Experimental validation of a PNS-optimized whole-body gradient coil.

PURPOSE: Peripheral nerve stimulation (PNS) limits the usability of state-of-the-art whole-body and head-only MRI gradient coils. We used detailed electromagnetic and neurodynamic modeling to set an explicit PNS constraint during the design of a whole-body gradient coil and constructed it to compare the predicted and experimentally measured PNS thresholds to those of a matched design without PNS constraints. METHODS: We designed, constructed, and tested two actively shielded whole-body Y-axis gradient coil winding patterns: YG1 is a conventional symmetric design without PNS-optimization, whereas YG2's design used an additional constraint on the allowable PNS threshold in the head-imaging landmark, yielding an asymmetric winding pattern. We measured PNS thresholds in 18 healthy subjects at five landmark positions (head, cardiac, abdominal, pelvic, and knee). RESULTS: The PNS-optimized design YG2 achieved 46% higher average experimental thresholds for a head-imaging landmark than YG1 while incurring a 15% inductance penalty. For cardiac, pelvic, and knee imaging landmarks, the PNS thresholds increased between +22% and +35%. For abdominal imaging, PNS thresholds did not change significantly between YG1 and YG2 (-3.6%). The agreement between predicted and experimental PNS thresholds was within 11.4% normalized root mean square error for both coils and all landmarks. The PNS model also produced plausible predictions of the stimulation sites when compared to the sites of perception reported by the subjects. CONCLUSION: The PNS-optimization improved the PNS thresholds for the target scan landmark as well as most other studied landmarks, potentially yielding a significant improvement in image encoding performance that can be safely used in humans.

Peripheral nerve stimulation informed design of a high-performance asymmetric head gradient coil.

PURPOSE: Peripheral nerve stimulation (PNS) limits the image encoding performance of both body gradient coils and the latest generation of head gradients. We analyze a variety of head gradient design aspects using a detailed PNS model to guide the design process of a new high-performance asymmetric head gradient to raise PNS thresholds and maximize the usable image-encoding performance. METHODS: A novel three-layer coil design underwent PNS optimization involving PNS predictions of a series of candidate designs. The PNS-informed design process sought to maximize the usable parameter space of a coil with <10% nonlinearity in a 22 cm region of linearity, a relatively large inner diameter (44 cm), maximum gradient amplitude of 200 mT/m, and a high slew rate of 900 T/m/s. PNS modeling allowed identification and iterative adjustment of coil features with beneficial impact on PNS such as the number of winding layers, shoulder accommodation strategy, and level of asymmetry. PNS predictions for the final design were compared to measured thresholds in a constructed prototype. RESULTS: The final head gradient achieved up to 2-fold higher PNS thresholds than the initial design without PNS optimization and compared to existing head gradients with similar design characteristics. The inclusion of a third intermediate winding layer provided the additional degrees of freedom necessary to improve PNS thresholds without significant sacrifices to the other design metrics. CONCLUSION: Augmenting the design phase of a new high-performance head gradient coil by PNS modeling dramatically improved the usable image-encoding performance by raising PNS thresholds.

Prediction of experimental cardiac magnetostimulation thresholds using pig-specific body models.

PURPOSE: Modern high-amplitude gradient systems can be limited by the International Electrotechnical Commission 60601-2-33 cardiac stimulation (CS) limit, which was set in a conservative manner based on electrode experiments and E-field simulations in uniform ellipsoidal body models. Here, we show that coupled electromagnetic-electrophysiological modeling in detailed body and heart models can predict CS thresholds, suggesting that such modeling might lead to more detailed threshold estimates in humans. Specifically, we compare measured and predicted CS thresholds in eight pigs. METHODS: We created individualized porcine body models using MRI (Dixon for the whole body, CINE for the heart) that replicate the anatomy and posture of the animals used in our previous experimental CS study. We model the electric fields induced along cardiac Purkinje and ventricular muscle fibers and predict the electrophysiological response of these fibers, yielding CS threshold predictions in absolute units for each animal. Additionally, we assess the total modeling uncertainty through a variability analysis of the 25 main model parameters. RESULTS: Predicted and experimental CS thresholds agree within 19% on average (normalized RMS error), which is smaller than the 27% modeling uncertainty. No significant difference was found between the modeling predictions and experiments (p < 0.05, paired t-test). CONCLUSION: Predicted thresholds matched the experimental data within the modeling uncertainty, supporting the model validity. We believe that our modeling approach can be applied to study CS thresholds in humans for various gradient coils, body shapes/postures, and waveforms, which is difficult to do experimentally.

Measurement of magnetostimulation thresholds in the porcine heart.

PURPOSE: Powerful MRI gradient systems can surpass the International Electrotechnical Commission (IEC) 60601-2-33 limit for cardiac stimulation (CS), which was determined by simple electromagnetic simulations and electrode stimulation experiments. Only a few canine studies measured magnetically induced CS thresholds in vivo and extrapolating them to human safety limits can be challenging. METHODS: We measured cardiac magnetostimulation thresholds in 10 healthy, anesthetized pigs using capacitors discharged into a flat spiral coil to produce damped sinusoidal waveforms with effective stimulus duration ts,eff  = 0.45 ms. Electrocardiography (ECG), blood pressure, and peripheral oximetry signals were recorded to determine threshold coil currents yielding cardiac capture. Dixon and CINE MR volumes from each animal were segmented to generate porcine-specific electromagnetic models to calculate dB/dt and E-field values in the porcine heart at threshold. For comparison, we also simulated maximum dB/dt and E-field values created by three MRI gradient systems in the heart of a human body model. RESULTS: The average dB/dt threshold estimated in the porcine heart was 1.66 ± 0.23 kT/s, which is 11-fold greater than the IEC dB/dt limit at ts,eff  = 0.45 ms, and 31-fold greater than the maximum value created by the investigated MRI gradients in the human heart. The average E-field threshold estimated in the porcine heart was 92.9 ± 13.5 V/m, which is 6-fold greater than the IEC E-field limit at ts,eff  = 0.45 ms and 37-fold greater than the maximum gradient-induced E-field in the human heart. CONCLUSION: This first measurement of cardiac magnetostimulation thresholds in pigs indicates that the IEC cardiac safety limit is conservative for the investigated stimulus duration (ts,eff  = 0.45 ms).

Investigating cardiac stimulation limits of MRI gradient coils using electromagnetic and electrophysiological simulations in human and canine body models.

PURPOSE: Cardiac stimulation (CS) limits to gradient coil switching speed are difficult to measure in humans; instead, current regulatory guidelines (IEC 60601-2-33) are based on animal experiments and electric field-to-dB/dt conversion factors computed for a simple, homogeneous body model. We propose improvement to this methodology by using more detailed CS modeling based on realistic body models and electrophysiological models of excitable cardiac fibers. METHODS: We compute electric fields induced by a solenoid, coplanar loops, and a commercial gradient coil in two human body models and a canine model. The canine simulations mimic previously published experiments. We generate realistic fiber topologies for the cardiac Purkinje and ventricular muscle fiber networks using rule-based algorithms, and evaluate CS thresholds using validated electrodynamic models of these fibers. RESULTS: We were able to reproduce the average measured canine CS thresholds within 5%. In all simulations, the Purkinje fibers were stimulated before the ventricular fibers, and therefore set the effective CS threshold. For the investigated gradient coil, simulated CS thresholds for the x-, y-, and z-axis were at least one order of magnitude greater than the International Electrotechnical Commission limit. CONCLUSION: We demonstrate an approach to simulate gradient-induced CS using a combination of electromagnetic and electrophysiological modeling. Pending additional validation, these simulations could guide the assessment of CS limits to MRI gradient coil switching speed. Such an approach may lead to less conservative, but still safe, operation limits, enabling the use of the maximum gradient amplitude versus slew rate parameter space of recent, powerful gradient systems.

Influence of peripheral axon geometry and local anatomy on magnetostimulation chronaxie.

Objective.Rapid switching of magnetic resonance imaging (MRI) gradient fields induces electric fields that can cause peripheral nerve stimulation (PNS) and so accurate characterization of PNS is required to maintain patient safety and comfort while maximizing MRI performance. The minimum magnetic gradient amplitude that causes stimulation, the PNS threshold, depends on intrinsic axon properties and the spatial and temporal properties of the induced electric field. The PNS strength-duration curve is widely used to characterize simulation thresholds for periodic waveforms and is parameterized by the chronaxie and rheobase. Safety limits to avoid unwanted PNS in MRI rely on a single chronaxie value to characterize the response of all nerves. However, experimental magnetostimulation peripheral nerve chronaxie values vary by an order of magnitude. Given the diverse range of chronaxies observed and the importance of this number in MRI safety models, we seek a deeper understanding of the mechanisms contributing to chronaxie variability.Approach.We use a coupled electromagnetic-neurodynamic PNS model to assess geometric sources of chronaxie variability. We study the impact of the position of the stimulating magnetic field coil relative to the body, along with the effect of local anatomical features and nerve trajectories on the driving function and the resulting chronaxie.Main results.We find realistic variation of local axon and tissue geometry can modulate a given axon's chronaxie by up to two-fold. Our results identify the temporal rate of charge redistribution as the underlying determinant of the chronaxie.Significance.This charge distribution is a function of both intrinsic axon properties and the spatial stimulus along the nerve; thus, examination of the local tissue topology, which shapes the electric fields, as well as the nerve trajectory, are critical for better understanding chronaxie variations and defining more biologically informed MRI safety guidelines.

Optimization of MRI Gradient Coils With Explicit Peripheral Nerve Stimulation Constraints.

Peripheral Nerve Stimulation (PNS) limits the acquisition rate of Magnetic Resonance Imaging data for fast sequences employing powerful gradient systems. The PNS characteristics are currently assessed after the coil design phase in experimental stimulation studies using constructed coil prototypes. This makes it difficult to find design modifications that can reduce PNS. Here, we demonstrate a direct approach for incorporation of PNS effects into the coil optimization process. Knowledge about the interactions between the applied magnetic fields and peripheral nerves allows the optimizer to identify coil solutions that minimize PNS while satisfying the traditional engineering constraints. We compare the simulated thresholds of PNS-optimized body and head gradients to conventional designs, and find an up to 2-fold reduction in PNS propensity with moderate penalties in coil inductance and field linearity, potentially doubling the image encoding performance that can be safely used in humans. The same framework may be useful in designing and operating magneto- and electro-stimulation devices.

Changes of Infant- and Family-Centered Care Practices Administered to Extremely Preterm Infants During Implementation of the NIDCAP Program.

Introduction: Many studies have evaluated the Neonatal Individualized Developmental Care and Assessment Program (NIDCAP), but few studies have assessed changes in infant- and family-centered developmental care (IFCDC) practices during its implementation. Objectives: The primary objective of this single center study was to investigate the impact of the implementation of the NIDCAP program on IFCDC practices used for management of extremely preterm infants (EPIs). The secondary objective was to determine during implementation the impact of this program on the short-term medical outcomes of all EPIs hospitalized at our center. Methods: All EPIs (<28 weeks gestational age) who were hospitalized at Strasbourg University Hospital from 2007 to 2014 were initially included. Outborn infants were excluded. The data of EPIs were compared for three time periods: 2007 to 2008 (pre-NIDCAP), 2010 to 2011, and 2013 to 2014 (during-NIDCAP implementation) using appropriate statistical tests. The clinical and caring procedures used during the first 14 days of life were analyzed, with a focus on components of individualized developmental care (NIDCAP observations), infant pain management (number of painful procedures, clinical pain assessment), skin-to-skin contact (SSC; frequency, day of initiation, and duration), and family access and involvement in the care of their children (duration of parental presence, parental participation in care). The short-term mortality and morbidity at discharge were evaluated. Results: We examined 228 EPIs who received care during the three time periods. Over time, painful procedures decreased, but pain evaluations, parental involvement in care, individualized observations, and SSC increased (all p < 0.01). In addition, the first SSC was performed earlier (p = 0.03) and lasted longer (p < 0.01). There were no differences in mortality and morbidity, but there were reductions in the duration of mechanical ventilation (p = 0.02) and the time from birth to first extubation (p = 0.02), and an increase of weight gain at discharge (p = 0.02). Conclusion: NIDCAP implementation was accompanied by progressive, measurable, and significant changes in IFCDC strategies. There were, concomitantly, moderate but statistically significant improvements in multiple important outcome measures of all hospitalized EPI.

Optimizing selective stimulation of peripheral nerves with arrays of coils or surface electrodes using a linear peripheral nerve stimulation metric.

OBJECTIVE: We present a PNS oracle, which solves these computation time and linearity problems and is, therefore, well-suited for fast optimization of voltage distributions in contact electrode arrays and current drive patterns in non-contact magnetic coil arrays. APPROACH: The PNS oracle metric for a nerve fiber is computed from an electric field map using only linear operations (projection, differentiation, convolution, scaling). Due to its linearity, this PNS metric can be precomputed for a set of coil or electrode segments, allowing rapid PNS prediction and comparison of any possible coil or electrode stimulation configuration constructed from this set. The PNS oracle is closely related to the classical activating function and modified driving functions but is adjusted to better correlate with full neurodynamic modeling of myelinated mammalian nerves. MAIN RESULTS: We validated the PNS oracle in three MRI gradient coils and two body models and found good correlation between the PNS oracle and the full neurodynamic modeling approach (R 2 > 0.995). Finally, we demonstrated its potential utility by optimizing the driving currents and voltages of arrays of 108 magnetic coils or 108 contact electrodes to selectively stimulate target nerves in the lower leg. SIGNIFICANCE: Peripheral nerve stimulation (PNS) by electromagnetic fields can be accurately simulated using coupled electromagnetic and neurodynamic modeling. Such simulations are slow and non-linear in the electric field, which makes it difficult to iteratively optimize coil and electrode configurations or drive patterns aiming to avoid PNS or to initiate it for therapeutic purposes.

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

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.

Using EGFP fusions to monitor the functional expression of GPCRs in the Drosophila Schneider 2 cells.

In combining fluorescence measurements with ligand binding assays, the versatility of the EGFP C-terminally fused to the human mu opioid receptor (EGFP-hMOR) has been exploited to notably improve the expression level of functional G protein-coupled receptors in Drosophila S2 cells. A selected array of efficient optimization approaches is presented herein, ranging from a cell-sorting method, allowing for a substantial enrichment in EGFP-hMOR expressing cells, to the addition of chemical and pharmacological chaperones, significantly enhancing the yield and the activity of the expressed receptors. Consistent with previous studies, significant discrepancies were observed between the total amounts of fluorescent receptors over a limited subpopulation capable of ligand binding, even after expression optimization. Subsequently, membrane isopycnic centrifugation experiments allowed to separate the ligand binding active from the non-active membrane fraction, the latter most probably containing misfolded receptors. Taken together, these results illustrate a coherent set of advantageous productive and preparative methods for the production of GPCRs in the highly valuable Drosophila S2 expression system.