Lateralization of mesial temporal lobe epilepsy with chronic ambulatory electrocorticography

Feasibility, Safety, and Performance of Full-Head Subscalp EEG Using Minimally Invasive Electrode Implantation

BACKGROUND AND OBJECTIVES

Current practice in clinical neurophysiology is limited to short recordings with conventional EEG (days) that fail to capture a range of brain (dys)functions at longer timescales (months). The future ability to optimally manage chronic brain disorders, such as epilepsy, hinges upon finding methods to monitor electrical brain activity in daily life. We developed a device for full-head subscalp EEG (Epios) and tested here the feasibility to safely insert the electrode leads beneath the scalp by a minimally invasive technique (primary outcome). As secondary outcome, we verified the noninferiority of subscalp EEG in measuring physiologic brain oscillations and pathologic discharges compared with scalp EEG, the established standard of care.

METHODS

Eight participants with pharmacoresistant epilepsy undergoing intracranial EEG received in the same surgery subscalp electrodes tunneled between the scalp and the skull with custom-made tools. Postoperative safety was monitored on an inpatient ward for up to 9 days. Sleep-wake, ictal, and interictal EEG signals from subscalp, scalp, and intracranial electrodes were compared quantitatively using windowed multitaper transforms and spectral coherence. Noninferiority was tested for pairs of neighboring subscalp and scalp electrodes with a Bland-Altman analysis for measurement bias and calculation of the interclass correlation coefficient (ICC).

RESULTS

As primary outcome, up to 28 subscalp electrodes could be safely placed over the entire head through 1-cm scalp incisions in a ∼1-hour procedure. Five of 10 observed perioperative adverse events were linked to the investigational procedure, but none were serious, and all resolved. As a secondary outcome, subscalp electrodes advantageously recorded EEG percutaneously without requiring any maintenance and were noninferior to scalp electrodes for measuring (1) variably strong, stage-specific brain oscillations (alpha in wake, delta, sigma, and beta in sleep) and (2) interictal spikes peak-potentials and ictal signals coherent with seizure propagation in different brain regions (ICC >0.8 and absence of bias).

DISCUSSION

Recording full-head subscalp EEG for localization and monitoring purposes is feasible up to 9 days in humans using minimally invasive techniques and noninferior to the current standard of care. A longer prospective ambulatory study of the full system will be necessary to establish the safety and utility of this innovative approach.

TRIAL REGISTRATION INFORMATION

clinicaltrials.gov/study/NCT04796597.

Canonical Wnt activator Chir99021 prevents epileptogenesis in the intrahippocampal kainate mouse model of temporal lobe epilepsy

The Wnt signaling pathway mediates the development of dentate granule cell neurons in the hippocampus. These neurons are central to the development of temporal lobe epilepsy and undergo structural and physiological remodeling during epileptogenesis, which results in the formation of epileptic circuits. The pathways responsible for granule cell remodeling during epileptogenesis have yet to be well defined, and represent therapeutic targets for the prevention of epilepsy. The current study explores Wnt signaling during epileptogenesis and for the first time describes the effect of Wnt activation using Wnt activator Chir99021 as a novel anti-epileptogenic therapeutic approach. Focal mesial temporal lobe epilepsy was induced by intrahippocampal kainate (IHK) injection in wild-type and POMC-eGFP transgenic mice. Wnt activator Chir99021 was administered daily, beginning 3 h after seizure induction, and continued up to 21-days. Immature granule cell morphology was quantified in the ipsilateral epileptogenic zone and the contralateral peri-ictal zone 14 days after IHK, targeting the end of the latent period. Bilateral hippocampal electrocorticographic recordings were performed for 28-days, 7-days beyond treatment cessation. Hippocampal behavioral tests were performed after completion of Chir99021 treatment. Consistent with previous studies, IHK resulted in the development of epilepsy after a 14 day latent period in this well-described mouse model. Activation of the canonical Wnt pathway with Chir99021 significantly reduced bilateral hippocampal seizure number and duration. Critically, this effect was retained after treatment cessation, suggesting a durable antiepileptogenic change in epileptic circuitry. Morphological analyses demonstrated that Wnt activation prevented pathological remodeling of the primary dendrite in both the epileptogenic zone and peri-ictal zone, changes in which may serve as a biomarker of epileptogenesis and anti-epileptogenic treatment response in pre-clinical studies. These findings were associated with improved object location memory with Chir99021 treatment after IHK. This study provides novel evidence that canonical Wnt activation prevents epileptogenesis in the IHK mouse model of mesial temporal lobe epilepsy, preventing pathological remodeling of dentate granule cells. Wnt signaling may therefore play a key role in mesial temporal lobe epileptogenesis, and Wnt modulation may represent a novel therapeutic strategy in the prevention of epilepsy.

Insights From Chronic ECoG by RNS

SUMMARY

The NeuroPace responsive neurostimulation system (RNS) has revolutionized the care of patients suffering from focal epilepsy since its approval in 2014. One major advantage of this device is its innate ability to gather long-term electrocorticographic (ECoG) data that the device uses in its novel closed-loop treatment paradigm. Beyond the standard stimulation treatments, which have been demonstrated to be safe and well-tolerated, the data collected by the RNS provide valuable information, such as the long-term circadian and ultradian variations that affect seizure risk, obtained under naturalistic conditions. Additionally, these data inform future surgical procedures, supplementing clinically reported seizures by patients, assessing the response to newly added anti-seizure medications, helping to forecast the risk of future seizures, and understanding the mechanisms of certain long-term outcomes in patients with postsurgical epilepsy. By leveraging these data, the delivery of high-quality clinical care for patients with epilepsy can only be enhanced. Finally, these data open significant avenues of research, including machine learning and artificial intelligence algorithms, which may also translate to improved outcomes in patients who struggle with recurrent seizures.

Ambulatory EEG-video

Hospital based EEG recordings have been the norm to assist in the diagnosis and management of patients with unclassified events and known drug resistant epilepsy. Ambulatory EEG (AEEG) is a tool that comes to serve the needs for a portable testing that can be done at home, often with higher accessibility compared to an epilepsy monitoring unit and with lower cost. The current technology provides good quality EEG tracing and can be done with video when needed. In this review we discuss how AEEG should be performed and the preferred indications in which this test may be of utmost help. The advent of ultra-long ambulatory recording may be the future for selected patients as this technology evolves.

Novel Surgical Approaches in Childhood Epilepsy: Laser, Brain Stimulation, and Focused Ultrasound

Pediatric epilepsy has a worldwide prevalence of approximately 1% (Berg et al., Handb Clin Neurol 111:391-398, 2013) and is associated with not only lower quality of life but also long-term deficits in executive function, significant psychosocial stressors, poor cognitive outcomes, and developmental delays (Schraegle and Titus, Epilepsy Behav 62:20-26, 2016; Puka and Smith, Epilepsia 56:873-881, 2015). With approximately one-third of patients resistant to medical control, surgical intervention can offer a cure or palliation to decrease the disease burden and improve neurological development. Despite its potential, epilepsy surgery is drastically underutilized. Even today only 1% of the millions of epilepsy patients are referred annually for neurosurgical evaluation, and the average delay between diagnosis of Drug Resistant Epilepsy (DRE) and surgical intervention is approximately 20 years in adults and 5 years in children (Solli et al., Epilepsia 61:1352-1364, 2020). It is still estimated that only one-third of surgical candidates undergo operative intervention (Pestana Knight et al., Epilepsia 56:375, 2015). In contrast to the stable to declining rates of adult epilepsy surgery (Englot et al., Neurology 78:1200-1206, 2012; Neligan et al., Epilepsia 54:e62-e65, 2013), rates of pediatric surgery are rising (Pestana Knight et al., Epilepsia 56:375, 2015). Innovations in surgical approaches to epilepsy not only minimize potential complications but also expand the definition of a surgical candidate. In this chapter, three alternatives to classical resection are presented. First, laser ablation provides a minimally invasive approach to focal lesions. Next, both central and peripheral nervous system stimulation can interrupt seizure networks without creating permanent lesions. Lastly, focused ultrasound is discussed as a potential new avenue not only for ablation but also modulation of small, deep foci within seizure networks. A better understanding of the potential surgical options can guide patients and providers to explore all treatment avenues.

Interictal intracranial EEG asymmetry lateralizes temporal lobe epilepsy

Patients with drug-resistant temporal lobe epilepsy often undergo intracranial EEG recording to capture multiple seizures in order to lateralize the seizure onset zone. This process is associated with morbidity and often ends in postoperative seizure recurrence. Abundant interictal (between-seizure) data is captured during this process, but these data currently play a small role in surgical planning. Our objective was to predict the laterality of the seizure onset zone using interictal (between-seizure) intracranial EEG data in patients with temporal lobe epilepsy. We performed a retrospective cohort study (single-center study for model development; two-center study for model validation). We studied patients with temporal lobe epilepsy undergoing intracranial EEG at the University of Pennsylvania (internal cohort) and the Medical University of South Carolina (external cohort) between 2015 and 2022. We developed a logistic regression model to predict seizure onset zone laterality using interictal EEG. We compared the concordance between the model-predicted seizure onset zone laterality and the side of surgery between patients with good and poor surgical outcomes. 47 patients (30 women; ages 20-69; 20 left-sided, 10 right-sided, and 17 bilateral seizure onsets) were analyzed for model development and internal validation. 19 patients (10 women; ages 23-73; 5 left-sided, 10 right-sided, 4 bilateral) were analyzed for external validation. The internal cohort cross-validated area under the curve for a model trained using spike rates was 0.83 for a model predicting left-sided seizure onset and 0.68 for a model predicting right-sided seizure onset. Balanced accuracies in the external cohort were 79.3% and 78.9% for the left- and right-sided predictions, respectively. The predicted concordance between the laterality of the seizure onset zone and the side of surgery was higher in patients with good surgical outcome. In conclusion, interictal EEG signatures are distinct across seizure onset zone lateralities. Left-sided seizure onsets are easier to distinguish than right-sided onsets. A model trained on spike rates accurately identifies patients with left-sided seizure onset zones and predicts surgical outcome.

Kindling in humans: Does secondary epileptogenesis occur?

The relevance of secondary epileptogenesis for human epilepsy remains a controversial subject decades after it was first described in animal models. Whether or not a previously normal brain region can become independently epileptogenic through a kindling-like process has not, and cannot, be definitely proven in humans. Rather than reliance on direct experimental evidence, attempts to answering this question must depend on observational data. In this review, observations based largely upon contemporary surgical series will advance the case for secondary epileptogenesis in humans. As will be argued, hypothalamic hamartoma-related epilepsy provides the strongest case for this process; all the stages of secondary epileptogenesis can be observed. Hippocampal sclerosis (HS) is another pathology where the question of secondary epileptogenesis frequently arises, and observations from bitemporal and dual pathology series are explored. The verdict here is far more difficult to reach, in large part because of the scarcity of longitudinal cohorts; moreover, recent experimental data have challenged the claim that HS is acquired consequent to recurrent seizures. Synaptic plasticity more than seizure-induced neuronal injury is the likely mechanism of secondary epileptogenesis. Postoperative running-down phenomenon provides the best evidence that a kindling-like process occurs in some patients, evidenced by its reversal. Finally, a network perspective of secondary epileptogenesis is considered, as well as the possible role for subcortical surgical interventions.

Passive and active markers of cortical excitability in epilepsy

Electroencephalography (EEG) has been the primary diagnostic tool in clinical epilepsy for nearly a century. Its review is performed using qualitative clinical methods that have changed little over time. However, the intersection of higher resolution digital EEG and analytical tools developed in the past decade invites a re-exploration of relevant methodology. In addition to the established spatial and temporal markers of spikes and high-frequency oscillations, novel markers involving advanced postprocessing and active probing of the interictal EEG are gaining ground. This review provides an overview of the EEG-based passive and active markers of cortical excitability in epilepsy and of the techniques developed to facilitate their identification. Several different emerging tools are discussed in the context of specific EEG applications and the barriers we must overcome to translate these tools into clinical practice.

Diagnostic yield and limitations of in-hospital documentation in patients with epilepsy

OBJECTIVE

To determine the diagnostic yield of in-hospital video-electroencephalography (EEG) monitoring to document seizures in patients with epilepsy.

METHODS

Retrospective analysis of electronic seizure documentation at the University Hospital Freiburg (UKF) and at King's College London (KCL). Statistical assessment of the role of the duration of monitoring, and subanalyses on presurgical patient groups and patients undergoing reduction of antiseizure medication.

RESULTS

Of more than 4800 patients with epilepsy undergoing in-hospital recordings at the two institutions since 2005, seizures with documented for 43% (KCL) and 73% (UKF).. Duration of monitoring was highly significantly associated with seizure recordings (p < .0001), and presurgical patients as well as patients with drug reduction had a significantly higher diagnostic yield (p < .0001). Recordings with a duration of >5 days lead to additional new seizure documentation in only less than 10% of patients.

SIGNIFICANCE

There is a need for the development of new ambulatory monitoring strategies to document seizures for diagnostic and monitoring purposes for a relevant subgroup of patients with epilepsy in whom in-hospital monitoring fails to document seizures.

Analysis of Electrocorticography in Epileptic Patients With Responsive Neurostimulation Undergoing Scalp Electroencephalography Monitoring

PURPOSE

To describe the relationship of electrocorticography events detected by a brain-responsive neurostimulation system (RNS) and their association with ictal and interictal activity detected on simultaneous scalp EEG.

METHODS

We retrospectively identified patients with drug-resistant epilepsy implanted with RNS who subsequently underwent long-term scalp EEG monitoring. RNS detections were correlated to simultaneous activity recorded on scalp EEG to determine the characteristics of electrocorticography-stored long episodes associated with seizures or other findings on scalp EEG.

RESULTS

Eleven patients were included with an average of 3.6 days of monitoring. Most RNS detections were of very brief duration (<10 seconds, 92.9%) and received one stimulation therapy (80.8%). A high proportion of long episodes (67.1%) were not identified as electrographic seizures on scalp EEG. Of those ictal-appearing (71.2%) long episodes, 68.2% had seizure correlates. Long episodes associated with seizures on scalp EEG had a longer median duration compared with those without (39.7 vs. 16.8 seconds, P < 0.002) and had broader spread pattern and were of higher amplitude on electrocorticography. Brief potentially ictal rhythmic discharges were the most common EEG findings associated with long episodes that did not have scalp EEG seizure correlates (100% for ictal- and 50% for non-ictal-appearing long episodes).

CONCLUSIONS

Longer, broader spread and higher amplitude intracranial RNS detections are more likely to manifest as electrographic seizures on scalp EEG. Brief potentially ictal rhythmic discharges may serve as a scalp EEG biomarker of ictal intracranial episodes that are detected as long episodes by the RNS but not identified as electrographic seizures on scalp EEG.

Long-Term Intracranial EEG Lateralization of Epileptogenicity in Patients With Confirmed or Suspected Bilateral Mesial Temporal Lobe Onsets During Epilepsy Surgical Evaluation

PURPOSE

The data resulting from epilepsy surgical evaluation are occasionally unclear in cases of mesial temporal lobe (MTL) epilepsy. Long-term intracranial EEG (iEEG) collected by the Responsive Neurostimulation (RNS) System may be an approach for capturing additional seizure data while treating patients with neurostimulation. We reviewed iEEG seizure lateralization and clinical outcomes in bilateral MTL patients at University of Utah.

METHODS

Long-term RNS System iEEG seizure lateralization was compared with pre-RNS System lateralization obtained during surgical evaluation. Safety and clinical outcomes were extracted retrospectively from patient records.

RESULTS

Twenty-six patients received an RNS System with bilateral MTL leads. Fifteen of the patients had adequate follow-up to report clinical outcomes (>1 year), and 25 patients had enough recorded data (>6 months) to perform iEEG analysis. Median percent reduction in clinical seizures at last follow-up was 58%, and 40% reported being seizure-free at last follow-up, for variable durations. The electrographic seizure lateralization (unilateral vs. bilateral) differed between surgical evaluation and long-term iEEG in 44% of our patients. In the subset of eight patients (32%) who had only unilateral seizures recorded during surgical evaluation, but were implanted with bilateral MTL leads based on bilateral interictal epileptiform discharges, 62% (5/8) had bilateral seizures recorded on long-term iEEG. Interestingly, in the 18 patients who had bilateral seizures recorded during surgical evaluation, 28% (5/18) were found to be unilateral on long-term iEEG.

CONCLUSIONS

Our data suggest that RNS System implantation in suspected bilateral MTL cases may be an option to assess a patient's true seizure lateralization on long-term iEEG. Responsive neuromodulation should be considered before resection or ablation in cases that have evaluation data suggesting bilaterality.

Advances in Bioresorbable Materials and Electronics

Transient electronic systems represent an emerging class of technology that is defined by an ability to fully or partially dissolve, disintegrate, or otherwise disappear at controlled rates or triggered times through engineered chemical or physical processes after a required period of operation. This review highlights recent advances in materials chemistry that serve as the foundations for a subclass of transient electronics, bioresorbable electronics, that is characterized by an ability to resorb (or, equivalently, to absorb) in a biological environment. The primary use cases are in systems designed to insert into the human body, to provide sensing and/or therapeutic functions for timeframes aligned with natural biological processes. Mechanisms of bioresorption then harmlessly eliminate the devices, and their associated load on and risk to the patient, without the need of secondary removal surgeries. The core content focuses on the chemistry of the enabling electronic materials, spanning organic and inorganic compounds to hybrids and composites, along with their mechanisms of chemical reaction in biological environments. Following discussions highlight the use of these materials in bioresorbable electronic components, sensors, power supplies, and in integrated diagnostic and therapeutic systems formed using specialized methods for fabrication and assembly. A concluding section summarizes opportunities for future research.

A click-based electrocorticographic brain-computer interface enables long-term high-performance switch-scan spelling

Background

Brain-computer interfaces (BCIs) can restore communication in movement- and/or speech-impaired individuals by enabling neural control of computer typing applications. Single command "click" decoders provide a basic yet highly functional capability.

Methods

We sought to test the performance and long-term stability of click-decoding using a chronically implanted high density electrocorticographic (ECoG) BCI with coverage of the sensorimotor cortex in a human clinical trial participant (ClinicalTrials.gov, NCT03567213) with amyotrophic lateral sclerosis (ALS). We trained the participant's click decoder using a small amount of training data (< 44 minutes across four days) collected up to 21 days prior to BCI use, and then tested it over a period of 90 days without any retraining or updating.

Results

Using this click decoder to navigate a switch-scanning spelling interface, the study participant was able to maintain a median spelling rate of 10.2 characters per min. Though a transient reduction in signal power modulation interrupted testing with this fixed model, a new click decoder achieved comparable performance despite being trained with even less data (< 15 min, within one day).

Conclusion

These results demonstrate that a click decoder can be trained with a small ECoG dataset while retaining robust performance for extended periods, providing functional text-based communication to BCI users.

Quantifying interictal intracranial EEG to predict focal epilepsy

Introduction

Intracranial EEG (IEEG) is used for 2 main purposes, to determine: (1) if epileptic networks are amenable to focal treatment and (2) where to intervene. Currently these questions are answered qualitatively and sometimes differently across centers. There is a need for objective, standardized methods to guide surgical decision making and to enable large scale data analysis across centers and prospective clinical trials.

Methods

We analyzed interictal data from 101 patients with drug resistant epilepsy who underwent presurgical evaluation with IEEG. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. 65 patients had unifocal seizure onset on IEEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal IEEG abnormalities for each patient. We compared these measures against the "5 Sense Score (5SS)," a pre-implant estimate of the likelihood of focal seizure onset, and assessed their ability to predict the clinicians' choice of therapeutic intervention and the patient outcome.

Results

The spatial dispersion of IEEG electrodes predicted network focality with precision similar to the 5SS (AUC = 0.67), indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5SS and the spatial dispersion of interictal IEEG abnormalities significantly improved this prediction (AUC = 0.79; p<0.05). The combined model predicted ultimate treatment strategy (surgery vs. device) with an AUC of 0.81 and post-surgical outcome at 2 years with an AUC of 0.70. The 5SS, interictal IEEG, and electrode placement were not correlated and provided complementary information.

Conclusions

Quantitative, interictal IEEG significantly improved upon pre-implant estimates of network focality and predicted treatment with precision approaching that of clinical experts. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery.

Chronic intracranial EEG recordings and interictal spike rate reveal multiscale temporal modulations in seizure states

Many biological processes are modulated by rhythms on circadian and multidien timescales. In focal epilepsy, various seizure features, such as spread and duration, can change from one seizure to the next within the same patient. However, the specific timescales of this variability, as well as the specific seizure characteristics that change over time, are unclear. Here, in a cross-sectional observational study, we analysed within-patient seizure variability in 10 patients with chronic intracranial EEG recordings (185-767 days of recording time, 57-452 analysed seizures/patient). We characterized the seizure evolutions as sequences of a finite number of patient-specific functional seizure network states. We then compared seizure network state occurrence and duration to (1) time since implantation and (2) patient-specific circadian and multidien cycles in interictal spike rate. In most patients, the occurrence or duration of at least one seizure network state was associated with the time since implantation. Some patients had one or more seizure network states that were associated with phases of circadian and/or multidien spike rate cycles. A given seizure network state's occurrence and duration were usually not associated with the same timescale. Our results suggest that different time-varying factors modulate within-patient seizure evolutions over multiple timescales, with separate processes modulating a seizure network state's occurrence and duration. These findings imply that the development of time-adaptive treatments in epilepsy must account for several separate properties of epileptic seizures and similar principles likely apply to other neurological conditions.

Expert and deep learning model identification of iEEG seizures and seizure onset times

Hundreds of 90-s iEEG records are typically captured from each NeuroPace RNS System patient between clinic visits. While these records provide invaluable information about the patient's electrographic seizure and interictal activity patterns, manually classifying them into electrographic seizure/non-seizure activity, and manually identifying the seizure onset channels and times is an extremely time-consuming process. A convolutional neural network based Electrographic Seizure Classifier (ESC) model was developed in an earlier study. In this study, the classification model is tested against iEEG annotations provided by three expert reviewers board certified in epilepsy. The three experts individually annotated 3,874 iEEG channels from 36, 29, and 35 patients with leads in the mesiotemporal (MTL), neocortical (NEO), and MTL + NEO regions, respectively. The ESC model's seizure/non-seizure classification scores agreed with the three reviewers at 88.7%, 89.6%, and 84.3% which was similar to how reviewers agreed with each other (92.9%-86.4%). On iEEG channels with all 3 experts in agreement (83.2%), the ESC model had an agreement score of 93.2%. Additionally, the ESC model's certainty scores reflected combined reviewer certainty scores. When 0, 1, 2 and 3 (out of 3) reviewers annotated iEEG channels as electrographic seizures, the ESC model's seizure certainty scores were in the range: [0.12-0.19], [0.32-0.42], [0.61-0.70], and [0.92-0.95] respectively. The ESC model was used as a starting-point model for training a second Seizure Onset Detection (SOD) model. For this task, seizure onset times were manually annotated on a relatively small number of iEEG channels (4,859 from 50 patients). Experiments showed that fine-tuning the ESC models with augmented data (30,768 iEEG channels) resulted in a better validation performance (on 20% of the manually annotated data) compared to training with only the original data (3.1s vs 4.4s median absolute error). Similarly, using the ESC model weights as the starting point for fine-tuning instead of other model weight initialization methods provided significant advantage in SOD model validation performance (3.1s vs 4.7s and 3.5s median absolute error). Finally, on iEEG channels where three expert annotations of seizure onset times were within 1.5 s, the SOD model's seizure onset time prediction was within 1.7 s of expert annotation.

Cervical Radiofrequency Ablation Artifact Mimicking an Electrographic Seizure on RNS

SUMMARY

The responsive neurostimulator continuously monitors the electrocorticogram. It delivers short bursts of high-frequency electrical stimulation when personalized patterns are detected. Intracranial EEG recording including electrocorticography is susceptible to artifacts, albeit at a lesser frequency compared with scalp recording. The authors describe a novel case of a patient with focal epilepsy, bitemporal responsive neurostimulation, and seizures without self-awareness manifest as focal impaired awareness seizures adversely affecting memory. At follow-up evaluation, the patient reported being clinically seizure-free although a single long episode was detected using the Patient Data Management System over the course of 3 years. Initial review identified a left-sided rhythmic discharge with a bilateral spatial field of involvement. In response to detection, the responsive neurostimulation delivered a series of five electrical stimulations. On further review, the patient recalled undergoing cervical radiofrequency ablation, which coincided with the appearance of the "electrographic seizure." Extrinsic electrical artifact involving monomorphic nonevolving waveforms confirmed electrical artifact identified and treated by responsive neurostimulation as an epileptic seizure. On rare occasion, implanted electrical devices may lead to misdiagnosis and mistreatment of patients because of intracranial artifact.

Resting state functional connectivity demonstrates increased segregation in bilateral temporal lobe epilepsy

OBJECTIVE

Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe seizures. The purpose of this study was to leverage network neuroscience to better understand the interictal whole brain network of bilateral TLE (BiTLE).

METHODS

In this study, using a multicenter resting state functional magnetic resonance imaging (rs-fMRI) data set, we constructed whole-brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting-state, whole-brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities. Curves of network density vs each network metric were compared between groups. Finally, we derived a combined metric, which we term the "integration-segregation axis," by combining whole-brain average clustering coefficient and global efficiency curves, and applying principal component analysis (PCA)-based dimensionality reduction.

RESULTS

Compared to UTLE, BiTLE had decreased global efficiency (p = .031), and decreased whole brain average participation coefficient across a range of network densities (p = .019). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p = .020). Differences in network properties separate BiTLE and UTLE along the integration-segregation axis, with regions within the axis having a specificity of up to 0.87 for BiTLE. Along the integration-segregation axis, UTLE patients with poor surgical outcomes were distributed in the same regions as BiTLE, and network metrics confirmed similar patterns of increased segregation in both BiTLE and poor outcome UTLE.

SIGNIFICANCE

Increased interictal whole-brain network segregation, as measured by rs-fMRI, is specific to BiTLE, as well as poor surgical outcome UTLE, and may assist in non-invasively identifying this patient population prior to intracranial electroencephalography or device implantation.

Responsive Neurostimulation in Drug-Resistant Pediatric Epilepsy: Findings From the Epilepsy Surgery Subgroup of the Pediatric Epilepsy Research Consortium

BACKGROUND

Responsive neurostimulation (RNS), a closed-loop intracranial electrical stimulation system, is a palliative surgical option for patients with drug-resistant epilepsy (DRE). RNS is approved by the US Food and Drug Administration for patients aged ≥18 years with pharmacoresistant partial seizures. The published experience of RNS in children is limited.

METHODS

This is a combined prospective and retrospective study of patients aged ≤18 years undergoing RNS placement. Patients were identified from the multicenter Pediatric Epilepsy Research Consortium Surgery Registry from January 2018 to December 2021, and additional data relevant to this study were retrospectively collected and analyzed.

RESULTS

Fifty-six patients received RNS during the study period. The mean age at implantation was 14.9 years; the mean duration of epilepsy, 8.1 years; and the mean number of previously trialed antiseizure medications, 4.2. Five patients (9%) previously trialed dietary therapy, and 19 patients (34%) underwent prior surgery. Most patients (70%) underwent invasive electroencephalography evaluation before RNS implantation. Complications occurred in three patients (5.3%) including malpositioned leads or transient weakness. Follow-up (mean 11.7 months) was available for 55 patients (one lost), and four were seizure-free with RNS off. Outcome analysis of stimulation efficacy was available for 51 patients: 33 patients (65%) were responders (≥50% reduction in seizure frequency), including five patients (10%) who were seizure free at follow-up.

CONCLUSIONS

For young patients with focal DRE who are not candidates for surgical resection, neuromodulation should be considered. Although RNS is off-label for patients aged <18 years, this multicenter study suggests that it is a safe and effective palliative option for children with focal DRE.

Spike patterns surrounding sleep and seizures localize the seizure-onset zone in focal epilepsy

OBJECTIVE

Interictal spikes help localize seizure generators as part of surgical planning for drug-resistant epilepsy. However, there are often multiple spike populations whose frequencies change over time, influenced by brain state. Understanding state changes in spike rates will improve our ability to use spikes for surgical planning. Our goal was to determine the effect of sleep and seizures on interictal spikes, and to use sleep and seizure-related changes in spikes to localize the seizure-onset zone (SOZ).

METHODS

We performed a retrospective analysis of intracranial electroencephalography (EEG) data from patients with focal epilepsy. We automatically detected interictal spikes and we classified different time periods as awake or asleep based on the ratio of alpha to delta power, with a secondary analysis using the recently published SleepSEEG algorithm. We analyzed spike rates surrounding sleep and seizures. We developed a model to localize the SOZ using state-dependent spike rates.

RESULTS

We analyzed data from 101 patients (54 women, age range 16-69). The normalized alpha-delta power ratio accurately classified wake from sleep periods (area under the curve = .90). Spikes were more frequent in sleep than wakefulness and in the post-ictal compared to the pre-ictal state. Patients with temporal lobe epilepsy had a greater wake-to-sleep and pre- to post-ictal spike rate increase compared to patients with extra-temporal epilepsy. A machine-learning classifier incorporating state-dependent spike rates accurately identified the SOZ (area under the curve = .83). Spike rates tended to be higher and better localize the seizure-onset zone in non-rapid eye movement (NREM) sleep than in wake or REM sleep.

SIGNIFICANCE

The change in spike rates surrounding sleep and seizures differs between temporal and extra-temporal lobe epilepsy. Spikes are more frequent and better localize the SOZ in sleep, particularly in NREM sleep. Quantitative analysis of spikes may provide useful ancillary data to localize the SOZ and improve surgical planning.

Machine Learning to Classify Relative Seizure Frequency From Chronic Electrocorticography

PURPOSE

Brain responsive neurostimulation (NeuroPace) treats patients with refractory focal epilepsy and provides chronic electrocorticography (ECoG). We explored how machine learning algorithms applied to interictal ECoG could assess clinical response to changes in neurostimulation parameters.

METHODS

We identified five responsive neurostimulation patients each with ≥200 continuous days of stable medication and detection settings (median, 358 days per patient). For each patient, interictal ECoG segments for each month were labeled as "high" or "low" to represent relatively high or low long-episode (i.e., seizure) count compared with the median monthly long-episode count. Power from six conventional frequency bands from four responsive neurostimulation channels were extracted as features. For each patient, five machine learning algorithms were trained on 80% of ECoG, then tested on the remaining 20%. Classifiers were scored by the area-under-the-receiver-operating-characteristic curve. We explored how individual circadian cycles of seizure activity could inform classifier building.

RESULTS

Support vector machine or gradient boosting models achieved the best performance, ranging from 0.705 (fair) to 0.892 (excellent) across patients. High gamma power was the most important feature, tending to decrease during low-seizure-frequency epochs. For two subjects, training on ECoG recorded during the circadian ictal peak resulted in comparable model performance, despite less data used.

CONCLUSIONS

Machine learning analysis on retrospective background ECoG can classify relative seizure frequency for an individual patient. High gamma power was the most informative, whereas individual circadian patterns of seizure activity can guide model building. Machine learning classifiers built on interictal ECoG may guide stimulation programming.

Beyond Resection: Neuromodulation and Minimally Invasive Epilepsy Surgery

Epilepsy is a common neurological disease impacting both patients and healthcare systems. Approximately one third of patients have drug-resistant epilepsy (DRE) and are candidates for surgical options. However, only a small percentage undergo surgical treatment due to factors such as patient misconception/fear of surgery, healthcare disparities in epilepsy care, complex presurgical evaluation, primary care knowledge gap, and lack of systemic structures to allow effective coordination between referring physician and surgical epilepsy centers. Resective surgical treatments are superior to medication management for DRE patients in terms of seizure outcomes but may be less palatable to patients. There have been major advancements in minimally invasive surgeries (MIS) and neuromodulation techniques that may allay these concerns. Both epilepsy MIS and neuromodulation have shown promising seizure outcomes while minimizing complications. Minimally invasive methods include Laser Interstitial Thermal Therapy (LITT), RadioFrequency Ablation (RFA), Stereotactic RadioSurgery (SRS). Neuromodulation methods, which are more palliative, include Vagus Nerve Stimulation (VNS), Deep Brain Stimulation (DBS), and Responsive Neurostimulation System (RNS). This review will discuss the role of these techniques in varied epilepsy subtypes, their effectiveness in improving seizure control, and adverse outcomes.

Functional connectivity between mesial temporal and default mode structures may help lateralize surgical temporal lobe epilepsy

OBJECTIVE

The most common surgically treatable epilepsy syndrome is mesial temporal lobe epilepsy (mTLE). Preoperative noninvasive lateralization of mTLE is challenging in part due to rapid contralateral seizure spread. Abnormal connections in both the mesial temporal lobe and resting-state networks have been described in mTLE, but it is unclear if connectivity between these networks may aid in lateralization.

METHODS

In 52 patients with left mTLE (LmTLE) or right mTLE (RmTLE) and 52 matched control subjects, the authors acquired 20 minutes of resting-state functional MRI (fMRI) and evaluated functional connectivity of bilateral hippocampi and amygdalae with selected resting-state networks. They used Pearson correlation, network-based statistic, and dynamic causal modeling. Also, to evaluate the clinical utility of a resting-state connectivity model in lateralizing unilateral presurgical mTLE patients, they used receiver operating characteristic curve analysis.

RESULTS

RmTLE patients demonstrated decreased nondirected connectivity between the right hippocampus and default mode network compared with LmTLE patients and control subjects. Network-based statistic analysis revealed that the network with most decreased connectivity that distinguished LmTLE from RmTLE patients included the right hippocampus and amygdala, right lateral orbitofrontal cortices, and bilateral inferior parietal lobules, precuneus, and medial orbitofrontal cortices. Dynamic causal modeling analysis revealed that cross-hemispheric connectivity between hippocampi and amygdalae was predominantly inward toward the epileptogenic side. A regression model incorporating these connectivity patterns was used to accurately lateralize mTLE patients with an area under the receiver operating characteristic curve of 0.87.

CONCLUSIONS

Evaluating fMRI connectivity between mesial temporal structures and default mode network may aid in mTLE lateralization, reduce need for intracranial monitoring, and guide surgical planning.

Seizure count forecasting to aid diagnostic testing in epilepsy

OBJECTIVE

Epilepsy monitoring unit (EMU) admissions are critical for presurgical evaluation of drug-resistant epilepsy but may be nondiagnostic if an insufficient number of seizures are recorded. Seizure forecasting algorithms have shown promise for estimating the likelihood of seizures as a binary event in individual patients, but methods to predict how many seizures will occur remain elusive. Such methods could increase the diagnostic yield of EMU admissions and help patients mitigate seizure-related morbidity. Here, we evaluated the performance of a state-space method that uses prior seizure count data to predict future counts.

METHODS

A Bayesian negative-binomial dynamic linear model (DLM) was developed to forecast daily electrographic seizure counts in 19 patients implanted with a responsive neurostimulation (RNS) device. Holdout validation was used to evaluate performance in predicting the number of electrographic seizures for forecast horizons ranging 1-7 days ahead.

RESULTS

One-day-ahead prediction of the number of electrographic seizures using a negative-binomial DLM resulted in improvement over chance in 73.1% of time segments compared to a random chance forecaster and remained >50% for forecast horizons of up to 7 days. Superior performance (mean error = .99) was obtained in predicting the number of electrographic seizures in the next day compared to three traditional methods for count forecasting (integer-valued generalized autoregressive conditional heteroskedasticity model or INGARCH, 1.10; Croston, 1.06; generalized linear autoregressive moving average model or GLARMA, 2.00). Number of electrographic seizures in the preceding day and laterality of electrographic pattern detections had highest predictive value, with greater number of electrographic seizures and RNS magnet swipes in the preceding day associated with a higher number of electrographic seizures the next day.

SIGNIFICANCE

This study demonstrates that DLMs can predict the number of electrographic seizures a patient will experience days in advance with above chance accuracy. This study represents an important step toward the translation of seizure forecasting methods into the optimization of EMU admissions.

Tracking Multisite Seizure Propagation Using Ictal High-Gamma Activity

PURPOSE

Spatial patterns of long-range seizure propagation in epileptic networks have not been well characterized. Here, we use ictal high-gamma activity (HGA) as a proxy of intense neuronal population firing to map the spatial evolution of seizure recruitment.

METHODS

Ictal HGA (80-150 Hz) was analyzed in 13 patients with 72 seizures recorded by stereotactic depth electrodes, using previously validated methods. Distinct spatial clusters of channels with the ictal high-gamma signature were identified, and seizure hubs were defined as stereotypically recruited nonoverlapping clusters. Clusters correlated with asynchronous seizure terminations to provide supportive evidence for independent seizure activity at these sites. The spatial overlap between seizure hubs and interictal ripples was compared.

RESULTS

Ictal HGA was detected in 71% of seizures and 10% of implanted contacts, enabling tracking of contiguous and noncontiguous seizure recruitment. Multiple seizure hubs were identified in 54% of cases, including 43% of patients thought preoperatively to have unifocal epilepsy. Noncontiguous recruitment was associated with asynchronous seizure termination (odds ratio = 19.7; p = 0.029). Interictal ripples demonstrated greater spatial overlap with ictal HGA in cases with single seizure hubs compared with those with multiple hubs (100% vs. 66% per patient; p = 0.03).

CONCLUSIONS

Ictal HGA may serve as a useful adjunctive biomarker to distinguish contiguous seizure spread from propagation to remote seizure sites. High-gamma sites were found to cluster in stereotyped seizure hubs rather than being broadly distributed. Multiple hubs were common even in cases that were considered unifocal.

Practical considerations in epilepsy neurostimulation

Neuromodulation is a key therapeutic tool for clinicians managing patients with drug-resistant epilepsy. Multiple devices are available with long-term follow-up and real-world experience. The aim of this review is to give a practical summary of available neuromodulation techniques to guide the selection of modalities, focusing on patient selection for devices, common approaches and techniques for initiation of programming, and outpatient management issues. Vagus nerve stimulation (VNS), deep brain stimulation of the anterior nucleus of the thalamus (DBS-ANT), and responsive neurostimulation (RNS) are all supported by randomized controlled trials that show safety and a significant impact on seizure reduction, as well as a suggestion of reduction in the risk of sudden unexplained death in epilepsy (SUDEP). Significant seizure reductions are observed after 3 months for DBS, RNS, and VNS in randomized controlled trials, and efficacy appears to improve with time out to 7 to 10 years of follow-up for all modalities, albeit in uncontrolled follow-up or retrospective studies. A significant number of patients experience seizure-free intervals of 6 months or more with all three modalities. Number and location of epileptogenic foci are important factors affecting efficacy, and together with comorbidities such as severe mood or sleep disorders, may influence the choice of modality. Programming has evolved-DBS is typically initiated at lower current/voltage than used in the pivotal trial, whereas target charge density is lower with RNS, however generalizable optimal parameters are yet to be defined. Noninvasive brain stimulation is an emerging stimulation modality, although it is currently not used widely. In summary, clinical practice has evolved from those established in pivotal trials. Guidance is now available for clinicians who wish to expand their approach, and choice of neuromodulation technique may be tailored to individual patients based on their epilepsy characteristics, risk tolerance, and preferences.

Neuromodulation in drug-resistant epilepsy: A review of current knowledge

Nearly 1% of the global population suffers from epilepsy. Drug-resistant epilepsy (DRE) affects one-third of epileptic patients who are unable to treat their condition with existing drugs. For the treatment of DRE, neuromodulation offers a lot of potential. The background, mechanism, indication, application, efficacy, and safety of each technique are briefly described in this narrative review, with an emphasis on three approved neuromodulation therapies: vagus nerve stimulation (VNS), deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS), and closed-loop responsive neurostimulation (RNS). Neuromodulatory approaches involving direct or induced electrical currents have been developed to lessen seizure frequency and duration in patients with DRE since the notion of electrical stimulation as a therapy for neurologic diseases originated in the early nineteenth century. Although few people have attained total seizure independence for more than 12 months using these treatments, more than half have benefitted from a 50% drop in seizure frequency over time. Although promising outcomes in adults and children with DRE have been achieved, challenges such as heterogeneity among epilepsy types and etiologies, optimization of stimulation parameters, a lack of biomarkers to predict response to neuromodulation therapies, high-level evidence to aid decision-making, and direct comparisons between neuromodulatory approaches remain. To solve these existing gaps, authorize new kinds of neuromodulation, and develop personalized closed-loop treatments, further research is needed. Finally, both invasive and non-invasive neuromodulation seems to be safe. Implantation-related adverse events for invasive stimulation primarily include infection and pain at the implant site. Intracranial hemorrhage is a frequent adverse event for DBS and RNS. Other stimulation-specific side-effects are mild with non-invasive stimulation.

Hippocampal recording via the RNS system reveals marked ipsilateral activation of epileptiform activity during Wada testing

Wada testing remains an important component of pre-surgical testing to assess the feasibility of temporal lobectomy for patients with intractable epilepsy. In this procedure, an anesthetic is injected into either internal carotid artery while memory and language testing is performed, simulating the effect of temporal lobe resection. The mechanism remains poorly understood because the hippocampal vasculature is predominantly via the posterior circulation. We recorded hippocampal EEG during bilateral methohexital Wada testing in three patients who had previously been implanted with a responsive neurostimulation system (RNS) to determine the effect of the injections on hippocampal activity. In all six injections from three patients, methohexital caused immediate, transient increases in hippocampal spikes. With at least two of these injections, the electrographic changes were consistent with electrographic seizures. In all cases, the epileptiform activity was not apparent on scalp EEG and was without obvious clinical correlate other than the negative findings expected from the anesthetic. The results demonstrate the utility of intracranial EEG during Wada testing and suggest that the elicitation of seizures or continuous spiking might contribute to dysfunction of the hippocampus during the Wada test. We hypothesize that this effect is due to disconnection and disinhibition of medial temporal structures.

Seizure freedom after laser amygdalohippocampotomy guided by bilateral responsive neurostimulation in pediatric epilepsy: illustrative case

BACKGROUND

For patients with difficult-to-lateralize temporal lobe epilepsy, the use of chronic recordings as a diagnostic tool to inform subsequent surgical therapy is an emerging paradigm that has been reported in adults but not in children.

OBSERVATIONS

The authors reported the case of a 15-year-old girl with pharmacoresistant temporal lobe epilepsy who was found to have bitemporal epilepsy during a stereoelectroencephalography (sEEG) admission. She underwent placement of a responsive neurostimulator system with bilateral hippocampal depth electrodes. However, over many months, her responsive neurostimulation (RNS) recordings revealed that her typical, chronic seizures were right-sided only. This finding led to a subsequent right-sided laser amygdalohippocampotomy, resulting in seizure freedom.

LESSONS

In this case, RNS chronic recording provided real-world data that enabled more precise seizure localization than inpatient sEEG data, informing surgical decision-making that led to seizure freedom. The use of RNS chronic recordings as a diagnostic adjunct to seizure localization procedures and laser ablation therapies in children is an area with potential for future study.

What is the optimal duration of home-video-EEG monitoring for patients with <1 seizure per day? A simulation study

Ambulatory “at home” video-EEG monitoring (HVEM) may offer a more cost-effective and accessible option as compared to traditional inpatient admissions to epilepsy monitoring units. However, home monitoring may not allow for safe tapering of anti-seizure medications (ASM). As a result, longer periods of monitoring may be necessary to capture a sufficient number of the patients' stereotypic seizures. We aimed to quantitatively estimate the necessary length of HVEM corresponding to various diagnostic scenarios in clinical practice. Using available seizure frequency statistics, we estimated the HVEM duration required to capture one, three, or five seizures on different days, by simulating 100,000 annual time-courses of seizure occurrence in adults and children with more than one and <30 seizures per month (89% of adults and 85% of children). We found that the durations of HVEM needed to record 1, 3, or 5 seizures in 80% of children were 2, 5, and 8 weeks (median 2, 12, and 21 days), respectively, and significantly longer in adults −2, 6, and 10 weeks (median 3, 14, and 26 days; p < 10⁻¹⁰ for all comparisons). Thus, longer HVEM than currently used is needed for expanding its clinical value from diagnosis of nonepileptic or very frequent epileptic events to a presurgical tool for patients with drug-resistant epilepsy. Technical developments and further studies are warranted.

Sub-scalp electroencephalography: A next-generation technique to study human neurophysiology

Sub-scalp electroencephalography (ssEEG) is emerging as a promising technology in ultra-long-term electroencephalography (EEG) recordings. Given the diversity of devices available in this nascent field, uncertainty persists about its utility in epilepsy evaluation. This review critically dissects the many proposed utilities of ssEEG devices including (1) seizure quantification, (2) seizure characterization, (3) seizure lateralization, (4) seizure localization, (5) seizure alarms, (6) seizure forecasting, (7) biomarker discovery, (8) sleep medicine, and (9) responsive stimulation. The different ssEEG devices in development have individual design philosophies with unique strengths and limitations. There are devices offering primarily unilateral recordings (24/7 EEG^TM SubQ, Neuroview^TM, Soenia® UltimateEEG™), bilateral recordings (Minder™, Epios™), and even those with responsive stimulation capability (EASEE®). We synthesize the current knowledge of these ssEEG systems. We review the (1) ssEEG devices, (2) use case scenarios, (3) challenges and (4) suggest a roadmap for ideal ssEEG designs.

Normative intracranial EEG maps epileptogenic tissues in focal epilepsy

Planning surgery for patients with medically refractory epilepsy often requires recording seizures using intracranial EEG. Quantitative measures derived from interictal intracranial EEG yield potentially appealing biomarkers to guide these surgical procedures; however, their utility is limited by the sparsity of electrode implantation as well as the normal confounds of spatiotemporally varying neural activity and connectivity. We propose that comparing intracranial EEG recordings to a normative atlas of intracranial EEG activity and connectivity can reliably map abnormal regions, identify targets for invasive treatment and increase our understanding of human epilepsy. Merging data from the Penn Epilepsy Center and a public database from the Montreal Neurological Institute, we aggregated interictal intracranial EEG retrospectively across 166 subjects comprising >5000 channels. For each channel, we calculated the normalized spectral power and coherence in each canonical frequency band. We constructed an intracranial EEG atlas by mapping the distribution of each feature across the brain and tested the atlas against data from novel patients by generating a z-score for each channel. We demonstrate that for seizure onset zones within the mesial temporal lobe, measures of connectivity abnormality provide greater distinguishing value than univariate measures of abnormal neural activity. We also find that patients with a longer diagnosis of epilepsy have greater abnormalities in connectivity. By integrating measures of both single-channel activity and inter-regional functional connectivity, we find a better accuracy in predicting the seizure onset zones versus normal brain (area under the curve = 0.77) compared with either group of features alone. We propose that aggregating normative intracranial EEG data across epilepsy centres into a normative atlas provides a rigorous, quantitative method to map epileptic networks and guide invasive therapy. We publicly share our data, infrastructure and methods, and propose an international framework for leveraging big data in surgical planning for refractory epilepsy.

Interictal SEEG Resting-State Connectivity Localizes the Seizure Onset Zone and Predicts Seizure Outcome

Localization of epileptogenic zone currently requires prolonged intracranial recordings to capture seizure, which may take days to weeks. The authors developed a novel method to identify the seizure onset zone (SOZ) and predict seizure outcome using short-time resting-state stereotacticelectroencephalography (SEEG) data. In a cohort of 27 drug-resistant epilepsy patients, the authors estimated the information flow via directional connectivity and inferred the excitation-inhibition ratio from the 1/f power slope. They hypothesized that the antagonism of information flow at multiple frequencies between SOZ and non-SOZ underlying the relatively stable epilepsy resting state could be related to the disrupted excitation-inhibition balance. They found flatter 1/f power slope in non-SOZ regions compared to the SOZ, with dominant information flow from non-SOZ to SOZ regions. Greater differences in resting-state information flow between SOZ and non-SOZ regions are associated with favorable seizure outcome. By integrating a balanced random forest model with resting-state connectivity, their method localized the SOZ with an accuracy of 88% and predicted the seizure outcome with an accuracy of 92% using clinically determined SOZ. Overall, this study suggests that brief resting-state SEEG data can significantly facilitate the identification of SOZ and may eventually predict seizure outcomes without requiring long-term ictal recordings.

Magnetic resonance imaging–guided laser interstitial thermal therapy for refractory focal epilepsy in a patient with a fully implanted RNS system: illustrative case

BACKGROUND

The resective surgery plus responsive neurostimulation (RNS) system is an effective treatment for patients with refractory focal epilepsy. Furthermore, the long-term intracranial electroencephalography data provided by the system can inform a future resection or ablation procedure. RNS patients may undergo 1.5-T magnetic resonance imaging (MRI) under the conditions specified in the RNS system MRI guidelines; however, it was unknown if the MRI artifact would limit intraoperative laser interstitial thermal therapy (LITT) in a patient with a fully implanted RNS system.

OBSERVATIONS

The authors were able to complete a successful awake LITT of epileptogenic tissue in a 1.5-T MRI scanner on the ipsilateral side to an implanted RNS system.

LESSONS

If a future LITT procedure is probable, the neurostimulator should be placed contralateral to the side of the potential ablation. Using twist drill holes versus burr holes for depth lead placement may assist in future laser bone anchor seating. Before a LITT procedure in a patient with the neurostimulator ipsilateral to the ablation, 1.5-T MRI thermography scanning should be scheduled preoperatively to assess artifact in the proposed ablation zone. Per the RNS system MRI guidelines, the patient must be positioned supine and awake, with no more than 30 minutes of active scan time before a 30-minute pause.

Normative brain mapping of interictal intracranial EEG to localize epileptogenic tissue

The identification of abnormal electrographic activity is important in a wide range of neurological disorders, including epilepsy for localizing epileptogenic tissue. However, this identification may be challenging during non-seizure (interictal) periods, especially if abnormalities are subtle compared to the repertoire of possible healthy brain dynamics. Here, we investigate if such interictal abnormalities become more salient by quantitatively accounting for the range of healthy brain dynamics in a location-specific manner. To this end, we constructed a normative map of brain dynamics, in terms of relative band power, from interictal intracranial recordings from 234 participants (21 598 electrode contacts). We then compared interictal recordings from 62 patients with epilepsy to the normative map to identify abnormal regions. We proposed that if the most abnormal regions were spared by surgery, then patients would be more likely to experience continued seizures postoperatively. We first confirmed that the spatial variations of band power in the normative map across brain regions were consistent with healthy variations reported in the literature. Second, when accounting for the normative variations, regions that were spared by surgery were more abnormal than those resected only in patients with persistent postoperative seizures (t = -3.6, P = 0.0003), confirming our hypothesis. Third, we found that this effect discriminated patient outcomes (area under curve 0.75 P = 0.0003). Normative mapping is a well-established practice in neuroscientific research. Our study suggests that this approach is feasible to detect interictal abnormalities in intracranial EEG, and of potential clinical value to identify pathological tissue in epilepsy. Finally, we make our normative intracranial map publicly available to facilitate future investigations in epilepsy and beyond.

Expert Perspective: Who May Benefit Most From the New Ultra Long-Term Subcutaneous EEG Monitoring?

Today's modalities for short-term monitoring of EEG are primarily meant for supporting clinical diagnosis of epilepsy or classifying seizures and interictal epileptiform discharges while long-term EEG adds the value of differential diagnosis investigation or pre-surgical evaluation. However, longitudinal epilepsy care relies on patient diaries, which is known to be unreliable for most patients and especially those with focal impaired awareness or nocturnal seizures. The subcutaneous ultra long-term EEG (ULT-EEG) systems alleviate those issue by enabling objective, continuous EEG monitoring for days, weeks, months, or years. Albeit a great advance in continuous EEG over extended periods, it comes with the caveat of limited spatial resolution of two channels. Therefore, the new subcutaneous EEG modality may be especially suited for a selected group of patients. We convened a panel of experienced epileptologists to consider the utility of a subcutaneous, two-channel ULT-EEG device with the goal of developing a consensus-based expert recommendation on selecting the optimal patient types for this investigative technique. The ideal patients to select for this type of monitoring would have focal impaired awareness seizures without predominant motor features and seizures with medium to high voltage patterns. As this technology matures and we learn more about its limitations and benefits we might find a wider array of use case scenarios as it is believed that the benefits for many patients are most likely to outweigh the risks and cost.

Bilateral temporal lobe epilepsy: How many seizures are required in chronic ambulatory electrocorticography to estimate the laterality ratio?

OBJECTIVE

This study was undertaken to measure the duration of chronic electrocorticography (ECoG) needed to attain stable estimates of the seizure laterality ratio in patients with drug-resistant bilateral temporal lobe epilepsy (BTLE).

METHODS

We studied 13 patients with drug-resistant BTLE who were implanted for at least 1 year with a responsive neurostimulation device (RNS System) that provides chronic ambulatory ECoG. Bootstrap analysis and nonlinear regression were applied to model the relationship between chronic ECoG duration and the probability of capturing at least one seizure. Laterality of electrographic seizures in chronic ECoG was compared with the seizure laterality ratio from Phase 1 scalp video-electroencephalographic (vEEG) monitoring. The Kaplan-Meier estimator was used to evaluate time to seizure laterality ratio convergence.

RESULTS

Seizure laterality ratios from Phase 1 scalp vEEG monitoring correlated poorly with those from RNS chronic ECoG (r = .31, p = .30). Across the 13 patients, average electrographic seizure frequencies ranged from 1.4 seizures/month to 5.1 seizures/day. A 50% probability of recording at least one electrographic seizure required 9.1 days of chronic ECoG, and 90% probability required 44.3 days of chronic ECoG. A median recording duration of 150.9 days (5 months), corresponding to a median of 16 seizures, was needed before confidence intervals for the seizure laterality ratio reliably contained the long-term value. The median recording duration before the point estimate of the seizure laterality ratio converged to a stationary value was 236.8 days (7.9 months).

SIGNIFICANCE

RNS chronic ECoG overcomes temporal sampling limitations intrinsic to inpatient Phase 1 vEEG evaluations. In patients with drug-resistant BTLE, approximately 8 months of chronic RNS ECoG are needed to precisely estimate the seizure laterality ratio, with 75% of people with BTLE achieving convergence after 1 year of RNS recording. For individuals who are candidates for unilateral resection based on seizure laterality, optimized recording duration may help avert morbidity associated with delay to definitive treatment.

Multiple mechanisms shape the relationship between pathway and duration of focal seizures

A seizure's electrographic dynamics are characterized by its spatiotemporal evolution, also termed dynamical 'pathway', and the time it takes to complete that pathway, which results in the seizure's duration. Both seizure pathways and durations have been shown to vary within the same patient. However, it is unclear whether seizures following the same pathway will have the same duration or if these features can vary independently. We compared within-subject variability in these seizure features using (i) epilepsy monitoring unit intracranial EEG (iEEG) recordings of 31 patients (mean: 6.7 days, 16.5 seizures/subject), (ii) NeuroVista chronic iEEG recordings of 10 patients (mean: 521.2 days, 252.6 seizures/subject) and (iii) chronic iEEG recordings of three dogs with focal-onset seizures (mean: 324.4 days, 62.3 seizures/subject). While the strength of the relationship between seizure pathways and durations was highly subject-specific, in most subjects, changes in seizure pathways were only weakly to moderately associated with differences in seizure durations. The relationship between seizure pathways and durations was strengthened by seizures that were 'truncated' versions, both in pathway and duration, of other seizures. However, the relationship was weakened by seizures that had a common pathway, but different durations ('elasticity'), or had similar durations, but followed different pathways ('semblance'). Even in subjects with distinct populations of short and long seizures, seizure durations were not a reliable indicator of different seizure pathways. These findings suggest that seizure pathways and durations are modulated by multiple different mechanisms. Uncovering such mechanisms may reveal novel therapeutic targets for reducing seizure duration and severity.

Neuromodulation for Refractory Epilepsy

Three neuromodulation therapies, all using implanted device and electrodes, have been approved to treat adults with drug-resistant focal epilepsy, namely, the vagus nerve stimulation in 1995, deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) in 2018 (2010 in Europe), and responsive neurostimulation (RNS) in 2014. Indications for VNS have more recently extended to children down to age of 4. Limited or anecdotal data are available in other epilepsy syndromes and refractory/super-refractory status epilepticus. Overall, neuromodulation therapies are palliative, with only a minority of patients achieving long-term seizure freedom, justifying favoring such treatments in patients who are not good candidates for curative epilepsy surgery. About half of patients implanted with VNS, ANT-DBS, and RNS have 50% or greater reduction in seizures, with long-term data suggesting increased efficacy over time. Besides their impact on seizure frequency, neuromodulation therapies are associated with various benefits and drawbacks in comparison to antiseizure drugs. Yet, we lack high-level evidence to best position each neuromodulation therapy in the treatment pathways of persons with difficult-to-treat epilepsy.

Minimum standards for inpatient long-term video-EEG monitoring: A clinical practice guideline of the international league against epilepsy and international federation of clinical neurophysiology

The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology develop guidelines aligned with the Epilepsy Guidelines Task Force. We reviewed published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. We found limited high-level evidence aimed at specific aspects of diagnosis for LTVEM performed to evaluate patients with seizures and nonepileptic events (see Table S1). For classification of evidence, we used the Clinical Practice Guideline Process Manual of the American Academy of Neurology. We formulated recommendations for the indications, technical requirements, and essential practice elements of LTVEM to derive minimum standards used in the evaluation of patients with suspected epilepsy using GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). Further research is needed to obtain evidence about long-term outcome effects of LTVEM and establish its clinical utility.

Minimum standards for inpatient long-term video-electroencephalographic monitoring: A clinical practice guideline of the International League Against Epilepsy and International Federation of Clinical Neurophysiology

The objective of this clinical practice guideline is to provide recommendations on the indications and minimum standards for inpatient long-term video-electroencephalographic monitoring (LTVEM). The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology develop guidelines aligned with the Epilepsy Guidelines Task Force. We reviewed published evidence using the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement. We found limited high-level evidence aimed at specific aspects of diagnosis for LTVEM performed to evaluate patients with seizures and nonepileptic events. For classification of evidence, we used the Clinical Practice Guideline Process Manual of the American Academy of Neurology. We formulated recommendations for the indications, technical requirements, and essential practice elements of LTVEM to derive minimum standards used in the evaluation of patients with suspected epilepsy using GRADE (Grading of Recommendations Assessment, Development, and Evaluation). Further research is needed to obtain evidence about long-term outcome effects of LTVEM and to establish its clinical utility.

Real-World Preliminary Experience With Responsive Neurostimulation in Pediatric Epilepsy: A Multicenter Retrospective Observational Study

BACKGROUND

Despite the well-documented utility of responsive neurostimulation (RNS, NeuroPace) in adult epilepsy patients, literature on the use of RNS in children is limited.

OBJECTIVE

To determine the real-world efficacy and safety of RNS in pediatric epilepsy patients.

METHODS

Patients with childhood-onset drug-resistant epilepsy treated with RNS were retrospectively identified at 5 pediatric centers. Reduction of disabling seizures and complications were evaluated for children (<18 yr) and young adults (>18 yr) and compared with prior literature pertaining to adult patients.

RESULTS

Of 35 patients identified, 17 were <18 yr at the time of RNS implantation, including a 3-yr-old patient. Four patients (11%) had concurrent resection. Three complications, requiring additional surgical interventions, were noted in young adults (2 infections [6%] and 1 lead fracture [3%]). No complications were noted in children. Among the 32 patients with continued therapy, 2 (6%) achieved seizure freedom, 4 (13%) achieved ≥90% seizure reduction, 13 (41%) had ≥50% reduction, 8 (25%) had <50% reduction, and 5 (16%) experienced no improvement. The average follow-up duration was 1.7 yr (median 1.8 yr, range 0.3-4.8 yr). There was no statistically significant difference for seizure reduction and complications between children and young adults in our cohort or between our cohort and the adult literature.

CONCLUSION

These preliminary data suggest that RNS is well tolerated and an effective off-label surgical treatment of drug-resistant epilepsy in carefully selected pediatric patients as young as 3 yr of age. Data regarding long-term efficacy and safety in children will be critical to optimize patient selection.

Ambulatory EEG: Crossing the divide during a pandemic

The COVID-19 pandemic forced temporary closure of epilepsy monitoring units across the globe due to potential hospital-based contagion. As COVID-19 exposures and deaths continues to surge in the United States and around the world, other types of long-term EEG monitoring have risen to fill the gap and minimize hospital exposure. AEEG has high yield compared to standard EEG. Prolonged audio-visual video-EEG capability can record events and epileptiform activity with quality like inpatient video-EEG monitoring. Technological advances in AEEG using miniaturized hardware and wireless secure transmission have evolved to small portable devices that are perfect for people forced to stay at home during the pandemic. Application of seizure detection algorithms and Cloud-based storage with real-time access provides connectivity to AEEG interpreters during prolonged "shut-down". In this article we highlight the benefits of AEEG as an alternative to diagnostic inpatient VEM during the paradigm shift to mobile heath forced by the Coronavirus.

Neuromodulation in epilepsy: state-of-the-art approved therapies

Three neuromodulation therapies have been appropriately tested and approved in refractory focal epilepsies: vagus nerve stimulation (VNS), deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS), and closed-loop responsive neurostimulation of the epileptogenic zone or zones. These therapies are primarily palliative. Only a few individuals have achieved complete freedom from seizures for more than 12 months with these therapies, whereas more than half have benefited from long-term reduction in seizure frequency of more than 50%. Implantation-related adverse events primarily include infection and pain at the implant site. Intracranial haemorrhage is a frequent adverse event for ANT-DBS and responsive neurostimulation. Other stimulation-specific side-effects are observed with VNS and ANT-DBS. Biomarkers to predict response to neuromodulation therapies are not available, and high-level evidence to aid decision making about when and for whom these therapies should be preferred over other antiepileptic treatments is scant. Future studies are thus needed to address these shortfalls in knowledge, approve other forms of neuromodulation, and develop personalised closed-loop therapies with embedded machine learning. Until then, neuromodulation could be considered for individuals with intractable seizures, ideally after the possibility of curative surgical treatment has been carefully assessed and ruled out or judged less appropriate.

Chronic electroencephalography in epilepsy with a responsive neurostimulation device: current status and future prospects

INTRODUCTION

Implanted neurostimulation devices are gaining traction as therapeutic options for people with certain forms of drug-resistant focal epilepsy. Some of these devices enable chronic electroencephalography (cEEG), which offers views of the dynamics of brain activity in epilepsy over unprecedented time horizons.

AREAS COVERED

This review focuses on clinical insights and basic neuroscience discoveries enabled by analyses of cEEG from an exemplar device, the NeuroPace RNS® System. Applications of RNS cEEG covered here include counting and lateralizing seizures, quantifying medication response, characterizing spells, forecasting seizures, and exploring mechanisms of cognition. Limitations of the RNS System are discussed in the context of next-generation devices in development.

EXPERT OPINION

The wide temporal lens of cEEG helps capture the dynamism of epilepsy, revealing phenomena that cannot be appreciated with short duration recordings. The RNS System is a vanguard device whose diagnostic utility rivals its therapeutic benefits, but emerging minimally invasive devices, including those with subscalp recording electrodes, promise to be more applicable within a broad population of people with epilepsy. Epileptology is on the precipice of a paradigm shift in which cEEG is a standard part of diagnostic evaluations and clinical management is predicated on quantitative observations integrated over long timescales.

Low frequency novel interictal EEG biomarker for localizing seizures and predicting outcomes

Localizing hyperexcitable brain tissue to treat focal seizures remains challenging. We want to identify the seizure onset zone from interictal EEG biomarkers. We hypothesize that a combination of interictal EEG biomarkers, including a novel low frequency marker, can predict mesial temporal involvement and can assist in prognosis related to surgical resections. Interictal direct current wide bandwidth invasive EEG recordings from 83 patients implanted with 5111 electrodes were retrospectively studied. Logistic regression was used to classify electrodes and patient outcomes. A feed-forward neural network was implemented to understand putative mechanisms. Interictal infraslow frequency EEG activity was decreased for seizure onset zone electrodes while faster frequencies such as delta (2-4 Hz) and beta-gamma (20-50 Hz) activity were increased. These spectral changes comprised a novel interictal EEG biomarker that was significantly increased for mesial temporal seizure onset zone electrodes compared to non-seizure onset zone electrodes. Interictal EEG biomarkers correctly classified mesial temporal seizure onset zone electrodes with a specificity of 87% and positive predictive value of 80%. These interictal EEG biomarkers also correctly classified patient outcomes after surgical resection with a specificity of 91% and positive predictive value of 87%. Interictal infraslow EEG activity is decreased near the seizure onset zone while higher frequency power is increased, which may suggest distinct underlying physiologic mechanisms. Narrowband interictal EEG power bands provide information about the seizure onset zone and can help predict mesial temporal involvement in seizure onset. Narrowband interictal EEG power bands may be less useful for predictions related to non-mesial temporal electrodes. Together with interictal epileptiform discharges and high-frequency oscillations, these interictal biomarkers may provide prognostic information prior to surgical resection. Computational modelling suggests changes in neural adaptation may be related to the observed low frequency power changes.

Smaller Knife, Fewer Seizures? Recent Advances in Minimally Invasive Techniques in Pediatric Epilepsy Surgery

Children with drug-resistant epilepsy are at high risk for developmental delay, increased mortality, psychiatric comorbidities, and requiring assistance with activities of daily living. Despite the advent of new and effective pharmacologic therapies, about one in 5 children will develop drug-resistant epilepsy, and most of these children continue to have seizures despite trials of other medication. Epilepsy surgery is often a safe and effective option which may offer seizure freedom or at least a significant reduction in seizure burden in many children. However, despite published evidence of safety and efficacy, epilepsy surgery remains underutilized in the pediatric population. Patient and family fears about the risks of surgery may contribute to this gap. Less invasive surgical techniques may be more palatable to children with epilepsy and their caregivers. In this review, we present recent advances in minimally invasive techniques for the surgical treatment of epilepsy as well as intriguing possibilities for the future. We describe the indications for, benefits of, and limits to minimally-invasive techniques including Stereo-encephalography, laser interstitial thermal ablation, deep brain stimulation, focused ultrasound, stereo-encephalography-guided radiofrequency ablation, endoscopic disconnections, and responsive neurostimulation.