Single breath-hold 3D cardiac T mapping using through-time spiral GRAPPA.

The quantification of cardiac T relaxation time holds great potential for the detection of various cardiac diseases. However, as a result of both cardiac and respiratory motion, only one two-dimensional T map can be acquired in one breath-hold with most current techniques, which limits its application for whole heart evaluation in routine clinical practice. In this study, an electrocardiogram (ECG)-triggered three-dimensional Look-Locker method was developed for cardiac T measurement.

Motion-Corrected Real-Time Cine Magnetic Resonance Imaging of the Heart: Initial Clinical Experience.

Objectives: Free-breathing real-time (RT) imaging can be used in patients with difficulty in breath-holding; however, RT cine imaging typically experiences poor image quality compared with segmented cine imaging because of low resolution. Here, we validate a novel unsupervised motion-corrected (MOCO) reconstruction technique for free-breathing RT cardiac images, called MOCO-RT. Motion-corrected RT uses elastic image registration to generate a single heartbeat of high-quality data from a free-breathing RT acquisition.

Real-time free-breathing cardiac imaging with self-calibrated through-time radial GRAPPA.

Purpose: Real-time free-breathing cardiac imaging with highly undersampled radial trajectories has previously been successfully demonstrated using calibrated radial generalized autocalibrating partially parallel acquisition (rGRAPPA). A self-calibrated approach for rGRAPPA is proposed that removes the need for the calibration prescan.

Methods: To investigate the effect of various parameters on image quality, a comprehensive imaging study on one normal swine was performed.

SVD compression for magnetic resonance fingerprinting in the time domain.

Magnetic resonance (MR) fingerprinting is a technique for acquiring and processing MR data that simultaneously provides quantitative maps of different tissue parameters through a pattern recognition algorithm. A predefined dictionary models the possible signal evolutions simulated using the Bloch equations with different combinations of various MR parameters and pattern recognition is completed by computing the inner product between the observed signal and each of the predicted signals within the dictionary. Though this matching algorithm has been shown to accurately predict the MR parameters of interest, one desires a more efficient method to obtain the quantitative images.

Quantitative high-resolution renal perfusion imaging using 3-dimensional through-time radial generalized autocalibrating partially parallel acquisition.

Objectives: Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) examinations of the kidneys provide quantitative information on renal perfusion and filtration. However, these examinations are often difficult to implement because of respiratory motion and their need for a high spatiotemporal resolution and 3-dimensional coverage. Here, we present a free-breathing quantitative renal DCE-MRI examination acquired with a highly accelerated stack-of-stars trajectory and reconstructed with 3-dimensional (3D) through-time radial generalized autocalibrating partially parallel acquisition (GRAPPA), using half and quarter doses of gadolinium contrast.

Real-time imaging with radial GRAPPA: Implementation on a heterogeneous architecture for low-latency reconstructions.

Combination of non-Cartesian trajectories with parallel MRI permits to attain unmatched acceleration rates when compared to traditional Cartesian MRI during real-time imaging. However, computationally demanding reconstructions of such imaging techniques, such as k-space domain radial generalized auto-calibrating partially parallel acquisitions (radial GRAPPA) and image domain conjugate gradient sensitivity encoding (CG-SENSE), lead to longer reconstruction times and unacceptable latency for online real-time MRI on conventional computational hardware. Though CG-SENSE has been shown to work with low-latency using a general purpose graphics processing unit (GPU), to the best of our knowledge, no such effort has been made for radial GRAPPA.

RT-GROG: parallelized self-calibrating GROG for real-time MRI.

A real-time implementation of self-calibrating Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) operator gridding for radial acquisitions is presented. Self-calibrating GRAPPA operator gridding is a parallel-imaging-based, parameter-free gridding algorithm, where coil sensitivity profiles are used to calculate gridding weights. Self-calibrating GRAPPA operator gridding's weight-set calculation and image reconstruction steps are decoupled into two distinct processes, implemented in C++ and parallelized.

Interventional MRI using multiple 3D angiography roadmaps with real-time imaging.

Purpose: To enhance real-time magnetic resonance (MR)-guided catheter navigation by overlaying colorized multiphase MR angiography (MRA) and cholangiopancreatography (MRCP) roadmaps in an anatomic context.

Materials And Methods: Time-resolved MRA and respiratory-gated MRCP were acquired prior to real-time imaging in a pig model. MRA and MRCP data were loaded into a custom real-time MRI reconstruction and visualization workstation where they were displayed as maximum intensity projections (MIPs) in distinct colors.

Visualization of active devices and automatic slice repositioning ("SnapTo") for MRI-guided interventions.

The accurate visualization of interventional devices is crucial for the safety and effectiveness of MRI-guided interventional procedures. In this paper, we introduce an improvement to the visualization of active devices. The key component is a fast, robust method ("CurveFind") that reconstructs the three-dimensional trajectory of the device from projection images in a fraction of a second.

HTGRAPPA: real-time B1-weighted image domain TGRAPPA reconstruction.

The temporal generalized autocalibrating partially parallel acquisitions (TGRAPPA) algorithm for parallel MRI was modified for real-time low latency imaging in interventional procedures using image domain, B(1)-weighted reconstruction. GRAPPA coefficients were calculated in k-space, but applied in the image domain after appropriate transformation. Convolution-like operations in k-space were thus avoided, resulting in improved reconstruction speed.

Parallelized hybrid TGRAPPA reconstruction for real-time interactive MRI.

Real-time parallel MRI reconstruction was demonstrated using a hybrid implementation of the TGRAPPA algorithm. The GRAPPA coefficients were calculated in k-space and applied in the image domain after appropriate transformation, thereby achieving improved speed and excellent image quality. Adaptive B1-weighted combining of the per coil images permitted use of pre-calculated composite image domain weights providing significant decrease in computation.