Purpose To introduce non‐rigid cardiac motion correction into a novel free‐running framework for the simultaneous acquisition of 3D whole‐heart myocardial and maps cine images, enabling 3‐min scan. Methods Data were acquired using golden‐angle radial readout interleaved with inversion recovery ‐preparation pulses. After translational respiratory motion, cardiac‐motion‐corrected reconstruction dictionary‐based low‐rank compression patch‐based regularization enabled mapping at any given phase...

Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment and management of adult patients with congenital heart disease (CHD). However, conventional techniques three-dimensional (3D) whole-heart acquisition involve long unpredictable scan times methods that accelerate scans via k-space undersampling often rely on iterative reconstructions. Deep-learning-based reconstruction have recently attracted much interest due to their capacity provide fast...

Abstract Shim coils used in magnetic resonance imaging and NMR to produce fields are commonly designed generate spherical harmonics, thus achieve accuracy over a region. Herein cylindrical basis set is presented as an alternative so better suit the coil geometry and, cases where it more closely matches cylinder, region of interest. Example winding patterns for selection functions this new derived using target field method. A computational approach taken determine their accuracy, found...

Recently, a free-running T1-T2 3D radial imaging sequence was proposed to enable simultaneous acquisition of T1 and T2 maps the hearth with isotropic spatial resolution. Here, we sought investigate feasibility this 1 mm3 resolution for characterization articular cartilage in scan time ~4 min. The approach evaluated on standardized phantom in-vivo healthy subjects, showing good agreement reference values.

Cardiac T1-T2 mapping provides information about focal and diffuse fibrosis inflammation of the myocardium. A recently proposed free-running 3D technique allows time efficient simultaneous whole-heart within a single scan, with retrospective respiratory motion correction. However, this approach loses temporal contrast evolution does not reconstruct multi-contrast images, which may carry useful clinical in patients myocardial infarction and, acute subacute thrombus. In work, we propose to...

A deep learning reconstruction framework, trained in an end-to-end fashion and incorporating both a non-rigid respiratory motion estimation network motion-informed model-based network, has been previously demonstrated to enable good quality images from seven-fold undersampled acquisitions for coronary magnetic resonance angiography applications. Herein, we apply the framework whole-heart MRI scans of patients with congenital heart disease, enabling fast 7×-accelerated achieving image...

Motivation: Whole-heart CMR with high isotropic spatial resolution involves long and unpredictable scan times. Goal(s): To propose validate a super-resolution motion-corrected reconstruction framework to enable accelerated high-resolution whole-heart from lower-resolution acquisitions. Approach: Low was treated as k-space down-sampling problem, enabling the adaptation of an end-to-end iterative deep-learning network reconstruction, previously demonstrated for undersampled CMRA. Results:...

Motivation: Low-field 0.55T knee imaging promises to provide more accessible assessment of injuries. Anatomic has been evaluated, however quantitative at not demonstrated. Goal(s): To investigate the feasibility 3D joint T1-T2 mapping for evaluation articular cartilage 0.55T. Approach: A free-running, 3D-radial sequence with golden-angle and spoiled gradient echo readout 1mm3 isotropic resolution was implemented using Pulseq mapping. Bloch simulations were used dictionary matching. Results:...

Motivation: Myocardial T1 and T2 mapping is crucial in the assessment of cardiovascular disease. 3D whole-heart joint T1/T2 approaches have been proposed, however they require long reconstruction times. Goal(s): By leveraging deep learning (DL)-based techniques, we aim to significantly reduce times for mapping, while maintaining high-quality results. Approach: Recently a group sparsity-based DL approach was proposed image undersampled multi-contrast MRI data. Here, propose extend this...

Motivation: SENSE-based reconstruction is challenging for clinical imaging when rotating the RRFCA into multiple positions; therefore, a novel calibration-free GRAPPA-based method was developed. Goal(s): To effectively reconstruct k-space data acquired from RRFCA, enhancing image quality compared to conventional stationary array without scan time penalty. Approach: Conventional GRAPPA extended by uncovering subset of radial grid cope with rotation RRFCA. Numerical and human brain images were...

Motivation: Cardiac CINE provides dynamic images of the heart for morphology and function assessment. Single-heartbeat enables faster acquisition times study rate variations, but conventional reconstruction methods incur significant computational cost. Goal(s): This aims to speed up single-heartbeat by using deep learning reconstruction. Approach: We propose a novel, rapid, end-to-end pipeline motion estimation motion-corrected with golden-angle radial acquisition. Results: The network...

Recent work has enabled the simultaneous acquisition of 3D myocardial T 1 and 2 maps with isotropic spatial resolution cardiac cine images from a ~10-minute scan. Herein, we propose to incorporate non-rigid motion correction into dictionary-based low-rank reconstruction scheme, allowing k-space data all phases be included in any given phase. Reconstructed without are presented demonstrate that reduction 30% acquired (~3-minute scan) can achieved while image quality is maintained.

Cardiac Magnetic Resonance Fingerprinting (MRF) produces co-registered, multi-parametric maps from highly accelerated acquisitions. Low rank methods leveraging temporal information have enabled undersampled MRF reconstructions. However, residual aliasing these reconstructions can potentially propagate through the framework into parametric maps. Region-Optimized Virtual coils recently been proposed for in conventional imaging, by suppressing unwanted sources of signal. Here we combine both...

Iterative reconstructions for multi-contrast multidimensional non-Cartesian MRI can require considerable computation time, with a large fraction dedicated to non-uniform fast Fourier transforms (NUFFTs). The Toeplitz approach has been previously shown allow NUFFT operations be replaced by computationally efficient (FFTs) without loss of accuracy. Herein, we combine this 3D low-rank cardiac-motion-corrected radial reconstruction patch-based regularisation achieve ~13.3-fold computational speed-up.

The recently developed single-element surface rotating radio-frequency coil (RRFC) for magnetic resonance imaging (MRI) is able to acquire signals from around the subject in manner of a multi-coil array, while exhibiting simplified construction and no size restrictions. Herein, we present novel image reconstruction algorithm data acquired with RRFC, which label WARF (a weighted-sum approach radial MRI RF coil). approaches problem by considering each pixel be weighted sum all k-space data,...