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.

This novel model-based reconstruction technique may become a new tool for clinical flow MRI in real time. Magn Reson Med 77:1082-1093, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

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.

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.

Abstract: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.

We investigate the effects of blood flow and extravascular tissue shearing on diffusing-wave spectroscopy (DWS) signals from deep tissue, using an ex vivo porcine kidney model perfused artificially at controlled arterial pressure and flow. Temporal autocorrelation functions g(1)(τ) of the multiply scattered light field show a decay which is described by diffusion for constant flow, with a diffusion coefficient scaling linearly with volume flow rate. Replacing blood by a non-scattering fluid reveals a flow-independent background dynamics of the extravascular tissue. For a sinusoidally driven perfusion, field autocorrelation functions g(1)(τ, t′) depend on the phase t′ within the pulsation cycle and are approximately described by diffusion. The effective diffusion coefficient Deff(t′) is modulated at the driving frequency in the presence of blood, showing coupling with flow rate; in the absence of blood, Deff(t′) is modulated at twice the driving frequency, indicating shearing of extravascular tissue as the origin of the DWS signal. For both constant and pulsatile flow the contribution of extravascular tissue shearing to the DWS signal is small.

The proposed phase unwrapping method for real-time flow MRI allows for measurements with reduced velocity encoding and increased VNR.

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.