Correction of gradient-induced phase errors in radial MRI.

Purpose To correct gradient-induced phase errors in radial MRI. Methods Gradient-induced eddy currents affect the MRI data acquisition by gradient delays and phase errors that may lead to severe image artifacts for non-Cartesian imaging scenarios such as radial trajectories. While gradient delays are dealt with by respective shifts of the acquisition window during radial image acquisition, this work introduces a simple method for quantifying and correcting phase errors from the actual data prior to image reconstruction. For a given gradient system, the approach yields a specific phase error per gradient that can be used for correcting the raw data. Results Phantom studies at 9.4 T demonstrated marked improvements in radial image quality. It could be shown that the phase correction is not compromised by data undersampling. Moreover, the selective correction of gradient-induced phase errors retained the phase information caused by different concentrations of a paramagnetic contrast agent. Conclusion The proposed method does not require additional reference measurements and separately corrects for phase errors induced by eddy currents, while retaining the residual phase of the object which may carry physiologic information

Spatiotemporal phase unwrapping for real-time phase-contrast flow MRI

Purpose: To develop and evaluate a practical phase unwrapping method for real-time phase-contrast flow MRI using temporal and spatial continuity. Methods: Real-time phase-contrast MRI of through-plane flow was performed using highly undersampled radial FLASH with phase-sensitive reconstructions by regularized nonlinear inversion. Experiments involved flow in a phantom and the human aorta (10 healthy subjects) with and without phase wrapping for velocity encodings of 100 cms1 and 200 cms1. Phase unwrapping was performed for each individual cardiac cycle and restricted to a region of interest automatically propagated to all time frames. The algorithm exploited temporal continuity in forward and backward direction for all pixels with a “continuous” representation of blood throughout the entire cardiac cycle (inner vessel lumen). Phase inconsistencies were corrected by a comparison with values from direct spatial neighbors. The latter approach was also applied to pixels exhibiting a discontinuous signal intensity time course due to movement-induced spatial displacements (peripheral vessel zone). Results: Phantom and human flow MRI data were successfully unwrapped. When halving the velocity encoding, the velocity-to-noise ratio (VNR) increased by a factor of two. Conclusion: The proposed phase unwrapping method for real-time flow MRI allows for measurements with reduced velocity encoding and increased VNR

Model-based reconstruction for real-time phase-contrast flow MRI: Improved spatiotemporal accuracy.

PURPOSE: To develop a model-based reconstruction technique for real-time phase-contrast flow MRI with improved spatiotemporal accuracy in comparison to methods using phase differences of two separately reconstructed images with differential flow encodings. METHODS: The proposed method jointly computes a common image, a phase-contrast map, and a set of coil sensitivities from every pair of flow-compensated and flow-encoded datasets obtained by highly undersampled radial FLASH. Real-time acquisitions with five and seven radial spokes per image resulted in 25.6 and 35.7 ms measuring time per phase-contrast map, respectively. The signal model for phase-contrast flow MRI requires the solution of a nonlinear inverse problem, which is accomplished by an iteratively regularized Gauss-Newton method. Aspects of regularization and scaling are discussed. The model-based reconstruction was validated for a numerical and experimental flow phantom and applied to real-time phase-contrast MRI of the human aorta for 10 healthy subjects and 2 patients. RESULTS: Under all conditions, and compared with a previously developed real-time flow MRI method, the proposed method yields quantitatively accurate phase-contrast maps (i.e., flow velocities) with improved spatial acuity, reduced phase noise and reduced streaking artifacts. CONCLUSION: This novel model-based reconstruction technique may become a new tool for clinical flow MRI in real time

Model-based reconstruction for T1 mapping using single-shot inversion-recovery radial FLASH.

Quantitative parameter mapping in MRI is typically performed as a two-step procedure where serial imaging is followed by pixelwise model fitting. In contrast, model-based reconstructions directly reconstruct parameter maps from raw data without explicit image reconstruction. Here, we propose a method that determines T1 maps directly from multi-channel raw data as obtained by a single-shot inversion-recovery radial FLASH acquisition with a Golden Angle view order. Joint reconstruction of a T1, spin-density and flip-angle map is formulated as a nonlinear inverse problem and solved by the iteratively regularized Gauss-Newton method. Coil sensitivity profiles are determined from the same data in a preparatory step of the reconstruction. Validations included numerical simulations, in vitro MRI studies of an experimental T1 phantom, and in vivo studies of brain and abdomen of healthy subjects at a field strength of 3 T. The results obtained for a numerical and experimental phantom demonstrated excellent accuracy and precision of model-based T1 mapping. In vivo studies allowed for high-resolution T1 mapping of human brain (0.5–0.75 mm in-plane, 4 mm section thickness) and liver (1.0 mm, 5 mm section) within 3.6–5 s. In conclusion, the proposed method for model-based T1 mapping may become an alternative to two-step techniques, which rely on model fitting after serial image reconstruction. More extensive clinical trials now require accelerated computation and online implementation of the algorithm

Advances in real-time phase-contrast flow MRI using asymmetric radial gradient echoes.

Purpose: To provide multidimensional velocity compensation for real-time phase-contrast flow MRI. Methods: The proposed method introduces asymmetric gradi- ent echoes for highly undersampled radial FLASH MRI with phase-sensitive image reconstruction by regularized nonlinear inversion (NLINV). Using an adapted gradient delay correction the resulting image quality was analyzed by simulations and experimentally validated at 3 Tesla. For real-time flow MRI the reduced gradient-echo timing allowed for the incorporation of velocity-compensating waveforms for all imaging gradients at even shorter repetition times. Results: The results reveal a usable degree of 20% asymme- try. Real-time flow MRI with full velocity compensation elimi- nated signal void in a flow phantom, confirmed flow parameters in healthy subjects and demonstrated signal recovery and phase conservation in a patient with aortic valve insufficiency and stenosis. Exemplary protocols at 1.4–1.5 mm resolution and 6 mm slice thickness achieved total acquisition times of 33.3–35.7 ms for two images (7 spokes each) with and without flow-encoding gradient. Conclusion: Asymmetric gradient echoes were successfully implemented for highly undersampled radial trajectories. The resulting temporal gain offers full velocity compensation for real-time phase-contrast flow MRI which minimizes false- positive contributions from complex flow and further enhances the temporal resolution compared with acquisitions with symmetric echoes

Rapid diffusion-weighted magnetic resonance imaging of the brain without susceptibility artifacts: Single-shot STEAM with radial undersampling and iterative reconstruction.

OBJECTIVE: The aim of this study was to develop a rapid diffusion-weighted (DW) magnetic resonance imaging (MRI) technique for whole-brain studies without susceptibility artifacts and measuring times below 3 minutes. MATERIALS AND METHODS: The proposed method combines a DW spin-echo module with a single-shot stimulated echo acquisition mode MRI sequence. Previous deficiencies in image quality due to limited signal-to-noise ratio are compensated for (1) by radial undersampling to enhance the flip angle and thus the signal strength of stimulated echoes; (2) by defining the image reconstruction as a nonlinear inverse problem, which is solved by the iteratively regularized Gauss-Newton method; and (3) by denoising with use of a modified nonlocal means filter. The method was implemented on a 3 T MRI system (64-channel head coil, 80 mT · m gradients) and evaluated for 10 healthy subjects and 2 patients with an ischemic lesion and epidermoid cyst, respectively. RESULTS: High-quality mean DW images of the entire brain were obtained by acquiring 1 non-DW image and 6 DW images with different diffusion directions at b = 1000 s · mm. The achievable resolution for a total measuring time of 84 seconds was 1.5 mm in plane with a section thickness of 4 mm (55 sections). A measuring time of 168 seconds allowed for an in-plane resolution of 1.25 mm and a section thickness of 3 mm (54 sections). Apparent diffusion coefficient values were in agreement with literature data. CONCLUSIONS: The proposed method for DW MRI offers immunity against susceptibility problems, high spatial resolution, adequate signal-to-noise ratio and clinically feasible scan times of less than 3 minutes for whole-brain studies. More extended clinical trials require accelerated computation and online reconstruction

On the temporal fidelity of nonlinear inverse reconstructions for real- time MRI – The motion challenge.

Purpose: To evaluate the temporal accuracy of a self-consistent nonlinear inverse reconstruction method (NLINV) for real-time MRI using highly undersampled radial gradient-echo sequences and to present an open source framework for the motion assessment of real-time MRI methods. Methods: Serial image reconstructions by NLINV combine a joint estimation of individual frames and corresponding coil sensitivities with temporal regularization to a preceding frame. The temporal fidelity of the method was determined with a phantom consisting of water-filled tubes rotating at defined angular velocity. The conditions tested correspond to realtime cardiac MRI using SSFP contrast at 1.5 T (40 ms resolution) and T1 contrast at 3.0 T (33 ms and 18 ms resolution). In addition, the performance of a post-processing temporal median filter was evaluated. Results: NLINV reconstructions without temporal filtering yield accurate estimations as long as the speed of a small moving object corresponds to a spatial displacement during the acquisition of a single frame which is smaller than the object itself. Faster movements may lead to geometric distortions. For small objects moving at high velocity, a median filter may severely compromise the spatiotemporal accuracy. Conclusion: NLINV reconstructions offer excellent temporal fidelity as long as the image acquisition time is short enough to adequately sample (“freeze”) the object movement. Temporal filtering should be applied with caution. The motion framework emerges as a valuable tool for the evaluation of real-time MRI methods

Dynamic water/fat separation and B₀ inhomogeneity mapping-joint estimation using undersampled triple-echo multi-spoke radial FLASH.

PURPOSE: To achieve dynamic water/fat separation and B0 field inhomogeneity mapping via model-based reconstructions of undersampled triple-echo multi-spoke radial FLASH acquisitions. METHODS: This work introduces an undersampled triple-echo multi-spoke radial FLASH sequence, which uses (i) complementary radial spokes per echo train for faster spatial encoding, (ii) asymmetric echoes for flexible and nonuniform echo spacing, and (iii) a golden angle increment across frames for optimal k-space coverage. Joint estimation of water, fat, B0 inhomogeneity, and coil sensitivity maps from undersampled triple-echo data poses a nonlinear and non-convex inverse problem which is solved by a model-based reconstruction with suitable regularization. The developed methods are validated using phantom experiments with different degrees of undersampling. Real-time MRI studies of the knee, liver, and heart are conducted without prospective gating or retrospective data sorting at temporal resolutions of 70, 158, and 40 ms, respectively. RESULTS: Up to 18-fold undersampling is achieved in this work. Even in the presence of rapid physiological motion, large B0 field inhomogeneities, and phase wrapping, the model-based reconstruction yields reliably separated water/fat maps in conjunction with spatially smooth inhomogeneity maps. CONCLUSIONS: The combination of a triple-echo acquisition and joint reconstruction technique provides a practical solution to time-resolved and motion robust water/fat separation at high spatial and temporal resolution