Convex gradient optimization for increased spatiotemporal resolution and improved accuracy in phase contrast MRI

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

PURPOSE

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.

METHODS

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 (M 2 $$ {M}_2 $$ andM 3 $$ {M}_3 $$ ) andb = 100 ,   450 $$ b=100,450 $$ , and 1000s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ (twice theb max $$ {b}_{\mathrm{max}} $$ 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]s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ and b = [100, 1000]s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ for bothM 2 $$ {M}_2 $$ andM 3 $$ {M}_3 $$ .

RESULTS

The MD values withM 3 $$ {M}_3 $$ are slightly higher than withM 2 $$ {M}_2 $$ withΔ MD = 0 . 05 ± 0 . 05 [ × 1 0 - 3 mm 2 / s ] ( p = 4 e - 5 ) $$ \Delta \mathrm{MD}=0.05\pm 0.05\kern0.3em \left[\times 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=4e-5\right) $$ forb max = 450 s / mm 2 $$ {b}_{\mathrm{max}}=450\kern0.3em \mathrm{s}/{\mathrm{mm}}^2 $$ andΔ MD = 0 . 03 ± 0 . 03 [ × 1 0 - 3 mm 2 / s ] ( p = 4 e - 4 ) $$ \Delta \mathrm{MD}=0.03\pm 0.03\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=4e-4\right) $$ forb max = 1000 s / mm 2 $$ {b}_{\mathrm{max}}=1000\kern0.3em \mathrm{s}/{\mathrm{mm}}^2 $$ . A reduction in MD is observed by increasing theb max $$ {b}_{\mathrm{max}} $$ from 450 to 1000s / mm 2 $$ \mathrm{s}/{\mathrm{mm}}^2 $$ (Δ MD = 0 . 06 ± 0 . 04 [ × 1 0 - 3 mm 2 / s ] ( p = 1 . 6 e - 9 ) $$ \Delta \mathrm{MD}=0.06\pm 0.04\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=1.6e-9\right) $$ forM 2 $$ {M}_2 $$ andΔ MD = 0 . 08 ± 0 . 05 [ × 1 0 - 3 mm 2 / s ] ( p = 1 e - 9 ) $$ \Delta \mathrm{MD}=0.08\pm 0.05\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=1e-9\right) $$ forM 3 $$ {M}_3 $$ ). The difference between FA, E2A, and HA was not significant in different schemes (p > 0 . 05 $$ p>0.05 $$ ).

CONCLUSION

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 fromM 2 $$ {M}_2 $$ toM 3 $$ {M}_3 $$ and the maximum b-value from 450 to 1000  s / mm 2 $$ \mathrm{s}/{\mathrm{mm}}^2 $$ 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.

Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications

Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs. These methods have become available for medical applications mainly due to the continuing development of image-based kinematic techniques, the maturity of the associated theories describing cardiovascular function, and recent progress in computer science, modeling, and simulation engineering. Inverse method applications are multidisciplinary, requiring tailored solutions to the available clinical data, pathology of interest, and available computational resources. Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. In the final section, the major advances in inverse modeling of human cardiovascular mechanics since its early development in the early 2000s are reviewed with emphasis on method-specific descriptions, results, and conclusions. We draw selected studies on healthy and diseased hearts, aortas, and pulmonary arteries achieved through the incorporation of tissue mechanics, hemodynamics, and fluid-structure interaction methods paired with patient-specific data acquired with medical imaging in inverse modeling approaches.

Velocity quantification in 44 healthy volunteers using accelerated multi-VENC 4D flow CMR

BACKGROUND

To evaluate the feasibility of a k-t accelerated multi-VENC 4D phase contrast flow MRI acquisition of the main heart-surrounding vessels, its benefits over a traditional single-VENC acquisition and to present reference flow and velocity values in a large cohort of volunteers.

METHODS

44 healthy volunteers were examined on a 3 T MRI scanner (Ingenia, Philips, Best, The Netherlands). 4D flow measurements were obtained with a FOV including the aorta and the pulmonary arteries. VENC values were set to 40, 100 and 200 cm/s and unfolded based on an MRI signal model. Unfolded multi-VENC data was compared to the single-VENC with VENC 200 cm/s. Flow and velocity quantification was performed in several regions of interest (ROI) placed in the ascending aorta and in the main pulmonary artery. Conservation of mass analysis was performed for single- and multi-VENC datasets. Values for mean and maximal flow velocity and stroke volume were calculated and compared to the literature.

RESULTS

Mean scan time was 13.8 ± 4 min. Differences between stroke volumes between the ascending aorta and the main pulmonary artery were significantly lower in multi-VENC datasets compared to single-VENC datasets (9.6 ± 7.8 mL vs. 25.4 ± 26.4 mL, p < 0.001). This was also true for differences in stroke volume between up- and downstream ROIs in the ascending aorta and pulmonary artery. Values for mean and maximal velocities and stroke volume were in-line with previous studies. To highlight potential clinical applications two exemplary 4D flow measurements in patients with different pathologies are shown and compared to single-VENC datasets.

CONCLUSIONS

k-t accelerated multi-VENC 4D phase contrast flow MRI acquisition of the great vessels is feasible in a clinically acceptable scan duration. It offers improvements over traditional single-VENC 4D flow, expectedly being valuable when vessels with different flow velocities or complex flow phenomena are evaluated.

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.

Phase-contrast MRI with hybrid one and two-sided flow-encoding and velocity spectrum separation

PURPOSE

To develop and evaluate a phase-contrast MRI (PC-MRI) technique with hybrid one and two-sided flow-encoding and velocity spectrum separation (HOTSPA) for accelerated blood flow and velocity measurement.

METHODS

In the HOTSPA technique, the two-sided flow encoding (FE) is used for two FE directions and one-sided is used for the remaining FE direction. Such a temporal modulation of the FE strategy allows for separations of the Fourier velocity spectrum into components for the flow-compensated and the three-directional velocity waveforms, accelerating PC-MRI by encoding three-directional velocities using only two repetition times (TRs) instead of four TRs as in standard PC-MRI. The HOTSPA was evaluated and compared with standard PC-MRI in the common carotid arteries of six healthy volunteers.

RESULTS

Total volumetric flow and peak velocity measurements based on HOTSPA and the conventional PC-MRI were in good agreement with a bias of -0.005 mL (-0.1% relative bias error) for total volumetric flow and 1.21 cm/s (1.1% relative bias error) for peak velocity, although the total acquisition time was 50% of the conventional PC-MRI.

CONCLUSION

The proposed HOTSPA technique achieved nearly two-fold acceleration of PC-MRI while maintaining accuracy for total volumetric flow and peak velocity quantification by separating the paired acquisitions in the Fourier velocity spectrum domain. Magn Reson Med 78:182-192, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

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.

Cardiovascular magnetic resonance phase contrast imaging

Cardiovascular magnetic resonance (CMR) phase contrast imaging has undergone a wide range of changes with the development and availability of improved calibration procedures, visualization tools, and analysis methods. This article provides a comprehensive review of the current state-of-the-art in CMR phase contrast imaging methodology, clinical applications including summaries of past clinical performance, and emerging research and clinical applications that utilize today's latest technology.

Improved spoiling efficiency in dynamic RF-spoiled imaging by ghost phase modulation and temporal filtering

PURPOSE

Radiofrequency-spoiled steady-state sequences offer rapid data acquisition with T1- or T2*-weighting. The spoiler gradients in these sequences must be large enough to suppress ghost artifacts, and are chosen empirically. However, certain factors such as the need to minimize gradient first moments or acoustic noise can limit the spoiler size and, hence, the ability to suppress ghosts. We present an acquisition and preprocessing strategy for improved spoiling efficiency in conventional and echo-shifted dynamic radiofrequency-spoiled 3D imaging.

THEORY AND METHODS

By requiring each time-frame in a dynamic imaging sequence to contain a particular (restricted) number of total radiofrequency shots, the ghost signal can be made to alternate in sign every other frame. The ghost is then suppressed by Fourier transforming along the temporal dimension, and removing the Nyquist frequency in preprocessing (similar to UNFOLD). The method works for both Cartesian and non-Cartesian imaging.

RESULTS

We demonstrate improved ghost suppression with the proposed approach, for both conventional and echo-shifted spoiled gradient echo imaging in stationary phantoms and in vivo. Cartesian echo-shifted spoiled gradient echo imaging produces two ghosts shifted in opposite directions, both of which are suppressed with our method.

CONCLUSION

For a given spoiler gradient area, the proposed approach substantially suppresses the ghost signal in both conventional and echo-shifted dynamic radiofrequency-spoiled imaging. Magn Reson Med 75:2388-2393, 2016. © 2015 Wiley Periodicals, Inc.