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

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.

Minimizing electric fields and increasing peripheral nerve stimulation thresholds using a body gradient array coil

PURPOSE

To demonstrate the performance of gradient array coils in minimizing switched-gradient-induced electric fields (E-fields) and improving peripheral nerve stimulation (PNS) thresholds while generating gradient fields with adjustable linearity across customizable regions of linearity (ROLs).

METHODS

A body gradient array coil is used to reduce the induced E-fields on the surface of a body model by modulating applied currents. This is achieved by performing an optimization problem with the peak E-field as the objective function and current amplitudes as unknown variables. Coil dimensions and winding patterns are fixed throughout the optimization, whereas other engineering metrics remain adjustable. Various scenarios are explored by manipulating adjustable parameters.

RESULTS

The array design consistently yields lower E-fields and higher PNS thresholds across all scenarios compared with a conventional coil. When the gradient array coil generates target gradient fields within a 44-cm-diameter spherical ROL, the maximum E-field is reduced by 10%, 18%, and 61% for the X, Y, and Z gradients, respectively. Transitioning to a smaller ROL (24 cm) and relaxing the gradient linearity error results in further E-field reductions. In oblique gradients, the array coil demonstrates the most substantial reduction of 40% in the Z-Y direction. Among the investigated scenarios, the most significant increase of 4.3-fold is observed in the PNS thresholds.

CONCLUSION

Our study demonstrated that gradient array coils offer a promising pathway toward achieving high-performance gradient coils regarding gradient strength, slew rate, and PNS thresholds, especially in scenarios in which linear magnetic fields are required within specific target regions.

Fast and silent MRI using nonlinear gradient fields at the ultrasonic gradient switching frequency of 20 kHz with a Point Spread Function framework reconstruction

PURPOSE

To demonstrate the feasibility of using a nonlinear gradient field for spatial encoding at the ultrasonic switching frequency of 20 kHz and present a framework to reconstruct data acquired in this way.

METHODS

Nonlinear encoding at 20 kHz was realized by using a single-axis silent gradient insert for imaging in the periphery, that, is the nonlinear region, of the gradient field. The gradient insert induces a rapidly oscillating gradient field in the phase-encode direction, which enables nonlinear encoding when combined with a Cartesian readout from the linear whole-body gradients. Data from a 2D gradient echo sequence were reconstructed using a point spread function (PSF) framework. Accelerated scans were also simulated via retrospective undersampling (R = 1 to R = 8) to determine the effectiveness of the PSF-framework for accelerated imaging.

RESULTS

Using a nonlinear gradient field switched at 20 kHz and the PSF-framework resulted in images of comparable quality to images from conventional Cartesian linear encoding. At increased acceleration factors (R ≤ 8), the PSF-framework outperformed linear SENSE reconstructions by improved controlling of aliasing artifacts.

CONCLUSION

Using the PSF-framework, images of comparable quality to conventional SENSE reconstructions are possible via combining traditional linear and ultrasonic oscillating nonlinear encoding fields. Using nonlinear gradient fields relaxes the demand for strictly linear gradient fields, enabling much higher slew rates with a reduced risk of peripheral nerve stimulation or cardiac stimulation, which could aid in extension to ultrasonic whole-body MRI. The lack of aliasing artifacts also highlights the potential of accelerated imaging using the PSF-framework.

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.

Bioelectronic Medicine: a multidisciplinary roadmap from biophysics to precision therapies

Bioelectronic Medicine stands as an emerging field that rapidly evolves and offers distinctive clinical benefits, alongside unique challenges. It consists of the modulation of the nervous system by precise delivery of electrical current for the treatment of clinical conditions, such as post-stroke movement recovery or drug-resistant disorders. The unquestionable clinical impact of Bioelectronic Medicine is underscored by the successful translation to humans in the last decades, and the long list of preclinical studies. Given the emergency of accelerating the progress in new neuromodulation treatments (i.e., drug-resistant hypertension, autoimmune and degenerative diseases), collaboration between multiple fields is imperative. This work intends to foster multidisciplinary work and bring together different fields to provide the fundamental basis underlying Bioelectronic Medicine. In this review we will go from the biophysics of the cell membrane, which we consider the inner core of neuromodulation, to patient care. We will discuss the recently discovered mechanism of neurotransmission switching and how it will impact neuromodulation design, and we will provide an update on neuronal and glial basis in health and disease. The advances in biomedical technology have facilitated the collection of large amounts of data, thereby introducing new challenges in data analysis. We will discuss the current approaches and challenges in high throughput data analysis, encompassing big data, networks, artificial intelligence, and internet of things. Emphasis will be placed on understanding the electrochemical properties of neural interfaces, along with the integration of biocompatible and reliable materials and compliance with biomedical regulations for translational applications. Preclinical validation is foundational to the translational process, and we will discuss the critical aspects of such animal studies. Finally, we will focus on the patient point-of-care and challenges in neuromodulation as the ultimate goal of bioelectronic medicine. This review is a call to scientists from different fields to work together with a common endeavor: accelerate the decoding and modulation of the nervous system in a new era of therapeutic possibilities.

Orthopedic implants affect the electric field induced by switching gradients in MRI

PURPOSE

To investigate whether the risk of peripheral nerve stimulation increases in the presence of bulky metallic prostheses implanted in a patient's body.

METHODS

A computational tool was used to calculate the electric field (E-field) induced in a realistic human model due to the action of gradient fields. The calculations were performed both on the original version of the anatomical model and on a version modified through "virtual surgery" to incorporate knee, hip, and shoulder prostheses. Five exam positions within a body gradient coil and one position using a head gradient coil were simulated, subjecting the human model to the readout gradient from an EPI sequence. The induced E-field in models with and without prostheses was compared, focusing on the nerves and all other tissues (both including and excluding the bones from the analysis).

RESULTS

In the nerves, the most pronounced increase in the E-field (+24%) was observed around the knee implant during an abdominal MRI (Y axis readout). When extending the analysis to encompass all tissues (excluding bones), the greatest amplification (+360%) occurred around the knee implant during pelvic MRI (Z axis readout). Notable increases in E-field peaks were also identified around the shoulder and hip implants in multiple scenarios.

CONCLUSION

Based on the presented results, further investigations aimed at quantifying the threshold of nerve stimulation in the presence of bulky implants are desirable.

Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla

To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m-1, 900 T m-1s-1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35-0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.

Patient safety in magnetic resonance imaging

Image acquisition involves the use of static magnetic fields, field gradients and radiofrequency waves. These elements make the MRI a different modality. More and more centers work with 3.0 T equipment that present higher risks for the patient, compared to those of 1.5 T. Therefore, there is a need for updating for radiology staff that allows them to understand the risks and reduce them, since serious and even fatal incidents can occur. The objective of this work is to present a review and update of the risks to which patients are subjected during the performance of a magnetic resonance imaging (MRI) study.

Stochastic optimization of three-dimensional non-Cartesian sampling trajectory

PURPOSE

Optimizing three-dimensional (3D) k-space sampling trajectories is important for efficient MRI yet presents a challenging computational problem. This work proposes a generalized framework for optimizing 3D non-Cartesian sampling patterns via data-driven optimization.

METHODS

We built a differentiable simulation model to enable gradient-based methods for sampling trajectory optimization. The algorithm can simultaneously optimize multiple properties of sampling patterns, including image quality, hardware constraints (maximum slew rate and gradient strength), reduced peripheral nerve stimulation (PNS), and parameter-weighted contrast. The proposed method can either optimize the gradient waveform (spline-based freeform optimization) or optimize properties of given sampling trajectories (such as the rotation angle of radial trajectories). Notably, the method can optimize sampling trajectories synergistically with either model-based or learning-based reconstruction methods. We proposed several strategies to alleviate the severe nonconvexity and huge computation demand posed by the large scale. The corresponding code is available as an open-source toolbox.

RESULTS

We applied the optimized trajectory to multiple applications including structural and functional imaging. In the simulation studies, the image quality of a 3D kooshball trajectory was improved from 0.29 to 0.22 (NRMSE) with Stochastic optimization framework for 3D NOn-Cartesian samPling trajectorY (SNOPY) optimization. In the prospective studies, by optimizing the rotation angles of a stack-of-stars (SOS) trajectory, SNOPY reduced the NRMSE of reconstructed images from 1.19 to 0.97 compared to the best empirical method (RSOS-GR). Optimizing the gradient waveform of a rotational EPI trajectory improved participants' rating of the PNS from "strong" to "mild."

CONCLUSION

SNOPY provides an efficient data-driven and optimization-based method to tailor non-Cartesian sampling trajectories.

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.

Advancements in Gradient System Performance for Clinical and Research MRI

In magnetic resonance imaging (MRI), spatial field gradients are applied along each axis to encode the location of the nuclear spin in the frequency domain. During recent years, the development of new gradient technologies has been focused on the generation of stronger and faster gradient fields for imaging with higher spatial and temporal resolution. This benefits imaging methods, such as brain diffusion and functional MRI, and enables human imaging at ultra-high field MRI. In addition to improving gradient performance, new technologies have been presented to minimize peripheral nerve stimulation and gradient-related acoustic noise, both generated by the rapid switching of strong gradient fields. This review will provide a general background on the gradient system and update on the state-of-the-art gradient technology. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Impact of partial bile duct ligation with or without repeated magnetic resonance imaging examinations in mice

Partial bile duct ligation (pBDL) is considered a well-tolerated cholestatic model. Magnetic resonance imaging (MRI) is one of the most widely used tools in noninvasive imaging. However, no systematic studies have reported the possible effects of repeated MRI assessments in the pBDL model. Sixty BALB/C mice were investigated. MRI images of each mouse were recorded once every 2 weeks for 6 weeks after pBDL or sham surgery. The reproducibility of the pBDL model and the reliability of MRI were examined by behavioral, physiological, biochemical, and pathological parameters. The mice showed no alterations on behavioral and physiological tests (P > 0.05) at 2, 4, and 6 weeks after pBDL. Repeated general anesthesia did not result in any impairment after pBDL (P > 0.05). The behavioral and biochemical parameters were not affected by repeated MRIs or repeated contrast-enhanced MRIs (P > 0.05). Pathological staining showed the homogeneous formation of collagenous fiber in the pBDL mice and did not indicate any influence of repeated contrast-enhanced MRI on the number of inflammatory cells or fibrotic formation (P > 0.05). Thus, pBDL is a reproducible model with many advantages for animal welfare and scientific research. Additionally, MRI, as a safe tool for longitudinal evaluation and is well tolerated in mice with cholestasis.

A handbook for beginners in skeletal muscle diffusion tensor imaging: physical basis and technical adjustments

Magnetic resonance imaging (MRI) of skeletal muscle is routinely performed using morphological sequences to acquire anatomical information. Recently, there is an increasing interest in applying advanced MRI techniques that provide pathophysiologic information for skeletal muscle evaluation to complement standard morphologic information. Among these advanced techniques, diffusion tensor imaging (DTI) has emerged as a potential tool to explore muscle microstructure. DTI can noninvasively assess the movement of water molecules in well-organized tissues with anisotropic diffusion, such as skeletal muscle. The acquisition of DTI studies for skeletal muscle assessment requires specific technical adjustments. Besides, knowledge of DTI physical basis and skeletal muscle physiopathology facilitates the evaluation of this advanced sequence and both image and parameter interpretation. Parameters derived from DTI provide a quantitative assessment of muscle microstructure with potential to become imaging biomarkers of normal and pathological skeletal muscle. KEY POINTS: • Diffusion tensor imaging (DTI) allows to evaluate the three-dimensional movement of water molecules inside biological tissues. • The skeletal muscle structure makes it suitable for being evaluated with DTI. • Several technical adjustments have to be considered for obtaining robust and reproducible DTI studies for skeletal muscle assessment, minimizing potential artifacts.

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).

Systematic Dimensional Analysis of the Scaling Relationship for Gradient and Shim Coil Design Parameters

PURPOSE

To demonstrate systematic, linear algebra-based, dimensional analysis to derive a scaling relationship among the design parameters of MRI gradient and harmonic shim coils.

THEORY AND METHODS

The dimensions of five physical quantities relevant for gradient coil design (inductance, gradient amplitude, inner diameter [ d $$ d $$ ], current, and the permeability of free space) were decomposed into fundamental units, and their exponents were arranged into a dimensional matrix. The resulting set of homogenous equations was solved using standard linear algebraic methods. Inclusion of the number of turns as an additional unit yielded a 5 × 5 dimensional matrix with a unique, nontrivial solution. The analysis was extended to harmonic shim coils. The gradient coil scaling relationship was compared with data from 24 published gradient coil sets.

RESULTS

Only when the unit of turns was included did the linear algebra-based analysis uniquely produce the known scaling relationship that gradient inductance is proportional to gradient efficiency squared times d 5 $$ {d}^5 $$ . By applying the same methodology to an lth order shim coil, a novel result is obtained: Shim inductance is proportional to its efficiency squared times d 2 l + 3 $$ {d}^{2l+3} $$ . The predicted power-law relationship between inductance-normalized gradient efficiency and the diameter accounted for > 92% of the efficiency variation of the surveyed gradient coils. A dimensionless parameter is proposed as an intrinsic figure-of-merit of gradient coil efficiency.

CONCLUSION

Systematic application of linear algebra-based dimensional analysis can provide new insight in gradient and shim coil design by revealing fundamental scaling relations and helping to guide the design and comparison of coils with different diameters.

A New Phased-Array Magnetic Resonance Imaging Receive-Only Coil for HBO2 Studies

The paper describes a new magnetic resonance imaging (MRI) phased-array receive-only (Rx) coil for studying decompression sickness and disorders of hyperbaricity, including nitrogen narcosis. Functional magnetic resonance imaging (fMRI) is noninvasive, is considered safe, and may allow studying the brain under hyperbaric conditions. All of the risks associated with simultaneous MRI and HBO2 therapy are described in detail, along with all of the mitigation strategies and regulatory testing. One of the most significant risks for this type of study is a fire in the hyperbaric chamber caused by the sparking of the MRI coils as a result of high-voltage RF arcs. RF pulses at 128 MHz elicit signals from human tissues, and RF sparking occurs commonly and is considered safe in normobaric conditions. We describe how we built a coil for HBO2-MRI studies by modifying an eight-channel phased-array MRI coil with all of the mitigation strategies discussed. The coil was fabricated and tested with a unique testing platform that simulated the worst-case RF field of a three-Tesla MRI in a Hyperlite hyperbaric chamber at 3 atm pressure. The coil was also tested in normobaric conditions for image quality in a 3 T scanner in volunteers and SNR measurement in phantoms. Further studies are necessary to characterize the coil safety in HBO2/MRI.

Comparing patient acceptability of MR-guided radiotherapy to conventional CBCT on two Elekta systems: a questionnaire-based survey

Background and Purpose:

The magnetic resonance linear accelerator system (MR Linac) is a novel piece of radiotherapy (RT) equipment allowing the routine application of daily MR-guided treatment adaptation. The hardware design required for such technical capabilities and the increased complexity of the treatment workflow entails a notable departure from cone beam computed tomography (CBCT)-based RT. Patient tolerability of treatment is paramount to RT practice where high compliance is required. Presented is a comparative analysis of how such modality specific characteristics may ultimately impact the patient experience of treatment.

Materials and Methods:

Forty patients undergoing RT for prostate cancer (PCa) on either the MR Linac (n = 20) or a CBCT-based linac (n = 20) were provided with a validated patient reported outcomes measures (PROM’s) questionnaire at fraction 1 and fraction 20. The 18-item questionnaire provided patient responses recorded using a 4-point Likert scale, 0 denoting a response of ‘Not at all’, 1 ‘Slightly’, 2 ‘Moderately’ and 3 signifying ‘Very’. The analysis provided insight into both comparisons between modalities at singular time points (fractions 1 and 20), as well as a temporal analysis within a single modality, denoting changing patient experience.

Results:

Patients generally found the MR Linac treatment couch more comfortable, however, found the increase in treatment duration harder to tolerate. Responses for all items remained stable between first and last fraction across both cohorts, indicating minimal temporal variation within a single modality. None of the responses were statistically significant at the 0·01 level.

Conclusion:

Whether radiotherapy for PCa is delivered on a CBCT linac or the MR Linac, there is little difference in patient experience with minimal experiential variation within a single modality.

Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact

Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide - one in the United Kingdom in Cardiff, Wales, another in continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength diffusion MRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for diffusion MRI and where the field is headed in the coming years.

Physiological effects of human body imaging with 300 mT/m gradients

PURPOSE

The use of high-performance gradient systems (i.e., high gradient strength and/or high slew rate) for human MRI is limited by physiological effects (including the elicitation of magnetophosphenes and peripheral nerve stimulation (PNS)). These effects, in turn, depend on the interaction between time-varying magnetic fields and the body, and thus on the participant's position with respect to the scanner's isocenter. This study investigated the occurrence of magnetophosphenes and PNS when scanning participants on a high-gradient (300 mT/m) system, for different gradient amplitudes, ramp times, and participant positions.

METHODS

Using a whole-body 300 mT/m gradient MRI system, a cohort of participants was scanned with the head, heart, and prostate at magnet isocenter and a train of trapezoidal bipolar gradient pulses, with ramp times from 0.88 to 4.20 ms and gradient amplitudes from 60 to 300 mT/m. Reports of magnetophosphenes and incidental reports of PNS were obtained. A questionnaire was used to record any additional subjective effects.

RESULTS

Magnetophosphenes were strongly dependent on participant position in the scanner. 87% of participants reported the effect with the heart at isocenter, 33% with the head at isocenter, and only 7% with the prostate at isocenter. PNS was most widely reported by participants for the vertical gradient axis (67% of participants), and was the dominant physiological effect for ramp times below 2 ms.

CONCLUSION

This study evaluates the probability of eliciting magnetophosphenes during whole-body imaging using an ultra-strong gradient MRI system. It provides empirical guidance on the use of high-performance gradient systems for whole-body human MRI.

Magneto-stimulation limits in medical imaging applications with rapid field dynamics

Objective. The goal of this work is to extend previous peripheral nerve stimulation (PNS) studies to scenarios relevant to magnetic particle imaging (MPI) and low-field magnetic resonance imaging (MRI), where field dynamics can evolve at kilo-hertz frequencies. Approach. We have constructed an apparatus for PNS threshold determination on a subject’s limb, capable of narrow and broad-band magnetic stimulation with pulse characteristic times down to 40 μs. Main result. From a first set of measurements on 51 volunteers, we conclude that the PNS dependence on pulse frequency/rise-time is compatible with traditional stimulation models where nervous responses are characterized by a rheobase and a chronaxie. Additionally, we have extended pulse length studies to these fast timescales and confirm thresholds increase significantly as trains transition from tens to a few pulses. We also look at the influence of field spatial distribution on PNS effects, and find that thresholds are higher in an approximately linearly inhomogeneous field (relevant to MRI) than in a rather homogeneous distribution (as in MPI). Significance. PNS constrains the clinical performance of MRI and MPI systems. Extensive magneto-stimulation studies have been carried out recently in the field of MPI, where typical operation frequencies range from single to tens of kilo-hertz. However, PNS literature is scarce for MRI in this fast regime, relevant to small (low inductance) dedicated MRI setups, and where the resonant character of MPI coils prevents studies of broad-band stimulation pulses. This work advances in this direction.

A 31-channel integrated "AC/DC" B0 shim and radiofrequency receive array coil for improved 7T MRI

PURPOSE

To test an integrated "AC/DC" array approach at 7T, where B0 inhomogeneity poses an obstacle for functional imaging, diffusion-weighted MRI, MR spectroscopy, and other applications.

METHODS

A close-fitting 7T 31-channel (31-ch) brain array was constructed and tested using combined Rx and ΔB0 shim channels driven by a set of rapidly switchable current amplifiers. The coil was compared to a shape-matched 31-ch reference receive-only array for RF safety, signal-to-noise ratio (SNR), and inter-element noise correlation. We characterize the coil array's ability to provide global and dynamic (slice-optimized) shimming using ΔB0 field maps and echo planar imaging (EPI) acquisitions.

RESULTS

The SNR and average noise correlation were similar to the 31-ch reference array. Global and slice-optimized shimming provide 11% and 40% improvements respectively compared to baseline second-order spherical harmonic shimming. Birdcage transmit coil efficiency was similar for the reference and AC/DC array setups.

CONCLUSION

Adding ΔB0 shim capability to a 31-ch 7T receive array can significantly boost 7T brain B0 homogeneity without sacrificing the array's rdiofrequency performance, potentially improving ultra-high field neuroimaging applications that are vulnerable to off-resonance effects.

Exposure of Infants to Gradient Fields in a Baby MRI Scanner

In pediatric magnetic resonance imaging (MRI), infants are exposed to rapid, time-varying gradient magnetic fields, leading to electric fields induced in the body of infants and potential safety risks (e.g. peripheral nerve stimulation). In this numerical study, the in situ electric fields in infants induced by small-sized gradient coils for a 1.5 T MRI scanner were evaluated. The gradient coil set was specially designed for the efficient imaging of infants within a small-bore (baby) scanner. The magnetic flux density and induced electric fields by the small x, y, z gradient coils in an infant model (8-week-old with a mass of 4.3 kg) were computed using the scalar potential finite differences method. The gradient coils were driven by a 1 kHz sinusoidal waveform and also a trapezoidal waveform with a 250 µs rise time. The model was placed at different scan positions, including the head area (position I), chest area (position II), and body center (position III). It was found that the induced electric fields in most tissues exceeded the basic restrictions of the ICNIRP 2010 guidelines for both waveforms. The electric fields were similar in the region of interest for all coil types and model positions but different outside the imaging region. The y-coil induced larger electric fields compared with the x- and z- coils. © 2022 Bioelectromagnetics Society.

A Huygens' surface approach to rapid characterization of peripheral nerve stimulation

PURPOSE

Peripheral nerve stimulation (PNS) modeling has a potential role in designing and operating MRI gradient coils but requires computationally demanding simulations of electromagnetic fields and neural responses. We demonstrate compression of an electromagnetic and neurodynamic model into a single versatile PNS matrix (P-matrix) defined on an intermediary Huygens' surface to allow fast PNS characterization of arbitrary coil geometries and body positions.

METHODS

The Huygens' surface approach divides PNS prediction into an extensive pre-computation phase of the electromagnetic and neurodynamic responses, which is independent of coil geometry and patient position, and a fast coil-specific linear projection step connecting this information to a specific coil geometry. We validate the Huygens' approach by performing PNS characterizations for 21 body and head gradients and comparing them with full electromagnetic-neurodynamic modeling. We demonstrate the value of Huygens' surface-based PNS modeling by characterizing PNS-optimized coil windings for a wide range of patient positions and poses in two body models.

RESULTS

The PNS prediction using the Huygens' P-matrix takes less than a minute (instead of hours to days) without compromising numerical accuracy (error ≤ 0.1%) compared to the full simulation. Using this tool, we demonstrate that coils optimized for PNS at the brain landmark using a male model can also improve PNS for other imaging applications (cardiac, abdominal, pelvic, and knee imaging) in both male and female models.

CONCLUSION

Representing PNS information on a Huygens' surface extended the approach's ability to assess PNS across body positions and models and test the robustness of PNS optimization in gradient design.

Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome

The first phase of the Human Connectome Project pioneered advances in MRI technology for mapping the macroscopic structural connections of the living human brain through the engineering of a whole-body human MRI scanner equipped with maximum gradient strength of 300 mT/m, the highest ever achieved for human imaging. While this instrument has made important contributions to the understanding of macroscale connectional topology, it has also demonstrated the potential of dedicated high-gradient performance scanners to provide unparalleled in vivo assessment of neural tissue microstructure. Building on the initial groundwork laid by the original Connectome scanner, we have now embarked on an international, multi-site effort to build the next-generation human 3T Connectome scanner (Connectome 2.0) optimized for the study of neural tissue microstructure and connectional anatomy across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current maximum gradient strength from 300 mT/m to 500 mT/m and tripling the maximum slew rate from 200 T/m/s to 600 T/m/s through the design of a one-of-a-kind head gradient coil optimized to minimize peripheral nerve stimulation; (2) developing high-sensitivity multi-channel radiofrequency receive coils for in vivo and ex vivo human brain imaging; (3) incorporating dynamic field monitoring to minimize image distortions and artifacts; (4) developing new pulse sequences to integrate the strongest diffusion encoding and highest spatial resolution ever achieved in the living human brain; and (5) calibrating the measurements obtained from this next-generation instrument through systematic validation of diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales with accompanying diffusion simulations in histology-based micro-geometries. We envision creating the ultimate diffusion MRI instrument capable of capturing the complex multi-scale organization of the living human brain - from the microscopic scale needed to probe cellular geometry, heterogeneity and plasticity, to the mesoscopic scale for quantifying the distinctions in cortical structure and connectivity that define cyto- and myeloarchitectonic boundaries, to improvements in estimates of macroscopic connectivity.

Occupational exposure to electromagnetic fields in magnetic resonance environment: an update on regulation, exposure assessment techniques, health risk evaluation, and surveillance

Magnetic resonance imaging (MRI) is one of the most-used diagnostic imaging methods worldwide. There are ∼50,000 MRI scanners worldwide each of which involves a minimum of five workers from different disciplines who spend their working days around MRI scanners. This review analyzes the state of the art of literature about the several aspects of the occupational exposure to electromagnetic fields (EMF) in MRI: regulations, literature studies on biological effects, and health surveillance are addressed here in detail, along with a summary of the main approaches for exposure assessment. The original research papers published from 2013 to 2021 in international peer-reviewed journals, in the English language, are analyzed, together with documents published by legislative bodies. The key points for each topic are identified and described together with useful tips for precise safeguarding of MRI operators, in terms of exposure assessment, studies on biological effects, and health surveillance.

Advances in resting state fMRI acquisitions for functional connectomics

Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.

MRI with ultrahigh field strength and high-performance gradients: challenges and opportunities for clinical neuroimaging at 7 T and beyond

Research in ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology has provided enormous gains in sensitivity, resolution, and contrast for neuroimaging. This article provides an overview of the technical advantages and challenges of performing clinical neuroimaging studies at ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology. Emerging clinical applications of 7-T MRI and state-of-the-art gradient systems equipped with up to 300 mT/m gradient strength are reviewed, and the impact and benefits of such advances to anatomical, structural and functional MRI are discussed in a variety of neurological conditions. Finally, an outlook and future directions for ultrahigh field MRI combined with ultrahigh and ultrafast gradient technology in neuroimaging are examined.

Minimum electric-field gradient coil design: Theoretical limits and practical guidelines

PURPOSE

To develop new concepts for minimum electric-field (E-field) gradient design, and to define the extents to which E-field can be reduced in gradient design while maintaining a desired imaging performance.

METHODS

Efficient calculation of induced electric field in simplified patient models was integrated into gradient design software, allowing constraints to be placed on the peak E-field. Gradient coils confined to various build envelopes were designed with minimum E-fields subject to standard magnetic field constraints. We examined the characteristics of E-field-constrained gradients designed for imaging the head and body and the importance of asymmetry and concomitant fields in achieving these solutions.

RESULTS

For transverse gradients, symmetric solutions create high levels of E-fields in the shoulder region, while fully asymmetric solutions create high E-fields on the top of the head. Partially asymmetric solutions result in the lowest E-fields, balanced between shoulders and head and resulting in factors of 1.8 to 2.8 reduction in E-field for x-gradient and y-gradient coils, respectively, when compared with the symmetric designs of identical gradient distortion.

CONCLUSIONS

We introduce a generalized method for minimum E-field gradient design and define the theoretical limits of magnetic energy and peak E-field for gradient coils of arbitrary cylindrical geometry.

Electric field calculation and peripheral nerve stimulation prediction for head and body gradient coils

PURPOSE

To demonstrate and validate electric field (E-field) calculation and peripheral nerve stimulation (PNS) prediction methods that are accurate, computationally efficient, and that could be used to inform regulatory standards.

METHODS

We describe a simplified method for calculating the spatial distribution of induced E-field over the volume of a body model given a gradient coil vector potential field. The method is easily programmed without finite element or finite difference software, allowing for straightforward and computationally efficient E-field evaluation. Using these E-field calculations and a range of body models, population-weighted PNS thresholds are determined using established methods and compared against published experimental PNS data for two head gradient coils and one body gradient coil.

RESULTS

A head-gradient-appropriate chronaxie value of 669 µs was determined by meta-analysis. Prediction errors between our calculated PNS parameters and the corresponding experimentally measured values were ~5% for the body gradient and ~20% for the symmetric head gradient. Our calculated PNS parameters matched experimental measurements to within experimental uncertainty for 73% of ∆G_min estimates and 80% of SR_min estimates. Computation time is seconds for initial E-field maps and milliseconds for E-field updates for different gradient designs, allowing for highly efficient iterative optimization of gradient designs and enabling new dimensions in PNS-optimal gradient design.

CONCLUSIONS

We have developed accurate and computationally efficient methods for prospectively determining PNS limits, with specific application to head gradient coils.

Influence of MRI Examinations on Animal Welfare and Study Results

OBJECTIVES

Magnetic resonance imaging (MRI) is considered to be well tolerated by laboratory animals. However, no systematic study has been performed yet, proving this assumption. Therefore, the aim of this study was to investigate the possible effects of longitudinal native and contrast-enhanced (CE) 1-T and 7-T MRI examinations on mouse welfare as well as 4T1 breast cancers progression and therapy response.

MATERIAL AND METHODS

Forty-seven healthy and 72 breast cancer-bearing mice (4T1) were investigated. One-Tesla (ICON) and 7-T (Biospec) MRI measurements were performed thrice per week under isoflurane anesthesia in healthy BALB/c mice for 4 weeks and 3 times within 2 weeks in tumor-bearing animals. Animal welfare was examined by an observational score sheet, rotarod performance, heart rate measurements, and assessment of fecal corticosterone metabolites. Furthermore, we investigated whether CE-MRI influences the study outcome. Therefore, hemograms and organ weights were obtained, and 4T1 tumor growth, perfusion, immune cell infiltration, as well as response to the multikinase inhibitor regorafenib were investigated. Statistical comparisons between groups were performed using analysis of variance and Tukey or Bonferroni post hoc tests.

RESULTS

Mice showed no alterations in the observational score sheet rating, rotarod performance, heart rate, and fecal corticosterone metabolites (P > 0.05) after repeated MRI at both field strengths. However, spleen weights were reduced in all healthy mouse groups that received isoflurane anesthesia (P < 0.001) including the groups investigated by 1-T and 7-T MRI (P = 0.02). Neither tumor progression nor response to the regorafenib treatment was affected by isoflurane anesthesia or CE-MRI monitoring. Furthermore, immunohistological tumor analysis did not indicate an effect of isoflurane and MRI on macrophage infiltration of tumors, perfusion of tumor vessels, and apoptotic cell rate (P > 0.05).

CONCLUSIONS

Repeated MRI did not influence the welfare of mice and did not affect tumor growth and therapy response of 4T1 tumors. However, systemic immunological effects of isoflurane anesthesia need to be considered to prevent potential bias.

Gradient waveform design for tensor-valued encoding in diffusion MRI

Diffusion encoding along multiple spatial directions per signal acquisition can be described in terms of a b-tensor. The benefit of tensor-valued diffusion encoding is that it unlocks the 'shape of the b-tensor' as a new encoding dimension. By modulating the b-tensor shape, we can control the sensitivity to microscopic diffusion anisotropy which can be used as a contrast mechanism; a feature that is inaccessible by conventional diffusion encoding. Since imaging methods based on tensor-valued diffusion encoding are finding an increasing number of applications we are prompted to highlight the challenge of designing the optimal gradient waveforms for any given application. In this review, we first establish the basic design objectives in creating field gradient waveforms for tensor-valued diffusion MRI. We also survey additional design considerations related to limitations imposed by hardware and physiology, potential confounding effects that cannot be captured by the b-tensor, and artifacts related to the diffusion encoding waveform. Throughout, we discuss the expected compromises and tradeoffs with an aim to establish a more complete understanding of gradient waveform design and its impact on accurate measurements and interpretations of data.

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.

New acquisition techniques and their prospects for the achievable resolution of fMRI

This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent progress in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.

MR Imaging Safety in the Interventional Environment

Interventional MR imaging procedures are rapidly growing in number owing to the excellent soft tissue resolution of MR imaging, lack of ionizing radiation, hardware and software advancements, and technical developments in MR imaging-compatible robots, lasers, and ultrasound equipment. The safe operation of an interventional MR imaging system is a complex undertaking, which is only possible with multidisciplinary planning, training, operations and oversight. Safety for both patients and operators is essential for successful operations. Herein, we review the safety concerns, solutions and challenges associated with the operation of a modern interventional MR imaging system.

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.

A half-century of innovation in technology-preparing MRI for the 21st century

MRI developed during the last half-century from a very basic concept to an indispensable non-ionising medical imaging technique that has found broad application in diagnostics, therapy control and far beyond. Due to its excellent soft-tissue contrast and the huge variety of accessible tissue- and physiological-parameters, MRI is often preferred to other existing modalities. In the course of its development, MRI underwent many substantial transformations. From the beginning, starting as a proof of concept, much effort was expended to develop the appropriate basic scanning technology and methodology, and to establish the many clinical contrasts (e.g., T₁, T₂, flow, diffusion, water/fat, etc.) that MRI is famous for today. Beyond that, additional prominent innovations to the field have been parallel imaging and compressed sensing, leading to significant scanning time reductions, and the move towards higher static magnetic field strengths, which led to increased sensitivity and improved image quality. Improvements in workflow and the use of artificial intelligence are among many current trends seen in this field, paving the way for a broad use of MRI. The 125th anniversary of the BJR is a good point to reflect on all these changes and developments and to offer some slightly speculative ideas as to what the future may bring.

Technological Advances of Magnetic Resonance Imaging in Today's Health Care Environment

Today's health care environment is shifting rapidly, driven by demographic change and high economic pressures on the system. Furthermore, modern precision medicine requires highly accurate and specific disease diagnostics in a short amount of time. Future imaging technology must adapt to these challenges.Demographic change necessitates scanner technologies tailored to the needs of an aging and increasingly multimorbid patient population. Accordingly, examination times have to be short enough that diagnostic images can be generated even for patients who can only lie in the scanner for a short time because of pain or with low breath-hold capacity.For economic reasons, the rate of nondiagnostic scans due to artifacts should be reduced as far as possible. As imaging plays an increasingly pivotal role in clinical-therapeutic decision making, magnetic resonance (MR) imaging facilities are confronted with an ever-growing number of patients, emphasizing the need for faster acquisitions while maintaining image quality.Lastly, modern precision medicine requires high and standardized image quality as well as quantifiable data in order to develop image-based biomarkers on which subsequent treatment management can rely.In recent decades, a variety of approaches have addressed the challenges of high throughput, demographic change, and precision medicine in MR imaging. These include field strength, gradient, coil and sequence development, as well as an increasing consideration of artificial intelligence. This article reviews state-of-the art MR technology and discusses future implementation from the perspective of what we know today.

Predicting in vivo MRI Gradient-Field Induced Voltage Levels on Implanted Deep Brain Stimulation Systems Using Neural Networks

Introduction

MRI gradient-fields may induce extrinsic voltage between electrodes and conductive neurostimulator enclosure of implanted deep brain stimulation (DBS) systems, and may cause unintended stimulation and/or malfunction. Electromagnetic (EM) simulations using detailed anatomical human models, therapy implant trajectories, and gradient coil models can be used to calculate clinically relevant induced voltage levels. Incorporating additional anatomical human models into the EM simulation library can help to achieve more clinically relevant and accurate induced voltage levels, however, adding new anatomical human models and developing implant trajectories is time-consuming, expensive and not always feasible.

Methods

MRI gradient-field induced voltage levels are simulated in six adult human anatomical models, along clinically relevant DBS implant trajectories to generate the dataset. Predictive artificial neural network (ANN) regression models are trained on the simulated dataset. Leave-one-out cross validation is performed to assess the performance of ANN regressors and quantify model prediction errors.

Results

More than 180,000 unique gradient-induced voltage levels are simulated. ANN algorithm with two fully connected layers is selected due to its superior generalizability compared to support vector machine and tree-based algorithms in this particular application. The ANN regression model is capable of producing thousands of gradient-induced voltage predictions in less than a second with mean-squared-error less than 200 mV.

Conclusion

We have integrated machine learning (ML) with computational modeling and simulations and developed an accurate predictive model to determine MRI gradient-field induced voltage levels on implanted DBS systems.

Oscillating diffusion-encoding with a high gradient-amplitude and high slew-rate head-only gradient for human brain imaging

PURPOSE

We investigate the importance of high gradient-amplitude and high slew-rate on oscillating gradient spin echo (OGSE) diffusion imaging for human brain imaging and evaluate human brain imaging with OGSE on the MAGNUS head-gradient insert (200 mT/m amplitude and 500 T/m/s slew rate).

METHODS

Simulations with cosine-modulated and trapezoidal-cosine OGSE at various gradient amplitudes and slew rates were performed. Six healthy subjects were imaged with the MAGNUS gradient at 3T with OGSE at frequencies up to 100 Hz and b = 450 s/mm² . Comparisons were made against standard pulsed gradient spin echo (PGSE) diffusion in vivo and in an isotropic diffusion phantom.

RESULTS

Simulations show that to achieve high frequency and b-value simultaneously for OGSE, high gradient amplitude, high slew rates, and high peripheral nerve stimulation limits are required. A strong linear trend for increased diffusivity (mean: 8-19%, radial: 9-27%, parallel: 8-15%) was observed in normal white matter with OGSE (20 Hz to 100 Hz) as compared to PGSE. Linear fitting to frequency provided excellent correlation, and using a short-range disorder model provided radial long-term diffusivities of D_∞,MD = 911 ± 72 µm² /s, D_∞,PD = 1519 ± 164 µm² /s, and D_∞,RD = 640 ± 111 µm² /s and correlation lengths of l_{c ,MD} = 0.802 ± 0.156 µm, l_{c ,PD} = 0.837 ± 0.172 µm, and l_{c ,RD} = 0.780 ± 0.174 µm. Diffusivity changes with OGSE frequency were negligible in the phantom, as expected.

CONCLUSION

The high gradient amplitude, high slew rate, and high peripheral nerve stimulation thresholds of the MAGNUS head-gradient enables OGSE acquisition for in vivo human brain imaging.

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.

Peripheral nerve stimulation limits of a high amplitude and slew rate magnetic field gradient coil for neuroimaging

PURPOSE

To establish peripheral nerve stimulation (PNS) thresholds for an ultra-high performance magnetic field gradient subsystem (simultaneous 200-mT/m gradient amplitude and 500-T/m/s gradient slew rate; 1 MVA per axis [MAGNUS]) designed for neuroimaging with asymmetric transverse gradients and 42-cm inner diameter, and to determine PNS threshold dependencies on gender, age, patient positioning within the gradient subsystem, and anatomical landmarks.

METHODS

The MAGNUS head gradient was installed in a whole-body 3T scanner with a custom 16-rung bird-cage transmit/receive RF coil compatible with phased-array receiver brain coils. Twenty adult subjects (10 male, mean ± SD age = 40.4 ± 11.1 years) underwent the imaging and PNS study. The tests were repeated by displacing subject positions by 2-4 cm in the superior-inferior and anterior-posterior directions.

RESULTS

The x-axis (left-right) yielded mostly facial stimulation, with mean ΔG_min = 111 ± 6 mT/m, chronaxie = 766 ± 76 µsec. The z-axis (superior-inferior) yielded mostly chest/shoulder stimulation (123 ± 7 mT/m, 620 ± 62 µsec). Y-axis (anterior-posterior) stimulation was negligible. X-axis and z-axis thresholds tended to increase with age, and there was negligible dependency with gender. Translation in the inferior and posterior directions tended to increase the x-axis and z-axis thresholds, respectively. Electric field simulations showed good agreement with the PNS results. Imaging at MAGNUS gradient performance with increased PNS threshold provided a 35% reduction in noise-to-diffusion contrast as compared with whole-body performance (80 mT/m gradient amplitude, 200 T/m/sec gradient slew rate).

CONCLUSION

The PNS threshold of MAGNUS is significantly higher than that for whole-body gradients, which allows for diffusion gradients with short rise times (under 1 msec), important for interrogating brain microstructure length scales.

Short-term effects experienced during examinations in an actively shielded 7 T MR

The objective of this study was to evaluate occurrence and strength of short-term effects experienced by study participants in an actively shielded (AS) 7 tesla (7 T) magnetic resonance (MR) scanner, to compare results with earlier reports on passively shielded (PS) 7 T MR scanners, and to outline possible healthcare strategies to improve patient compliance. Study participants (n = 124) completed a web-based questionnaire directly after being examined in an AS 7 T MR (n = 154 examinations). Most frequently experienced short-term effects were dizziness (84%) and inconsistent movement (70%), especially while moving into or out of the magnet. Peripheral nerve stimulation (PNS)-twitching-was experienced in 67% of research examinations and showed a dependence between strength of twitches and recorded predicted PNS values. Of the participants, 74% experienced noise levels as acceptable and the majority experienced body and room temperature as comfortable. Of the study participants, 95% felt well-informed and felt they had had good contact with the staff before the examination. Willingness to undergo a future 7 T examination was high (>90%). Our study concludes short-term effects are often experienced during examinations in an AS 7 T MR, leaving room for improvement in nursing care strategies to increase patient compliance. Bioelectromagnetics. 2019;9999:XX-XX. © 2019 The Authors. Bioelectromagnetics Published by Wiley Periodicals, Inc.

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.