Purpose To develop a fast and flexible free-breathing dynamic volumetric MRI technique, iterative Golden-angle RAdial Sparse Parallel MRI (iGRASP), that combines compressed sensing, parallel imaging, and golden-angle radial sampling. Methods Radial k-space data are acquired continuously using the golden-angle scheme and sorted into time series by grouping an arbitrary number of consecutive spokes into temporal frames. An iterative reconstruction procedure is then performed on the undersampled time series where joint multicoil sparsity is enforced by applying a total-variation constraint along the temporal dimension. Required coil-sensitivity profiles are obtained from the time-averaged data. Results iGRASP achieved higher acceleration capability than either parallel imaging or coil-by-coil compressed sensing alone. It enabled dynamic volumetric imaging with high spatial and temporal resolution for various clinical applications, including free-breathing dynamic contrast-enhanced imaging in the abdomen of both adult and pediatric patients, and in the breast and neck of adult patients. Conclusion The high performance and flexibility provided by iGRASP can improve clinical studies that require robustness to motion and simultaneous high spatial and temporal resolution.

Purpose To develop a novel framework for free-breathing MRI called XD-GRASP, which sorts dynamic data into extra motion-state dimensions using the self-navigation properties of radial imaging and reconstructs the multidimensional dataset using compressed sensing. Methods Radial k-space data are continuously acquired using the golden-angle sampling scheme and sorted into multiple motion-states based on respiratory and/or cardiac motion signals derived directly from the data. The resulting under-sampled multidimensional dataset is reconstructed using a compressed sensing approach that exploits sparsity along the new dynamic dimensions. The performance of XD-GRASP is demonstrated for free-breathing three-dimensional (3D) abdominal imaging, two-dimensional (2D) cardiac cine imaging and 3D dynamic contrast-enhanced (DCE) MRI of the liver, comparing against reconstructions without motion sorting in both healthy volunteers and patients. Results XD-GRASP separates respiratory motion from cardiac motion in cardiac imaging, and respiratory motion from contrast enhancement in liver DCE-MRI, which improves image quality and reduces motion-blurring artifacts. Conclusion XD-GRASP represents a new use of sparsity for motion compensation and a novel way to handle motions in the context of a continuous acquisition paradigm. Instead of removing or correcting motion, extra motion-state dimensions are reconstructed, which improves image quality and also offers new physiological information of potential clinical value.

Purpose To apply the low-rank plus sparse (L+S) matrix decomposition model to reconstruct undersampled dynamic MRI as a superposition of background and dynamic components in various problems of clinical interest. Theory and Methods The L+S model is natural to represent dynamic MRI data. Incoherence between k−t space (acquisition) and the singular vectors of L and the sparse domain of S is required to reconstruct undersampled data. Incoherence between L and S is required for robust separation of background and dynamic components. Multicoil L+S reconstruction is formulated using a convex optimization approach, where the nuclear-norm is used to enforce low-rank in L and the l1-norm to enforce sparsity in S. Feasibility of the L+S reconstruction was tested in several dynamic MRI experiments with true acceleration including cardiac perfusion, cardiac cine, time-resolved angiography, abdominal and breast perfusion using Cartesian and radial sampling. Results The L+S model increased compressibility of dynamic MRI data and thus enabled high acceleration factors. The inherent background separation improved background suppression performance compared to conventional data subtraction, which is sensitive to motion. Conclusion The high acceleration and background separation enabled by L+S promises to enhance spatial and temporal resolution and to enable background suppression without the need of subtraction or modeling.

First-pass cardiac perfusion MRI is a natural candidate for compressed sensing acceleration since its representation in the combined temporal Fourier and spatial domain is sparse and the required incoherence can be effectively accomplished by k-t random undersampling. However, the required number of samples in practice (three to five times the number of sparse coefficients) limits the acceleration for compressed sensing alone. Parallel imaging may also be used to accelerate cardiac perfusion MRI, with acceleration factors ultimately limited by noise amplification. In this work, compressed sensing and parallel imaging are combined by merging the k-t SPARSE technique with sensitivity encoding (SENSE) reconstruction to substantially increase the acceleration rate for perfusion imaging. We also present a new theoretical framework for understanding the combination of k-t SPARSE with SENSE based on distributed compressed sensing theory. This framework, which identifies parallel imaging as a distributed multisensor implementation of compressed sensing, enables an estimate of feasible acceleration for the combined approach. We demonstrate feasibility of 8-fold acceleration in vivo with whole-heart coverage and high spatial and temporal resolution using standard coil arrays. The method is relatively insensitive to respiratory motion artifacts and presents similar temporal fidelity and image quality when compared to Generalized autocalibrating partially parallel acquisitions (GRAPPA) with 2-fold acceleration. Magn Reson Med 64:767-776,

Objective The objectives of this study were to develop a new method for free-breathing contrast-enhanced multiphase liver magnetic resonance imaging (MRI) using a combination of compressed sensing, parallel imaging, and radial k-space sampling and to demonstrate the feasibility of this method by performing image quality comparison with breath-hold cartesian T1-weighted (conventional) postcontrast acquisitions in healthy participants. Materials and Methods This Health Insurance Portability and Accountability Act–compliant prospective study received approval from the institutional review board. Eight participants underwent 3 separate contrast-enhanced fat-saturated T1-weighted gradient-echo MRI examinations with matching imaging parameters: conventional breath-hold examination with cartesian k-space sampling volumetric interpolate breath hold examination (BH-VIBE) and free-breathing acquisitions with interleaved angle-bisection and continuous golden-angle radial sampling schemes. Interleaved angle-bisection and golden-angle data from each 100 consecutive spokes were reconstructed using a combination of compressed sensing and parallel imaging (interleaved-angle radial sparse parallel [IARASP] and golden-angle radial sparse parallel [GRASP]) to generate multiple postcontrast phases. Arterial- and venous-phase BH-VIBE, IARASP, and GRASP reconstructions were evaluated by 2 radiologists in a blinded fashion. The readers independently assessed quality of enhancement (QE), overall image quality (IQ), and other parameters of image quality on a 5-point scale, with the highest score indicating the most desirable examination. Mixed model analysis of variance was used to compare each measure of image quality. Results Images of BH-VIBE and GRASP had significantly higher QE and IQ values compared with IARASP for both phases (P < 0.05). The differences in QE between BH-VIBE and GRASP for the arterial and venous phases were not significant (P > 0.05). Although GRASP had lower IQ score compared with BH-VIBE for the arterial (3.9 vs 4.8; P < 0.0001) and venous (4.2 vs 4.8; P = 0.005) phases, GRASP received IQ scores of 3 or more in all participants, which was consistent with acceptable or better diagnostic image quality. Conclusion Contrast-enhanced multiphase liver MRI of diagnostic quality can be performed during free breathing using a combination of compressed sensing, parallel imaging, and golden-angle radial sampling.

For patients with impaired breath-hold capacity and/or arrhythmias, real-time cine MRI may be more clinically useful than breath-hold cine MRI. However, commercially available real-time cine MRI methods using parallel imaging typically yield relatively poor spatio-temporal resolution due to their low image acquisition speed. We sought to achieve relatively high spatial resolution (~2.5mm × 2.5mm) and temporal resolution (~40ms), to produce high-quality real-time cine MR images that could be applied clinically for wall motion assessment and measurement of left ventricular (LV) function. In this work, we present an 8-fold accelerated real-time cardiac cine MRI pulse sequence using a combination of compressed sensing and parallel imaging (k-t SPARSE-SENSE). Compared with reference, breath-hold cine MRI, our 8-fold accelerated real-time cine MRI produced significantly worse qualitative grades (1–5 scale), but its image quality and temporal fidelity scores were above 3.0 (adequate) and artifacts and noise scores were below 3.0 (moderate), suggesting that acceptable diagnostic image quality can be achieved. Additionally, both 8-fold accelerated real-time cine and breath-hold cine MRI yielded comparable LV function measurements, with coefficient of variation < 10% for LV volumes. Our proposed 8-fold accelerated real-time cine MRI with k-t SPARSE-SENSE is a promising modality for rapid imaging of myocardial function.

5D whole-heart sparse imaging represents a robust and promising framework for simplified comprehensive cardiac MRI without the need for breath-hold and motion correction. Magn Reson Med 79:826-838, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

In this multicenter study, 2D spatial mapping of J-coupled resonances at 3T and 4T was performed using short-TE (15 ms) proton echo-planar spectroscopic imaging (PEPSI). Water-suppressed (WS) data were acquired in 8.5 min with 1-cm 3 spatial resolution from a supraventricular axial slice. Optimized outer volume suppression (OVS) enabled mapping in close proximity to peripheral scalp regions. Constrained spectral fitting in reference to a non-WS (NWS) scan was performed with LCModel using correction for relaxation attenuation and partial-volume effects. The concentrations of total choline (tCho), creatine ؉ phosphocreatine (Cr؉PCr), glutamate (Glu), glutamate ؉ glutamine (Glu؉Gln), myo-inositol (Ins), NAA, NAA؉NAAG, and two macromolecular resonances at 0.9 and 2.0 ppm were mapped with mean Cramer-Rao lower bounds (CRLBs) between 6% and 18% and ϳ150-cm 3 sensitive volumes. Aspartate, GABA, glutamine (Gln), glutathione (GSH), phosphoethanolamine (PE), and macromolecules (MMs) at 1.2 ppm were also mapped, although with larger mean CRLBs between 30% and 44%. The CRLBs at 4T were 19% lower on average as compared to 3T, consistent with a higher signal-to-noise ratio (SNR) and increased spectral resolution. Metabolite concentrations were in the ranges reported in previous studies. Glu concentration was significantly higher in gray matter (GM) compared to white matter ( Key words: magnetic resonance spectroscopic imaging; proton echo planar spectroscopic imaging; glutamate; spectral quantification; human brain Proton magnetic resonance spectroscopic mapping ( 1 H-MRSI) of brain metabolites can identify biomarkers relevant to psychiatric and neurological disease. There is currently increasing interest in extending 1 H-MRSI techniques and processing capabilities to map J-coupled brain metabolite resonances. Glutamate (Glu) and glutamine (Gln) mapping is of particular interest because these metabolites are key components of energy metabolism and nitrogen homeostasis pathways, and are also involved in excitatory synaptic neurotransmission (1). In vivo mapping of Glu in clinically feasible acquisition times may have important diagnostic applications in psychiatric disorders (2,3) and studies of aging (4).Thus far, Glu and Gln have been studied mostly by single-voxel MR spectroscopy (MRS) using a variety of techniques, including model-based fitting of short-TE spectra (4 -7), use of optimized intermediate TE (8) and Carr-Purcell refocusing pulses (9), spectral editing (10), and 2D J-resolved spectroscopy (11,12). MRSI studies of Glu and Gln have used spectral fitting at short TE (13,14), J-refocused coherence transfer (15), and, more recently, 2D J-resolved spectroscopic imaging (16,17). Spectral editing and 2D J-resolved MRSI techniques enable highly selective mapping of Glu and Gln, but they require multistep encoding, which prolongs the acquisition times and limits the sensitivity gains at high field, as metabolite T 2 values have been shown to decrease with field strength (18,19). Short-TE acquisition of single-voxel spect...