Data adaptive regularization with reference tissue constraints for liver quantitative susceptibility mapping.

PURPOSE: To improve repeatability and reproducibility across acquisition parameters and reduce bias in quantitative susceptibility mapping (QSM) of the liver, through development of an optimized regularized reconstruction algorithm for abdominal QSM. METHODS: An optimized approach to estimation of magnetic susceptibility distribution is formulated as a constrained reconstruction problem that incorporates estimates of the input data reliability and anatomical priors available from chemical shift-encoded imaging. The proposed data-adaptive method was evaluated with respect to bias, repeatability, and reproducibility in a patient population with a wide range of liver iron concentration (LIC). The proposed method was compared to the previously proposed and validated approach in liver QSM for two multi-echo spoiled gradient-recalled echo protocols with different acquisition parameters at 3T. Linear regression was used for evaluation of QSM methods against a reference FDA-approved R 2 $$ {R}_2 $$ -based LIC measure and R 2 ∗ $$ {R}_2^{\ast } $$ measurements; repeatability/reproducibility were assessed by Bland-Altman analysis. RESULTS: The data-adaptive method produced susceptibility maps with higher subjective quality due to reduced shading artifacts. For both acquisition protocols, higher linear correlation with both R 2 $$ {R}_2 $$ - and R 2 ∗ $$ {R}_2^{\ast } $$ -based measurements were observed for the data-adaptive method ( r 2 = 0 . 74 / 0 . 69 $$ {r}^2=0.74/0.69 $$ for R 2 $$ {R}_2 $$ , 0 . 97 / 0 . 95 $$ 0.97/0.95 $$ for R 2 ∗ $$ {R}_2^{\ast } $$ ) than the standard method ( r 2 = 0 . 60 / 0 . 66 $$ {r}^2=0.60/0.66 $$ and 0 . 79 / 0 . 88 $$ 0.79/0.88 $$ ). For both protocols, the data-adaptive method enabled better test-retest repeatability (repeatability coefficients 0.19/0.30 ppm for the data-adaptive method, 0.38/0.47 ppm for the standard method) and reproducibility across protocols (reproducibility coefficient 0.28 vs. 0.53ppm) than the standard method. CONCLUSIONS: The proposed data-adaptive QSM algorithm may enable quantification of LIC with improved repeatability/reproducibility across different acquisition parameters as 3T.

High-resolution dynamic susceptibility contrast perfusion imaging using higher-order temporal smoothness regularization.

PURPOSE: To improve image quality and resolution of dynamic susceptibility contrast perfusion weighted imaging (DSC-PWI) by developing acquisition and reconstruction methods exploiting the temporal regularity property of DSC-PWI signal. THEORY AND METHODS: A novel regularized reconstruction is proposed that recovers DSC-PWI series from interleaved segmented spiral k-space acquisition using higher order temporal smoothness (HOTS) properties of the DSC-PWI signal. The HOTS regularization is designed to tackle representational insufficiency of the standard first-order temporal regularizations for supporting higher accelerations. The higher accelerations allow for k-space coverage with shorter spiral interleaves resulting in improved acquisition point spread function, and acquisition of images at multiple TEs for more accurate DSC-PWI analysis. RESULTS: The methods were evaluated in simulated and in-vivo studies. HOTS regularization provided increasingly more accurate models for DSC-PWI than the standard first-order methods with either quadratic or robust norms at the expense of increased noise. HOTS DSC-PWI optimized for noise and accuracy demonstrated significant advantages over both spiral DSC-PWI without temporal regularization and traditional echo-planar DSC-PWI, improving resolution and mitigating image artifacts associated with long readout, including blurring and geometric distortions. In context of multi-echo DSC-PWI, the novel methods allowed ∼4.3× decrease of voxel volume, providing 2× number of TEs compared to the previously published results. CONCLUSIONS: Proposed HOTS reconstruction combined with dynamic spiral sampling represents a valid mechanism for improving image quality and resolution of DSC-PWI significantly beyond those available with established fast imaging techniques.

The Influence of Data-Driven Compressed Sensing Reconstruction on Quantitative Pharmacokinetic Analysis in Breast DCE MRI.

Radial acquisition with MOCCO reconstruction has been previously proposed for high spatial and temporal resolution breast DCE imaging. In this work, we characterize MOCCO across a wide range of temporal contrast enhancement in a digital reference object (DRO). Time-resolved radial data was simulated using a DRO with lesions in different PK parameters. The under sampled data were reconstructed at 5 s temporal resolution using the data-driven low-rank temporal model for MOCCO, compressed sensing with temporal total variation (CS-TV) and more conventional low-rank reconstruction (PCB). Our results demonstrated that MOCCO was able to recover curves with Ktrans values ranging from 0.01 to 0.8 min-1 and fixed Ve = 0.3, where the fitted results are within a 10% bias error range. MOCCO reconstruction showed less impact on the selection of different temporal models than conventional low-rank reconstruction and the greater error was observed with PCB. CS-TV showed overall underestimation in both Ktrans and Ve. For the Monte-Carlo simulations, MOCCO was found to provide the most accurate reconstruction results for curves with intermediate lesion kinetics in the presence of noise. Initial in vivo experiences are reported in one patient volunteer. Overall, MOCCO was able to provide reconstructed time-series data that resulted in a more accurate measurement of PK parameters than PCB and CS-TV.

Comparison of data-driven and general temporal constraints on compressed sensing for breast DCE MRI.

PURPOSE: Current breast DCE-MRI strategies provide high sensitivity for cancer detection but are known to be insufficient in fully capturing rapidly changing contrast kinetics at high spatial resolution across both breasts. Advanced acquisition and reconstruction strategies aim to improve spatial and temporal resolution and increase specificity for disease characterization. In this work, we evaluate the spatial and temporal fidelity of a modified data-driven low-rank-based model (known as MOCCO, model consistency condition) compressed-sensing (CS) reconstruction compared to CS with temporal total variation with radial acquisition for high spatial-temporal breast DCE MRI. METHODS: Reconstruction performance was characterized using numerical simulations of a golden-angle stack-of-stars breast DCE-MRI acquisition at 5-second temporal resolution. Specifically, MOCCO was compared with CS total variation and conventional SENSE reconstructions. The temporal model for MOCCO was prelearned over the source data, whereas CS total variation was performed using a first-order temporal gradient sparsity transform. RESULTS: The MOCCO reconstruction was able to capture rapid lesion kinetics while providing high image quality across a range of optimal regularization values. It also recovered kinetics in small lesions (1.5 mm) in line-profile analysis and error images, whereas g-factor maps showed relatively low and constant values with no significant artifacts. The CS-TV method demonstrated either recovery of high spatial resolution with reduced temporal accuracy using large regularization values, or recovery of rapid lesion kinetics with reduced image quality using low regularization values. CONCLUSION: Simulations demonstrated that MOCCO with radial acquisition provides a robust imaging technique for improving temporal fidelity, while maintaining high spatial resolution and image quality in the setting of bilateral breast DCE MRI.

Resolving estimation uncertainties of chemical shift encoded fat-water imaging using magnetization transfer effect.

PURPOSE: B0 field inhomogeneity may cause significant errors in chemical shift encoding-based fat-water (F/W) separation. We describe a new approach to improve its robustness using novel B0 field map pre-estimation. METHODS: Our method exploits insensitivity of fat to magnetization transfer effect, which allows generating fat-insensitive B0 field priors with full or partial spatial support using a low-resolution magnetization transfer-weighted scan. The full prior can be employed by most F/W separation methods for initialization or data demodulation. We also propose a modified region-growing algorithm in which the partial prior is utilized for its initial seeding. RESULTS: The magnetization transfer-based B0 priors significantly reduced F/W errors of three representative F/W separation methods in all cases. In cases with moderate B0 inhomogeneity, the full prior allowed error-free separation even with basic, voxel-independent processing. When coupled with methods exploiting B0 field smoothness, it significantly improved separation accuracy even in the presence of strong inhomogeneities. Seeding the region-growing with the partial prior significantly improved performance of F/W separation, including cases with spatially disconnected tissues. CONCLUSION: Magnetization transfer-based B0 field pre-estimation provides valuable prior information for F/W separation, which may significantly improve its robustness at the expense of nominal (< 5%-10%) scan time increase.

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model.

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexible representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplified treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed  âˆ¼ 200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure.

Advancing RF pulse design using an open-competition format: Report from the 2015 ISMRM challenge.

PURPOSE: To advance the best solutions to two important RF pulse design problems with an open head-to-head competition. METHODS: Two sub-challenges were formulated in which contestants competed to design the shortest simultaneous multislice (SMS) refocusing pulses and slice-selective parallel transmission (pTx) excitation pulses, subject to realistic hardware and safety constraints. Short refocusing pulses are needed for spin echo SMS imaging at high multiband factors, and short slice-selective pTx pulses are needed for multislice imaging in ultra-high field MRI. Each sub-challenge comprised two phases, in which the first phase posed problems with a low barrier of entry, and the second phase encouraged solutions that performed well in general. The Challenge ran from October 2015 to May 2016. RESULTS: The pTx Challenge winners developed a spokes pulse design method that combined variable-rate selective excitation with an efficient method to enforce SAR constraints, which achieved 10.6 times shorter pulse durations than conventional approaches. The SMS Challenge winners developed a time-optimal control multiband pulse design algorithm that achieved 5.1 times shorter pulse durations than conventional approaches. CONCLUSION: The Challenge led to rapid step improvements in solutions to significant problems in RF excitation for SMS imaging and ultra-high field MRI. Magn Reson Med 78:1352-1361, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Reconstruction of dynamic image series from undersampled MRI data using data-driven model consistency condition (MOCCO).

PURPOSE: To accelerate dynamic MR imaging through development of a novel image reconstruction technique using low-rank temporal signal models preestimated from training data. THEORY: We introduce the model consistency condition (MOCCO) technique, which utilizes temporal models to regularize reconstruction without constraining the solution to be low-rank, as is performed in related techniques. This is achieved by using a data-driven model to design a transform for compressed sensing-type regularization. The enforcement of general compliance with the model without excessively penalizing deviating signal allows recovery of a full-rank solution. METHODS: Our method was compared with a standard low-rank approach utilizing model-based dimensionality reduction in phantoms and patient examinations for time-resolved contrast-enhanced angiography (CE-MRA) and cardiac CINE imaging. We studied the sensitivity of all methods to rank reduction and temporal subspace modeling errors. RESULTS: MOCCO demonstrated reduced sensitivity to modeling errors compared with the standard approach. Full-rank MOCCO solutions showed significantly improved preservation of temporal fidelity and aliasing/noise suppression in highly accelerated CE-MRA (acceleration up to 27) and cardiac CINE (acceleration up to 15) data. CONCLUSIONS: MOCCO overcomes several important deficiencies of previously proposed methods based on pre-estimated temporal models and allows high quality image restoration from highly undersampled CE-MRA and cardiac CINE data.

Three-dimensional pulmonary perfusion MRI with radial ultrashort echo time and spatial-temporal constrained reconstruction.

PURPOSE: To assess the feasibility of spatial-temporal constrained reconstruction for accelerated regional lung perfusion using highly undersampled dynamic contrast-enhanced (DCE) three-dimensional (3D) radial MRI with ultrashort echo time (UTE). METHODS: A combined strategy was used to accelerate DCE MRI for 3D pulmonary perfusion with whole lung coverage. A highly undersampled 3D radial UTE MRI acquisition was combined with an iterative constrained reconstruction exploiting principal component analysis and wavelet soft-thresholding for dimensionality reduction in space and time. The performance of the method was evaluated using a 3D fractal-based DCE digital lung phantom. Simulated perfusion maps and contrast enhancement curves were compared with ground truth using the structural similarity index (SSIM) to determine robust threshold and regularization levels. Feasibility studies were then performed in a canine and a human subject with 3D radial UTE (TE=0.08 ms) acquisition to assess feasibility of mapping regional 3D perfusion. RESULTS: The method was able to accurately recover perfusion maps in the phantom with a nominal isotropic spatial resolution of 1.5 mm (SSIM of 0.949). The canine and human subject studies demonstrated feasibility for providing artifact-free perfusion maps in a simple 3D breath-held acquisition. CONCLUSION: The proposed method is promising for fast and flexible 3D pulmonary perfusion imaging. Magn Reson

Accelerating MR parameter mapping using sparsity-promoting regularization in parametric dimension.

MR parameter mapping requires sampling along additional (parametric) dimension, which often limits its clinical appeal due to a several-fold increase in scan times compared to conventional anatomic imaging. Data undersampling combined with parallel imaging is an attractive way to reduce scan time in such applications. However, inherent SNR penalties of parallel MRI due to noise amplification often limit its utility even at moderate acceleration factors, requiring regularization by prior knowledge. In this work, we propose a novel regularization strategy, which uses smoothness of signal evolution in the parametric dimension within compressed sensing framework (p-CS) to provide accurate and precise estimation of parametric maps from undersampled data. The performance of the method was demonstrated with variable flip angle T1 mapping and compared favorably to two representative reconstruction approaches, image space-based total variation regularization and an analytical model-based reconstruction. The proposed p-CS regularization was found to provide efficient suppression of noise amplification and preservation of parameter mapping accuracy without explicit utilization of analytical signal models. The developed method may facilitate acceleration of quantitative MRI techniques that are not suitable to model-based reconstruction because of complex signal models or when signal deviations from the expected analytical model exist.

PC HYPR flow: a technique for rapid imaging of contrast dynamics.

PURPOSE: To improve spatial and temporal resolution and signal-to-noise ratio (SNR) in three-dimensional (3D) radial contrast-enhanced (CE) time-resolved MR angiography by means of a novel hybrid phase contrast (PC) and CE MRA acquisition and HYPR reconstruction (PC HYPR Flow). MATERIALS AND METHODS: PC HYPR Flow consists of a CE exam immediately followed by a PC scan used to constrain the HYPR reconstruction of the time series. Temporal resolution of the new method was studied in computer simulations. The feasibility of the new technique was studied in healthy subjects and patients with brain arteriovenous malformations and in a canine model of aneurysms. RESULTS: Simulations demonstrated preservation of contrast agent dynamics in proximal vessels, showing better performance than peer methods for acceleration up to 20 in 2D. In vivo, PC HYPR Flow yielded 3D time series with frame rate of 0.5 s and significantly outperformed two peer methods by means of a major increase in spatial resolution (0.8 x 0.8 x 0.8 mm(3)) and arterial/venous ratio, while maintaining necessary temporal waveform fidelity and high SNR. CONCLUSION: This initial study indicates that PC HYPR Flow simultaneously provides 3D isotropic sub-millimeter spatial resolution, sub-second temporal reconstruction windows and high SNR level, which may benefit a wide range of CE MRA applications.

Three-dimensional imaging of ventilation dynamics in asthmatics using multiecho projection acquisition with constrained reconstruction.

The purpose of this work is to detect dynamic gas trapping in three dimensions during forced exhalation at isotropic high spatial resolution and high temporal resolution using hyperpolarized helium-3 MRI. Ten subjects underwent hyperpolarized helium-3 MRI and multidetector CT. MRI was performed throughout inspiration, breath-hold, and forced expiration. A multiecho three-dimensional projection acquisition was used to improve data collection efficiency and an iterative constrained reconstruction was implemented to improve signal to noise ratio (SNR) and increase robustness to motion. Two radiologists evaluated the dynamic MRI and breath-held multidetector CT data for gas and air trapping, respectively. Phantom studies showed the proposed technique significantly improved depiction of moving objects compared to view-sharing methods. Gas trapping was detected using MRI in five of the six asthmatic subjects who displayed air trapping with multidetector CT. Locations in disagreement were found to represent small to moderate regions of air trapping. The proposed technique provides whole-lung three-dimensional imaging of respiration dynamics at high spatial and temporal resolution and compares well to the current standard, multidetector CT. While multidetector CT can provide information about static regional air trapping, it is unable to depict dynamics in a setting more comparable to a spirometry maneuver and explore the longitudinal time evolution of the trapped regions.