EEG Reactivity Predicts Individual Efficacy of Vagal Nerve Stimulation in Intractable Epileptics

Entropy in scalp EEG can be used as a preimplantation marker for VNS efficacy

Vagus nerve stimulation (VNS) is a therapeutic option in drug-resistant epilepsy. VNS leads to ≥ 50% seizure reduction in 50 to 60% of patients, termed "responders". The remaining 40 to 50% of patients, "non-responders", exhibit seizure reduction < 50%. Our work aims to differentiate between these two patient groups in preimplantation EEG analysis by employing several Entropy methods. We identified 59 drug-resistant epilepsy patients treated with VNS. We established their response to VNS in terms of responders and non-responders. A preimplantation EEG with eyes open/closed, photic stimulation, and hyperventilation was found for each patient. The EEG was segmented into eight time intervals within four standard frequency bands. In all, 32 EEG segments were obtained. Seven Entropy methods were calculated for all segments. Subsequently, VNS responders and non-responders were compared using individual Entropy methods. VNS responders and non-responders differed significantly in all Entropy methods except Approximate Entropy. Spectral Entropy revealed the highest number of EEG segments differentiating between responders and non-responders. The most useful frequency band distinguishing responders and non-responders was the alpha frequency, and the most helpful time interval was hyperventilation and rest 4 (the end of EEG recording).

Functional brain connectivity indexes derived from low-density EEG of pre-implanted patients as VNS outcome predictors

Objective. In 1/3 of patients, anti-seizure medications may be insufficient, and resective surgery may be offered whenever the seizure onset is localized and situated in a non-eloquent brain region. When surgery is not feasible or fails, vagus nerve stimulation (VNS) therapy can be used as an add-on treatment to reduce seizure frequency and/or severity. However, screening tools or methods for predicting patient response to VNS and avoiding unnecessary implantation are unavailable, and confident biomarkers of clinical efficacy are unclear.Approach. To predict the response of patients to VNS, functional brain connectivity measures in combination with graph measures have been primarily used with respect to imaging techniques such as functional magnetic resonance imaging, but connectivity graph-based analysis based on electrophysiological signals such as electroencephalogram, have been barely explored. Although the study of the influence of VNS on functional connectivity is not new, this work is distinguished by using preimplantation low-density EEG data to analyze discriminative measures between responders and non-responder patients using functional connectivity and graph theory metrics.Main results. By calculating five functional brain connectivity indexes per frequency band upon partial directed coherence and direct transform function connectivity matrices in a population of 37 refractory epilepsy patients, we found significant differences (p< 0.05) between the global efficiency, average clustering coefficient, and modularity of responders and non-responders using the Mann-Whitney U test with Benjamini-Hochberg correction procedure and use of a false discovery rate of 5%.Significance. Our results indicate that these measures may potentially be used as biomarkers to predict responsiveness to VNS therapy.

Electroencephalographic Patterns in taVNS: A Systematic Review

Transcutaneous auricular vagus nerve stimulation (taVNS) is a newer delivery system using a non-invasive stimulation device placed at the ear. taVNS research is focused on clinical trials showing potential therapeutic benefits, however the neurophysiological effects of this stimulation on brain activity are still unclear. We propose a systematic review that aims to describe the effects of taVNS on EEG measures and identify taVNS parameters that can potentially lead to consistent EEG-mediated biomarkers for this therapy. A systematic literature review was carried out following the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) and the Cochrane handbook for systematic reviews. Clinical trials examining EEG parameters were considered, including absolute and relative power, coherence, degree of symmetry, evoked potentials, and peak frequency of all bands. According to our criteria, 18 studies (from 122 articles) were included. Our findings show a general trend towards increased EEG power spectrum activity in lower frequencies, and changes on early components of the ERP related to inhibitory tasks. This review suggests that quantitative electroencephalography can be used to assess the effects of taVNS on brain activity, however more studies are needed to systematically establish the specific effects and metrics that would reflect the non-invasive stimulation through the auricular branch of the vagus nerve.

Latest Views on the Mechanisms of Action of Surgically Implanted Cervical Vagal Nerve Stimulation in Epilepsy

BACKGROUND

Vagus nerve stimulation (VNS) is approved as an adjunctive treatment for drug-resistant epilepsy. Although there is a substantial amount of literature aiming at unraveling the mechanisms of action of VNS in epilepsy, it is still unclear how the cascade of events triggered by VNS leads to its antiepileptic effect.

OBJECTIVE

In this review, we integrated available peer-reviewed data on the effects of VNS in clinical and experimental research to identify those that are putatively responsible for its therapeutic effect. The topic of transcutaneous VNS will not be covered owing to the current lack of data supporting the differences and commonalities of its mechanisms of action in relation to invasive VNS.

SUMMARY OF THE MAIN FINDINGS

There is compelling evidence that the effect is obtained through the stimulation of large-diameter afferent myelinated fibers that project to the solitary tract nucleus, then to the parabrachial nucleus, which in turn alters the activity of the limbic system, thalamus, and cortex. VNS-induced catecholamine release from the locus coeruleus in the brainstem plays a pivotal role. Functional imaging studies tend to point toward a common vagal network that comes into play, made up of the amygdalo-hippocampal regions, left thalamus, and insular cortex.

CONCLUSIONS

Even though some crucial pieces are missing, neurochemical, molecular, cellular, and electrophysiological changes occur within the vagal afferent network at three main levels (the brainstem, the limbic system [amygdala and hippocampus], and the cortex). At this final level, VNS notably alters functional connectivity, which is known to be abnormally high within the epileptic zone and was shown to be significantly decreased by VNS in responders. The effect of crucial VNS parameters such as frequency or current amplitude on functional connectivity metrics is of utmost importance and requires further investigation.

Vagus nerve stimulation for conservative therapy-refractive epilepsy and depression

Numerous studies confirm that the vagus nerve stimulation (VNS) is an efficient, indirect neuromodulatory therapy with electrically induced current for epilepsy that cannot be treated by epilepsy surgery and is therapy-refractory and for drug therapy-refractory depression. VNS is an established, evidence-based and in the long-term cost-effective therapy in an interdisciplinary overall concept.Long-term data on the safety and tolerance of the method are available despite the heterogeneity of the patient populations. Stimulation-related side effects like hoarseness, paresthesia, cough or dyspnea depend on the stimulation strength and often decrease with continuing therapy duration in the following years. Stimulation-related side effects of VNS can be well influenced by modifying the stimulation parameters. Overall, the invasive vagus nerve stimulation may be considered as a safe and well-tolerated therapy option.For invasive and transcutaneous vagus nerve stimulation, antiepileptic and antidepressant as well as positive cognitive effects could be proven. In contrast to drugs, VNS has no negative effect on cognition. In many cases, an improvement of the quality of life is possible.iVNS therapy has a low probability of complete seizure-freedom in cases of focal and genetically generalized epilepsy. It must be considered as palliative therapy, which means that it does not lead to healing and requires the continuation of specific medication. The functional principle is a general reduction of the neuronal excitability. This effect is achieved by a slow increase of the effectiveness sometimes over several years. Responders are those patients who experience a 50% reduction of the seizure incidence. Some studies even reveal seizure-freedom in 20% of the cases. Currently, it is not possible to differentiate between potential responders and non-responders before therapy/implantation.The current technical developments of the iVNS generators of the new generation like closed-loop system (cardiac-based seizure detection, CBSD) reduce also the risk for SUDEP (sudden unexpected death in epilepsy patients), a very rare, lethal complication of epilepsies, beside the seizure severity.iVNS may deteriorate an existing sleep apnea syndrome and therefore requires possible therapy interruption during nighttime (day-night programming or magnet use) beside the close cooperation with sleep physicians.The evaluation of the numerous iVNS trials of the past two decades showed multiple positive effects on other immunological, cardiological, and gastroenterological diseases so that additional therapy indications may be expected depending on future study results. Currently, the vagus nerve stimulation is in the focus of research in the disciplines of psychology, immunology, cardiology as well as pain and plasticity research with the desired potential of future medical application.Beside invasive vagus nerve stimulation with implantation of an IPG and an electrode, also devices for transdermal and thus non-invasive vagus nerve stimulation have been developed during the last years. According to the data that are currently available, they are less effective with regard to the reduction of the seizure severity and duration in cases of therapy-refractory epilepsy and slightly less effective regarding the improvement of depression symptoms. In this context, studies are missing that confirm high evidence of effectiveness. The same is true for the other indications that have been mentioned like tinnitus, cephalgia, gastrointestinal complaints etc. Another disadvantage of transcutaneous vagus nerve stimulation is that the stimulators have to be applied actively by the patients and are not permanently active, in contrast to implanted iVNS therapy systems. So they are only intermittently active; furthermore, the therapy adherence is uncertain.

Prediction of Vagal Nerve Stimulation Efficacy in Drug-Resistant Epilepsy (PRECISE): Prospective Study for Pre-implantation Prediction/Study Design

Background

Vagal nerve stimulation (VNS) can be indicated in patients with drug-resistant epilepsy, who are not eligible for resective epilepsy surgery. In VNS therapy, the responder rate (i.e., percentage of subjects experiencing ≥50% seizure reduction) is ~50%. At the moment, there is no widely-accepted possibility to predict VNS efficacy in a particular patient based on pre-implantation data, which can lead to unnecessary surgery and improper allocation of financial resources. The principal aim of PRediction of vagal nerve stimulation EfficaCy In drug-reSistant Epilepsy (PRECISE) study is to verify the predictability of VNS efficacy by analysis of pre-implantation routine electroencephalogram (EEG).

Methods

PRECISE is designed as a prospective multicentric study in which patients indicated to VNS therapy will be recruited. Patients will be classified as predicted responders vs. predicted non-responders using pre-implantation EEG analyses. After the first and second year of the study, the real-life outcome (responder vs. non-responder) will be determined. The real-life outcome and predicted outcome will be compared in terms of accuracy, specificity, and sensitivity. In the meantime, the patients will be managed according to the best clinical practice to obtain the best therapeutic response. The primary endpoint will be the accuracy of the statistical model for prediction of response to VNS therapy in terms of responders and non-responders. The secondary endpoint will be the quantification of differences in EEG power spectra (Relative Mean Power, %) between real-life responders and real-life non-responders to VNS therapy in drug-resistant epilepsy and the sensitivity and specificity of the model.

Discussion

PRECISE relies on the results of our previous work, through which we developed a statistical classifier for VNS response (responders vs. non-responders) based on differences in EEG power spectra dynamics (Pre-X-Stim).

Trial Registration

www.ClinicalTrials.gov, identifier: NCT04935567.

Vagal Nerve Stimulation: The Effect on the Brain Oscillatory Field Potential

More than thirty years of medical treatment with the use of vagal nerve stimulation (VNS) has shown that this therapeutic procedure works in a number of homeostatic disturbances. Although the clinical usage of VNS has a long history, our knowledge about the central mechanisms underlying this treatment is still limited. In the present paper we review the effects of VNS on brain oscillations as a possible electrophysiological bio-marker of VNS efficacy. The review was prepared mainly on the basis of data delivered from clinical observations and the outcomes of electrophysiological experiments conducted on laboratory animals that are available in PubMed. We consciously did not focus on epileptiform activity understood as a pathologic oscillatory activity, which was widely discussed in the numerous previously published reviews. The main conclusion of the present paper is that further, well-designed experiments on laboratory animals are absolutely necessary to address the electrophysiological issues. These will fill a number of gaps in our present knowledge of the central mechanisms underlying VNS therapy.

Pre-implant Heart Activity Differs in Responders and Non-responders to Vagal Nerve Stimulation Therapy in Epileptic Patients

Vagal Nerve Stimulation (VNS) is used to treat patients with pharmacoresistant epilepsy. However, generally accepted tools to predict VNS response do not exist. Here we examined two heart activity measures - mean RR and pNN50 and their complex behavior during activation in pre-implant measurements. The ECG recordings of 73 patients (38 responders, 36 non-responders) were examined in a 30-sec floating window before (120 sec), during (2x120 sec), and after (120 sec) the hyperventilation by nose and mouth. The VNS response differentiation by pNN50 was significant (min p=0.01) in the hyperventilation by a nose with a noticeable descendant trend in nominal values. The mean RR was significant (p=0.01) in the rest after the hyperventilation by mouth but after an approximately 40-sec delay.Clinical Relevance- Our study shows that pNN50 and mean RR can be used to distinguish between VNS responders and non-responders. However, details of dynamic behavior showed how this ability varies in tested measurement segments.

Preoperative Heart Rate Variability During Sleep Predicts Vagus Nerve Stimulation Outcome Better in Patients With Drug-Resistant Epilepsy

Objective: Vagus nerve stimulation (VNS) is an adjunctive and well-established treatment for patients with drug-resistant epilepsy (DRE). However, it is still difficult to identify patients who may benefit from VNS surgery. Our study aims to propose a VNS outcome prediction model based on machine learning with multidimensional preoperative heart rate variability (HRV) indices. Methods: The preoperative electrocardiography (ECG) of 59 patients with DRE and of 50 healthy controls were analyzed. Responders were defined as having at least 50% average monthly seizure frequency reduction at 1-year follow-up. Time domain, frequency domain, and non-linear indices of HRV were compared between 30 responders and 29 non-responders in awake and sleep states, respectively. For feature selection, univariate filter and recursive feature elimination (RFE) algorithms were performed to assess the importance of different HRV indices to VNS outcome prediction and improve the classification performance. Random forest (RF) was used to train the classifier, and leave-one-out (LOO) cross-validation was performed to evaluate the prediction model. Results: Among 52 HRV indices, 49 showed significant differences between DRE patients and healthy controls. In sleep state, 35 HRV indices of responders were significantly higher than those of non-responders, while 16 of them showed the same differences in awake state. Low-frequency power (LF) ranked first in the importance ranking results by univariate filter and RFE methods, respectively. With HRV indices in sleep state, our model achieved 74.6% accuracy, 80% precision, 70.6% recall, and 75% F1 for VNS outcome prediction, which was better than the optimal performance in awake state (65.3% accuracy, 66.4% precision, 70.5% recall, and 68.4% F1). Significance: With the ECG during sleep state and machine learning techniques, the statistical model based on preoperative HRV could achieve a better performance of VNS outcome prediction and, therefore, help patients who are not suitable for VNS to avoid the high cost of surgery and possible risks of long-term stimulation.

A Novel Statistical Model for Predicting the Efficacy of Vagal Nerve Stimulation in Patients With Epilepsy (Pre-X-Stim) Is Applicable to Different EEG Systems

Background: Identifying patients with intractable epilepsy who would benefit from therapeutic chronic vagal nerve stimulation (VNS) preoperatively remains a major clinical challenge. We have developed a statistical model for predicting VNS efficacy using only routine preimplantation electroencephalogram (EEG) recorded with the TruScan EEG device (Brazdil et al., 2019). It remains to be seen, however, if this model can be applied in different clinical settings.

Objective: To validate our model using EEG data acquired with a different recording system.

Methods: We identified a validation cohort of eight patients implanted with VNS, whose preimplantation EEG was recorded on the BrainScope device and who underwent the EEG recording according to the protocol. The classifier developed in our earlier work, named Pre-X-Stim, was then employed to classify these patients as predicted responders or non-responders based on the dynamics in EEG power spectra. Predicted and real-world outcomes were compared to establish the applicability of this classifier. In total, two validation experiments were performed using two different validation approaches (single classifier or classifier voting).

Results: The classifier achieved 75% accuracy, 67% sensitivity, and 100% specificity. Only two patients, both real-life responders, were classified incorrectly in both validation experiments.

Conclusion: We have validated the Pre-X-Stim model on EEGs from a different recording system, which indicates its application under different technical conditions. Our approach, based on preoperative EEG, is easily applied and financially undemanding and presents great potential for real-world clinical use.

International Consensus Based Review and Recommendations for Minimum Reporting Standards in Research on Transcutaneous Vagus Nerve Stimulation (Version 2020)

Given its non-invasive nature, there is increasing interest in the use of transcutaneous vagus nerve stimulation (tVNS) across basic, translational and clinical research. Contemporaneously, tVNS can be achieved by stimulating either the auricular branch or the cervical bundle of the vagus nerve, referred to as transcutaneous auricular vagus nerve stimulation(VNS) and transcutaneous cervical VNS, respectively. In order to advance the field in a systematic manner, studies using these technologies need to adequately report sufficient methodological detail to enable comparison of results between studies, replication of studies, as well as enhancing study participant safety. We systematically reviewed the existing tVNS literature to evaluate current reporting practices. Based on this review, and consensus among participating authors, we propose a set of minimal reporting items to guide future tVNS studies. The suggested items address specific technical aspects of the device and stimulation parameters. We also cover general recommendations including inclusion and exclusion criteria for participants, outcome parameters and the detailed reporting of side effects. Furthermore, we review strategies used to identify the optimal stimulation parameters for a given research setting and summarize ongoing developments in animal research with potential implications for the application of tVNS in humans. Finally, we discuss the potential of tVNS in future research as well as the associated challenges across several disciplines in research and clinical practice.

Response to Vagal Stimulation by Heart-rate Features in Drug-resistant Epileptic Patients

Vagal Nerve Stimulation (VNS) is an option in the treatment of drug-resistant epilepsy. However, approximately a quarter of VNS subjects does not respond to the therapy. In this retrospective study, we introduce heart-rate features to distinguish VNS responders and non-responders. Standard pre-implantation measurements of 66 patients were segmented in relation to specific stimuli (open/close eyes, photic stimulation, hyperventilation, and rests between). Median interbeat intervals were found for each segment and normalized (NMRR). Five NMRRs were significant; the strongest feature achieved significance with p=0.013 and AUC=0.66. Low mutual correlation and independence on EEG signals mean that presented features could be considered as an addition for models predicting VNS response using EEG.

[Application of scalp electroencephalogram in treatment of refractory epilepsy with vagus nerve stimulation]

Electroencephalogram (EEG) has been an important tool for scientists to study epilepsy and evaluate the treatment of epilepsy for half a century, since epilepsy seizures are caused by the diffusion of excessive discharge of brain neurons. This paper reviews the clinical application of scalp EEG in the treatment of intractable epilepsy with vagus nerve stimulation (VNS) in the past 30 years. It mainly introduces the prediction of the therapeutic effect of VNS on intractable epilepsy based on EEG characteristics and the effect of VNS on EEG of patients with intractable epilepsy, and expounds some therapeutic mechanisms of VNS. For predicting the efficacy of VNS based on EEG characteristics, EEG characteristics such as epileptiform discharge, polarity of slow cortical potential changes, changes of EEG symmetry level and changes of EEG power spectrum are described. In view of the influence of VNS treatment on patients' EEG characteristics, the change of epileptiform discharge, power spectrum, synchrony, brain network and amplitude of event-related potential P300 are described. Although no representative EEG markers have been identified for clinical promotion, this review paves the way for prospective studies of larger patient populations in the future to better apply EEG to the clinical treatment of VNS, and provides ideas for predicting VNS efficacy, assessing VNS efficacy, and understanding VNS treatment mechanisms, with broad medical and scientific implications.

Alteration in brain connectivity in patients with Dravet syndrome after vagus nerve stimulation (VNS): exploration of its effectiveness using graph theory analysis with electroencephalography

OBJECTIVE

Vagus nerve stimulation (VNS) is a nonpharmacologic therapeutic option for patients who have pharmaco-resistant Dravet syndrome (DS). Plentiful efforts have been made for delivering VNS to DS patients, but its effectiveness still requires further verification. We investigated the effectiveness of the VNS treatment of DS patients using brain connectivity analysis with electroencephalography (EEG).

APPROACH

Twenty pharmaco-resistant DS patients were selected to undergo VNS implantation and classified into responder and non-responder groups after 24 months post-VNS. The effect of VNS between 6 months pre- and 6, 12, and 24 months post-VNS in all patients, responders, and non-responders on four different frequency categories of four brain parameters were compared using resting-state EEG.

MAIN RESULTS

In alpha and beta bands, all patients showed positive results for characteristic path length (CPL), global efficiency (GE), and transitivity after VNS treatment, and changes in betweenness centrality (BC) were not significant. The difference in transitivity between responders and non-responders is more pronounced than those in CPL and GE are, in both the alpha (p < 0.015) and beta (p < 0.001) bands. There was an obvious change in BC, especially in the alpha band, as the hubs tended to move from frontal lobe to parietal lobe for responders; however, there was no change for the non-responders.

SIGNIFICANCE

We investigated the alteration in brain connectivity of DS patients in alpha and beta bands during a long-term follow-up and found the responders have a decreased transitivity after the VNS treatment. Moreover, the hubs with high values in the alpha band tended to move from frontal lobe to parietal lobe for responders after VNS treatment.

Can we predict response to vagus nerve stimulation in intractable epilepsy

BACKGROUND

Since vagus nerve stimulation (VNS) was approved by the Food and Drug Administration (FDA). A number of studies show that VNS was effective to reduce seizure frequency. However, there was still some patients treated with VNS having poor or even no clinical effect.

OBJECTIVES

The purpose of the present review was to identify factors predicting the effect of VNS therapy and to select patients suitable for VNS treatment.

METHOD

PubMed and Medline was searched with this terms "epilepsy," "vagus nerve stimulation," "vagal nerve stimulation," "VNS," "intractable," and "refractory".We selected studies by predefining inclusion and exclusion criteria.

RESULTS

the effectiveness of VNA was confirmed by a number of studies. We find many studies exploring the predictive factors to VNS. However there was no any study finding factors correlating clearly with the outcome of VNS. Although, we find these factors, such as post-traumatic epilepsy, temporal lobe epilepsy and focal interictal epileptiform discharges (IEDs), were favorable for the treatment of VNS, while comprehensive IEDs and neuronal migration disorders were indicative of the poor effect. Also, temporal lobe epilepsy was generally effectively controlled by this therapy and yougers seemed to get more benefit from VNS. Additionally, other indexes, such as cytokine profile, slow cortical potential (SCP) shift, preoperative heart rate variability (HRV), EEG reactivity and connectomic profiling, maybe predict the results of VNS.

CONCLUSION

In summary, these conventional and other new factors should be analyzed further by more science and rigorous experimental design to identify the clear correlation with the outcome of VNS therapy.

Vagus nerve stimulation for pediatric patients with drug-resistant epilepsy caused by genetic mutations: Two cases

Vagus nerve stimulation (VNS) is a neuromodulation therapy increasingly used for treating drug-resistant epilepsy. However, it remains to be determined which patients are best suited for the treatment, and it is difficult to predict the therapeutic effect before the implantation. Mutations in some genes could lead to epilepsy. Here we report two cases of pediatric patients with drug-resistant epilepsy treated by VNS therapy: Patient 1 with ARX mutation achieved good outcomes; Patient 2 with the CDKL5 mutation did not show improvement. Additionally, the therapeutic impact of VNS on brain networks was investigated, hoping to provide some empirical evidence for a better understanding of the mechanism of VNS treatment.