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.

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.

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.

Maintaining Image Quality While Reducing Acoustic Noise and Switched Gradient Field Exposure During Lumbar MRI

BACKGROUND

MR-generated acoustic noise can contribute to patient discomfort and potentially be harmful. One way to reduce this noise is by altering the gradient output and/or waveform using software optimization. Such modifications might influence image quality and switched gradient field exposure, and different techniques appear to affect sound pressure levels (SPLs) to various degrees.

PURPOSE

To evaluate SPLs, image quality, switched gradient field exposure, and participants' perceived noise levels during two different acoustic noise reduction (ANR) techniques, Quiet Suite (QS) and Whisper Mode (WM), and to compare them with conventional T2-weighted turbo spin echo (T2W TSE) of the lumbar spine.

DESIGN

Prospective.

SUBJECTS

Forty adults referred for lumbar MRI.

FIELD STRENGTH/SEQUENCE

Conventional T2W TSE, T2W TSE with QS, and T2W TSE with WM were acquired at 1.5 T.

ASSESSMENT

Peak SPL (A-weighted decibels, dBA), perceived noise levels (Borg CR10®-scale), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), three radiologists' qualitative assessments in image quality on an ordinal scale 1-4, switched gradient field exposure (% general public), and gradient currents were measured. Interobserver reliability was reported as percentage agreement.

STATISTICAL TESTS

Repeated measures ANOVA, Friedman's ANOVA, and Wilcoxon's Signed-Rank Test for acoustic noise measurements and image quality assessments.

RESULTS

Mean peak SPLs were 89.9 dBA, 74.3 dBA, and 78.8 dBA for conventional, QS, and WM, respectively (P < 0.05). Participants perceived QS as the quietest and conventional as the loudest sequence (P < 0.05). No qualitative differences in image quality were seen (P > 0.05), although QS showed significantly improved SNR and CNR (P < 0.05). Switched gradient field exposure was reduced by 66% and 48% for QS and WM, respectively.

DATA CONCLUSION

Without degrading image quality, both QS and WM are viable ANR techniques in lumbar T2W TSE. QS provided the lowest SPL, the lowest gradient field exposure and was perceived as the most silent among the three sequences.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 5.

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.

A gradient optimization toolbox for general purpose time-optimal MRI gradient waveform design

Purpose

To introduce and demonstrate a software library for time‐optimal gradient waveform optimization with a wide range of applications. The software enables direct on‐the‐fly gradient waveform design on the scanner hardware for multiple vendors.

Methods

The open‐source gradient optimization (GrOpt) toolbox was implemented in C with both Matlab and Python wrappers. The toolbox enables gradient waveforms to be generated based on a set of constraints that define the features and encodings for a given acquisition. The GrOpt optimization routine is based on the alternating direction method of multipliers (ADMM). Additional constraints enable error corrections to be added, or patient comfort and safety to be adressed. A range of applications and compute speed metrics are analyzed. Finally, the method is implemented and tested on scanners from different vendors.

Results

Time‐optimal gradient waveforms for different pulse sequences and the constraints that define them are shown. Additionally, the ability to add, arbitrary motion (gradient moment) compensation or limit peripheral nerve stimulation is demonstrated. There exists a trade‐off between computation time and gradient raster time, but it was observed that acceptable gradient waveforms could be generated in 1‐40 ms. Gradient waveforms generated and run on the different scanners were functionally equivalent, and the images were comparable.

Conclusions

GrOpt is an open source toolbox that enables on‐the‐fly optimization of gradient waveform design, subject to a set of defined constraints. GrOpt was presented for a range of imaging applications, analyzed in terms of computational complexity, and implemented to run on the scanner for a multi‐vendor demonstration.

Optimization methods for magnetic resonance imaging gradient waveform design

The development and implementation of novel MRI pulse sequences remains challenging and laborious. Gradient waveforms are typically designed using a combination of analytical and ad hoc methods to construct each gradient waveform axis independently. This strategy makes coding the pulse sequence complicated, in addition to being time inefficient. As a consequence, nearly all commercial MRI pulse sequences fail to maximize use of the available gradient hardware or efficiently mitigate physiological effects. This results in expensive MRI systems that underperform relative to their inherent hardware capabilities. To address this problem, a software solution is proposed that incorporates numerical optimization methods into MRI pulse sequence programming. Examples are shown for rotational variant vs. invariant waveform designs, acceleration nulled velocity encoding gradients, and mitigation of peripheral nerve stimulation for diffusion encoding. The application of optimization methods to MRI pulse sequence design incorporates gradient hardware limits and the prescribed MRI protocol parameters (e.g. field-of-view, resolution, gradient moments, and/or b-value) to simultaneously construct time-optimal gradient waveforms. In many cases, the resulting constrained gradient waveform design problem is convex and can be solved on-the-fly on the MRI scanner. The result is a set of multi-axis time-optimal gradient waveforms that satisfy the design constraints, thereby increasing SNR-efficiency. These optimization methods can also be used to mitigate imaging artifacts (e.g. eddy currents) or account for peripheral nerve stimulation. The result of the optimization method is to enable easier pulse sequence gradient waveform design and permit on-the-fly implementation for a range of MRI pulse sequences.

Reducing PNS with minimal performance penalties via simple pulse sequence modifications on a high-performance compact 3T scanner

One of the major concerns associated with high-performance gradients is peripheral nerve stimulation (PNS) of the subject during MRI exams. Since the installation, more than 680 volunteer subjects (patients and controls) have been scanned on a compact 3 T MRI system with high-performance gradients, capable of 80 mT m^-1 gradient amplitude and 700 T m^-1 s^-1 slew rate simultaneously. Despite PNS concerns associated with the high-performance gradients, due to the smaller physical dimensions of the gradient coils, minimal or no PNS sensation was reported with most pulse sequences. The exception was PNS reported by only five of 252 subjects (about 2%) scanned with a specific 3D fast spin echo pulse sequence (3DFLAIR). Rather than derating the entire system performance across all pulse sequences and all gradient lobes, we addressed reported PNS effect with a simple and specific modification to the targeted lobes of the problematic pulse sequence. in addition, the PNS convolutional model was adapted to predict sequence-specific PNS threshold level and its reduction after derating. The effectiveness of the targeted pulse sequence modification was demonstrated by successfully re-scanning four of the subjects who previously reported PNS sensations without further reported PNS. The pulse sequence modification did not result in noticeable degradation of image quality or substantial increase in scan time. The results demonstrated that PNS was rarely reported on the compact 3 T, and when it was, utilizing a specific modification of the gradient waveform causing PNS was an effective strategy, rather than derating the performance of the entire gradient system.

UTE-SPECIAL for3D localization at an echo time of 4 ms on a clinical 3 T scanner

Reducing the echo time of magnetic resonance spectroscopy experiments is appealing because it increases the available signal and reduces J-evolution of coupled metabolites. In this manuscript a novel sequence, referred to as Ultrashort echo TimE, SPin ECho, full Intensity Acquired Localized (UTE-SPECIAL), is described which is able to achieve ultrashort echo times (4 ms) on a standard clinical 3 T MR system while recovering the entirety of the available magnetization. UTE-SPECIAL obtains full 3D spatial localization through a 2D adiabatic inversion pulse which is cycled "on" and "off" every other repetition, in combination with a slice-selective excitation pulse. In addition to an ultrashort echo time, UTE-SPECIAL has negligible chemical shift displacement artefact and, because it uses no slice-selective refocusing pulse, has no signal cancellation at the borders for J-coupled metabolites. Spectra with an ultrashort echo time of 4 ms are demonstrated in vivo at 3 T, as well as J-resolved spectra obtained in a phantom and a healthy volunteer.

Magnetic Resonance Examinations of Patients With Implanted Active Devices. A Low-Cost Approach in Slew Rate Evaluation

Time-varying magnetic field gradients involved in magnetic resonance examinations can damage implanted electronic systems. The quantity related to this side effect is the gradient slew rate, which is usually not directly available on magnetic resonance console. The present study proposes a low-cost approach in slew rate assessment, which is useful in risks versus benefits evaluation as well as in sequences optimization. The experimental method is based on an analog circuit, which senses the output voltage of the scanner waveform generator. This allows taking easy and reliable slew rate measurements, even during clinical examinations on patients. Whereas previous studies required managing a considerable amount of data, the present work addresses only the maximal slew rate of any clinical sequence. Experimental results show that the smooth gradient mode, selectable on the two scanners examined, is very effective in patient safety improvement. In particular, it reduces slew rate values in the range from 52.4 up to 132.4 T m^-1 s^-1 , i.e. far below the interval 216-346 T m^-1 s^-1 , indicated as slew rate tolerance limit of modern implanted electronic devices. Bioelectromagnetics. 2019;40:512-521. © 2019 Bioelectromagnetics Society.

Optimized Diffusion-Weighting Gradient Waveform Design (ODGD) formulation for motion compensation and concomitant gradient nulling

PURPOSE

To present a novel Optimized Diffusion-weighting Gradient waveform Design (ODGD) method for the design of minimum echo time (TE), bulk motion-compensated, and concomitant gradient (CG)-nulling waveforms for diffusion MRI.

METHODS

ODGD motion-compensated waveforms were designed for various moment-nullings M_n (n = 0, 1, 2), for a range of b-values, and spatial resolutions, both without (ODGD-M_n ) and with CG-nulling (ODGD-M_n -CG). Phantom and in-vivo (brain and liver) experiments were conducted with various ODGD waveforms to compare motion robustness, signal-to-noise ratio (SNR), and apparent diffusion coefficient (ADC) maps with state-of-the-art waveforms.

RESULTS

ODGD-M_n and ODGD-M_n -CG waveforms reduced the TE of state-of-the-art waveforms. This TE reduction resulted in significantly higher SNR (P < 0.05) in both phantom and in-vivo experiments. ODGD-M₁ improved the SNR of BIPOLAR (42.8 ± 5.3 vs. 32.9 ± 3.3) in the brain, and ODGD-M₂ the SNR of motion-compensated (MOCO) and Convex Optimized Diffusion Encoding-M₂ (CODE-M₂ ) (12.3 ± 3.6 vs. 9.7 ± 2.9 and 10.2 ± 3.4, respectively) in the liver. Further, ODGD-M₂ also showed excellent motion robustness in the liver. ODGD-M_n -CG waveforms reduced the CG-related dephasing effects of non CG-nulling waveforms in phantom and in-vivo experiments, resulting in accurate ADC maps.

CONCLUSIONS

ODGD waveforms enable motion-robust diffusion MRI with reduced TEs, increased SNR, and reduced ADC bias compared to state-of-the-art waveforms in theoretical results, simulations, phantoms and in-vivo experiments.

Dephasing optimization through coherence order pathway selection (DOTCOPS) for improved crusher schemes in MR spectroscopy

PURPOSE

To develop an algorithm which can robustly eliminate all unwanted coherence pathways for an arbitrary magnetic resonance spectroscopy experiment through the adjustment of the relative amplitudes of crusher gradients, thereby reducing the effects of spurious echoes and mislocalization.

THEORY AND METHODS

The effect of crushing gradients for all coherence pathways was modeled according to the associated physics, and a cost function was optimized which maximally crushes all unwanted coherence pathways, while unaffecting the desired coherence pathway(s). The efficacy of the method was tested versus literature schemes from 2 separate MR spectroscopy (MRS) sequences: sLASER and MEGA-sLASER with both phantom and in vivo experiments.

RESULTS

Improved crushing power for 2 separate MRS sequences was demonstrated for 2 crushing schemes adopted from the literature in both phantom and in vivo data.

CONCLUSION

A novel algorithm and associated software was developed based on rigorous treatment of all coherence pathways, which can be applied to any arbitrary magnetic resonance spectroscopic pulse sequence of interest and any arbitrary coupled spin system. This developed method solves a long-standing problem in in vivo MRS and is expected to critically improve the data quality of virtually all MRS applications.

Magnetic resonance examination of patients with implanted pacemakers: An evaluation of magnetic field gradients slew rate

Performing safe magnetic resonance imaging of patients with "MR conditional" pacemakers needs to meet some specific restrictions. One of these is related to the slew rate (SR) parameter, defined as the speed of magnetic field gradients rising up to their required strengths. Unfortunately, SR values cannot be easily checked at the tomograph console. The present work provides an accurate evaluation of the maximum SR for a set of widely used clinical MR sequences. The experimental approach is based on indirect measurement of time-varying spatial magnetic field gradients. All MR sequences evaluated match safety SR prescriptions. Moreover, an appropriate choice of sequence scan parameters defines some optimized scan protocols tailored for the tomograph considered in the present study. Bioelectromagnetics. 38:307-314, 2017. © 2017 Wiley Periodicals, Inc.

Convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo time and bulk motion-compensated diffusion-weighted MRI

PURPOSE

To evaluate convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo time and bulk motion-compensated diffusion-weighted imaging (DWI).

METHODS

Diffusion-encoding gradient waveforms were designed for a range of b-values and spatial resolutions with and without motion compensation using the CODE framework. CODE, first moment (M₁ ) nulled CODE-M₁ , and first and second moment (M₂ ) nulled CODE-M₁ M₂ were used to acquire neuro, liver, and cardiac ADC maps in healthy subjects (n=10) that were compared respectively to monopolar (MONO), BIPOLAR (M₁  = 0), and motion-compensated (MOCO, M₁  + M₂  = 0) diffusion encoding.

RESULTS

CODE significantly improved the SNR of neuro ADC maps compared with MONO (19.5 ± 2.5 versus 14.5 ± 1.9). CODE-M₁ liver ADCs were significantly lower (1.3 ± 0.1 versus 1.8 ± 0.3 × 10^-3 mm² /s, ie, less motion corrupted) and more spatially uniform (6% versus 55% ROI difference) than MONO and had higher SNR than BIPOLAR (SNR = 14.9 ± 5.3 versus 8.0 ± 3.1). CODE-M₁ M₂ cardiac ADCs were significantly lower than MONO (1.9 ± 0.6 versus 3.8 ± 0.3 x10^-3 mm² /s) throughout the cardiac cycle and had higher SNR than MOCO at systole (9.1 ± 3.9 versus 7.0 ± 2.6) while reporting similar ADCs (1.5 ± 0.2 versus 1.4 ± 0.6 × 10^-3 mm² /s).

CONCLUSIONS

CODE significantly improved SNR for ADC mapping in the brain, liver and heart, and significantly improved DWI bulk motion robustness in the liver and heart. Magn Reson Med 77:717-729, 2017. © 2016 International Society for Magnetic Resonance in Medicine.