Responsive Neurostimulation for Seizure Control: Current Status and Future Directions

The role of neuromodulation in the management of drug-resistant epilepsy

Drug-resistant epilepsy (DRE) poses significant challenges in terms of effective management and seizure control. Neuromodulation techniques have emerged as promising solutions for individuals who are unresponsive to pharmacological treatments, especially for those who are not good surgical candidates for surgical resection or laser interstitial therapy (LiTT). Currently, there are three neuromodulation techniques that are FDA-approved for the management of DRE. These include vagus nerve stimulation (VNS), deep brain stimulation (DBS), and responsive neurostimulation (RNS). Device selection, optimal time, and DBS and RNS target selection can also be challenging. In general, the number and localizability of the epileptic foci, alongside the comorbidities manifested by the patients, substantially influence the selection process. In the past, the general axiom was that DBS and VNS can be used for generalized and localized focal seizures, while RNS is typically reserved for patients with one or two highly localized epileptic foci, especially if they are in eloquent areas of the brain. Nowadays, with the advance in our understanding of thalamic involvement in DRE, RNS is also very effective for general non-focal epilepsy. In this review, we will discuss the underlying mechanisms of action, patient selection criteria, and the evidence supporting the use of each technique. Additionally, we explore emerging technologies and novel approaches in neuromodulation, such as closed-loop systems. Moreover, we examine the challenges and limitations associated with neuromodulation therapies, including adverse effects, complications, and the need for further long-term studies. This comprehensive review aims to provide valuable insights on present and future use of neuromodulation.

Therapeutic approaches targeting seizure networks

Epilepsy is one of the most common neurological disorders, affecting over 65 million people worldwide. Despite medical management with anti-seizure medications (ASMs), many patients fail to achieve seizure freedom, with over one-third of patients having drug-resistant epilepsy (DRE). Even with surgical management through resective surgery and/or neuromodulatory interventions, over 50 % of patients continue to experience refractory seizures within a year of surgery. Over the past 2 decades, studies have increasingly suggested that treatment failure is likely driven by untreated components of a pathological seizure network, a shift in the classical understanding of epilepsy as a focal disorder. However, this shift in thinking has yet to translate to improved treatments and seizure outcomes in patients. Here, we present a narrative review discussing the process of surgical epilepsy management. We explore current surgical interventions and hypothesized mechanisms behind treatment failure, highlighting evidence of pathologic seizure networks. Finally, we conclude by discussing how the network theory may inform surgical management, guiding the identification and targeting of more appropriate surgical regions. Ultimately, we believe that adapting current surgical practices and neuromodulatory interventions towards targeting seizure networks offers new therapeutic strategies that may improve seizure outcomes in patients suffering from DRE.

Origami-inspired soft fluidic actuation for minimally invasive large-area electrocorticography

Electrocorticography is an established neural interfacing technique wherein an array of electrodes enables large-area recording from the cortical surface. Electrocorticography is commonly used for seizure mapping however the implantation of large-area electrocorticography arrays is a highly invasive procedure, requiring a craniotomy larger than the implant area to place the device. In this work, flexible thin-film electrode arrays are combined with concepts from soft robotics, to realize a large-area electrocorticography device that can change shape via integrated fluidic actuators. We show that the 32-electrode device can be packaged using origami-inspired folding into a compressed state and implanted through a small burr-hole craniotomy, then expanded on the surface of the brain for large-area cortical coverage. The implantation, expansion, and recording functionality of the device is confirmed in-vitro and in porcine in-vivo models. The integration of shape actuation into neural implants provides a clinically viable pathway to realize large-area neural interfaces via minimally invasive surgical techniques.

The present and future of seizure detection, prediction, and forecasting with machine learning, including the future impact on clinical trials

Seizures have a profound impact on quality of life and mortality, in part because they can be challenging both to detect and forecast. Seizure detection relies upon accurately differentiating transient neurological symptoms caused by abnormal epileptiform activity from similar symptoms with different causes. Seizure forecasting aims to identify when a person has a high or low likelihood of seizure, which is related to seizure prediction. Machine learning and artificial intelligence are data-driven techniques integrated with neurodiagnostic monitoring technologies that attempt to accomplish both of those tasks. In this narrative review, we describe both the existing software and hardware approaches for seizure detection and forecasting, as well as the concepts for how to evaluate the performance of new technologies for future application in clinical practice. These technologies include long-term monitoring both with and without electroencephalography (EEG) that report very high sensitivity as well as reduced false positive detections. In addition, we describe the implications of seizure detection and forecasting upon the evaluation of novel treatments for seizures within clinical trials. Based on these existing data, long-term seizure detection and forecasting with machine learning and artificial intelligence could fundamentally change the clinical care of people with seizures, but there are multiple validation steps necessary to rigorously demonstrate their benefits and costs, relative to the current standard.

The comparison of DBS and RNS for adult drug-resistant epilepsy: a systematic review and meta-analysis

Objective

Neuromodulation has been proven to be a promising alternative treatment for adult patients with drug-resistant epilepsy (DRE). Deep brain stimulation (DBS) and responsive neurostimulation (RNS) were approved by many countries for the treatment of DRE. However, there is a lack of systematic studies illustrating the differences between them. This meta-analysis is performed to assess the efficacy and clinical characteristics of DBS and RNS in adult patients with DRE.

Methods

PubMed, Web of Science, and Embase were retrieved to obtain related studies including adult DRE patients who accepted DBS or RNS. The clinical characteristics of these patients were compiled for the following statistical analysis.

Results

A total of 55 studies (32 of DBS and 23 of RNS) involving 1,568 adult patients with DRE were included in this meta-analysis. There was no significant difference in seizure reduction and responder rate between DBS and RNS for DRE. The seizure reduction of DBS and RNS were 56% (95% CI 50-62%, p > 0.05) and 61% (95% CI 54-68%, p > 0.05). The responder rate of DBS and RNS were 67% (95% CI 58-76%, p > 0.05) and 71% (95% CI 64-78%, p > 0.05). Different targets of DBS did not show significant effect on seizure reduction (p > 0.05). Patients with DRE who accepted DBS were younger than those of RNS (32.9 years old vs. 37.8 years old, p < 0.01). The mean follow-up time was 47.3 months for DBS and 39.5 months for RNS (p > 0.05).

Conclusion

Both DBS and RNS are beneficial and alternative therapies for adult DRE patients who are not eligible to accept resection surgery. Further and larger studies are needed to clarify the characteristics of different targets and provide tailored treatment for patients with DRE.

MR-Guided Focused Ultrasound for Refractory Epilepsy: Where Are We Now?

Epilepsy is one of the most common neurological diseases in both adults and children. Despite improvements in medical care, 20 to 30% of patients are still resistant to the best medical treatment. The quality of life, neurologic morbidity, and even mortality of patients are significantly impacted by medically intractable epilepsy. Nowadays, conservative therapeutic approaches consist of increasing medication dosage, changing to a different anti-seizure drug as monotherapy, and combining different antiseizure drugs using an add-on strategy. However, such measures may not be sufficient to efficiently control seizure recurrence. Resective surgery, ablative procedures and non-resective neuromodulatory (deep-brain stimulation, vagus nerve stimulation) treatments are the available treatments for these kinds of patients. However, invasive procedures may involve lengthy inpatient stays for the patients, risks of long-term neurological impairment, general anesthesia, and other possible surgery-related complications (i.e., hemorrhage or infection). In the last few years, MR-guided focused ultrasound (MRgFUS) has been proposed as an emerging treatment for neurological diseases because of technological advancements and the goal of minimally invasive neurosurgery. By outlining the current knowledge obtained from both preclinical and clinical studies and discussing the technical opportunities of this therapy for particular epileptic phenotypes, in this perspective review, we explore the various mechanisms and potential applications (thermoablation, blood-brain barrier opening for drug delivery, neuromodulation) of high- and low-intensity ultrasound, highlighting possible novel strategies to treat drug-resistant epileptic patients who are not eligible or do not accept currently established surgical approaches. Taken together, the available studies support a possible role for lesional treatment over the anterior thalamus with high-intensity ultrasound and neuromodulation of the hippocampus via low-intensity ultrasound in refractory epilepsy. However, more studies, likely conceiving epilepsy as a network disorder and bridging together different scales and modalities, are required to make ultrasound delivery strategies meaningful, effective, and safe.

The Utility of Responsive Neurostimulation for the Treatment of Pediatric Drug-Resistant Epilepsy

Drug-resistant epilepsy (DRE) has a strongly negative impact on quality of life, as well as the development of pediatric patients. Surgical treatments have evolved over time, including more invasive craniotomies for resection or disconnection. More recently, neuromodulation techniques have been employed as a less invasive option for patients. Responsive neurostimulation (RNS) is the first closed-loop technology that allows for both treatment and device data collection, which allows for an internal assessment of the efficacy of treatment. This novel technology has been approved in adults and has been used off label in pediatrics. This review seeks to describe this technology, its history, and future directions.