Dataset Information

Sensitivity analysis of neurodynamic and electromagnetic simulation parameters for robust prediction of peripheral nerve stimulation.

ABSTRACT: Peripheral nerve stimulation (PNS) has become an important limitation for fast MR imaging using the latest gradient hardware. We have recently developed a simulation framework to predict PNS thresholds and stimulation locations in the body for arbitrary coil geometries to inform the gradient coil optimization process. Our approach couples electromagnetic field simulations in realistic body models to a neurodynamic model of peripheral nerve fibers. In this work, we systematically analyze the impact of key parameters on the predicted PNS thresholds to assess the robustness of the simulation results. We analyze the sensitivity of the simulated thresholds to variations of the most important simulation parameters, including parameters of the electromagnetic field simulations (dielectric tissue properties, body model size, position, spatial resolution, and coil model discretization) and parameters of the neurodynamic simulation (length of the simulated nerves, position of the nerve model relative to the extracellular potential, temporal resolution of the nerve membrane dynamics). We found that for the investigated setup, the subject-dependent parameters (e.g. tissue properties or body size) can affect PNS prediction by up to ~26% when varied in a natural range. This is in accordance with the standard deviation of ~30% reported in human subject studies. Parameters related to numerical aspects can cause significant simulation errors (>30%), if not chosen cautiously. However, these perturbations can be controlled to yield errors below 5% for all investigated parameters without an excessive increase in computation time. Our sensitivity analysis shows that patient-specific parameter fluctuations yield PNS threshold variations similar to the variations observed in experimental PNS studies. This may become useful to estimate population-average PNS thresholds and understand their standard deviation. Our analysis indicates that the simulated PNS thresholds are numerically robust, which is important for ranking different MRI gradient coil designs or assessing different PNS mitigation strategies.

SUBMITTER: Klein V

PROVIDER: S-EPMC6530798 | biostudies-other | 2018 Dec

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Sensitivity analysis of neurodynamic and electromagnetic simulation parameters for robust prediction of peripheral nerve stimulation.

Klein Valerie V Davids Mathias M Wald Lawrence L LL Schad Lothar R LR Guérin Bastien B

Physics in medicine and biology 20181219 1

Peripheral nerve stimulation (PNS) has become an important limitation for fast MR imaging using the latest gradient hardware. We have recently developed a simulation framework to predict PNS thresholds and stimulation locations in the body for arbitrary coil geometries to inform the gradient coil optimization process. Our approach couples electromagnetic field simulations in realistic body models to a neurodynamic model of peripheral nerve fibers. In this work, we systematically analyze the impa ...[more]

PMID: 30523884

Similar Datasets

Project description:Although the therapeutic effects of Vagus Nerve Stimulation (VNS) have been recognized in pre-clinical and pilot clinical studies, the effect of different stimulation configurations on the cardiovascular response is still an open question, especially in the case of VNS delivered synchronously with cardiac activity. In this paper, we propose a formal mathematical methodology to analyze the acute cardiac response to different VNS configurations, jointly considering the chronotropic, dromotropic and inotropic cardiac effects. A latin hypercube sampling method was chosen to design a uniform experimental plan, composed of 75 different VNS configurations, with different values for the main parameters (current amplitude, number of delivered pulses, pulse width, interpulse period and the delay between the detected cardiac event and VNS onset). These VNS configurations were applied to 6 healthy, anesthetized sheep, while acquiring the associated cardiovascular response. Unobserved VNS configurations were estimated using a Gaussian process regression (GPR) model. In order to quantitatively analyze the effect of each parameter and their combinations on the cardiac response, the Sobol sensitivity method was applied to the obtained GPR model and inter-individual sensitivity markers were estimated using a bootstrap approach. Results highlight the dominant effect of pulse current, pulse width and number of pulses, which explain respectively 49.4%, 19.7% and 6.0% of the mean global cardiovascular variability provoked by VNS. More interestingly, results also quantify the effect of the interactions between VNS parameters. In particular, the interactions between current and pulse width provoke higher cardiac effects than the changes on the number of pulses alone (between 6 and 25% of the variability). Although the sensitivity of individual VNS parameters seems similar for chronotropic, dromotropic and inotropic responses, the interacting effects of VNS parameters provoke significantly different cardiac responses, showing the feasibility of a parameter-based functional selectivity. These results are of primary importance for the optimal, subject-specific definition of VNS parameters for a given therapy and may lead to new closed-loop methods allowing for the optimal adaptation of VNS therapy through time.

Project description:BackgroundAutonomic nerve stimulation is used as a treatment for a growing number of diseases. We have previously demonstrated that application of efferent vagus nerve stimulation (eVNS) has promising glucose lowering effects in a rat model of type 2 diabetes. This paradigm combines high frequency pulsatile stimulation to block nerve activation in the afferent direction with low frequency stimulation to activate the efferent nerve section. In this study we explored the effects of the parameters for nerve blocking on the ability to inhibit nerve activation in the afferent direction. The overarching aim is to establish a blocking stimulation strategy that could be applied using commercially available implantable pulse generators used in the clinic.MethodsMale rats (n = 20) had the anterior abdominal vagus nerve implanted with a multi-electrode cuff. Evoked compound action potentials (ECAP) were recorded at the proximal end of the electrode cuff. The efficacy of high frequency stimulation to block the afferent ECAP was assessed by changes in the threshold and saturation level of the response. Blocking frequency and duty cycle of the blocking pulses were varied while maintaining a constant 4 mA current amplitude.ResultsDuring application of blocking at lower frequencies (≤ 4 kHz), the ECAP threshold increased (ANOVA, p < 0.001) and saturation level decreased (p < 0.001). Application of higher duty cycles (> 70%) led to an increase in evoked neural response threshold (p < 0.001) and a decrease in saturation level (p < 0.001). During the application of a constant pulse width and frequency (1 or 1.6 kHz, > 70% duty cycle), the charge delivered per pulse had a significant influence on the magnitude of the block (ANOVA, p = 0.003), and was focal (< 2 mm range).ConclusionsThis study has determined the range of frequencies, duty cycles and currents of high frequency stimulation that generate an efficacious, focal axonal block of a predominantly C-fiber tract. These findings could have potential application for the treatment of type 2 diabetes.

Project description:BACKGROUND:Transcutaneous cervical vagus nerve stimulation (tcVNS) is a promising alternative to implantable stimulation of the vagus nerve. With demonstrated potential in myriad applications, ranging from systemic inflammation reduction to traumatic stress attenuation, closed-loop tcVNS during periods of risk could improve treatment efficacy and reduce ineffective delivery. However, achieving this requires a deeper understanding of biomarker changes over time. OBJECTIVE:The aim of the present study was to reveal the dynamics of relevant cardiovascular biomarkers, extracted from wearable sensing modalities, in response to tcVNS. METHODS:Twenty-four human subjects were recruited for a randomized double-blind clinical trial, for whom electrocardiography and photoplethysmography were used to measure heart rate and photoplethysmogram amplitude responses to tcVNS, respectively. Modeling these responses in state-space, we (1) compared the biomarkers in terms of their predictability and active vs sham differentiation, (2) studied the latency between stimulation onset and measurable effects, and (3) visualized the true and model-simulated biomarker responses to tcVNS. RESULTS:The models accurately predicted future heart rate and photoplethysmogram amplitude values with root mean square errors of approximately one-fifth the standard deviations of the data. Moreover, (1) the photoplethysmogram amplitude showed superior predictability (P=.03) and active vs sham separation compared to heart rate; (2) a consistent delay of greater than 5 seconds was found between tcVNS onset and cardiovascular effects; and (3) dynamic characteristics differentiated responses to tcVNS from the sham stimulation. CONCLUSIONS:This work furthers the state of the art by modeling pertinent biomarker responses to tcVNS. Through subsequent analysis, we discovered three key findings with implications related to (1) wearable sensing devices for bioelectronic medicine, (2) the dominant mechanism of action for tcVNS-induced effects on cardiovascular physiology, and (3) the existence of dynamic biomarker signatures that can be leveraged when titrating therapy in closed loop. TRIAL REGISTRATION:ClinicalTrials.gov NCT02992899; https://clinicaltrials.gov/ct2/show/NCT02992899. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):RR2-10.1016/j.brs.2019.08.002.

Project description:BackgroundPeripheral nerve stimulation (PNS) has been increasingly used to manage acute and chronic pain. However, the level of clinical evidence to support its use is not clear.ObjectivesTo assess the clinical evidence of PNS in the treatment of acute or chronic pain.Study designA systematic review of the efficacy and safety of PNS in managing acute or chronic pain.MethodsData sources were PubMed, Cochrane Library, Scopus, CINAHL Plus, Google Scholar, and reference lists. The literature search was performed up to December 2019. Study selection included randomized trials, observational studies, and case reports of PNS in acute or chronic pain. Data extraction and methodological quality assessment were performed utilizing Cochrane review methodologic quality assessment and Interventional Pain Management Techniques-Quality Appraisal of Reliability and Risk of Bias Assessment (IPM-QRB) and Interventional Pain Management Techniques-Quality Appraisal of Reliability and Risk of Bias Assessment for Nonrandomized Studies (IPM-QRBNR). The evidence was summarized utilizing principles of best evidence synthesis on a scale of 1 to 5. Data syntheses: 227 studies met inclusion criteria and were included in qualitative synthesis.ResultsEvidence synthesis based on randomized controlled trials (RCTs) and observational studies showed Level I and II evidence of PNS in chronic migraine headache; Level II evidence in cluster headache, postamputation pain, chronic pelvic pain, chronic low back and lower extremity pain; and Level IV evidence in peripheral neuropathic pain, and postsurgical pain. Peripheral field stimulation has Level II evidence in chronic low back pain, and Level IV evidence in cranial pain.LimitationsLack of high-quality RCTs. Meta-analysis was not possible due to wide variations in experimental design, research protocol, and heterogeneity of study population.ConclusionsThe findings of this systematic review suggest that PNS may be effective in managing chronic headaches, postamputation pain, chronic pelvic pain, and chronic low back and lower extremity pain, with variable levels of evidence in favor of this technique.

Dataset Information

Sensitivity analysis of neurodynamic and electromagnetic simulation parameters for robust prediction of peripheral nerve stimulation.

Publications

Sensitivity analysis of neurodynamic and electromagnetic simulation parameters for robust prediction of peripheral nerve stimulation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets