Clinical and electrocorticographic response to antiepileptic drugs in patients treated with responsive stimulation

Corticothalamic Responsive Neurostimulation for Focal Epilepsy: A Single-Center Experience

PURPOSE

Owing to its extensive, reciprocal connectivity with the cortex and other subcortical structures, the thalamus is considered an important target for neuromodulation in drug-resistant focal epilepsy. Using corticothalamic stimulation, it is possible to modulate both the thalamus and the cortical seizure onset zone. Limited published clinical experience describes corticothalamic stimulation with depth leads targeting one of the anterior (ANT), centromedian (centromedian nucleus), or pulvinar (PUL) thalamic nuclei. However, it is not clear which of these nuclei is the "best" therapeutic target.

METHODS

This study comprised a single-center experience with corticothalamic responsive neurostimulation using the RNS System to target these three thalamic nuclei. Presented here are the methods for target selection and device programming as well as clinical outcomes and a comparison of ictal and nonictal electrophysiological features.

RESULTS

In this small retrospective study ( N = 19), responsive corticothalamic neurostimulation was an effective therapy for 79% of patients (≥50% reduction in disabling seizure frequency), regardless of whether the thalamic lead was implanted in the ANT ( N = 2), PUL ( N = 6), or centromedian nucleus ( N = 11). Twenty-six percent of patients reported a reduction in disabling seizure frequency ≥90%. Both high frequency (≥100 Hz) and low (≤20 Hz) frequency were used to stimulate the thalamus depending on the patient's response and ability to tolerate higher charge densities. In all patients, a longer burst duration (2000-5000 ms) was ultimately implemented on the thalamic leads. Across patients, peaks in the intracranial EEG were observed at theta, beta, gamma, and sleep spindle frequencies. Changes in frequency content and distribution were observed over time in all three nuclei.

CONCLUSIONS

These results indicate that both high frequency and low frequency corticothalamic responsive neurostimulation can potentially be an effective adjunctive therapy in drug-resistant focal epilepsy. These data can also contribute to a broader understanding of thalamic electrophysiology in the context of focal epilepsy.

OxcarNet: sinc convolutional network with temporal and channel attention for prediction of oxcarbazepine monotherapy responses in patients with newly diagnosed epilepsy

Objective.Monotherapy with antiepileptic drugs (AEDs) is the preferred strategy for the initial treatment of epilepsy. However, an inadequate response to the initially prescribed AED is a significant indicator of a poor long-term prognosis, emphasizing the importance of precise prediction of treatment outcomes with the initial AED regimen in patients with epilepsy.Approach. We introduce OxcarNet, an end-to-end neural network framework developed to predict treatment outcomes in patients undergoing oxcarbazepine monotherapy. The proposed predictive model adopts a Sinc Module in its initial layers for adaptive identification of discriminative frequency bands. The derived feature maps are then processed through a Spatial Module, which characterizes the scalp distribution patterns of the electroencephalography (EEG) signals. Subsequently, these features are fed into an attention-enhanced Temporal Module to capture temporal dynamics and discrepancies. A channel module with an attention mechanism is employed to reveal inter-channel dependencies within the output of the Temporal Module, ultimately achieving response prediction. OxcarNet was rigorously evaluated using a proprietary dataset of retrospectively collected EEG data from newly diagnosed epilepsy patients at Nanjing Drum Tower Hospital. This dataset included patients who underwent long-term EEG monitoring in a clinical inpatient setting.Main results.OxcarNet demonstrated exceptional accuracy in predicting treatment outcomes for patients undergoing Oxcarbazepine monotherapy. In the ten-fold cross-validation, the model achieved an accuracy of 97.27%, and in the validation involving unseen patient data, it maintained an accuracy of 89.17%, outperforming six conventional machine learning methods and three generic neural decoding networks. These findings underscore the model's effectiveness in accurately predicting the treatment responses in patients with newly diagnosed epilepsy. The analysis of features extracted by the Sinc filters revealed a predominant concentration of predictive frequencies in the high-frequency range of the gamma band.Significance. The findings of our study offer substantial support and new insights into tailoring early AED selection, enhancing the prediction accuracy for the responses of AEDs.

Seizure Cycles under Pharmacotherapy

OBJECTIVE

This study was undertaken to determine the effects of antiseizure medications (ASMs) on multidien (multiday) cycles of interictal epileptiform activity (IEA) and seizures and evaluate their potential clinical significance.

METHODS

We retrospectively analyzed up to 10 years of data from 88 of the 256 total adults with pharmacoresistant focal epilepsy who participated in the clinical trials of the RNS System, an intracranial device that keeps records of IEA counts. Following adjunctive ASM trials, we evaluated changes over months in (1) rates of self-reported disabling seizures and (2) multidien IEA cycle strength (spectral power for periodicity between 4 and 40 days). We used a survival analysis and the receiver operating characteristics to assess changes in IEA as a predictor of seizure control.

RESULTS

Among 56 (33.3%) of the 168 adjunctive ASM trials suitable for analysis, ASM introduction was followed by an average 50 to 70% decrease in multidien IEA cycle strength and a concomitant 50 to 70% decrease in relative seizure rate for up to 12 months. Individuals with a ≥50% decrease in IEA cycle strength in the first 3 months of an ASM trial had a higher probability of remaining seizure responders (≥50% seizure rate reduction, p < 10-7) or super-responders (≥90%, p < 10-8) over the next 12 months.

INTERPRETATION

In this large cohort, a decrease in multidien IEA cycle strength following initiation of an adjunctive ASM correlated with seizure control for up to 12 months, suggesting that fluctuations in IEA mirror "disease activity" in pharmacoresistant focal epilepsy and may have clinical utility as a biomarker to predict treatment response. ANN NEUROL 2024;95:743-753.

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.

Intracerebral electrographic activity following a single dose of diazepam nasal spray: A pilot study

OBJECTIVE

Rescue benzodiazepine medication can be used to treat seizure clusters, which are intermittent, stereotypic episodes of frequent seizure activity that are distinct from a patient's usual seizure pattern. The NeuroPace RNS® System is a device that detects abnormal electrographic activity through intracranial electrodes and administers electrical stimulation to control seizures. Reductions in electrographic activity over days to weeks have been associated with the longer-term efficacy of daily antiseizure medications (ASMs). In this pilot study, electrographic activity over hours to days was examined to assess the impact of a single dose of a proven rescue therapy (diazepam nasal spray) with a rapid onset of action.

METHODS

Adult volunteers (>18 years old) with clinically indicated RNS (stable settings and ASM usage) received a weight-based dose of diazepam nasal spray in the absence of a clinical seizure. Descriptive statistics for a number of detections and a sum of durations of detections at 10-min, hourly, and 24-h intervals during the 7-day (predose) baseline period were calculated. Post-dose detections at each time interval were compared with the respective baseline-detection intervals using a 1 SD threshold. The number of long episodes that occurred after dosing also were compared with the baseline.

RESULTS

Five participants were enrolled, and four completed the study; the excluded participant had recurrent seizures during the study. There were no consistent changes (difference >1 SD) in detections between post-dose and mean baseline values. Although variability was high (1 SD was often near or exceeded the mean), three participants showed possible trends for reductions in one or more electrographic variables following treatment.

SIGNIFICANCE

RNS-assessed electrographic detections and durations were not shown to be sensitive measures of short-term effects associated with a single dose of rescue medication in this small group of participants. The variability of detections may have masked a measurable drug effect.

PLAIN LANGUAGE SUMMARY

Rescue drugs are used to treat seizure clusters. Responsive neurostimulation (RNS) devices detect and record epilepsy brain waves and then send a pulse to help stop seizures. This pilot study looked at whether one dose of a rescue treatment changes brain activity detected by RNS. There was a very wide range of detections, which made it difficult to see if or how the drug changed brain activity. New studies should look at other types of brain activity, multiple doses, and larger patient groups.

Utility of Chronic Intracranial Electroencephalography in Responsive Neurostimulation Therapy

Responsive neurostimulation (RNS) therapy is an effective treatment for reducing seizures in some patients with focal epilepsy. Utilizing a chronically implanted device, RNS involves monitoring brain activity signals for user-defined patterns of seizure activity and delivering electrical stimulation in response. Devices store chronic data including counts of detected activity patterns and brief recordings of intracranial electroencephalography signals. Data platforms for reviewing stored chronic data retrospectively may be used to evaluate therapy performance and to fine-tune detection and stimulation settings. New frontiers in RNS research can leverage raw chronic data to reverse engineer neurostimulation mechanisms and improve therapy effectiveness.

Thermal neuromodulation using pulsed and continuous infrared illumination in a penicillin-induced acute epilepsy model

Infrared neuromodulation (INM) is a promising neuromodulation tool that utilizes pulsed or continuous-wave near-infrared (NIR) laser light to produce an elevation of the background temperature of the neural tissue. The INM-based cortical heating has been proven as an effective modality to induce changes in neuronal activities. In this paper, we investigate the effect of INM-based cortical heating on the characteristics of interictal epileptiform discharges (IEDs) induced by penicillin in anesthetized rats. Cortical heating was conducted using a NIR laser light guided through a needle-like silicon-based waveguide probe. We detected penicillin-induced cortical IEDs from preprocessed micro-electrocorticography ([Formula: see text]ECoG) recordings, then we assessed changes in various temporal and spectral features of IEDs due to INM. Our findings show that the fast cortical heating phase obtained with continuous-wave NIR light is highly associated with a reduction of IED amplitudes, small but significant changes in the negative amplitude of IEDs compared with the baseline, and a proportional increase in the power of frequency bands related to delta/theta (2-8 Hz) and gamma (28-80 Hz) oscillations. Furthermore, a low rate of cortical heating with pulsed NIR illumination has a more inhibitory impact on the sharp negative polarity of IEDs. Our findings do not indicate a clear reduction in the frequency of IEDs in anesthetized rodents. In contrast, 2-4 min of continuous laser illumination leads to a notable increase in IED frequency. This effect of INM could potentially restrict its use in therapeutic applications related to epilepsy. However, the thermal effect of INM on cortical neurons induces changes in other characteristics of IEDs, which could prove beneficial for future applications.

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.

Prognostic interictal electroencephalographic biomarkers and models to assess antiseizure medication efficacy for clinical practice: A scoping review

Antiseizure medication (ASM) is the primary treatment for epilepsy. In clinical practice, methods to assess ASM efficacy (predict seizure freedom or seizure reduction), during any phase of the drug treatment lifecycle, are limited. This scoping review identifies and appraises prognostic electroencephalographic (EEG) biomarkers and prognostic models that use EEG features, which are associated with seizure outcomes following ASM initiation, dose adjustment, or withdrawal. We also aim to summarize the population and context in which these biomarkers and models were identified and described, to understand how they could be used in clinical practice. Between January 2021 and October 2022, four databases, references, and citations were systematically searched for ASM studies investigating changes to interictal EEG or prognostic models using EEG features and seizure outcomes. Study bias was appraised using modified Quality in Prognosis Studies criteria. Results were synthesized into a qualitative review. Of 875 studies identified, 93 were included. Biomarkers identified were classed as qualitative (visually identified by wave morphology) or quantitative. Qualitative biomarkers include identifying hypsarrhythmia, centrotemporal spikes, interictal epileptiform discharges (IED), classifying the EEG as normal/abnormal/epileptiform, and photoparoxysmal response. Quantitative biomarkers were statistics applied to IED, high-frequency activity, frequency band power, current source density estimates, pairwise statistical interdependence between EEG channels, and measures of complexity. Prognostic models using EEG features were Cox proportional hazards models and machine learning models. There is promise that some quantitative EEG biomarkers could be used to assess ASM efficacy, but further research is required. There is insufficient evidence to conclude any specific biomarker can be used for a particular population or context to prognosticate ASM efficacy. We identified a potential battery of prognostic EEG biomarkers, which could be combined with prognostic models to assess ASM efficacy. However, many confounders need to be addressed for translation into clinical practice.

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.

Intracranial electroencephalographic biomarker predicts effective responsive neurostimulation for epilepsy prior to treatment

OBJECTIVE

Despite the overall success of responsive neurostimulation (RNS) therapy for drug-resistant focal epilepsy, clinical outcomes in individuals vary significantly and are hard to predict. Biomarkers that indicate the clinical efficacy of RNS-ideally before device implantation-are critically needed, but challenges include the intrinsic heterogeneity of the RNS patient population and variability in clinical management across epilepsy centers. The aim of this study is to use a multicenter dataset to evaluate a candidate biomarker from intracranial electroencephalographic (iEEG) recordings that predicts clinical outcome with subsequent RNS therapy.

METHODS

We assembled a federated dataset of iEEG recordings, collected prior to RNS implantation, from a retrospective cohort of 30 patients across three major epilepsy centers. Using ictal iEEG recordings, each center independently calculated network synchronizability, a candidate biomarker indicating the susceptibility of epileptic brain networks to RNS therapy.

RESULTS

Ictal measures of synchronizability in the high-γ band (95-105 Hz) significantly distinguish between good and poor RNS responders after at least 3 years of therapy under the current RNS therapy guidelines (area under the curve = .83). Additionally, ictal high-γ synchronizability is inversely associated with the degree of therapeutic response.

SIGNIFICANCE

This study provides a proof-of-concept roadmap for collaborative biomarker evaluation in federated data, where practical considerations impede full data sharing across centers. Our results suggest that network synchronizability can help predict therapeutic response to RNS therapy. With further validation, this biomarker could facilitate patient selection and help avert a costly, invasive intervention in patients who are unlikely to benefit.

Closed-Loop Brain Stimulation and Paradigm Shifts in Epilepsy Surgery

Advances in device technology have created greater flexibility in treating seizures as emergent properties of networks that exist on a local to global continuum. All patients with drug-resistant epilepsy are potential surgical candidates, given that intracranial neuromodulation through deep brain stimulation and responsive neurostimulation can reduce seizures and improve quality of life, even in multifocal and generalized epilepsies. To achieve this goal, indications and strategies for diagnostic epilepsy surgery are evolving. This article describes the state-of-the-art in epilepsy surgery and related changes in how we define indications for diagnostic and therapeutic surgical intervention.

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.

A Primer on Hyperdimensional Computing for iEEG Seizure Detection

A central challenge in today's care of epilepsy patients is that the disease dynamics are severely under-sampled in the currently typical setting with appointment-based clinical and electroencephalographic examinations. Implantable devices to monitor electrical brain signals and to detect epileptic seizures may significantly improve this situation and may inform personalized treatment on an unprecedented scale. These implantable devices should be optimized for energy efficiency and compact design. Energy efficiency will ease their maintenance by reducing the time of recharging, or by increasing the lifetime of their batteries. Biological nervous systems use an extremely small amount of energy for information processing. In recent years, a number of methods, often collectively referred to as brain-inspired computing, have also been developed to improve computation in non-biological hardware. Here, we give an overview of one of these methods, which has in particular been inspired by the very size of brains' circuits and termed hyperdimensional computing. Using a tutorial style, we set out to explain the key concepts of hyperdimensional computing including very high-dimensional binary vectors, the operations used to combine and manipulate these vectors, and the crucial characteristics of the mathematical space they inhabit. We then demonstrate step-by-step how hyperdimensional computing can be used to detect epileptic seizures from intracranial electroencephalogram (EEG) recordings with high energy efficiency, high specificity, and high sensitivity. We conclude by describing potential future clinical applications of hyperdimensional computing for the analysis of EEG and non-EEG digital biomarkers.

Neuromodulation in Drug Resistant Epilepsy

Epilepsy affects approximately 70 million people worldwide, and it is a significant contributor to the global burden of neurological disorders. Despite the advent of new AEDs, drug resistant-epilepsy continues to affect 30-40% of PWE. Once identified as having drug-resistant epilepsy, these patients should be referred to a comprehensive epilepsy center for evaluation to establish if they are candidates for potential curative surgeries. Unfortunately, a large proportion of patients with drug-resistant epilepsy are poor surgical candidates due to a seizure focus located in eloquent cortex, multifocal epilepsy or inability to identify the zone of ictal onset. An alternative treatment modality for these patients is neuromodulation. Here we present the evidence, indications and safety considerations for the neuromodulation therapies in vagal nerve stimulation (VNS), responsive neurostimulation (RNS), or deep brain stimulation (DBS).

Behavioral and Neural Variability of Naturalistic Arm Movements

Motor behaviors are central to many functions and dysfunctions of the brain, and understanding their neural basis has consequently been a major focus in neuroscience. However, most studies of motor behaviors have been restricted to artificial, repetitive paradigms, far removed from natural movements performed "in the wild." Here, we leveraged recent advances in machine learning and computer vision to analyze intracranial recordings from 12 human subjects during thousands of spontaneous, unstructured arm reach movements, observed over several days for each subject. These naturalistic movements elicited cortical spectral power patterns consistent with findings from controlled paradigms, but with considerable neural variability across subjects and events. We modeled interevent variability using 10 behavioral and environmental features; the most important features explaining this variability were reach angle and day of recording. Our work is among the first studies connecting behavioral and neural variability across cortex in humans during unstructured movements and contributes to our understanding of long-term naturalistic behavior.

Recent Advancement of Technologies and the Transition to New Concepts in Epilepsy Surgery

Fruitful progress and change have been accomplished in epilepsy surgery as science and technology advance. Stereotactic electroencephalography (SEEG) was originally developed by Talairach and Bancaud at Hôspital Sainte-Anne in the middle of the 20th century. SEEG has survived, and is now being recognized once again, especially with the development of neurosurgical robots. Many epilepsy centers have already replaced invasive monitoring with subdural electrodes (SDEs) by SEEG with depth electrodes worldwide. SEEG has advantages in terms of complication rates as shown in the previous reports. However, it would be more indispensable to demonstrate how much SEEG has contributed to improving seizure outcomes in epilepsy surgery. Vagus nerve stimulation (VNS) has been an only implantable device since 1990s, and has obtained the autostimulation mode which responds to ictal tachycardia. In addition to VNS, responsive neurostimulator (RNS) joined in the options of palliative treatment for medically refractory epilepsy. RNS is winning popularity in the United States because the device has abilities of both neurostimulation and recording of ambulatory electrocorticography (ECoG). Deep brain stimulation (DBS) has also attained approval as an adjunctive therapy in Europe and the United States. Ablative procedures such as SEEG-guided radiofrequency thermocoagulation (RF-TC) and laser interstitial thermal therapy (LITT) have been developed as less invasive options in epilepsy surgery. There will be more alternatives and tools in this field than ever before. Consequently, we will need to define benefits, indications, and limitations of these new technologies and concepts while adjusting ourselves to a period of fundamental transition in our foreseeable future.

Accuracy and Workflow Improvements for Responsive Neurostimulation Hippocampal Depth Electrode Placement Using Robotic Stereotaxy

Background: Robotic stereotaxy is increasingly common in epilepsy surgery for the implantation of stereo-electroencephalography (sEEG) electrodes for intracranial seizure monitoring. The use of robots is also gaining popularity for permanent stereotactic lead implantation applications such as in deep brain stimulation and responsive neurostimulation (RNS) procedures.

Objective: We describe the evolution of our robotic stereotactic implantation technique for placement of occipital-approach hippocampal RNS depth leads.

Methods: We performed a retrospective review of 10 consecutive patients who underwent robotic RNS hippocampal depth electrode implantation. Accuracy of depth lead implantation was measured by registering intraoperative post-implantation fluoroscopic CT images and post-operative CT scans with the stereotactic plan to measure implantation accuracy. Seizure data were also collected from the RNS devices and analyzed to obtain initial seizure control outcome estimates.

Results: Ten patients underwent occipital-approach hippocampal RNS depth electrode placement for medically refractory epilepsy. A total of 18 depth electrodes were included in the analysis. Six patients (10 electrodes) were implanted in the supine position, with mean target radial error of 1.9 ± 0.9 mm (mean ± SD). Four patients (8 electrodes) were implanted in the prone position, with mean radial error of 0.8 ± 0.3 mm. The radial error was significantly smaller when electrodes were implanted in the prone position compared to the supine position (p = 0.002). Early results (median follow-up time 7.4 months) demonstrate mean seizure frequency reduction of 26% (n = 8), with 37.5% achieving ≥50% reduction in seizure frequency as measured by RNS long episode counts.

Conclusion: Prone positioning for robotic implantation of occipital-approach hippocampal RNS depth electrodes led to lower radial target error compared to supine positioning. The robotic platform offers a number of workflow advantages over traditional frame-based approaches, including parallel rather than serial operation in a bilateral case, decreased concern regarding human error in setting frame coordinates, and surgeon comfort.

Responsive Neurostimulation as a Novel Palliative Option in Epilepsy Surgery

Patients with drug-resistant focal onset epilepsy are not always suitable candidates for resective surgery, a definitive intervention to control their seizures. The alternative surgical treatment for these patients in Japan has been vagus nerve stimulation (VNS). Besides VNS, epileptologists in the United States can choose a novel palliative option called responsive neurostimulation (RNS), a closed-loop neuromodulation system approved by the US Food and Drug Administration in 2013. The RNS System continuously monitors neural electroencephalography (EEG) activity at the possible seizure onset zone (SOZ) where electrodes are placed and responds with electrical stimulation when a pre-defined epileptic activity is detected. The controlled clinical trials in the United States have demonstrated long-term utility and safety of the RNS System. Seizure reduction rates have continued to improve over time, reaching 75% over 9 years of treatment. The incidence of implant-site infection, the most frequent device-related adverse event, is similar to those of other neuromodulation devices. The RNS System has shown favorable efficacy for both mesial temporal lobe epilepsy (TLE) and neocortical epilepsy of the eloquent cortex. Another unique advantage of the RNS System is its ability to provide chronic monitoring of ambulatory electrocorticography (ECoG). Valuable information obtained from ECoG monitoring provides a better understanding of the state of epilepsy in each patient and improves clinical management. This article reviews the developmental history, structure, and clinical utility of the RNS System, and discusses its indications as a novel palliative option for drug-resistant epilepsy.

Brain-responsive corticothalamic stimulation in the centromedian nucleus for the treatment of regional neocortical epilepsy

OBJECTIVE

The aim of the study was to determine if corticothalamic responsive stimulation targeting the centromedian nucleus of the thalamus (CMT) is a potential treatment for neocortical epilepsies with regional onsets.

METHODS

We assessed efficacy and safety of CMT and neocortical responsive stimulation, detection, and stimulation programming, methods for implantation, and location and patterns of electrographic seizure onset and spread in 7 patients with medically intractable focal seizures with a regional neocortical onset.

RESULTS

The median follow-up duration was 17 months (average: 17 months, range: 8-28 months). The median % reduction in disabling seizures (excludes auras) in the 7 patients was 88% (mean: 80%, range: 55-100%). The median % reduction in all seizure types (disabling + auras) was 73% (mean: 67%, range: 15-94%). There were no adverse events related to implantation of the responsive neurostimulator and leads or related to the delivery of responsive stimulation. Stimulation-related contralateral paresthesias were addressed by adjusting stimulation parameters in the clinic during stimulation testing. Electrographic seizures were detected in the CMT and neocortex in all seven patients. Four patients had simultaneous or near simultaneous seizure onsets in the neocortex and CMT and three had onsets in the neocortex with spread to the CMT.

CONCLUSION

In this small series of patients with medically intractable focal seizures and regional neocortical onset, responsive neurostimulation to the neocortex and CMT improved seizure control and was well tolerated.

SIGNIFICANCE

Responsive corticothalamic neurostimulation of the CMT and neocortex is a potential treatment for patients with regional neocortical epilepsies.

The RNS System: brain-responsive neurostimulation for the treatment of epilepsy

Introduction: Epilepsy affects more than 1% of the US population, and over 30% of adults with epilepsy do not respond to antiseizure medications without life-impacting medication-related side effects. Resection of the seizure focus is not an option for many patients because it would cause unacceptable neurological or cognitive harm. For these patients, neuromodulation has emerged as a nondestructive, effective, and safe alternative. The NeuroPace® RNS® System, the only brain-responsive neurostimulation device, records neural activity from leads placed at one or two seizure foci. When the neurostimulator detects epileptiform activity, as defined for each patient by his or her physician, brief pulses of electrical stimulation are delivered to normalize the activity.Areas covered: This review describes the RNS System, the results of multi-year clinical trials, and the research discoveries enabled by the chronic ambulatory brain data collected by the RNS System.Expert commentary: Brain-responsive neurostimulation could potentially be used to treat any episodic neurological disorder that's accompanied by a neurophysiological biomarker of severity. Combining advanced machine learning approaches with the chronic ambulatory brain data collected by the RNS System could eventually enable automatic fine-tuning of detection and stimulation for each patient, creating a general-purpose neurotechnological platform for precision medicine.

Nine-year prospective efficacy and safety of brain-responsive neurostimulation for focal epilepsy

OBJECTIVE

To prospectively evaluate safety and efficacy of brain-responsive neurostimulation in adults with medically intractable focal onset seizures (FOS) over 9 years.

METHODS

Adults treated with brain-responsive neurostimulation in 2-year feasibility or randomized controlled trials were enrolled in a long-term prospective open label trial (LTT) to assess safety, efficacy, and quality of life (QOL) over an additional 7 years. Safety was assessed as adverse events (AEs), efficacy as median percent change in seizure frequency and responder rate, and QOL with the Quality of Life in Epilepsy (QOLIE-89) inventory.

RESULTS

Of 256 patients treated in the initial trials, 230 participated in the LTT. At 9 years, the median percent reduction in seizure frequency was 75% (p < 0.0001, Wilcoxon signed rank), responder rate was 73%, and 35% had a ≥90% reduction in seizure frequency. We found that 18.4% (47 of 256) experienced ≥1 year of seizure freedom, with 62% (29 of 47) seizure-free at the last follow-up and an average seizure-free period of 3.2 years (range 1.04-9.6 years). Overall QOL and epilepsy-targeted and cognitive domains of QOLIE-89 remained significantly improved (p < 0.05). There were no serious AEs related to stimulation, and the sudden unexplained death in epilepsy (SUDEP) rate was significantly lower than predefined comparators (p < 0.05, 1-tailed χ2).

CONCLUSIONS

Adjunctive brain-responsive neurostimulation provides significant and sustained reductions in the frequency of FOS with improved QOL. Stimulation was well tolerated; implantation-related AEs were typical of other neurostimulation devices; and SUDEP rates were low.

CLINICALTRIALSGOV IDENTIFIER

NCT00572195.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that brain-responsive neurostimulation significantly reduces focal seizures with acceptable safety over 9 years.

Cues for seizure timing

The cyclical organization of seizures in epilepsy has been described since antiquity. However, historical explanations for seizure cycles-based on celestial, hormonal, and environmental factors-have only recently become testable with the advent of chronic electroencephalography (cEEG) and modern statistical techniques. Here, factors purported over millennia to influence seizure timing are viewed through a contemporary lens. We discuss the emerging concept that seizures are organized over multiple timescales, each involving differential influences of external and endogenous rhythm generators. Leveraging large cEEG datasets and circular statistics appropriate for cyclical phenomena, we present new evidence for circadian (day-night), multidien (multi-day), and circannual (about-yearly) variation in seizure activity. Modulation of seizure timing by multiscale temporal variables has implications for diagnosis and therapy in clinical epilepsy. Uncovering the mechanistic basis for seizure cycles, particularly the factors that govern multidien periodicity, will be a major focus of future work.

How technology is driving the landscape of epilepsy surgery

This article emphasizes the role of the technological progress in changing the landscape of epilepsy surgery and provides a critical appraisal of robotic applications, laser interstitial thermal therapy, intraoperative imaging, wireless recording, new neuromodulation techniques, and high-intensity focused ultrasound. Specifically, (a) it relativizes the current hype in using robots for stereo-electroencephalography (SEEG) to increase the accuracy of depth electrode placement and save operating time; (b) discusses the drawback of laser interstitial thermal therapy (LITT) when it comes to the need for adequate histopathologic specimen and the fact that the concept of stereotactic disconnection is not new; (c) addresses the ratio between the benefits and expenditure of using intraoperative magnetic resonance imaging (MRI), that is, the high technical and personnel expertise needed that might restrict its use to centers with a high case load, including those unrelated to epilepsy; (d) soberly reviews the advantages, disadvantages, and future potentials of neuromodulation techniques with special emphasis on the differences between closed and open-loop systems; and (e) provides a critical outlook on the clinical implications of focused ultrasound, wireless recording, and multipurpose electrodes that are already on the horizon. This outlook shows that although current ultrasonic systems do have some limitations in delivering the acoustic energy, further advance of this technique may lead to novel treatment paradigms. Furthermore, it highlights that new data streams from multipurpose electrodes and wireless transmission of intracranial recordings will become available soon once some critical developments will be achieved such as electrode fidelity, data processing and storage, heat conduction as well as rechargeable technology. A better understanding of modern epilepsy surgery will help to demystify epilepsy surgery for the patients and the treating physicians and thereby reduce the surgical treatment gap.

Brain-responsive neurostimulation treatment in patients with GAD65 antibody-associated autoimmune mesial temporal lobe epilepsy

Glutamic acid decarboxylase 65‐kilodalton isoform (GAD65) antibodies have been associated with multiple nonneurological and neurological syndromes including autoimmune epilepsy (AE). Although immunotherapy remains the cornerstone for the treatment of AE, those with GAD65 Ab‐associated AE (GAD65‐AE) remain refractory to immunotherapy and antiseizure medication (ASM). Outcomes of epilepsy surgery in this patient population have also been unsatisfactory. The role of neuromodulation therapy, particularly direct brain‐responsive neurostimulation therapy, has not been previously examined in GAD65‐AE. Here, we describe four consecutive patients with refractory GAD‐65‐associated temporal lobe epilepsy (GAD65‐TLE) receiving bilateral hippocampal RNS System treatment. The RNS System treatment was well tolerated and effective in this study cohort. Three patients had a >50% clinical seizure reduction, and one patient became clinically seizure‐free following resective surgery informed by the RNS System data with continued RNS System treatment. In all four of our patients, the long‐term ambulatory data provided by the RNS System allowed us to gain objective insights on electrographic seizure lateralization, patterns, and burden as well as guided immunotherapy and ASM optimization. Our results suggest the potential utility of the RNS System in the management of ASM intractable GAD65‐AE.

Antiepileptic drug optimization using ambulatory electrocorticographic data from an implanted brain-responsive neurostimulator

Effectiveness of antiepileptic drugs (AEDs) has been traditionally monitored by patient-reported seizures. A 31-year-old male patient was treated with a responsive neurostimulation system (RNS). The ambulatory electrocorticographic data were used to guide AED choice and dosing in achieving subsidence of disabling seizures and minimization of the adverse effects of polypharmacy.

Optimizing therapies for neurobehavioral comorbidities of epilepsy using chronic ambulatory electrocorticography

There is an unmet need to improve therapy for neuropsychiatric comorbidities that are highly prevalent in persons with epilepsy (PWE). However, diagnosing and monitoring the neurobehavioral symptoms is challenging as their presentation can overlap with seizures. In this retrospective study, we report the advantage of chronic ambulatory electrocorticography (ECoG) from implanted Responsive Neurostimulator System (RNS®) in characterizing these psychosomatic paroxysms as a possible ictal, postictal, or interictal phenomenon and how the diagnosis guided the therapy choices. Five out of 21 patients with RNS had neuropsychiatric symptoms (panic attack, psychosis, conversion, and somatization disorders) that overlapped with their seizure semiology and were found to benefit from the use of RNS ECoG data by timely diagnosing and titrating targeted therapies. The cases illustrate the use of RNS ECoG data in diagnosing and improving the management of comorbidities in PWE. The ability to access RNS ECoG data and correlate it with patient symptoms is unique among available therapeutic options for PWE.

Early detection rate changes from a brain-responsive neurostimulation system predict efficacy of newly added antiseizure drugs

OBJECTIVE

Brain-responsive neurostimulation (RNS System, NeuroPace) is used to treat medically refractory focal epilepsy and also provides long-term ambulatory neurophysiologic data. We sought to determine whether these data could predict the clinical response to antiseizure drugs (ASDs).

METHODS

First, newly added medications were identified in RNS System patients followed at a single epilepsy center. Daily detection rates including "episode starts" (predominantly interictal activity) and "long episodes" (often electrographic seizures) were compared before and after ASD initiation. Efficacy was determined from documentation of clinical improvement and medication retention. Next, the analysis was repeated on an independent sample of patients from a multicenter long-term treatment trial, using an efficacy measure of ≥50% reduction in diary-recorded seizure frequency after 3 months.

RESULTS

In the single center cohort, long episodes, but not episode starts, had a significantly greater reduction in the first week for clinically efficacious compared to inefficacious medications. In this cohort, having no long episodes in the first week was highly predictive of ASD efficacy. In the multicenter cohort, both long episodes and episode starts had a significantly greater reduction for effective medications starting in the first 1-2 weeks. In this larger dataset, a ≥50% decrease in episode starts was 90% specific for efficacy with a positive predictive value (PPV) of 67%, and a ≥84% decrease in long episodes was 80% specific with a PPV of 48%. Conversely, a <25% decrease in long episodes (including any increase) or a <20% decrease in episode starts had a predictive value for inefficacy of >80%.

SIGNIFICANCE

In RNS System patients with stable detection settings, when new ASDs are started, detection rates within the first 1-2 weeks may provide an early, objective indication of efficacy. These data could be used to identify responses to medication trials early to allow more rapid medication adjustments than conventionally possible.

Responsive neurostimulation for regional neocortical epilepsy

OBJECTIVE

Surgical resection of seizure-producing brain tissue is a gold standard treatment for drug-resistant focal epilepsy. However, several patient-specific factors can preclude resective surgery, including a spatially extensive ("regional") seizure-onset zone (SOZ). For such patients, responsive neurostimulation (RNS) represents a potential treatment, but its efficacy has not been investigated in this population.

METHODS

We performed a multicenter retrospective cohort study of patients (N = 30) with drug-resistant focal epilepsy and a regional neocortical SOZ delineated by intracranial monitoring who were treated with the RNS System for at least 6 months. RNS System leads were placed at least 1-cm apart over the SOZ, and most patients were treated with a lead-to-lead stimulation pathway. Five patients underwent partial resection of the SOZ concurrent with RNS System implantation. We assessed change in seizure frequency relative to preimplant baseline and evaluated correlation between clinical outcome and stimulation parameters.

RESULTS

Median follow-up duration was 21.5 months (range 6-52). Median reduction in clinical seizure frequency was 75.5% (interquartile range [IQR] 40%-93.9%). There was no significant difference in outcome between patients treated with and without concurrent partial resection. Most patients were treated with low charge densities (1-2.5 µC/cm² ), but charge density, interlead distance, and duration of treatment were not significantly correlated with outcome.

SIGNIFICANCE

RNS is a feasible and effective treatment in patients with drug-resistant regional neocortical seizures. Prospective studies in larger cohorts are necessary to determine optimal lead configuration and stimulation parameters, although our results suggest that lead-to-lead stimulation and low charge density may be effective in some patients.

Perspectives on the current developments with neuromodulation for the treatment of epilepsy

Introduction: As deep brain stimulation revolutionized the treatment of movement disorders in the late 80s, neuromodulation in the treatment of epilepsy will undoubtedly undergo transformative changes in the years to come with the exponential growth of technological development moving into mainstream practice; the appearance of companies such as Facebook, Google, Neuralink within the realm of brain-computer interfaces points to this trend.Areas covered: This perspective piece will talk about the history of brain stimulation in epilepsy, current-approved treatments, technical developments and the future of neurostimulation.Expert opinion: Further understanding of the brain alongside machine learning and innovative technology will be the future of neuromodulation for the treatment of epilepsy. All of these innovations and advances should pave the way toward overcoming the vexing underutilization of surgery in the therapeutic armamentarium against medically refractory seizures, given the implicit advantage of a neuromodulatory rather than neurodestructive approach.

Brain-responsive neurostimulation for epilepsy (RNS® System)

Controlled clinical trials in adults with medically intractable focal seizures treated with the RNS^® System demonstrate that closed-loop responsive neurostimulation to the seizure focus reduces the frequency of disabling seizures, is well tolerated, and is acceptably safe. Seizure reductions begin with initiation of treatment and continue over time, reaching median reductions of 75% after 9 years of treatment. Treatment with responsive cortical stimulation is also associated with improvement in quality of life and cognitive function related to the functional area being treated. In addition, the RNS System's chronic ambulatory electrocorticographic monitoring provides unprecedented insight into each patient's disease management, and into the study of epilepsy itself, in ways that may enhance the treatment of epilepsy in the future.

Responsive Neurostimulation for the Treatment of Epilepsy

There are a significant number of patients with epilepsy who are drug-resistant and for whom resective procedures are not an option. For these patients, neuromodulation may be an option, including closed-loop stimulation, such as responsive neurostimulation (RNS). The RNS System is a programmable and responsive device that consists of leads, a pulse generator, and an external programmer. An algorithm detects specific patterns of epileptogenic activity and triggers focal stimulation to interrupt a seizure. RNS is an effective and safe adjunctive therapy that in addition to seizure frequency reduction may have other applications, such as drug-response evaluation and long-term electrocorticography recording.

Hippocampal gamma predicts associative memory performance as measured by acute and chronic intracranial EEG

Direct recordings from the human brain have historically involved epilepsy patients undergoing invasive electroencephalography (iEEG) for surgery. However, these measurements are temporally limited and affected by clinical variables. The RNS System (NeuroPace, Inc.) is a chronic, closed-loop electrographic seizure detection and stimulation system. When adapted by investigators for research, it facilitates cognitive testing in a controlled ambulatory setting, with measurements collected over months to years. We utilized an associative learning paradigm in 5 patients with traditional iEEG and 3 patients with chronic iEEG, and found increased hippocampal gamma (60–100 Hz) sustained at 1.3–1.5 seconds during encoding in successful versus failed trials in surgical patients, with similar results in our RNS System patients (1.4–1.6 seconds). Our findings replicate other studies demonstrating that sustained hippocampal gamma supports encoding. Importantly, we have validated the RNS System to make sensitive measurements of hippocampal dynamics during cognitive tasks in a chronic ambulatory research setting.

Responsive neurostimulation: Review of clinical trials and insights into focal epilepsy

The responsive neurostimulator (RNS ®, NeuroPace Inc.) has been available clinically since 2013 for the treatment of medically refractory partial epilepsy. Using intracranial electrodes and a cranially implanted device, RNS ® provides on-demand electrical cortical stimulation to reduce seizures. A randomized, multicenter, double-blind clinical trial demonstrated seizure reduction compared with sham stimulation. Seizure reduction was improved and sustained over years in a long-term treatment trial. The RNS ® provides chronic ambulatory electrographic monitoring over years giving unprecedented insight into epilepsy dynamics. Studies to date have looked at the length of time to detecting bilateral seizure onsets in mesial temporal lobe epilepsy (MTLE), demonstrated biorhythms in interictal epileptiform activity over varied time scales, and shown promise in early detection of benefits of adding a new antiepileptic drug. Questions remain as to the boundaries of patient selection and lead placement. "This article is part of the Supplement issue Neurostimulation for Epilepsy."

Responsive neurostimulation: Candidates and considerations

Responsive neurostimulation (RNS) has recently emerged as a safe and effective treatment for some patients with medically refractory focal epilepsy who are not candidates for surgical resection. Responsive neurostimulation involves an implanted neurostimulator and intracranial leads that detect incipient seizures and respond with electrical counterstimulation. Over 1800 patients have been treated with RNS since its FDA approval in 2013. Despite its widespread use, however, RNS presents distinct challenges for clinicians. What types of patients are most well-suited for treatment with RNS? Given the availability of two other neurostimulation modalities, vagus nerve stimulation (VNS) and thalamic deep brain stimulation (DBS), what patient characteristics favor or disfavor RNS? Once RNS candidates are identified, lead placement presents another challenge. Unlike VNS and thalamic DBS, which both involve prespecified electrode locations, RNS involves intracranial strip and/or depth electrodes that can be flexibly configured based on knowledge of the seizure onset zone. The efficacy of RNS may depend on optimal lead configuration, but there are few resources to guide clinicians in formulating lead placement strategies. Here, we address these challenges, first by reviewing clinical trial data supporting the safety and efficacy of RNS. Then, through a series of clinical vignettes from our center, we provide a framework for RNS patient selection. For each clinical scenario, we illustrate typical strategies for RNS lead placement. We outline considerations for choosing among available neurostimulation devices based on their intrinsic features. For example, a unique feature of RNS is that the neurostimulator provides chronic electrocorticography (ECoG), which has powerful diagnostic potential. We highlight emerging applications of chronic ECoG, and we discuss how the limitations of RNS will inform development of next-generation devices.