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PURPOSE To develop a 3D sequence for T1ρ relaxation mapping using radial volumetric encoding (3D-T1ρ -RAVE) and to evaluate the multi relaxation components in the liver of healthy controls and chronic liver disease (CLD) patients. METHODS Fat saturation and T1ρ preparation modules were followed by a train of gradient-echo acquisitions and T1 restoration delay. The series of T1ρ -weighted images were fitted using mono-exponential, bi-exponential, and stretched-exponential models. The repeatability and reproducibility of the proposed technique were evaluated on National Institute of Standards and Technology phantom by calculating the coefficient of variation between test-retest scans on the same scanner and between two different 3T scanners, respectively. Mann-Whitney U-test was performed to assess differences in T1ρ components among patients (n = 3) and a control group (n = 10). RESULTS The phantom study showed an error of 8.9% and 11.5% in mono T2 relaxation time measurement relative to the reference on 2 different scanners. The coefficient of variation for test-retest scans performed on the same scanner was 5.7% and 2.4% for scans performed on 2 scanners. The comparison between healthy controls and CLD patients showed a significant difference (P < .05) in mono relaxation time (P = .002), stretched-exponential relaxation parameter (P = .04). The Akaike information criteria C criterion showed 2.53 ± 0.9% (2.3 ± 0.3% for CLD) of the voxels are bi-exponential while in 65.3 ± 5.8% (81.2 ± 0.06% for CLD) of the liver voxels, the stretched-exponential model was preferred. CONCLUSION The 3D-T1ρ -RAVE sequence allows volumetric, multicomponent T1ρ assessment of the liver during free breathing and can distinguish between healthy volunteers and CLD patients.

Purpose To compare a novel multicoil compressed sensing technique with flexible temporal resolution, golden-angle radial sparse parallel (GRASP), to conventional fat-suppressed spoiled three-dimensional (3D) gradient-echo (volumetric interpolated breath-hold examination, VIBE) MRI in evaluating the conspicuity of benign and malignant breast lesions. Materials and Methods Between March and August 2015, 121 women (24–84 years; mean, 49.7 years) with 180 biopsy-proven benign and malignant lesions were imaged consecutively at 3.0 Tesla in a dynamic contrast-enhanced (DCE) MRI exam using sagittal T1-weighted fat-suppressed 3D VIBE in this Health Insurance Portability and Accountability Act-compliant, retrospective study. Subjects underwent MRI-guided breast biopsy (mean, 13 days [1–95 days]) using GRASP DCE-MRI, a fat-suppressed radial “stack-of-stars” 3D FLASH sequence with golden-angle ordering. Three readers independently evaluated breast lesions on both sequences. Statistical analysis included mixed models with generalized estimating equations, kappa-weighted coefficients and Fisher's exact test. Results All lesions demonstrated good conspicuity on VIBE and GRASP sequences (4.28 ± 0.81 versus 3.65 ± 1.22), with no significant difference in lesion detection (P = 0.248). VIBE had slightly higher lesion conspicuity than GRASP for all lesions, with VIBE 12.6% (0.63/5.0) more conspicuous (P

Radial spin-echo diffusion imaging allows motion-robust imaging of tissues with very low T2 values like articular cartilage with high spatial resolution and signal-to-noise ratio (SNR). However, in vivo measurements are challenging, due to the significantly slower data acquisition speed of spin-echo sequences and the less efficient k-space coverage of radial sampling, which raises the demand for accelerated protocols by means of undersampling. This work introduces a new reconstruction approach for undersampled diffusion-tensor imaging (DTI). A model-based reconstruction implicitly exploits redundancies in the diffusion-weighted images by reducing the number of unknowns in the optimization problem and compressed sensing is performed directly in the target quantitative domain by imposing a total variation (TV) constraint on the elements of the diffusion tensor. Experiments were performed for an anisotropic phantom and the knee and brain of healthy volunteers (three and two volunteers, respectively). Evaluation of the new approach was conducted by comparing the results with reconstructions performed with gridding, combined parallel imaging and compressed sensing and a recently proposed model-based approach. The experiments demonstrated improvements in terms of reduction of noise and streaking artifacts in the quantitative parameter maps, as well as a reduction of angular dispersion of the primary eigenvector when using the proposed method, without introducing systematic errors into the maps. This may enable an essential reduction of the acquisition time in radial spin-echo diffusion-tensor imaging without degrading parameter quantification and/or SNR.

Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of the prostate comprises sequential T1-weighted imaging (T1WI) acquisitions following injection of gadolinium-based contrast agent and aims to depict abnormal pharmacokinetics within tumorous regions (1). DCE has become a routine component of multiparametric prostate MRI protocols and improves the detection, localization, and staging of prostate cancer (2,3). Findings on DCE have been incorporated into standardized reporting schemes for prostate MRI (2) and are useful for guiding prostate biopsy (4), planning treatment (5), and monitoring posttherapy recurrences (6). One challenge in the implementation of DCE in the prostate is the inherent trade-off between spatial and temporal resolution in MRI (Table 1) (7–9). As the prostate is often highly vascular, differences in enhancement kinetics between benign and malignant regions can be subtle, such that high temporal resolution can assist in their differentiation (1). Indeed, recent expert guidelines advise a temporal resolution of at least 15 seconds (2). Nonetheless, many investigations report a considerably higher temporal resolution, in some instances under 3 seconds per acquisition (10). A higher temporal resolution is also essential for advanced pharmacokinetic modeling requiring an arterial input function (11). However, as prostate tumors are frequently small in size, potentially measuring less than 1 cm (12), their precise depiction can be critical for guiding a targeted biopsy or treatment, and a higher spatial resolution may be preferred. To this end, other studies have achieved higher spatial resolution by using a temporal resolution as low as 30 seconds (13,14). Also influencing this balance between spatial and temporal resolution is the impact of acquisition parameters on anatomic coverage, tissue contrast, motion robustness, and other artifacts (7). Given these confounding factors, there is currently a lack of technical standardization for prostate DCE in clinical practice (7). Table 1 Representative Combinations of Spatial and Temporal Resolutions Reported for DCE-MRI of the Prostate Within the Recent Peer-Reviewed Literaturea A number of recent advances in 3D gradient-echo T1WI may be useful for addressing these challenges. Compressed sensing (CS) exploits spatial correlations within images or spatiotemporal correlations among sequentially acquired images to substantially accelerate acquisitions (15). CS requires randomly under-sampled k-space data, which are preferably acquired using non-Cartesian k-space sampling schemes such as radial trajectories (16). Furthermore, advanced reconstruction techniques allow for the synergistic combination of CS and parallel imaging for processing of DCE data (17), which collectively offers simultaneous high spatial and high temporal resolution. The use of an underlying radial k-space sampling technique for this approach additionally increases robustness with respect to motion artifacts (18,19). A robust combination of CS and parallel imaging for rapid continuous acquisition with flexible spatiotemporal resolution using the golden-angle radial sampling scheme (20,21) (termed Golden-angle RAdial Sparse Parallel, or GRASP, imaging) has recently been applied to perform high-quality multiphase DCE of the liver during free-breathing (22). The prostate may provide an ideal additional application of the GRASP technique. The high degree of spatiotemporal correlation of data over the course of a DCE acquisition facilitates the sparse data representations that form the basis of CS reconstruction. In addition, given the small size of prostate tumors, overlap in tumors’ enhancement characteristics with benign prostate, and presence of prostatic motion during an extended DCE acquisition, prostate DCE would stand to benefit greatly from the advantages offered by GRASP. Therefore, our aim in this study was to demonstrate the feasibility of performing high-spatiotemporal resolution DCE of the prostate by using GRASP and to compare image quality and lesion depiction between GRASP and conventional DCE in patients with biopsy-proven prostate cancer.