Gradient Waveforms Research Articles

Phase stabilization with motion compensated diffusion weighted imaging.

Diffusion encoding gradient waveforms can impart intra-voxel and inter-voxel dephasing owing to bulk motion, limiting achievable signal-to-noise and complicating multishot acquisitions. In this study, we characterize improvements in phase consistency via gradient moment nulling of diffusion encoding waveforms. Healthy volunteers received neuro ( ) and cardiac ( ) MRI. Three gradient moment nulling levels were evaluated: compensation for position ( ), position + velocity ( ), and position + velocity + acceleration ( ). Three experiments were completed: (Exp-1) Fixed Trigger Delay Neuro DWI; (Exp-2) Mixed Trigger Delay Neuro DWI; and (Exp-3) Fixed Trigger Delay Cardiac DWI. Significant differences ( ) of the temporal phase SD between repeated acquisitions and the spatial phase gradient across a given image were assessed. moment nulling was a reference for all measures. In Exp-1, temporal phase SD for diffusion encoding was significantly reduced with (35% of t-tests) and (68% of t-tests). The spatial phase gradient was reduced in 23% of t-tests for and 2% of cases for . In Exp-2, temporal phase SD significantly decreased with gradient moment nulling only for (83% of t-tests), but spatial phase gradient significantly decreased with only (50% of t-tests). In Exp-3, gradient moment nulling significantly reduced temporal phase SD and spatial phase gradients (100% of t-tests), resulting in less signal attenuation and more accurate ADCs. We characterized gradient moment nulling phase consistency for DWI. Using M1 for neuroimaging and M1 + M2 for cardiac imaging minimized temporal phase SDs and spatial phase gradients.

In vivo rat brain mapping of multiple gray matter water populations using nonparametric D(ω)-R1-R2 distributions MRI.

Massively multidimensional diffusion magnetic resonance imaging combines tensor-valued encoding, oscillating gradients, and diffusion-relaxation correlation to provide multicomponent subvoxel parameters depicting some tissue microstructural features. This method was successfully implemented ex vivo in microimaging systems and clinical conditions with tensor-valued gradient waveform of variable duration giving access to a narrow diffusion frequency (ω) range. We demonstrate here its preclinical in vivo implementation with a protocol of 389 contrast images probing a wide diffusion frequency range of 18 to 92 Hz at b-values up to 2.1ms/μm2 enabled by the use of modulated gradient waveforms and combined with multislice high-resolution and low-distortion echo planar imaging acquisition with segmented and full reversed phase-encode acquisition. This framework allows the identification of diffusion ω-dependence in the rat cerebellum and olfactory bulb gray matter (GM), and the parameter distributions are shown to resolve two water pools in the cerebellum GM with different diffusion coefficients, shapes, ω-dependence, relaxation rates, and spatial repartition whose attribution to specific microstructure could modify the current understanding of the origin of restriction in GM.

Phase contrast MRI with minimized background phase errors.

Phase contrast MRI (PC-MRI) is used clinically to measure velocities in the body, but systematic background phase errors caused by magnetic field imperfections corrupt the velocity measurements with offsets that limit clinical utility. This work aims to minimize systematic background phase errors in PC-MRI, thereby maximizing the accuracy of velocity measurements. The MRI scanner's background phase errors from eddy currents and mechanical oscillations were modeled using the gradient impulse response function (GIRF). Gradient waveforms were then numerically optimized using the GIRF to create pulse sequences that minimize the background phase errors. The pulse sequences were tested in a static phantom where the predicted response could be compared directly to the measured background velocity. The optimized acquisitions were then tested in human subjects, where flow rates and background errors were compared to conventional PC-MRI. When using the GIRF-optimized gradient waveforms, the predicted background phase was within 0.6 [95% CI = -3.4, 5.4] mm/s of the measured background phase in a static phantom. Excellent agreement was seen for in vivo blood flow values (flow rate agreement = 0.96), and the background phase was reduced by 78.8 18.7%. This work shows that using a GIRF to model the effects of magnetic field imperfections combined with numerically optimized gradient waveforms enables PC-MRI waveforms to be designed to produce a minimal background phase in the most time-efficient manner. The methodology could be adapted for other MRI sequences where similar magnetic field errors affect measurements.

Assessing tumor microstructure with time-dependent diffusion imaging: Considerations and feasibility on clinical MRI and MRI-Linac.

Quantitative imaging biomarkers (QIBs) can characterize tumor heterogeneity and provide information for biological guidance in radiotherapy (RT). Time-dependent diffusion MRI (TDD-MRI) derived parameters are promising QIBs, as they describe tissue microstructure with more specificity than traditional diffusion-weighted MRI (DW-MRI). Specifically, TDD-MRI can provide information about both restricted diffusion and diffusional exchange, which are the two time-dependent effects affecting diffusion in tissue, and relevant in tumors. However, exhaustive modeling of both effects can require long acquisitions and complex model fitting. Furthermore, several introduced TDD-MRI measurements can require high gradient strengths and/or complex gradient waveforms that are possibly not available in RT settings. In this study, we investigated the feasibility of a simple analysis framework for the detection of restricted diffusion and diffusional exchange effects in the TDD-MRI signal. To promote the clinical applicability, we use standard gradient waveforms on a conventional 1.5 T MRI system with moderate gradient strength (Gmax=45 mT/m), and on a hybrid 1.5 T MRI-Linac system with low gradient strength (Gmax=15 mT/m). Restricted diffusion and diffusional exchange were simulated in geometries mimicking tumor microstructure to investigate the DW-MRI signal behavior and to determine optimal experimental parameters. TDD-MRI was implemented using pulsed field gradient spin echo with the optimized parameters on a conventional MRI system and a MRI-Linac. Experiments in green asparagus and 10 patients with brain lesions were performed to evaluate the time-dependent diffusion (TDD) contrast in the source DW-images. Simulations demonstrated how the TDD contrast was able to differentiate only dominating diffusional exchange in smaller cells from dominating restricted diffusion in larger cells. The maximal TDD contrast in simulations with typical cancer cell sizes and in asparagus measurements exceeded 5% on the conventional MRI but remained below 5% on the MRI-Linac. In particular, the simulated TDD contrast in typical cancer cell sizes (r=5-10µm) remained below or around 2% with the MRI-Linac gradient strength. In patients measured with the conventional MRI, we found sub-regions reflecting either dominating restricted diffusion or dominating diffusional exchange in and around brain lesions compared to the noisy appearing white matter. On the conventional MRI system, the TDD contrast maps showed consistent tumor sub-regions indicating different dominating TDD effects, potentially providing information on the spatial tumor heterogeneity. On the MRI-Linac, the available TDD contrast measured in asparagus showed the same trends as with the conventional MRI but remained close to typical measurement noise levels when simulated in common cancer cell sizes. On conventional MRI systems with moderate gradient strengths, the TDD contrast could potentially be used as a tool to identify which time-dependent effects to include when choosing a biophysical model for more specific tumor characterization.

On the correction of spiral trajectories on a preclinical MRI scanner with a high-performance gradient insert.

This study aimed to examine different trajectory correction methods for spiral imaging on a preclinical scanner with high-performance gradients with respect to image quality in a phantom and in vivo. The gold standard method of measuring the trajectories in a separate experiment is compared to an isotropic delay-correction, a correction using the gradient system transfer function (GSTF), and a combination of the two. Three different spiral trajectories, with 96, 16, and three interleaves, are considered. The best image quality is consistently achieved when determining the trajectory in a separate phantom measurement. However, especially for the spiral with 96 interleaves, the other correction methods lead to almost comparable results. Remaining imperfections in the corrected gradient waveforms and trajectories are attributed to asymmetrically occurring undulations in the actual, generated gradients, suggesting that the underlying assumption of linearity is violated. In conclusion, images of sufficient quality can be acquired on preclinical small-animal scannersusing spiral k-space trajectories without the need to carry out separate trajectory measurements each time. Depending on the trajectory, a simple isotropic delay-correction or a GSTF-based correction can provide images of similar quality.

High-quality FLORET UTE imaging for clinical translation.

To develop a robust 3D ultrashort-TE (UTE) protocol that can reproducibly provide high-quality images, assessed by the ability to yield clinically diagnostic images, and is suitable for clinical translation. Building on previous work, a UTE sampled with Fermat looped orthogonally encoded trajectories (FLORET) was chosen as a starting point due to its shorter, clinically reasonable scan times. Modifications to previous FLORET implementations included gradient waveform frequency limitations, a new trajectory ordering scheme, a balanced SSFP implementation, fast gradient spoiling, and full inline reconstruction. FLORET images were collected in phantoms and humans on multiple scanners and sites to demonstrate these improvements. The updates to FLORET provided high-quality images in phantom, musculoskeletal, and pulmonary applications. The gradient waveform modifications and new trajectory ordering scheme significantly reduced visible artifacts. Fast spoiling reduced acquisition time by 20%-28%. Across the various scanners and sites, the inline image quality was consistent and of diagnostic quality. Total image acquisition plus reconstruction time was less than 4 min for musculoskeletal and pulmonary applications with reconstructions taking less than 1 min. Recently developed improvements for the FLORET sequence have enabled robust, high-quality UTE acquisitions with short acquisition and reconstruction times. This enables clinical UTE imaging as demonstrated by the implementation of the sequence and acquisition on five MRI scanners, at three different sites, without the need for any additional system characterization or measurements.

Nonparametric distributions of tensor-valued Lorentzian diffusion spectra for model-free data inversion in multidimensional diffusion MRI.

Magnetic resonance imaging (MRI) is the method of choice for noninvasive studies of micrometer-scale structures in biological tissues via their effects on the time- and frequency-dependent (restricted) and anisotropic self-diffusion of water. While new designs of time-dependent magnetic field gradient waveforms have enabled disambiguation between different aspects of translational motion that are convolved in traditional MRI methods relying on single pairs of field gradient pulses, data analysis for complex heterogeneous materials remains a challenge. Here, we propose and demonstrate nonparametric distributions of tensor-valued Lorentzian diffusion spectra, or "D(ω) distributions," as a general representation with sufficient flexibility to describe the MRI signal response from a wide range of model systems and biological tissues investigated with modulated gradient waveforms separating and correlating the effects of restricted and anisotropic diffusion.

Tuned exchange imaging: Can the filter exchange imaging pulse sequence be adapted for applications with thin slices and restricted diffusion?

Filter exchange imaging (FEXI) is a double diffusion-encoding (DDE) sequence that is specifically sensitive to exchange between sites with different apparent diffusivities. FEXI uses a diffusion-encoding filtering block followed by a detection block at varying mixing times to map the exchange rate. Long mixing times enhance the sensitivity to exchange, but they pose challenges for imaging applications that require a stimulated echo sequence with crusher gradients. Thin imaging slices require strong crushers, which can introduce significant diffusion weighting and bias exchange rate estimates. Here, we treat the crushers as an additional encoding block and consider FEXI as a triple diffusion-encoding sequence. This allows the bias to be corrected in the case of multi-Gaussian diffusion, but not easily in the presence of restricted diffusion. Our approach addresses challenges in the presence of restricted diffusion and relies on the ability to independently gauge sensitivities to exchange and restricted diffusion for arbitrary gradient waveforms. It follows two principles: (i) the effects of crushers are included in the forward model using signal cumulant expansion; and (ii) timing parameters of diffusion gradients in filter and detection blocks are adjusted to maintain the same level of restriction encoding regardless of the mixing time. This results in the tuned exchange imaging (TEXI) protocol. The accuracy of exchange mapping with TEXI was assessed through Monte Carlo simulations in spheres of identical sizes and gamma-distributed sizes, and in parallel hexagonally packed cylinders. The simulations demonstrate that TEXI provides consistent exchange rates regardless of slice thickness and restriction size, even with strong crushers. However, the accuracy depends on b-values, mixing times, and restriction geometry. The constraints and limitations of TEXI are discussed, including suggestions for protocol adaptations. Further studies are needed to optimize the precision of TEXI and assess the approach experimentally in realistic, heterogeneous substrates.

Multiphoton parallel transmission (MP-pTx): Pulse design methods and numerical validation.

We propose and evaluate multiphoton parallel transmission (MP-pTx) to mitigate flip angle inhomogeneities in high-field MRI. MP-pTx is an excitation method that utilizes a single, conventional birdcage coil supplemented with low-frequency (kHz) irradiation from a multichannel shim array and/or gradient channels. SAR analysis is simplified to that of a conventional birdcage coil, because only the radiofrequency (RF) field from the birdcage coil produces significant SAR. MP-pTx employs an off-resonance RF pulse from a conventional birdcage coil supplemented with oscillating -directed fields from a multichannel shim array and/or the gradient coils. We simulate the ability of MP-pTx to create uniform nonselective brain excitations at 7 T using realistic and field maps. The RF, shim array, and gradient waveform's amplitudes and phases are optimized using a genetic algorithm followed by sequential quadratic programming. A 1 ms MP-pTx excitation using a 32-channel shim array with current constrained to less than 50 Amp-turns reduced the transverse magnetization's normalized root-mean-squared error from 29% for a conventional birdcage excitation to 6.6% and was nearly 40% better than a 1 ms birdcage coil 5 kT-point excitation with optimized kT-point locations and comparable pulse power. The MP-pTx method resembles conventional pTx in its goals and approach but replaces the parallel RF channels with cheaper, low-frequency shim channels. The method mitigates high-field flip angle inhomogeneities to a level better than 3 T CP-mode and comparable to 7 T pTx while retaining the straightforward SAR characteristics of conventional birdcage excitations, as low-frequency shim array fields produce negligible SAR.

Inertial focusing of small particles in oscillatory channel flows

This study leverages the immersed boundary-lattice Boltzmann method to investigate the inertial focusing dynamics of a small neutrally buoyant particle in oscillatory channel flows driven by two distinct pressure gradient (PG) waveforms. Through an in-depth analysis of particle behavior, this research delineates the effects of PG waveforms, particle Reynolds number (Rep), and Womersley number (Wo) on the inertial focusing processes, and contrasts these findings with conventional Poiseuille flow-induced inertial focusing. Our results reveal that oscillatory flows induce more intricate focusing patterns than those observed in Poiseuille flow. The streamwise PG oscillation alters the particle focusing positions and introduces minor lateral oscillations in the post-focusing phase. The square PG waveform positions particles closer to the channel wall compared to Poiseuille flow, whereas the sine PG waveform positions particles closer to the channel center. Moreover, an increase in Rep nudges the focusing positions towards the channel center, while a higher Wo pushes them towards the walls. Notably, at Wo ≥ 5, the flow's oscillatory effect dominates over its inertial effect (i.e. Rep) on particle focusing. The study also underscores the capability of oscillatory flows to reduce the required channel length for particle focusing, albeit at the cost of increased focusing time. Contrary to Poiseuille flow, where the focusing length shortens with an increased Rep, oscillatory flow demonstrates an inverse correlation, with an increase in Rep extending the focusing length. Furthermore, while a higher Rep is beneficial in Poiseuille flow, it adversely affects the focusing effect in oscillatory flow. The focusing efficiency peaks at Wo = 3.5 for both waveforms, with the sine PG waveform offering superior efficiency due to the lower lift forces generated. Consequently, for optimal focusing in similar conditions, it is recommended to set Rep and Wo to 0.075 and 3.5, respectively.

In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI.

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, , in addition to the diffusion tensor, , and relaxation, , , correlations. A clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

In vivo diffusion MRI of the human heart using a 300 mT/m gradient system.

This work reports for the first time on the implementation and application of cardiac diffusion-weighted MRI on a Connectom MR scanner with a maximum gradient strength of 300 mT/m. It evaluates the benefits of the increased gradient performance for the investigation of the myocardial microstructure. Cardiac diffusion-weighted imaging (DWI) experiments were performed on 10 healthy volunteers using a spin-echo sequence with up to second- and third-order motion compensation ( and ) and , and 1000 (twice the commonly used on clinical scanners). Mean diffusivity (MD), fractional anisotropy (FA), helix angle (HA), and secondary eigenvector angle (E2A) were calculated for b = [100, 450] and b = [100, 1000] for both and . The MD values with are slightly higher than with with for and for . A reduction in MD is observed by increasing the from 450 to 1000 ( for and for ). The difference between FA, E2A, and HA was not significant in different schemes ( ). This work demonstrates cardiac DWI in vivo with higher b-value and higher order of motion compensated diffusion gradient waveforms than is commonly used. Increasing the motion compensation order from to and the maximum b-value from 450 to 1000 affected the MD values but FA and the angular metrics (HA and E2A) remained unchanged. Our work paves the way for cardiac DWI on the next-generation MR scanners with high-performance gradient systems.

Precision of liver and pancreas apparent diffusion coefficients using motion-compensated gradient waveforms in DWI

BackgroundDiffusion weighted imaging (DWI) with optimized motion-compensated gradient waveforms reduces signal dropouts in the liver and pancreas caused by cardiovascular-associated motion, however its precision is unknown. We hypothesized that DWI with motion-compensated DW gradient waveforms would improve apparent diffusion coefficient (ADC)-repeatability and inter-reader reproducibility compared to conventional DWI in these organs. MethodsIn this IRB-approved, prospective, single center study, subjects recruited between October 2019 and March 2020 were scanned twice on a 3 T scanner, with repositioning between test and retest. Each scan included two respiratory-triggered DWI series with comparable acquisition time: 1) conventional (monopolar) 2) motion- compensated diffusion gradients. Three readers measured ADC values. One-way ANOVA, Bland-Altman analysis were used for statistical analysis. ResultsEight healthy participants (4 male/4 female), with a mean age of 29 ± 4 years, underwent the liver and pancreas MRI protocol. Four patients with liver metastases (2 male/2 female) with a mean age of 58 ± 5 years underwent the liver MRI protocol.In healthy participants, motion-compensated DWI outperformed conventional DWI with mean repeatability coefficient of 0.14 × 10−3 (CI:0.12–0.17) vs. 0.31 × 10−3 (CI:0.27–0.37) mm2/s for liver, and 0.11 × 10−3 (CI:0.08–0.15) vs. 0.34 × 10−3 (CI:0.27–0.49) mm2/s for pancreas; and with mean reproducibility coefficient of 0.20 × 10−3 (CI:0.18–0.23) vs. 0.51 × 10−3 (CI:0.46–0.58) mm2/s for liver, and 0.16 × 10−3 (CI:0.13–0.20) vs. 0.42 × 10−3 (CI:0.34–0.52) mm2/s for pancreas.In patients, improved repeatability was observed for motion-compensated DWI in comparison to conventional with repeatability coefficient of 0.51 × 10− 3 mm2/s (CI:0.35–0.89) vs. 0.70 × 10−3 mm2/s (CI:0.49–1.20). ConclusionMotion-compensated DWI enhances the precision of ADC measurements in the liver and pancreas compared to conventional DWI.

Field camera input to virtual phantom (ViP) scanner acquisitions for quality assurance of derived MRI quantities: first implementation and proof-of-principle.

Quality assurance (QA) of measurements derived from MRI can require complicated test phantoms. This work introduces a new QA concept using gradient and transmit RF recordings by a limited field camera (FC) to govern the previous Virtual Phantom (ViP) method. The purpose is to describe the first technical implementation of combined FC+ViP, and illustrate its performance in examples, including quantitative first-pass myocardial perfusion. The new QA concept starts with a synthetic test object (STO) representing some arbitrary test input. Using recordings of the unmodified standard sequence by a gradient and RF waveform camera (FC), ViP calculates by Bloch simulation the continuous RF signal emitted by the STO during this sequence (hence FC+ViP). During nominally identical repetition of the sequence acquisition, ViP transmits the RF signal for scanner reception, reconstruction and any further parametric derivations by the unmodified standard scanner image reconstruction and analysis software. The scanner outputs were compared against the input STOs. First proof-of-principle was discussed and supported by correlation between scanner outputs and the input STO. The work makes no claim that its examples are valid QA methods. It concludes by proposing a new industrial standard for QA without the FC.

FastPtx: a versatile toolbox for rapid, joint design of pTx RF and gradient pulses using Pytorch's autodifferentiation.

With modern optimization methods, free optimization of parallel transmit pulses together with their gradient waveforms can be performed on-line within a short time. A toolbox which uses PyTorch's autodifferentiation for simultaneous optimization of RF and gradient waveforms is presented and its performance is evaluated. MR measurements were performed on a 9.4T MRI scanner using a 3D saturated single-shot turboFlash sequence for [Formula: see text] mapping. RF pulse simulation and optimization were done using a Python toolbox and a dedicated server. An RF- and Gradient pulse design toolbox was developed, including a cost function to balance different metrics and respect hardware and regulatory limits. Pulse performance was evaluated in GRE and MPRAGE imaging. Pulses for non-selective and for slab-selective excitation were designed. Universal pulses for non-selective excitation reduced the flip angle error to an NRMSE of (12.3±1.7)% relative to the targeted flip angle in simulations, compared to (42.0±1.4)% in CP mode. The tailored pulses performed best, resulting in a narrow flip angle distribution with NRMSE of (8.2±1.0)%. The tailored pulses could be created in only 66s, making it feasible to design them during an experiment. A 90° pulse was designed as preparation pulse for a satTFL sequence and achieved a NRMSE of 7.1%. We showed that both MPRAGE and GRE imaging benefited from the pTx pulses created with our toolbox. The pTx pulse design toolbox can freely optimize gradient and pTx RF waveforms in a short time. This allows for tailoring high-quality pulses in just over a minute.

Study on wave propagation in the modulation structure with gradually changing impedance according to specific waveform based on magneto-rheological fluid

This work proposes a novel hierarchical modulation structure with gradually-changed impedance built by magneto-rheological (MR) fluid and investigates its wave propagation characteristics theoretically and experimentally. Based on the impedance tunable property of the MR fluid, applying multiple magnetic fields to MR fluid realizes the modulation of this proposed structure, and regulating its magnetic field distribution law can effectively change the impedance variation forms in the structure. Establish the elastic wave propagation model of this modulated structure, and analyze the variation trends of its elastic wave propagation characteristics with different impedance distribution patterns, taking the vibration level difference as an indicator. Subsequently, conduct experimental testing for the transmissibility of elastic waves. The results show that the elastic wave transmission characteristics of the proposed modulation structure mainly depend on its impedance variation rate and the frequency of external excitation. On a broader band of the frequency range (20–300 Hz) studied in this paper, the gradual impedance distribution of MR fluid enhances the transmission loss of elastic waves compared to a uniform distribution of its impedance. Moreover, in the lower frequency range (40–125 Hz), the layered modulation structure with a non-monotonic variation of impedance following a wave-like waveform presents more significant attenuation on elastic waves than the structure whose impedance varies monotonously in a gradient waveform. This work contributes to expanding the design thoughts of the structure with gradually changing impedance and providing new ideas and means for the control of elastic waves.

Compensation of concomitant field effects in double diffusion encoding by means of added oscillating gradients

Maxwell or concomitant fields imprint additional phases on the transverse magnetization. This concomitant phase may cause severe image artifacts like signal voids or distort the quantitative parameters due to the induced intravoxel dephasing. In particular, double diffusion encoding (DDE) schemes with two pairs of bipolar diffusion-weighting gradients separated by a refocusing radiofrequency (RF) pulse are prone to concomitant field-induced artifacts. In this work, a method for reducing concomitant field effects in these DDE sequences based on additional oscillating gradients is presented. These oscillating gradient pulses obtained by constrained optimization were added to the original gradient waveforms. The modified sequences reduced the accumulated concomitant phase without significant changes in the original sequence characteristics. The proposed method was applied to a DDE acquisition scheme consisting of 60 pairs of diffusion wave vectors. For phantom as well as for in vivo experiments, a considerable increase in the signal-to-noise ratio (SNR) was obtained. For phantom measurements with a diffusion weighting of b = 2000 s/mm2 for each of the gradient pairs, an SNR increase of up to 40% was observed for a transversal slice that had a distance of 5 cm from the isocenter. For equivalent slice parameters, in vivo measurements in the brain of a healthy volunteer exhibited an increase in SNR of up to 35% for b = 750 s/mm2 for each weighting. These findings are supported by corresponding simulations, which also predict a positive effect on the SNR. In summary, the presented method leads to an SNR gain without additional RF refocusing pulses.

Diffusion MRI with free gradient waveforms on a high-performance gradient system: Probing restriction and exchange in the human brain

The dependence of the diffusion MRI signal on the diffusion time carries signatures of restricted diffusion and exchange. Here we seek to highlight these signatures in the human brain by performing experiments using free gradient waveforms designed to be selectively sensitive to the two effects. We examine six healthy volunteers using both strong and ultra-strong gradients (80, 200 and 300 mT/m). In an experiment featuring a large set of 150 gradient waveforms with different sensitivities to restricted diffusion and exchange, our results reveal unique and different time-dependence signatures in grey and white matter. Grey matter was characterised by both restricted diffusion and exchange and white matter predominantly by restricted diffusion. Exchange in grey matter was at least twice as fast as in white matter, across all subjects and all gradient strengths. The cerebellar cortex featured relatively short exchange times (115 ms). Furthermore, we show that gradient waveforms with tailored designs can be used to map exchange in the human brain. We also assessed the feasibility of clinical applications of the method used in this work and found that the exchange-related contrast obtained with a 25-minute protocol at 300 mT/m was preserved in a 4-minute protocol at 300 mT/m and a 10-minute protocol at 80 mT/m. Our work underlines the utility of free waveforms for detecting time dependence signatures due to restricted diffusion and exchange in vivo, which may potentially serve as a tool for studying diseased tissue.

Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs.

The study aims to develop easy-to-implement concomitant field-compensated gradient waveforms with varying velocity-weighting (M1) and acceleration-weighting (M2) levels and to evaluate their efficacy in correcting signal dropouts and preserving the black-blood state in liver diffusion-weighted imaging. Additionally, we seek to determine an optimal degree of compensation that minimizes signal dropouts while maintaining blood signal suppression. Numerically optimized gradient waveforms were adapted using a novel method that allows for the simultaneous tuning of M1- and M2-weighting by changing only one timing variable. Seven healthy volunteers underwent diffusion-weighted magnetic resonance imaging (DWI) with five diffusion encoding schemes (monopolar, velocity-compensated (M1 = 0), acceleration-compensated (M1 = M2 = 0), 84%-M1-M2-compensated, 67%-M1-M2-compensated) at b-values of 50 and 800 s/mm2 at a constant echo time of 70 ms. Signal dropout correction and apparent diffusion coefficients (ADCs) were quantified using regions of interest in the left and right liver lobe. The blood appearance was evaluated using two five-point Likert scales. Signal dropout was more pronounced in the left lobe (19%-42% less signal than in the right lobe with monopolar scheme) and best corrected by acceleration-compensation (8%-10% less signal than in the right lobe). The black-blood state was best with monopolar encodings and decreased significantly (p < 0.001) with velocity- and/or acceleration-compensation. The partially M1-M2-compensated encoding schemes could restore the black-blood state again. Strongest ADC bias occurred for monopolar encodings (difference between left/right lobe of 0.41 μm2/ms for monopolar vs. < 0.12 μm2/ms for the other encodings). All of the diffusion encodings used in this study demonstrated suitability for routine DWI application. The results indicate that a perfect value for the level of M1-M2-compensation does not exist. However, among the examined encodings, the 84%-M1-M2-compensated encodings provided a suitable tradeoff.

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

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