Diagnostic utility of invasive EEG for epilepsy surgery: Indications, modalities, and techniques

Cost-effectiveness of invasive monitoring strategies in epilepsy surgery

OBJECTIVE

Drug-resistant epilepsy occurs in up to 40% of patients with epilepsy who may be considered for epilepsy surgery. For drug-resistant focal epilepsy, up to 50% of patients require invasive monitoring prior to surgery. Of the most common invasive monitoring strategies (subdural electrodes [SDEs] and stereo-electroencephalography [sEEG]), the most cost-effective strategy is unknown despite substantial differences in morbidity profiles.

METHODS

Using data collected from an internationally representative sample published in available systematic reviews and meta-analyses, this economic evaluation study employs a decision analysis model to simulate the risks and benefits of SDE and sEEG invasive monitoring strategies. In this model, patients faced differing risks of morbidity, mortality, resection, and seizure freedom depending on which invasive monitoring strategy they underwent. A range of cost values was obtained from a recently published single-center cost-utility analysis. The model considers a base case simulation of a characteristic patient with drug-resistant epilepsy using clinical parameters obtained from systematic reviews of invasive monitoring available in the literature. The main outcome measure was the probability of a positive outcome after invasive monitoring, which was defined as improvement in seizures without a complication. Cost-effectiveness was measured using an incremental cost-effectiveness ratio (ICER).

RESULTS

Invasive monitoring with sEEG had an increased cost of $274 and increased probability of effectiveness of 0.02 compared with SDEs, yielding an ICER of $12,630 per positive outcome obtained. Sensitivity analyses varied parameters widely and revealed consistent model results across the range of clinical parameters reported in the literature. One-way sensitivity analyses revealed that invasive monitoring strategy costs were the most influential parameter for model outcome.

CONCLUSIONS

In this analysis, based on available observational data and estimates of complication costs, invasive monitoring with either SDEs or sEEG was nearly equivalent in terms of cost-effectiveness.

Interictal Functional Connectivity in Focal Refractory Epilepsies Investigated by Intracranial EEG

Introduction: Focal epilepsies are diseases of neuronal excitability affecting macroscopic networks of cortical and subcortical neural structures. These networks ("epileptogenic networks") can generate pathological electrophysiological activities during seizures, and also between seizures (interictal period). Many works attempt to describe these networks by using quantification methods, particularly based on the estimation of statistical relationships between signals produced by brain regions, namely functional connectivity (FC). Results: FC has been shown to be greatly altered during seizures and in the immediate peri-ictal period. An increasing number of studies have shown that FC is also altered during the interictal period depending on the degree of epileptogenicity of the structures. Furthermore, connectivity values could be correlated with other clinical variables including surgical outcome. Significance: This leads to a conceptual change and to consider epileptic areas as both hyperexcitable and abnormally connected. These data open the door to the use of interictal FC as a marker of epileptogenicity and as a complementary tool for predicting the effect of surgery. Aim: In this article, we review the available data concerning interictal FC estimated from intracranial electroencephalograhy (EEG) in focal epilepsies and discuss it in the light of data obtained from other modalities (EEG imaging) and modeling studies.

Speech decoding from a small set of spatially segregated minimally invasive intracranial EEG electrodes with a compact and interpretable neural network

Objective. Speech decoding, one of the most intriguing brain-computer interface applications, opens up plentiful opportunities from rehabilitation of patients to direct and seamless communication between human species. Typical solutions rely on invasive recordings with a large number of distributed electrodes implanted through craniotomy. Here we explored the possibility of creating speech prosthesis in a minimally invasive setting with a small number of spatially segregated intracranial electrodes.Approach. We collected one hour of data (from two sessions) in two patients implanted with invasive electrodes. We then used only the contacts that pertained to a single stereotactic electroencephalographic (sEEG) shaft or an electrocorticographic (ECoG) stripe to decode neural activity into 26 words and one silence class. We employed a compact convolutional network-based architecture whose spatial and temporal filter weights allow for a physiologically plausible interpretation.Mainresults. We achieved on average 55% accuracy using only six channels of data recorded with a single minimally invasive sEEG electrode in the first patient and 70% accuracy using only eight channels of data recorded for a single ECoG strip in the second patient in classifying 26+1 overtly pronounced words. Our compact architecture did not require the use of pre-engineered features, learned fast and resulted in a stable, interpretable and physiologically meaningful decision rule successfully operating over a contiguous dataset collected during a different time interval than that used for training. Spatial characteristics of the pivotal neuronal populations corroborate with active and passive speech mapping results and exhibit the inverse space-frequency relationship characteristic of neural activity. Compared to other architectures our compact solution performed on par or better than those recently featured in neural speech decoding literature.Significance. We showcase the possibility of building a speech prosthesis with a small number of electrodes and based on a compact feature engineering free decoder derived from a small amount of training data.

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.

Organic Neuroelectronics: From Neural Interfaces to Neuroprosthetics

Requirements and recent advances in research on organic neuroelectronics are outlined herein. Neuroelectronics such as neural interfaces and neuroprosthetics provide a promising approach to diagnose and treat neurological diseases. However, the current neural interfaces are rigid and not biocompatible, so they induce an immune response and deterioration of neural signal transmission. Organic materials are promising candidates for neural interfaces, due to their mechanical softness, excellent electrochemical properties, and biocompatibility. Also, organic nervetronics, which mimics functional properties of the biological nerve system, is being developed to overcome the limitations of the complex and energy-consuming conventional neuroprosthetics that limit long-term implantation and daily-life usage. Examples of organic materials for neural interfaces and neural signal recordings are reviewed, recent advances of organic nervetronics that use organic artificial synapses are highlighted, and then further requirements for neuroprosthetics are discussed. Finally, the future challenges that must be overcome to achieve ideal organic neuroelectronics for next-generation neuroprosthetics are discussed.

Thalamic stereoelectroencephalography in epilepsy surgery: a scoping literature review

OBJECTIVE

Stereoelectroencephalography (sEEG) is a well-established surgical method for defining the epileptogenic network. Traditionally reserved for identifying discrete cortical regions for resection or ablation, sEEG in current practice is also used for identifying more broadly involved subcortical epileptic network components, driven by the availability of brain-based neuromodulation strategies. In particular, sEEG investigations including thalamic nuclei are becoming more frequent in parallel with the increase in therapeutic strategies involving thalamic targets such as deep brain stimulation (DBS) and responsive neurostimulation (RNS). The objective to this study was to evaluate existing evidence and trends regarding the purpose, techniques, and relevant electrographic findings of thalamic sEEG.

METHODS

MEDLINE and Embase databases were systematically queried for eligible peer-reviewed studies involving sEEG electrode implantation into thalamic nuclei of patients with epilepsy. Available data were abstracted concerning preoperative workup and purpose for implanting the thalamus, thalamic targets and trajectories, and electrophysiological methodology and findings.

RESULTS

sEEG investigations have included thalamic targets for both basic and clinical research purposes. Medial pulvinar, dorsomedial, anterior, and centromedian nuclei have been the most frequently studied. Few studies have reported any complications with thalamic sEEG implantation, and no studies have reported long-term complications. Various methods have been utilized to characterize thalamic activity in epileptic disorders including evoked potentials, power spectrograms, synchronization indices, and the epileptogenicity index. Thalamic intracranial recordings are beginning to be used to guide neuromodulation strategies including RNS and DBS, as well as to understand complex, network-dependent seizure disorders.

CONCLUSIONS

Inclusion of thalamic coverage during sEEG evaluation in drug-resistant epilepsy is a growing practice and is amenable to various methods of electrographic data analysis. Further study is required to establish well-defined criteria for thalamic implantation during invasive investigations as well as safety and ethical considerations.

Electrochemical Testing of a New Polyimide Thin Film Electrode for Stimulation, Recording, and Monitoring of Brain Activity

Subdural electrode arrays are used for monitoring cortical activity and functional brain mapping in patients with seizures. Until recently, the only commercially available arrays were silicone-based, whose thickness and lack of conformability could impact their performance. We designed, characterized, manufactured, and obtained FDA clearance for 29-day clinical use (510(k) K192764) of a new thin-film polyimide-based electrode array. This study describes the electrochemical characterization undertaken to evaluate the quality and reliability of electrical signal recordings and stimulation of these new arrays. Two testing paradigms were performed: a short-term active soak with electrical stimulation and a 29-day passive soak. Before and after each testing paradigm, the arrays were evaluated for their electrical performance using Electrochemical Impedance Spectroscopy (EIS), Cyclic Voltammetry (CV) and Voltage Transients (VT). In all tests, the impedance remained within an acceptable range across all frequencies. The different CV curves showed no significant changes in shape or area, which is indicative of stable electrode material. The electrode polarization remained within appropriate limits to avoid hydrolysis.

Stereoelectroencephalography before 2 years of age

OBJECTIVE

Stereoelectroencephalography (SEEG) is a widely used technique for localizing seizure onset zones prior to resection. However, its use has traditionally been avoided in children under 2 years of age because of concerns regarding pin fixation in the immature skull, intraoperative and postoperative electrode bolt security, and stereotactic registration accuracy. In this retrospective study, the authors describe their experience using SEEG in patients younger than 2 years of age, with a focus on the procedure’s safety, feasibility, and accuracy as well as surgical outcomes.

METHODS

A retrospective review of children under 2 years of age who had undergone SEEG while at Children’s Hospital of Philadelphia between November 2017 and July 2021 was performed. Data on clinical characteristics, surgical procedure, imaging results, electrode accuracy measurements, and postoperative outcomes were examined.

RESULTS

Five patients younger than 2 years of age underwent SEEG during the study period (median age 20 months, range 17–23 months). The mean age at seizure onset was 9 months. Developmental delay was present in all patients, and epilepsy-associated genetic diagnoses included tuberous sclerosis (n = 1), KAT6B (n = 1), and NPRL3 (n = 1). Cortical lesions included tubers from tuberous sclerosis (n = 1), mesial temporal sclerosis (n = 1), and cortical dysplasia (n = 3). The mean number of placed electrodes was 11 (range 6–20 electrodes). Bilateral electrodes were placed in 1 patient. Seizure onset zones were identified in all cases. There were no SEEG-related complications, including skull fracture, electrode misplacement, hemorrhage, infection, cerebrospinal fluid leakage, electrode pullout, neurological deficit, or death. The mean target point error for all electrodes was 1.0 mm. All patients proceeded to resective surgery, with a mean follow-up of 21 months (range 8–53 months). All patients attained a favorable epilepsy outcome, including Engel class IA (n = 2), IC (n = 1), ID (n = 1), and IIA (n = 1).

CONCLUSIONS

SEEG can be safely, accurately, and effectively utilized in children under age 2 with good postoperative outcomes using standard SEEG equipment. With minimal modification, this procedure is feasible in those with immature skulls and guides the epilepsy team’s decision-making for early and optimal treatment of refractory epilepsy through effective localization of seizure onset zones.

Subdural electrodes versus stereoelectroencephalography for pediatric epileptogenic zone localization: a retrospective cohort study

OBJECTIVE

The objective of this study was to compare the relative safety and effectiveness of invasive monitoring with subdural electrodes (SDEs) and stereoelectroencephalography (sEEG) in pediatric patients with drug-resistant epilepsy.

METHODS

A retrospective cohort study was performed in 176 patients who underwent invasive monitoring evaluations at UPMC Children’s Hospital of Pittsburgh between January 2000 and September 2021. To examine differences between SDE and sEEG groups, independent-samples t-tests for continuous variables and Pearson chi-square tests for categorical variables were performed. A p value < 0.1 was considered statistically significant.

RESULTS

There were 134 patients (76%) in the SDE group and 42 (24%) in the sEEG group. There was a difference in the proportion with complications (17.9% in the SDE group vs 7.1% in the sEEG group, p = 0.09) and resection (75.4% SDE vs 21.4% sEEG, p < 0.01) between SDE and sEEG patients. However, there was no observable difference in the rates of postresection seizure freedom at 1-year clinical follow-up (60.2% SDE vs 75.0% sEEG, p = 0.55).

CONCLUSIONS

These findings reveal a difference in rates of surgical complications and resection between SDEs and sEEG. Larger prospective, multi-institutional pediatric comparative effectiveness studies may further explore these associations.

Patient-specific solution of the electrocorticography forward problem in deforming brain

Invasive intracranial electroencephalography (iEEG), or electrocorticography (ECoG), measures electric potential directly on the surface of the brain and can be used to inform treatment planning for epilepsy surgery. Combined with numerical modeling it can further improve accuracy of epilepsy surgery planning. Accurate solution of the iEEG forward problem, which is a crucial prerequisite for solving the iEEG inverse problemin epilepsy seizure onset zone localization, requires accurate representation of the patient's brain geometry and tissue electrical conductivity after implantation of electrodes. However, implantation of subdural grid electrodes causes the brain to deform, which invalidates preoperatively acquired image data. Moreover, postoperative magnetic resonance imaging (MRI) is incompatible with implanted electrodes and computed tomography (CT) has insufficient range of soft tissue contrast, which precludes both MRI and CT from being used to obtain the deformed postoperative geometry. In this paper, we present a biomechanics-based image warping procedure using preoperative MRI for tissue classification and postoperative CT for locating implanted electrodes to perform non-rigid registration of the preoperative image data to the postoperative configuration. We solve the iEEG forward problem on the predicted postoperative geometry using the finite element method (FEM) which accounts for patient-specific inhomogeneity and anisotropy of tissue conductivity. Results for the simulation of a current source in the brain show large differences in electric potential predicted by the models based on the original images and the deformed images corresponding to the brain geometry deformed by placement of invasive electrodes. Computation of the lead field matrix (useful for solution of the iEEG inverse problem) also showed significant differences between the different models. The results suggest that rapid and accurate solution of the forward problem in a deformed brain for a given patient is achievable.

Stimulation induced aura during subdural recording: A useful predictor of postoperative outcome in refractory epilepsy

INTRODUCTION

Electrical cortical stimulation (ECS) is a routine procedure commonly conducted in intracranial EEG (iEEG) monitoring in refractory epilepsy and associated with postoperative outcome in stereoelectroencephalography (SEEG) exploration. To better understand this effective method, this study aimed to examine the role of ECS in subdural recording.

METHODS

The ECS results of 144 consecutive patients who were monitored via subdural electrodes and received epilepsy surgery were retrospectively collected. The occurrence of stimulation induced aura (SIA) and seizure (SIS) and their distributions as well as their associations with postoperative outcomes were analyzed.

RESULTS

Among all 144 patients, 47.2% (68/144) achieved Engel class I recovery with a mean follow-up of 6.6±2.2 years (2.0-9.8 years). The percentages of patients who showed SIA and SIS were 16.0% (23/144) and 43.8% (63/144), respectively. Our data indicated that 30.4% (42/138) of SIS occurred in frontal lobe, which was significantly higher than the 7.7% (10/130) occurred in temporal lobe and the 8.5% (11/129) in parieto-occipital region (p<0.001). Meanwhile, no such distribution difference was discovered in SIA (p=0.229). Univariate and multifactorial analyses showed that SIA was the only independent predictor for postoperative outcome and patients with SIA were 4.8 times more likely to achieve seizure-free (95% CI 1.557-14.789, p = 0.006).

CONCLUSIONS

Our study demonstrated that SIS sites are more likely to be located in the frontal lobe and SIA independently predicts optimal postoperative outcome in subdural recording.

In Vivo Neural Interfaces—From Small- to Large-Scale Recording

Brain functions arise from the coordinated activation of neuronal assemblies distributed across multiple brain regions. The electrical potential from the neuron captured by the electrode can be processed to extract brain information. A large number of densely and simultaneously recorded neuronal potential signals from neurons spanning multiple brain regions contribute to the insight of specific behaviors encoded by the neural ensembles. In this review, we focused on the neural interfaces developed for small- to large-scale recordings and discussed the developmental challenges and strategies in microsystem, electrode device, and interface material levels for the future larger-scale neural ensemble recordings.

Stereo-Encephalographic Presurgical Evaluation of Temporal Lobe Epilepsy: An Evolving Science

Drug-resistant epilepsy is present in nearly 30% of patients. Resection of the epileptogenic zone has been found to be the most effective in achieving seizure freedom. The study of temporal lobe epilepsy for surgical treatment is extensive and complex. It involves a multidisciplinary team in decision-making with initial non-invasive studies (Phase I), providing 70% of the required information to elaborate a hypothesis and treatment plans. Select cases present more complexity involving bilateral clinical or electrographic manifestations, have contradicting information, or may involve deeper structures as a part of the epileptogenic zone. These cases are discussed by a multidisciplinary team of experts with a hypothesis for invasive methods of study. Subdural electrodes were once the mainstay of invasive presurgical evaluation and in later years most Comprehensive Epilepsy Centers have shifted to intracranial recordings. The intracranial recording follows original concepts since its development by Bancaud and Talairach, but great advances have been made in the field. Stereo-electroencephalography is a growing field of study, treatment, and establishment of seizure pattern complexities. In this comprehensive review, we explore the indications, usefulness, discoveries in interictal and ictal findings, pitfalls, and advances in the science of presurgical stereo-encephalography for temporal lobe epilepsy.

Presurgical video-EEG monitoring with foramen ovale and epidural peg electrodes: a 25-year perspective

Background

Epilepsy surgery cases are becoming more complex and increasingly require invasive video-EEG monitoring (VEM) with intracranial subdural or intracerebral electrodes, exposing patients to substantial risks. We assessed the utility and safety of using foramen ovale (FO) and epidural peg electrodes (FOP) as a next step diagnostic approach following scalp VEM.

Methods

We analyzed clinical, electrophysiological, and imaging characteristics of 180 consecutive patients that underwent FOP VEM between 1996 and 2021. Multivariate logistic regression was used to assess predictors of clinical and electrophysiological outcomes.

Results

FOP VEM allowed for immediate resection recommendation in 36 patients (20.0%) and excluded this option in 85 (47.2%). Fifty-nine (32.8%) patients required additional invasive EEG investigations; however, only eight with bilateral recordings. FOP VEM identified the ictal onset in 137 patients, compared to 96 during prior scalp VEM, p = .004. Predictors for determination of ictal onset were temporal lobe epilepsy (OR 2.9, p = .03) and lesional imaging (OR 3.1, p = .01). Predictors for surgery recommendation were temporal lobe epilepsy (OR 6.8, p < .001), FO seizure onset (OR 6.1, p = .002), and unilateral interictal epileptic activity (OR 3.8, p = .02). One-year postsurgical seizure freedom (53.3% of patients) was predicted by FO ictal onset (OR 5.8, p = .01). Two patients experienced intracerebral bleeding without persisting neurologic sequelae.

Conclusion

FOP VEM adds clinically significant electrophysiological information leading to treatment decisions in two-thirds of cases with a good benefit–risk profile. Predictors identified for electrophysiological and clinical outcome can assist in optimally selecting patients for this safe diagnostic approach.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-022-11208-6.

Non-invasive sleep EEG measurement in hand raised wolves

Sleep research greatly benefits from comparative studies to understand the underlying physiological and environmental factors affecting the different features of sleep, also informing us about the possible evolutionary changes shaping them. Recently, the domestic dog became an exceedingly valuable model species in sleep studies, as the use of non-invasive polysomnography methodologies enables direct comparison with human sleep data. In this study, we applied the same polysomnography protocol to record the sleep of dog’s closest wild relative, the wolf. We measured the sleep of seven captive (six young and one senior), extensively socialized wolves using a fully non-invasive sleep EEG methodology, originally developed for family dogs. We provide the first descriptive analysis of the sleep macrostructure and NREM spectral power density of wolves using a completely non-invasive methodology. For (non-statistical) comparison, we included the same sleep data of similarly aged dogs. Although our sample size was inadequate to perform statistical analyses, we suggest that it may form the basis of an international, multi-site collection of similar samples using our methodology, allowing for generalizable, unbiased conclusions. As we managed to register both macrostructural and spectral sleep data, our procedure appears to be suitable for collecting valid data in other species too, increasing the comparability of non-invasive sleep studies.

Virtual Epileptic Patient brain modeling: relationships with seizure onset and surgical outcome

Objective

The virtual epileptic patient (VEP) is a large‐scale brain modeling method based on virtual brain technology, using stereoelectroencephalography (SEEG), anatomical data (magnetic resonance imaging [MRI] and connectivity), and a computational neuronal model to provide computer simulations of a patient's seizures. VEP has potential interest in the presurgical evaluation of drug‐resistant epilepsy by identifying regions most likely to generate seizures. We aimed to assess the performance of the VEP approach in estimating the epileptogenic zone and in predicting surgical outcome.

Methods

VEP modeling was retrospectively applied in a cohort of 53 patients with pharmacoresistant epilepsy and available SEEG, T1‐weighted MRI, and diffusion‐weighted MRI. Precision recall was used to compare the regions identified as epileptogenic by VEP (EZ_VEP) to the epileptogenic zone defined by clinical analysis incorporating the Epileptogenicity Index (EI) method (EZ_C). In 28 operated patients, we compared the VEP results and clinical analysis with surgical outcome.

Results

VEP showed a precision of 64% and a recall of 44% for EZ_VEP detection compared to EZ_C. There was a better concordance of VEP predictions with clinical results, with higher precision (77%) in seizure‐free compared to non‐seizure‐free patients. Although the completeness of resection was significantly correlated with surgical outcome for both EZ_C and EZ_VEP, there was a significantly higher number of regions defined as epileptogenic exclusively by VEP that remained nonresected in non‐seizure‐free patients.

Significance

VEP is the first computational model that estimates the extent and organization of the epileptogenic zone network. It is characterized by good precision in detecting epileptogenic regions as defined by a combination of visual analysis and EI. The potential impact of VEP on improving surgical prognosis remains to be exploited. Analysis of factors limiting the performance of the actual model is crucial for its further development.

EEG Essentials

PURPOSE OF REVIEW

EEG is the best study for evaluating the electrophysiologic function of the brain. The relevance of EEG is based on an accurate interpretation of the recording. Understanding the neuroscientific basis for EEG is essential. The basis for recording and interpreting EEG is both brain site-specific and technique-dependent to detect and represent a complex series of waveforms. Separating normal from abnormal EEG lies at the foundation of essential interpretative skills.

RECENT FINDINGS

Seizures and epilepsy are the primary targets for clinical use of EEG in diagnosis, seizure classification, and management. Interictal epileptiform discharges on EEG support a clinical diagnosis of seizures, but only when an electrographic seizure is recorded is the diagnosis confirmed. New variations of normal waveforms, benign variants, and artifacts can mimic epileptiform patterns and are potential pitfalls for misinterpretation for inexperienced interpreters. A plethora of medical conditions involve nonepileptiform and epileptiform abnormalities on EEG along the continuum of people who appear healthy to those who are critically ill. Emerging trends in long-term EEG monitoring to diagnose, classify, quantify, and characterize patients with seizures have unveiled epilepsy syndromes in patients and expanded medical and surgical options for treatment. Advances in terminology and application of continuous EEG help unify neurologists in the diagnosis of nonconvulsive seizures and status epilepticus in patients with encephalopathy and prognosticate recovery from serious neurologic injury involving the brain.

SUMMARY

After 100 years, EEG has retained a key role in the neurologist's toolkit as a safe, widely available, versatile, portable test of neurophysiology, and it is likely to remain at the forefront for patients with neurologic diseases. Interpreting EEG is based on qualitative review, and therefore, the accuracy of reporting is based on the interpreter's training, experience, and exposure to many new and older waveforms.

Epidural grid, a new methodology of invasive intracranial EEG monitoring: A technical note and experience of a single center

INTRODUCTION

Subdural grid monitoring (SDG) has the advantage to provide continuous coverage over a larger area of cortex, direct visualization of electrode location and functional mapping. However, SDG can cause direct irritation of the cortex or postoperative headaches due to cerebrospinal fluid (CSF) leakage. Epidural grid monitoring (EDG) without opening the dura is thought to reduce the possibility of these complications. We report our experience with EDG.

METHODS

We described our surgical technique of EDG in invasive intracranial electroencephalography (iEEG) monitoring. A retrospective review of 30 patients who underwent grid placement of iEEG between March 2019 and December 2020 was performed to compare SDG and EDG.

RESULTS

Of the 30 patients, 10 patients underwent SDG and 20 patients underwent EDG. There was no difference in age between SDG and EDG groups (p = 0.13). Also, there was no difference in the number of grid electrodes, craniotomy size, number of electrodes per craniotomy area and postoperative complication rate (p = 0.32, 0.84, 0.58 and 0.40). However, the maximum number of electrodes that have been undermined from the bone margin was much higher in SDG group (SDG 4.6 ± 2.2 vs. EDG 2.0 ± 0.9; p = 0.001). The demand for postoperative analgesics was significantly lower in EDG group (SDG 13.4 ± 9.1 vs. EDG 4.1 ± 4.3; p = 0.012); and the demand for postoperative antiemetics also tended to be low (SDG 4.6 ± 3.6 vs. EDG 1.8 ± 1.6; p = 0.078).

CONCLUSIONS

There was no significant difference in craniotomy and electrode insertion between the two groups; however, the EDG group showed less postoperative headache and nausea. Though not in direct contact with the cortex, the quality of the electrophysiological signal received through the electrode in EDG is comparable to that of the SDG. The EDG enables to detect the onset of seizure and delineate the epileptogenic zone sufficiently. Moreover, functional mapping is possible with EDG. Therefore, EDG has the sufficient potential to replace SDG for monitoring of the lateral surface of brain.

Safety of Intracranial Electroencephalography During Functional Electromagnetic Resonance Imaging in Humans at 1.5 Tesla Using a Head Transmit RF Coil: Histopathological and Heat-Shock Immunohistochemistry Observations

OBJECTIVES

Simultaneous intracranial EEG and functional MRI (icEEG-fMRI) recordings in humans, whereby EEG is recorded from electrodes implanted inside the cranium during fMRI scanning, were made possible following safety studies on test phantoms and our specification of a rigorous data acquisition protocol. In parallel with this work, other investigations in our laboratory revealed the damage caused by the EEG electrode implantation procedure at the cellular level. The purpose of this report is to further explore the safety of performing MRI, including simultaneous icEEG-fMRI data acquisitions, in the presence of implanted intra-cranial EEG electrodes, by presenting some histopathological and heat-shock immunopositive labelling observations in surgical tissue samples from patients who underwent the scanning procedure.

METHODS

We performed histopathology and heat shock protein expression analyses on surgical tissue samples from nine patients who had been implanted with icEEG electrodes. Three patients underwent icEEG-fMRI and structural MRI (sMRI); three underwent sMRI only, all at similar time points after icEEG implantation; and three who did not undergo functional or sMRI with icEEG electrodes.

RESULTS

The histopathological findings from the three patients who underwent icEEG-fMRI were similar to those who did not, in that they showed no evidence of additional damage in the vicinity of the electrodes, compared to cases who had no MRI with implanted icEEG electrodes. This finding was similar to our observations in patients who only underwent sMRI with implanted icEEG electrodes.

CONCLUSION

This work provides unique evidence on the safety of functional MRI in the presence of implanted EEG electrodes. In the cases studied, icEEG-fMRI performed in accordance with our protocol based on low-SAR (≤0.1 W/kg) sequences at 1.5T using a head-transmit RF coil, did not result in measurable additional damage to the brain tissue in the vicinity of implanted electrodes. Furthermore, while one cannot generalize the results of this study beyond the specific electrode implantation and scanning conditions described herein, we submit that our approach is a useful framework for the post-hoc safety assessment of MR scanning with brain implants.

Utilization of Epidural Electrodes as a Diagnostic Tool in Intractable Epilepsy—A Technical Note

The utilization of epidural electrodes in the preoperative evaluation of intractable epilepsy is a valuable but underrepresented tool. In recent years, we have adapted the use of cylindrical epidural 1-contact electrodes (1-CE) instead of Peg electrodes. 1-CEs are more versatile since their explantation is a possible bedside procedure. Here we report our experience with 1-CEs as well as associated technical nuances. This retrospective analysis included 56 patients with intractable epilepsy who underwent epidural electrode placement for presurgical evaluation at the Department of Neurosurgery at the Charité University Hospital from September 2011 to July 2021. The median age at surgery was 36.3 years (range: 18–87), with 30 (53.6%) female and 26 (46.4%) male patients. Overall, 507 electrodes were implanted: 93 Fo electrodes, 33 depth electrodes, and 381 epidural electrodes, with a mean total surgical time of 100.5 ± 38 min and 11.8 ± 5 min per electrode. There was a total number of 24 complications in 21 patients (8 Fo electrode dislocations, 6 CSF leaks, 6 epidural electrode dislocations or malfunction, 3 wound infections, and 2 hemorrhages); 11 of these required revision surgery. The relative electrode complication rates were 3/222 (1.4%) in Peg electrodes and 3/159 (1.9%) in 1-CE. In summary, epidural recording via 1-CE is technically feasible, harbours an acceptable complication rate, and adequately replaces Peg electrodes.

Underutilization of advanced presurgical studies and high rates of vagus nerve stimulation for drug-resistant epilepsy: a single-center experience and recommendations

INTRODUCTION

Epilepsy surgery continues to be profoundly underutilized despite its safety and effectiveness. We sought to investigate factors that may contribute to this phenomenon, with a particular focus on the antecedent underutilization of appropriate preoperative studies.

METHODS

We reviewed patient data from a pediatric epilepsy clinic over an 18-month period. Patients with drug-resistant epilepsy (DRE) were categorized according to brain magnetic resonance imaging (MRI) findings (lesional, MRI-negative, or multifocal abnormalities) and type of epilepsy diagnosis based on semiology and electroencephalography (EEG) (focal or generalized). We then analyzed the rates of diagnostic test utilization, surgical referral, and subsequent epilepsy surgery as well as vagus nerve stimulation (VNS).

RESULTS

Of the 249 patients with a diagnosis of epilepsy, 138 (55.4%) were found to have DRE. Excluding the 10 patients with DRE who did not undergo MRI, 76 patients (59.4%) were found to be MRI-negative (non-lesional epilepsy), 37 patients (28.9%) were found to have multifocal abnormalities, and 15 patients (11.7%) were found to have a single epileptogenic lesion on MRI (lesional epilepsy). Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) were each completed in nine patients (7.0%) and magnetoencephalography (MEG) in four patients (3.1%). Despite the low utilization rate of adjunctive studies, over half (56.3%) ultimately underwent VNS alone, and 8.6% ultimately underwent definitive intracranial resection or disconnection surgery.

CONCLUSIONS

The underutilization of appropriate non-invasive, presurgical testing in patients with focal DRE may in part explain the continued underutilization of definitive, resective/disconnective surgery. For patients without access to a high-volume, multidisciplinary surgical epilepsy center, adjunctive presurgical studies [e.g., PET, SPECT, MEG, electrical source imaging (ESI), EEG-functional magnetic resonance imaging (fMRI)], even when available, are rarely ordered, and this may contribute to excessive rates of VNS in lieu of definitive intracranial surgery.

Theoretical stereoelectroencephalography density on the brain convexity

INTRODUCTION

Invasive electroencephalography (EEG) remains the "gold standard" for diagnosing the epileptogenic zone in patients with drug-resistant epilepsy and discrepancies between seizure semiology, video-EEG and magnetic resonance imaging (MRI) findings. However, the possibilities of stereoelectroencephalography (SEEG) to explore the brain surface remain a matter of debate and subdural EEG (SDEEG) is still preferred in some centers for cases when the supposed epileptogenic zone is on the brain convexity. The aim of our study was to evaluate the theoretical safe SEEG coverage on the brain convexity and to compare the theoretical SEEG cortical density with the usual SDEEG density.

MATERIALS AND METHODS

Our material included 10 hemispheres in 5 patients, who had been already investigated with SEEG for drug-resistant epilepsy. We translated our previously described technique in a theoretical model in an attempt to calculate the maximal number of avascular windows for each cerebral hemisphere. The distance between every entry point and the other entry points for each hemisphere was calculated using a mathematical formula. Subsequently, the theoretical SEEG coverage on the brain convexity was described using the maximal, minimal and average distances between each entry point and the closest 4 neighboring points. This type of measurement allows a direct comparison between SEEG and SDEEG in their ability to explore the brain convexity.

RESULTS

Ten hemispheres had 1328 safe entry points with a safety margin of 2.5 mm and a minimal distance of 2.5 mm between 2 entry points (average number of entry points: 132.8 (SD ± 5). The number of entry points in the explored 10 hemispheres varied from 104 to 156. The average distance between each entry point and its 4 neighbors was 11.47 mm. The maximal distance between two entry points in these 10 hemispheres was ranging from 20.28 to 27.23 mm (average: 24.67 mm). The closest entry points for the explored hemispheres were at an average distance of 4.67 mm (range: 2.82 - 5.96 mm). The average convexity surface was 223.68 cm2 (range: 204.63-238.77 cm2). The safe electrode density without electrode collision on the cortical surface was ranging from 0.46 to 0.69 electrodes per cm2 (average: 0.59 electrodes per cm2) (SD ± 0.023).

CONCLUSION

The theoretical SEEG cortical density is comparable with the usual SDEEG density. These findings, combined with the better safety profile of SEEG and the possibilities to explore deep cortical structures, explain the progressive shift from SDEEG to SEEG during the last years.

Automatic Detection of High-Frequency Oscillations Based on an End-to-End Bi-Branch Neural Network and Clinical Cross-Validation

Accurate identification of high-frequency oscillation (HFO) is an important prerequisite for precise localization of epileptic foci and good prognosis of drug-refractory epilepsy. Exploring a high-performance automatic detection method for HFOs can effectively help clinicians reduce the error rate and reduce manpower. Due to the limited analysis perspective and simple model design, it is difficult to meet the requirements of clinical application by the existing methods. Therefore, an end-to-end bi-branch fusion model is proposed to automatically detect HFOs. With the filtered band-pass signal (signal branch) and time-frequency image (TFpic branch) as the input of the model, two backbone networks for deep feature extraction are established, respectively. Specifically, a hybrid model based on ResNet1d and long short-term memory (LSTM) is designed for signal branch, which can focus on both the features in time and space dimension, while a ResNet2d with a Convolutional Block Attention Module (CBAM) is constructed for TFpic branch, by which more attention is paid to useful information of TF images. Then the outputs of two branches are fused to realize end-to-end automatic identification of HFOs. Our method is verified on 5 patients with intractable epilepsy. In intravalidation, the proposed method obtained high sensitivity of 94.62%, specificity of 92.7%, and F1-score of 93.33%, and in cross-validation, our method achieved high sensitivity of 92.00%, specificity of 88.26%, and F1-score of 89.11% on average. The results show that the proposed method outperforms the existing detection paradigms of either single signal or single time-frequency diagram strategy. In addition, the average kappa coefficient of visual analysis and automatic detection results is 0.795. The method shows strong generalization ability and high degree of consistency with the gold standard meanwhile. Therefore, it has great potential to be a clinical assistant tool.

Imaging the effective networks associated with cortical function through intracranial high-frequency stimulation

Direct electrical stimulation (DES) is considered to be the gold standard for mapping cortical function. A careful mapping of the eloquent cortex is key to successful resective or ablative surgeries, with a minimal postoperative deficit, for treatment of drug‐resistant epilepsy. There is accumulating evidence suggesting that not only local, but also remote activations play an equally important role in evoking clinical effects. By introducing a new intracranial stimulation paradigm and signal analysis methodology allowing to disambiguate EEG responses from stimulation artifacts we highlight the spatial extent of the networks associated with clinical effects. Our study includes 26 patients that underwent stereoelectroencephalographic investigations for drug‐resistant epilepsy, having 337 depth electrodes with 4,351 contacts sampling most brain structures. The routine high‐frequency electrical stimulation protocol for eloquent cortex mapping was altered in a subtle way, by alternating the polarity of the biphasic pulses in a train, causing the splitting the spectral lines of the artifactual components, exposing the underlying tissue response. By performing a frequency‐domain analysis of the EEG responses during DES we were able to capture remote activations and highlight the effect's network. By using standard intersubject averaging and a fine granularity HCP‐MMP parcellation, we were able to create local and distant connectivity maps for 614 stimulations evoking specific clinical effects. The clinical value of such maps is not only for a better understanding of the extent of the effects' networks guiding the invasive exploration, but also for understanding the spatial patterns of seizure propagation given the timeline of the seizure semiology.

Development and Validation of the 5-SENSE Score to Predict Focality of the Seizure-Onset Zone as Assessed by Stereoelectroencephalography

Importance

Stereoelectroencephalography (SEEG) has become the criterion standard in case of inconclusive noninvasive presurgical epilepsy workup. However, up to 40% of patients are subsequently not offered surgery because the seizure-onset zone is less focal than expected or cannot be identified.

Objective

To predict focality of the seizure-onset zone in SEEG, the 5-point 5-SENSE score was developed and validated.

Design, Setting, and Participants

This was a monocentric cohort study for score development followed by multicenter validation with patient selection intervals between February 2002 to October 2018 and May 2002 to December 2019. The minimum follow-up period was 1 year. Patients with drug-resistant epilepsy undergoing SEEG at the Montreal Neurological Institute were analyzed to identify a focal seizure-onset zone. Selection criteria were 2 or more seizures in electroencephalography and availability of complete neuropsychological and neuroimaging data sets. For validation, patients from 9 epilepsy centers meeting these criteria were included. Analysis took place between May and July 2021.

Main Outcomes and Measures

Based on SEEG, patients were grouped as focal and nonfocal seizure-onset zone. Demographic, clinical, electroencephalography, neuroimaging, and neuropsychology data were analyzed, and a multiple logistic regression model for developing a score to predict SEEG focality was created and validated in an independent sample.

Results

A total of 128 patients (57 women [44.5%]; median [range] age, 31 [13-58] years) were analyzed for score development and 207 patients (97 women [46.9%]; median [range] age, 32 [16-70] years) were analyzed for validation. The score comprised the following 5 predictive variables: focal lesion on structural magnetic resonance imaging, absence of bilateral independent spikes in scalp electroencephalography, localizing neuropsychological deficit, strongly localizing semiology, and regional ictal scalp electroencephalography onset. The 5-SENSE score had an optimal mean (SD) probability cutoff for identifying a focal seizure-onset zone of 37.6 (3.5). Area under the curve, specificity, and sensitivity were 0.83, 76.3% (95% CI, 66.7-85.8), and 83.3% (95% CI, 72.30-94.1), respectively. Validation showed 76.0% (95% CI, 67.5-84.0) specificity and 52.3% (95% CI, 43.0-61.5) sensitivity.

Conclusions and Relevance

High specificity in score development and validation confirms that the 5-SENSE score predicts patients where SEEG is unlikely to identify a focal seizure-onset zone. It is a simple and useful tool for assisting clinicians to reduce unnecessary invasive diagnostic burden on patients and overutilization of limited health care resources.

Comparative Effectiveness of Stereotactic Electroencephalography Versus Subdural Grids in Epilepsy Surgery

OBJECTIVE

The aim was to compare the outcomes of subdural electrode (SDE) implantations versus stereotactic electroencephalography (SEEG), the 2 predominant methods of intracranial electroencephalography (iEEG) performed in difficult-to-localize drug-resistant focal epilepsy.

METHODS

The Surgical Therapies Commission of the International League Against Epilepsy created an international registry of iEEG patients implanted between 2005 and 2019 with ≥1 year of follow-up. We used propensity score matching to control exposure selection bias and generate comparable cohorts. Study endpoints were: (1) likelihood of resection after iEEG; (2) seizure freedom at last follow-up; and (3) complications (composite of postoperative infection, symptomatic intracranial hemorrhage, or permanent neurological deficit).

RESULTS

Ten study sites from 7 countries and 3 continents contributed 2,012 patients, including 1,468 (73%) eligible for analysis (526 SDE and 942 SEEG), of whom 988 (67%) underwent subsequent resection. Propensity score matching improved covariate balance between exposure groups for all analyses. Propensity-matched patients who underwent SDE had higher odds of subsequent resective surgery (odds ratio [OR] = 1.4, 95% confidence interval [CI] 1.05, 1.84) and higher odds of complications (OR = 2.24, 95% CI 1.34, 3.74; unadjusted: 9.6% after SDE vs 3.3% after SEEG). Odds of seizure freedom in propensity-matched resected patients were 1.66 times higher (95% CI 1.21, 2.26) for SEEG compared with SDE (unadjusted: 55% seizure free after SEEG-guided resections vs 41% after SDE).

INTERPRETATION

In comparison to SEEG, SDE evaluations are more likely to lead to brain surgery in patients with drug-resistant epilepsy but have more surgical complications and lower probability of seizure freedom. This comparative-effectiveness study provides the highest feasible evidence level to guide decisions on iEEG. ANN NEUROL 2021;90:927-939.

Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements

Non-invasive MEG/EEG source imaging provides valuable information about the epileptogenic brain areas which can be used to aid presurgical planning in focal epilepsy patients suffering from drug-resistant seizures. However, the source extent estimation for electrophysiological source imaging remains to be a challenge and is usually largely dependent on subjective choice. Our recently developed algorithm, fast spatiotemporal iteratively reweighted edge sparsity minimization (FAST-IRES) strategy, has been shown to objectively estimate extended sources from EEG recording, while it has not been applied to MEG recordings. In this work, through extensive numerical experiments and real data analysis in a group of focal drug-resistant epilepsy patients' interictal spikes, we demonstrated the ability of FAST-IRES algorithm to image the location and extent of underlying epilepsy sources from MEG measurements. Our results indicate the merits of FAST-IRES in imaging the location and extent of epilepsy sources for pre-surgical evaluation from MEG measurements.

Quantification of Epileptogenic Network From Stereo EEG Recordings Using Epileptogenicity Ranking Method

Introduction: Precise localization of the epileptogenic zone is very essential for the success of epilepsy surgery. Epileptogenicity index (EI) computationally estimates epileptogenicity of brain structures based on the temporal domain parameters and magnitude of ictal discharges. This method works well in cases of mesial temporal lobe epilepsy but it showed reduced accuracy in neocortical epilepsy. To overcome this scenario, in this study, we propose Epileptogenicity Rank (ER), a modified method of EI for quantifying epileptogenicity, that is based on spatio-temporal properties of Stereo EEG (SEEG). Methods: Energy ratio during ictal discharges, the time of involvement and Euclidean distance between brain structures were used to compute the ER. Retrospectively, we localized the EZ for 33 patients (9 for mesial-temporal lobe epilepsy and 24 for neocortical epilepsy) using post op MRI and Engel 1 surgical outcome at a mean of 40.9 months and then optimized the ER in this group. Results: Epileptic network estimation based on ER successfully differentiated brain regions involved in the seizure onset from the propagation network. ER was calculated at multiple thresholds leading to an optimum value that differentiated the seizure onset from the propagation network. We observed that ER < 7.1 could localize the EZ in neocortical epilepsy with a sensitivity of 94.6% and specificity of 98.3% and ER < 7.3 in mesial temporal lobe epilepsy with a sensitivity of 95% and specificity of 98%. In non-seizure-free patients, the EZ localization based on ER pointed to brain area beyond the cortical resections. Significance: Methods like ER can improve the accuracy of EZ localization for brain resection and increase the precision of minimally invasive surgery techniques (radio-frequency or laser ablation) by identifying the epileptic hubs where the lesion is extensive or in nonlesional cases. For inclusivity with other clinical applications, this ER method has to be studied in more patients.

Multilobar unilateral hypoplasia with emphasis on the posterior quadrant and severe epilepsy in children with FCD ILAE Type 1A

OBJECTIVE

Focal cortical dysplasia (FCD) Type 1 and its three subtypes have yet not been fully characterized at the clinical, anatomopathological, and molecular level (International League Against Epilepsy [ILAE] FCD classification from 2011). We aimed to describe the clinical phenotype of patients with histopathologically confirmed FCD1A obtained from a single epilepsy center between 2002 and 2016.

METHODS

Medical records were retrieved from the hospital's archive. Results from electroencephalography (EEG) video recordings, neuroimaging, and histopathology were reevaluated. Magnetic resonance imaging (MRI) post-processing was retrospectively performed in nine patients. DNA methylation studies were carried out from archival surgical brain tissue in 11 patients.

RESULTS

Nineteen children with a histopathological diagnosis of FCD1A were included. The average onset of epilepsy was 0.9 years (range 0.2-10 years). All children had severe cognitive impairment and one third had mild motor deficits, yet fine finger movements were preserved in all patients. All patients had daily seizures, being drug resistant from disease onset. Interictal electroencephalography revealed bilateral multi-regional epileptiform discharges. Interictal status epilepticus was observed in 8 and countless subclinical seizures in 11 patients. Regional continuous irregular slow waves were of higher lateralizing and localizing yield than spikes. Posterior background rhythms were normal in 16 of 19 children. Neuroimaging showed unilateral multilobar hypoplasia and increased T2-FLAIR signals of the white matter in 18 of 19 patients. All children underwent tailored multilobar resections, with seizure freedom achieved in 47% (Engel class I). There was no case with frontal involvement without involvement of the posterior quadrant by MRI and histopathology. DNA methylation profiling distinguished FCD1A samples from all other epilepsy specimens and controls.

SIGNIFICANCE

We identified a cohort of young children with drug resistance from seizure onset, bad EEG with posterior emphasis, lack of any focal neurological deficits but severe cognitive impairment, subtle hypoplasia of the epileptogenic area on MRI, and histopathologically defined and molecularly confirmed by DNA methylation analysis as FCD ILAE Type 1A.

[Invasive EEG for temporal lobe epilepsy: selection of technique]

BACKGROUND

Non-invasive EEG reveals epileptogenic zone in 70% of patients. In other cases, invasive EEG monitoring is indicated. Various implantation strategies and techniques of intracranial EEG (icEEG) potentially provide different outcomes. Choosing the optimal icEEG technique may be challenging.

OBJECTIVE

To analyze the results of icEEG in adults with temporal lobe epilepsy and to determine the algorithm for selection of optimal invasive EEG technique.

MATERIAL AND METHODS

The study included 82 patients with temporal lobe epilepsy who underwent invasive EEG. Effectiveness of invasive EEG was determined by detection of epileptogenic zone and post-resection outcomes. Postoperative results were analyzed throughout more than 6-month follow-up period using the Engel grading system. Statistical analysis was conducted using the Fisher's exact test.

RESULTS

Epileptogenic zone was revealed in 72 (88%) cases. Invasive EEG was supplemented by another modality in 3 (4%) patients. Mean follow-up period after resection was 17 months in 45 patients. Favorable outcomes were achieved in 31 (69%) cases. Statistical analysis showed that identification of epileptogenic zone depends existing of lesion and symptoms of seizures. Selection algorithm for optimal technique of invasive EEG was determined considering own results and literature data.

CONCLUSION

Invasive EEG results and post-resection outcomes demonstrated favorable efficacy of original algorithm. The last one may be used in decision-making on optimal technique of invasive EEG in adults with temporal lobe epilepsy.

Extracting seizure onset from surface EEG with independent component analysis: Insights from simultaneous scalp and intracerebral EEG

The success of stereoelectroencephalographic (SEEG) investigations depends crucially on the hypotheses on the putative location of the seizure onset zone. This information is derived from non-invasive data either based on visual analysis or advanced source localization algorithms. While source localization applied to interictal spikes recorded on scalp is the classical method, it does not provide unequivocal information regarding the seizure onset zone. Raw ictal activity contains a mixture of signals originating from several regions of the brain as well as EMG artifacts, hampering direct input to the source localization algorithms. We therefore introduce a methodology that disentangles the various sources contributing to the scalp ictal activity using independent component analysis and uses equivalent current dipole localization as putative locus of ictal sources. We validated the results of our analysis pipeline by performing long-term simultaneous scalp - intracerebral (SEEG) recordings in 14 patients and analyzing the wavelet coherence between the independent component encoding the ictal discharge and the SEEG signals in 8 patients passing the inclusion criteria. Our results show that invasively recorded ictal onset patterns, including low-voltage fast activity, can be captured by the independent component analysis of scalp EEG. The visibility of the ictal activity strongly depends on the depth of the sources. The equivalent current dipole localization can point to the seizure onset zone (SOZ) with an accuracy that can be as high as 10 mm for superficially located sources, that gradually decreases for deeper seizure generators, averaging at 47 mm in the 8 analyzed patients. Independent component analysis is therefore shown to have a promising SOZ localizing value, indicating whether the seizure onset zone is neocortical, and its approximate location, or located in mesial structures. That may contribute to a better crafting of the hypotheses used as basis of the stereo-EEG implantations.

The role of hybrid FDG-PET/MRI on decision-making in presurgical evaluation of drug-resistant epilepsy

Background

When MRI fails to detect a potentially epileptogenic lesion, the chance of a favorable outcome after epilepsy surgery becomes significantly lower (from 60 to 90% to 20–65%). Hybrid FDG-PET/MRI may provide additional information for identifying the epileptogenic zone. We aimed to investigate the possible effect of the introduction of hybrid FDG-PET/MRI into the algorithm of the decision-making in both lesional and non-lesional drug-resistant epileptic patients.

Methods

In a prospective study of patients suffering from drug-resistant focal epilepsy, 30 nonlesional and 30 lesional cases with discordant presurgical results were evaluated using hybrid FDG-PET/MRI.

Results

The hybrid imaging revealed morphological lesion in 18 patients and glucose hypometabolism in 29 patients within the nonlesional group. In the MRI positive group, 4 patients were found to be nonlesional, and in 9 patients at least one more epileptogenic lesion was discovered, while in another 17 cases the original lesion was confirmed by means of hybrid FDG-PET/MRI. As to the therapeutic decision-making, these results helped to indicate resective surgery instead of intracranial EEG (iEEG) monitoring in 2 cases, to avoid any further invasive diagnostic procedures in 7 patients, and to refer 21 patients for iEEG in the nonlesional group. Hybrid FDG-PET/MRI has also significantly changed the original therapeutic plans in the lesional group. Prior to the hybrid imaging, a resective surgery was considered in 3 patients, and iEEG was planned in 27 patients. However, 3 patients became eligible for resective surgery, 6 patients proved to be inoperable instead of iEEG, and 18 cases remained candidates for iEEG due to the hybrid FDG-PET/MRI. Two patients remained candidates for resective surgery and one patient became not eligible for any further invasive intervention.

Conclusions

The results of hybrid FDG-PET/MRI significantly altered the original plans in 19 of 60 cases. The introduction of hybrid FDG-PET/MRI into the presurgical evaluation process had a potential modifying effect on clinical decision-making.

Trial registration

Trial registry: Scientific Research Ethics Committee of the Medical Research Council of Hungary. Trial registration number: 008899/2016/OTIG. Date of registration: 08 February 2016.

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.

Using 3D-Printed Mesh-Like Brain Cortex with Deep Structures for Planning Intracranial EEG Electrode Placement

Surgical evaluation of medically refractory epilepsy frequently necessitates implantation of multiple intracranial electrodes for the identification of the seizure focus. Knowledge of the individual brain's surface anatomy and deep structures is crucial for planning the electrode implantation. We present a novel method of 3D printing a brain that allows for the simulation of placement of all types of intracranial electrodes. We used a DICOM dataset of a T1-weighted 3D-FSPGR brain MRI from one subject. The segmentation tools of Materialise Mimics 21.0 were used to remove the osseous anatomy from brain parenchyma. Materialise 3-matic 13.0 was then utilized in order to transform the cortex of the segmented brain parenchyma into a mesh-like surface. Using 3-matic tools, the model was modified to incorporate deep brain structures and create an opening in the medial aspect. The final model was then 3D printed as a cerebral hemisphere with nylon material using selective laser sintering technology. The final model was light and durable and reflected accurate details of the surface anatomy and some deep structures. Additionally, standard surgical depth electrodes could be passed through the model to reach deep structures without damaging the model. This novel 3D-printed brain model provides a unique combination of visualizing both the surface anatomy and deep structures through the mesh-like surface while allowing repeated needle insertions. This relatively low-cost technique can be implemented for interdisciplinary preprocedural planning in patients requiring intracranial EEG monitoring and for any intervention that requires needle insertion into a solid organ with unique anatomy and internal targets.

Supplementing Extraoperative Electrocorticography With Real-Time Intraoperative Recordings Using the Same Chronically Implanted Electrodes

BACKGROUND

The practice of intraoperative electrocorticography (iECoG) to guide resective epilepsy surgery is variable. Limitations of iECoG include variability in recordings from previously unsampled cortex, increased operative time and cost, and a lack of clear benefit to surgical decision-making.

OBJECTIVE

To describe a simple technique to supplement extraoperative intracranial recordings with real-time iECoG using the same chronically implanted electrodes that overcome some of these limitations.

METHODS

We describe the technical procedure, intraoperative findings, and outcomes of 7 consecutive children undergoing 2-stage resective epilepsy surgery with invasive subdural grid monitoring between January 2017 and December 2019. All children underwent placement of subdural grids, strips, and depth electrodes. Planned neocortical resection was based on extraoperative mapping of ictal and interictal recordings. During resection in the second stage, the same electrodes were used to perform real-time iECoG.

RESULTS

Real-time iECoG using this technique leads to modification of resection for 2 of the 7 children. The first was extended due to an electroencephalographic seizure from a distant electrode not part of the original resection plan. The second was restricted due to attenuation of epileptiform activity following a partial resection, thereby limiting the extent of a Rolandic resection. No infections or other adverse events were encountered.

CONCLUSION

We report a simple technique to leverage chronically implanted electrodes for real-time iECoG during 2-stage resective surgery. This technique presents fewer limitations than traditional approaches and may alter intraoperative decision-making.

MRI and CT Fusion in Stereotactic Electroencephalography: A Literature Review

Epilepsy is a common neurological disease characterized by spontaneous recurrent seizures. Resection of the epileptogenic tissue may be needed in approximately 25% of all cases due to ineffective treatment with anti-epileptic drugs. The surgical intervention depends on the correct detection of epileptogenic zones. The detection relies on invasive diagnostic techniques such as Stereotactic Electroencephalography (SEEG), which uses multi-modal fusion to aid localizing electrodes, using pre-surgical magnetic resonance and intra-surgical computer tomography as the input images. Moreover, it is essential to know how to measure the performance of fusion methods in the presence of external objects, such as electrodes. In this paper, a literature review is presented, applying the methodology proposed by Kitchenham to determine the main techniques of multi-modal brain image fusion, the most relevant performance metrics, and the main fusion tools. The search was conducted using the databases and search engines of Scopus, IEEE, PubMed, Springer, and Google Scholar, resulting in 15 primary source articles. The literature review found that rigid registration was the most used technique when electrode localization in SEEG is required, which was the proposed method in nine of the found articles. However, there is a lack of standard validation metrics, which makes the performance measurement difficult when external objects are presented, caused primarily by the absence of a gold-standard dataset for comparison.

Computer-Aided Intracranial EEG Signal Identification Method Based on a Multi-Branch Deep Learning Fusion Model and Clinical Validation

Surgical intervention or the control of drug-refractory epilepsy requires accurate analysis of invasive inspection intracranial EEG (iEEG) data. A multi-branch deep learning fusion model is proposed to identify epileptogenic signals from the epileptogenic area of the brain. The classical approach extracts multi-domain signal wave features to construct a time-series feature sequence and then abstracts it through the bi-directional long short-term memory attention machine (Bi-LSTM-AM) classifier. The deep learning approach uses raw time-series signals to build a one-dimensional convolutional neural network (1D-CNN) to achieve end-to-end deep feature extraction and signal detection. These two branches are integrated to obtain deep fusion features and results. Resampling is employed to split the imbalanced epileptogenic and non-epileptogenic samples into balanced subsets for clinical validation. The model is validated over two publicly available benchmark iEEG databases to verify its effectiveness on a private, large-scale, clinical stereo EEG database. The model achieves high sensitivity (97.78%), accuracy (97.60%), and specificity (97.42%) on the Bern–Barcelona database, surpassing the performance of existing state-of-the-art techniques. It is then demonstrated on a clinical dataset with an average intra-subject accuracy of 92.53% and cross-subject accuracy of 88.03%. The results suggest that the proposed method is a valuable and extremely robust approach to help researchers and clinicians develop an automated method to identify the source of iEEG signals.

One-Stage, Limited-Resection Epilepsy Surgery for Bottom-of-Sulcus Dysplasia

OBJECTIVE

To determine whether 1-stage, limited corticectomy controls seizures in patients with MRI-positive, bottom-of-sulcus dysplasia (BOSD).

METHODS

We reviewed clinical, neuroimaging, electrocorticography (ECoG), operative, and histopathology findings in consecutively operated patients with drug-resistant focal epilepsy and MRI-positive BOSD, all of whom underwent corticectomy guided by MRI and ECoG.

RESULTS

Thirty-eight patients with a median age at surgery of 10.2 (interquartile range [IQR] 6.0-14.1) years were included. BOSDs involved eloquent cortex in 15 patients. Eighty-seven percent of patients had rhythmic spiking on preresection ECoG. Rhythmic spiking was present in 22 of 24 patients studied with combined depth and surface electrodes, being limited to the dysplastic sulcus in 7 and involving the dysplastic sulcus and gyral crown in 15. Sixty-eight percent of resections were limited to the dysplastic sulcus, leaving the gyral crown. Histopathology was focal cortical dysplasia (FCD) type IIb in 29 patients and FCDIIa in 9. Dysmorphic neurons were present in the bottom of the sulcus but not the top or the gyral crown in 17 of 22 patients. Six (16%) patients required reoperation for postoperative seizures and residual dysplasia; reoperation was not correlated with ECoG, neuroimaging, or histologic abnormalities in the gyral crown. At a median 6.3 (IQR 4.8-9.9) years of follow-up, 33 (87%) patients are seizure-free, 31 off antiseizure medication.

CONCLUSION

BOSD can be safely and effectively resected with MRI and ECoG guidance, corticectomy potentially being limited to the dysplastic sulcus, without need for intracranial EEG monitoring and functional mapping.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that 1-stage, limited corticectomy for BOSD is safe and effective for control of seizures.

Gray Matter Sampling Differences Between Subdural Electrodes and Stereoelectroencephalography Electrodes

Objective: Stereoelectroencephalography (SEEG) has seen a recent increase in popularity in North America; however, concerns regarding the spatial sampling capabilities of SEEG remain. We aimed to quantify and compare the spatial sampling of subdural electrode (SDE) and SEEG implants.

Methods: Patients with drug-resistant epilepsy who underwent invasive monitoring were included in this retrospective case-control study. Ten SEEG cases were compared with ten matched SDE cases based on clinical presentation and pre-implantation hypothesis. To quantify gray matter sampling, MR and CT images were coregistered and a 2.5mm radius sphere was superimposed over the center of each electrode contact. The estimated recording volume of gray matter was defined as the cortical voxels within these spherical models. Paired t-tests were performed to compare volumes and locations of SDE and SEEG recording. A Ripley's K-function analysis was performed to quantify differences in spatial distributions.

Results: The average recording volume of gray matter by each individual contact was similar between the two modalities. SEEG implants sampled an average of 20% more total gray matter, consisted of an average of 17% more electrode contacts, and had 77% more of their contacts covering gray matter within sulci. Insular coverage was only achieved with SEEG. SEEG implants generally consist of discrete areas of dense local coverage scattered across the brain; while SDE implants cover relatively contiguous areas with lower density recording.

Significance: Average recording volumes per electrode contact are similar for SEEG and SDE, but SEEG may allow for greater overall volumes of recording as more electrodes can be routinely implanted. The primary difference lies in the location and distribution of gray matter than can be sampled. The selection between SEEG and SDE implantation depends on sampling needs of the invasive implant.

Fast Automated Stereo-EEG Electrode Contact Identification and Labeling Ensemble

INTRODUCTION

Stereotactic electroencephalography (SEEG) has emerged as the preferred modality for intracranial monitoring in drug-resistant epilepsy (DRE) patients being evaluated for neurosurgery. After implantation of SEEG electrodes, it is important to determine the neuroanatomic locations of electrode contacts (ECs), to localize ictal onset and propagation, and integrate functional information to facilitate surgical decisions. Although there are tools for coregistration of preoperative MRI and postoperative CT scans, identification, sorting, and labeling of SEEG ECs is often performed manually, which is resource intensive. We report development and validation of a software named Fast Automated SEEG Electrode Contact Identification and Labeling Ensemble (FASCILE).

METHODS

FASCILE is written in Python 3.8.3 and employs a novel automated method for identifying ECs, assigning them to respected SEEG electrodes, and labeling. We compared FASCILE with our clinical process of identifying, sorting, and labeling ECs, by computing localization error in anteroposterior, superoinferior, and lateral dimensions. We also measured mean Euclidean distances between ECs identified by FASCILE and the clinical method. We compared time taken for EC identification, sorting, and labeling for the software developer using FASCILE, a first-time clinical user using FASCILE, and the conventional clinical process.

RESULTS

Validation in 35 consecutive DRE patients showed a mean overall localization error of 0.73 ± 0.15 mm. FASCILE required 10.7 ± 5.5 min/patient for identifying, sorting, and labeling ECs by a first-time clinical user, compared to 3.3 ± 0.7 h/patient required for the conventional clinical process.

CONCLUSION

Given the accuracy, speed, and ease of use, we expect FASCILE to be used frequently for SEEG-driven epilepsy surgery. It is freely available for noncommercial use. FASCILE is specifically designed to expedite localization of ECs, assigning them to respective SEEG electrodes (sorting), and labeling them and not for coregistration of CT and MRI data as there are commercial software available for this purpose.

Intracranial monitoring contributes to seizure freedom for temporal lobectomy patients with nonconcordant preoperative data

Objective

The question of whether a patient with presumed temporal lobe seizures should proceed directly to temporal lobectomy surgery versus undergo intracranial monitoring arises commonly. We evaluate the effect of intracranial monitoring on seizure outcome in a retrospective cohort of consecutive subjects who specifically underwent an anterior temporal lobectomy (ATL) for refractory temporal lobe epilepsy (TLE).

Methods

We performed a retrospective analysis of 85 patients with focal refractory TLE who underwent ATL following: (a) intracranial monitoring via craniotomy and subdural/depth electrodes (SDE/DE), (b) intracranial monitoring via stereotactic electroencephalography (sEEG), or (c) no intracranial monitoring (direct ATL—dATL). For each subject, the presurgical primary hypothesis for epileptogenic zone localization was characterized as unilateral TLE, unilateral TLE plus (TLE+), or TLE with bilateral/poor lateralization.

Results

At one‐year and most recent follow‐up, Engel Class I and combined I/II outcomes did not differ significantly between the groups. Outcomes were better in the dATL group compared to the intracranial monitoring groups for lesional cases but were similar in nonlesional cases. Those requiring intracranial monitoring for a hypothesis of TLE+had similar outcomes with either intracranial monitoring approach. sEEG was the only approach used in patients with bilateral or poorly lateralized TLE, resulting in 77.8% of patients seizure‐free at last follow‐up. Importantly, for 85% of patients undergoing SEEG, recommendation for ATL resulted from modifying the primary hypothesis based on iEEG data.

Significance

Our study highlights the value of intracranial monitoring in equalizing seizure outcomes in difficult‐to‐treat TLE patients undergoing ATL.

Objective interictal electrophysiology biomarkers optimize prediction of epilepsy surgery outcome

Researchers have looked for rapidly- and objectively-measurable electrophysiology biomarkers that accurately localize the epileptogenic zone. Promising candidates include interictal high-frequency oscillation and phase-amplitude coupling. Investigators have independently created the toolboxes that compute the high-frequency oscillation rate and the severity of phase-amplitude coupling. This study of 135 patients determined what toolboxes and analytic approaches would optimally classify patients achieving post-operative seizure control. Four different detector toolboxes computed the rate of high-frequency oscillation at ≥80 Hz at intracranial EEG channels. Another toolbox calculated the modulation index reflecting the strength of phase-amplitude coupling between high-frequency oscillation and slow-wave at 3–4 Hz. We defined the completeness of resection of interictally-abnormal regions as the subtraction of high-frequency oscillation rate (or modulation index) averaged across all preserved sites from that averaged across all resected sites. We computed the outcome classification accuracy of the logistic regression-based standard model considering clinical, ictal intracranial EEG and neuroimaging variables alone. We then determined how well the incorporation of high-frequency oscillation/modulation index would improve the standard model mentioned above. To assess the anatomical variability across non-epileptic sites, we generated the normative atlas of detector-specific high-frequency oscillation and modulation index. Each atlas allowed us to compute the statistical deviation of high-frequency oscillation/modulation index from the non-epileptic mean. We determined whether the model accuracy would be improved by incorporating absolute or normalized high-frequency oscillation/modulation index as a biomarker assessing interictally-abnormal regions. We finally determined whether the model accuracy would be improved by selectively incorporating high-frequency oscillation verified to have high-frequency oscillatory components unattributable to a high-pass filtering effect. Ninety-five patients achieved successful seizure control, defined as International League against Epilepsy class 1 outcome. Multivariate logistic regression analysis demonstrated that complete resection of interictally-abnormal regions additively increased the chance of success. The model accuracy was further improved by incorporating z-score normalized high-frequency oscillation/modulation index or selective incorporation of verified high-frequency oscillation. The standard model had a classification accuracy of 0.75. Incorporation of normalized high-frequency oscillation/modulation index or verified high-frequency oscillation improved the classification accuracy up to 0.82. These outcome prediction models survived the cross-validation process and demonstrated an agreement between the model-based likelihood of success and the observed success on an individual basis. Interictal high-frequency oscillation and modulation index had a comparably additive utility in epilepsy presurgical evaluation. Our empirical data support the theoretical notion that the prediction of post-operative seizure outcomes can be optimized with the consideration of both interictal and ictal abnormalities.

Efficient automated localization of ECoG electrodes in CT images via shape analysis

Purpose

People with drug-refractory epilepsy are potential candidates for surgery. In many cases, epileptogenic zone localization requires intracranial investigations, e.g., via ElectroCorticoGraphy (ECoG), which uses subdural electrodes to map eloquent areas of large cortical regions. Precise electrodes localization on cortical surface is mandatory to delineate the seizure onset zone. Simple thresholding operations performed on patients’ computed tomography (CT) volumes recognize electrodes but also other metal objects (e.g., wires, stitches), which need to be manually removed. A new automated method based on shape analysis is proposed, which provides substantially improved performances in ECoG electrodes recognition.

Methods

The proposed method was retrospectively tested on 24 CT volumes of subjects with drug-refractory focal epilepsy, presenting a large number (> 1700) of round platinum electrodes. After CT volume thresholding, six geometric features of voxel clusters (volume, symmetry axes lengths, circularity and cylinder similarity) were used to recognize the actual electrodes among all metal objects via a Gaussian support vector machine (G-SVM). The proposed method was further tested on seven CT volumes from a public repository. Simultaneous recognition of depth and ECoG electrodes was also investigated on three additional CT volumes, containing penetrating depth electrodes.

Results

The G-SVM provided a 99.74% mean classification accuracy across all 24 single-patient datasets, as well as on the combined dataset. High accuracies were obtained also on the CT volumes from public repository (98.27% across all patients, 99.68% on combined dataset). An overall accuracy of 99.34% was achieved for the recognition of depth and ECoG electrodes.

Conclusions

The proposed method accomplishes automated ECoG electrodes localization with unprecedented accuracy and can be easily implemented into existing software for preoperative analysis process. The preliminary yet surprisingly good results achieved for the simultaneous depth and ECoG electrodes recognition are encouraging.

Ethical approval n°NCT04479410 by “IRCCS Neuromed” (Pozzilli, Italy), 30th July 2020.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11548-021-02325-0.