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Prediction of peripheral nerve stimulation thresholds of MRI gradient coils using coupled electromagnetic and neurodynamic simulations.

ABSTRACT: PURPOSE:As gradient performance increases, peripheral nerve stimulation (PNS) is becoming a significant constraint for fast MRI. Despite its impact, PNS is not directly included in the coil design process. Instead, the PNS characteristics of a gradient are assessed on healthy subjects after prototype construction. We attempt to develop a tool to inform coil design by predicting the PNS thresholds and activation locations in the human body using electromagnetic field simulations coupled to a neurodynamic model. We validate the approach by comparing simulated and experimentally determined thresholds for 3 gradient coils. METHODS:We first compute the electric field induced by the switching fields within a detailed electromagnetic body model, which includes a detailed atlas of peripheral nerves. We then calculate potential changes along the nerves and evaluate their response using a neurodynamic model. Both a male and female body model are used to study 2 body gradients and 1 head gradient. RESULTS:There was good agreement between the average simulated thresholds of the male and female models with the experimental average (normalized root-mean-square error: <10% and <5% in most cases). The simulation could also interrogate thresholds above those accessible by the experimental setup and allowed identification of the site of stimulation. CONCLUSIONS:Our simulation framework allows accurate prediction of gradient coil PNS thresholds and provides detailed information on location and "next nerve" thresholds that are not available experimentally. As such, we hope that PNS simulations can have a potential role in the design phase of high performance MRI gradient coils.

SUBMITTER: Davids M

PROVIDER: S-EPMC6258337 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Prediction of peripheral nerve stimulation thresholds of MRI gradient coils using coupled electromagnetic and neurodynamic simulations.

Davids Mathias M Guérin Bastien B Vom Endt Axel A Schad Lothar R LR Wald Lawrence L LL

Magnetic resonance in medicine 20180809 1

<h4>Purpose</h4>As gradient performance increases, peripheral nerve stimulation (PNS) is becoming a significant constraint for fast MRI. Despite its impact, PNS is not directly included in the coil design process. Instead, the PNS characteristics of a gradient are assessed on healthy subjects after prototype construction. We attempt to develop a tool to inform coil design by predicting the PNS thresholds and activation locations in the human body using electromagnetic field simulations coupled t ...[more]

PMID: 30094874

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Project description: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.

Project description:BackgroundPeripheral magnetic stimulation (PMS) is emerging as a complement to standard electrical stimulation (ES) of the peripheral nervous system (PNS). PMS may stimulate sensory and motor nerve fibers without the discomfort associated with the ES used for standard nerve conduction studies. The PMS coils are the same ones used in transcranial magnetic stimulation (TMS) and lack focality and selectiveness in the stimulation.PurposeThis study presents a novel coil for PMS, developed using Flexible technologies, and characterized by reduced dimensions for a precise and controlled targeting of peripheral nerves.MethodsWe performed hybrid electromagnetic (EM) and electrophysiological simulations to study the EM exposure induced by a novel miniaturized coil (or mcoil) in and around the radial nerve of the neuro-functionalized virtual human body model Yoon-Sun, and to estimate the current threshold to induce magnetic stimulation (MS) of the radial nerve. Eleven healthy subjects were studied with the mcoil, which consisted of two 15 mm diameter coils in a figure-of-eight configuration, each with a hundred turns of a 25 μm copper-clad four-layer foil. Sensory nerve action potentials (SNAPs) were measured in each subject using two electrodes and compared with those obtained from standard ES. The SNAPs conduction velocities were estimated as a performance metric.ResultsThe induced electric field was estimated numerically to peak at a maximum intensity of 39 V/m underneath the mcoil fed by 70 A currents. In such conditions, the electrophysiological simulations suggested that the mcoil elicits SNAPs originating at 7 mm from the center of the mcoil. Furthermore, the numerically estimated latencies and waveforms agreed with those obtained during the PMS experiments on healthy subjects, confirming the ability of the mcoil to stimulate the radial nerve sensory fibers.ConclusionHybrid EM-electrophysiological simulations assisted the development of a miniaturized coil with a small diameter and a high number of turns using flexible electronics. The numerical dosimetric analysis predicted the threshold current amplitudes required for a suprathreshold peripheral nerve sensory stimulation, which was experimentally confirmed. The developed and now validated computational pipeline will be used to improve the performances (e.g., focality and minimal currents) of new generations of mcoil designs.

Dataset Information

Prediction of peripheral nerve stimulation thresholds of MRI gradient coils using coupled electromagnetic and neurodynamic simulations.

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Prediction of peripheral nerve stimulation thresholds of MRI gradient coils using coupled electromagnetic and neurodynamic simulations.

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