (DSC; range: 0-1). Additionally, the best segmentation pipeline was trained to provide an automated anatomical report of the resection (based on presurgical brain atlas). We found that the best-performing set of parameters presented DSC of 0.83 (0.72-0.85), high robustness to seed-selection variability and anatomical accuracy of 90% to the clinical postoperative MRI report. We presented a novel user-friendly open-source GUI that implements a semiautomated segmentation pipeline specifically optimized to generate resection models and their anatomical reports from epilepsy surgery patients, while minimizing user interaction.

Single-stage resection of bottom-of-a-sulcus dysplasia involving eloquent cortex using navigated transcranial magnetic stimulation and intraoperative modalities.

BACKGROUND: Focal cortical dysplasia (FCD) is a common etiology of refractory epilepsy, particularly in children. Surgical management is potentially curative, but poses the challenge of distinguishing the border between ictogenic regions of dysplasia and functionally critical brain tissue. Bottom-of-a-sulcus dysplasia (BOSD) amplifies this challenge, due to difficulties in physiologic mapping of the deep tissue. METHODS: We report a one-stage resection of a dysplasia-associated seizure focus abutting and involving the hand and face primary motor cortex. In doing so, we describe our surgical planning integrating neuronavigated transcranial magnetic stimulation (nTMS) for functional motor mapping, combined with intraoperative ultrasonography, intracranial electroencephalography, and magnetic resonance imaging (MRI). A 5-year-old girl with intractable focal epilepsy was referred to our comprehensive epilepsy program. Despite attentive pharmacotherapy, she experienced status epilepticus and up to 70 seizures per day, accompanied by multiple side effects from her antiseizure medication. A right frontal BOSD in close proximity to the hand motor area of the precentral gyrus was identified on MRI. Postoperatively, she is seizure-free for over 1 year with no hand deficit. CONCLUSION: Although technically complex, single-stage resection taking advantage of comprehensive surgical planning with optimized fusion of functional mapping and intraoperative modalities merits consideration given the invasiveness of a two-stage approach for limited added value. Integrated pre-surgical nTMS allowed for mapping of eloquent cortex without invasive electrocortical stimulation.

Presurgical accuracy of dipole clustering in MRI-negative pediatric patients with epilepsy: Validation against intracranial EEG and resection.

OBJECTIVE: To assess the utility of interictal magnetic and electric source imaging (MSI and ESI) using dipole clustering in magnetic resonance imaging (MRI)-negative patients with drug resistant epilepsy (DRE). METHODS: We localized spikes in low-density (LD-EEG) and high-density (HD-EEG) electroencephalography as well as magnetoencephalography (MEG) recordings using dipoles from 11 pediatric patients. We computed each dipole's level of clustering and used it to discriminate between clustered and scattered dipoles. For each dipole, we computed the distance from seizure onset zone (SOZ) and irritative zone (IZ) defined by intracranial EEG. Finally, we assessed whether dipoles proximity to resection was predictive of outcome. RESULTS: LD-EEG had lower clusterness compared to HD-EEG and MEG (p < 0.05). For all modalities, clustered dipoles showed higher proximity to SOZ and IZ than scattered (p < 0.001). Resection percentage was higher in optimal vs. suboptimal outcome patients (p < 0.001); their proximity to resection was correlated to outcome (p < 0.001). No difference in resection percentage was seen for scattered dipoles between groups. CONCLUSION: MSI and ESI dipole clustering helps to localize the SOZ and IZ and facilitate the prognostic assessment of MRI-negative patients with DRE. SIGNIFICANCE: Assessing the MSI and ESI clustering allows recognizing epileptogenic areas whose removal is associated with optimal outcome.

Mapping Functional Connectivity of Epileptogenic Networks through Virtual Implantation.

Children with medically refractory epilepsy (MRE) require resective neurosurgery to achieve seizure freedom, whose success depends on accurate delineation of the epileptogenic zone (EZ). Functional connectivity (FC) can assess the extent of epileptic brain networks since intracranial EEG (icEEG) studies have shown its link to the EZ and predictive value for surgical outcome in these patients. Here, we propose a new noninvasive method based on magnetoencephalography (MEG) and high-density (HD-EEG) data that estimates FC metrics at the source level through an "implantation" of virtual sensors (VSs). We analyzed MEG, HD-EEG, and icEEG data from eight children with MRE who underwent surgery having good outcome and performed source localization (beamformer) on noninvasive data to build VSs at the icEEG electrode locations. We analyzed data with and without Interictal Epileptiform Discharges (IEDs) in different frequency bands, and computed the following FC matrices: Amplitude Envelope Correlation (AEC), Correlation (CORR), and Phase Locking Value (PLV). Each matrix was used to generate a graph using Minimum Spanning Tree (MST), and for each node (i.e., each sensor) we computed four centrality measures: betweenness, closeness, degree, and eigenvector. We tested the reliability of VSs measures with respect to icEEG (regarded as benchmark) via linear correlation, and compared FC values inside vs. outside resection. We observed higher FC inside than outside resection (p<0.05) for AEC [alpha (8-12 Hz), beta (12-30 Hz), and broadband (1-50 Hz)] on data with IEDs and AEC theta (4-8 Hz) on data without IEDs for icEEG, AEC broadband (1-50 Hz) on data without IEDs for MEG-VSs, as well as for all centrality measures of icEEG and MEG/HD-EEG-VSs. Additionally, icEEG and VSs metrics presented high correlation (0.6-0.9, p<0.05). Our data support the notion that the proposed method can potentially replicate the icEEG ability to map the epileptogenic network in children with MRE.Clinical Relevance - The estimation of FC with noninvasive techniques, such as MEG and HD-EEG, via VSs is a promising tool that would help the presurgical evaluation by delineating the EZ without waiting for a seizure to occur, and potentially improve the surgical outcome of patients with MRE undergoing surgery.

Electric Source Imaging on Intracranial EEG Localizes Spatiotemporal Propagation of Interictal Spikes in Children with Epilepsy.

Interictal epileptiform discharges (IEDs) serve as sensitive but not specific biomarkers of epilepsy that can delineate the epileptogenic zone (EZ) in patients with drug resistant epilepsy (DRE) undergoing surgery. Intracranial EEG (icEEG) studies have shown that IEDs propagate in time across large areas of the brain. The onset of this propagation is regarded as a more specific biomarker of epilepsy than areas of spread. Yet, the limited spatial resolution of icEEG does not allow to identify the onset of this activity with high precision. Here, we propose a new method of mapping the spatiotemporal propagation of IEDs (and identify its onset) by using Electrical Source Imaging (ESI) on icEEG bypassing the spatial limitations of icEEG. We validated our method on icEEG recordings from 8 children with DRE who underwent surgery with good outcome (Engel score =1). On each icEEG channel, we detected IEDs and identified the propagation onset using an automated algorithm. We localized the propagation of IEDs with dynamic Statistical Parametric Mapping (dSPM) using a time-sliding window approach. We defined two brain regions: the ESI-onset and ESI-spread zone. We estimated the overlap of these regions with resection volume (in percentage), which served as the gold-standard of the EZ. We also estimated the mean distance of these regions from resection and clinically defined seizure onset zone (SOZ). We observed spatio-temporal propagation of IEDs in all patients across several channels (98 [85-102]) with a mean duration of 155 ms [96-186 ms]. A higher overlap with resection was seen for the ESI-onset zone compared to spread (73.3 % [ 47.4-100 %], 36.5 % [20.3-59.9 %], p = 0.008). The distance of the ESI-onset from resection was shorter compared to the ESI-spread zone (4.3 mm [3.4-5.5 mm], 7.4 mm [6.0-20.6 mm], p = 0.008) and the same trend was observed for the distance from the SOZ (11.9 mm [7.2-15.1 mm], 20.6 mm [15.4-27.2 mm], p = 0.02). These findings show that our method can map the spatiotemporal propagation of IEDs and de-lineate its onset, which is a reliable and focal biomarker of the EZ in children with DRE.Clinical Relevance - ESI on icEEG recordings of children with DRE can localize the spikes propagation phenomenon and help in the delineation of the EZ.

Extensions of Granger Causality Calculations on Brain Networks for Efficient and Accurate Seizure Focus Identification via iEEGs.

Current epilepsy surgery planning protocol determines the seizure onset zone (SOZ) through resource-intensive, invasive monitoring of ictal events. Recently, we have reported that Granger Causality (GC) maps produced from analysis of interictal iEEG recordings have potential in revealing SOZ. In this study, we investigate GC maps' network connectivity patterns to determine possible clinical correlation with patients' SOZ and resection zone (RZ). While building understanding of interictal network topography and its relationship to the RZ/SOZ, we identify algorithmic tools with potential applications in epilepsy surgery planning. These graph algorithms are retrospectively tested on data from 25 patients and compared to the neurologist-determined SOZ and surgical RZ, viewed as sources of truth. Centrality algorithms yielded statistically significant RZ rank order sums for 16 of 24 patients with RZ data, representing an improvement from prior algorithms. While SOZ results remained largely the same, this study validates the applicability of graph algorithms to RZ/SOZ detection, opening the door to further exploration of iEEG datasets. Furthermore, this study offers previously inaccessible insights into the relationship between interictal brain connectivity patterns and epileptic brain networks, utilizing the overall topology of the graphs as well as data on edge weights and quantity of edges contained in GC maps.