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Background Myocardial late gadolinium enhancement (LGE) MRI has become a standard clinical exam for characterizing myocardial viability after infarction and for assessing many nonischemic myocardial diseaseses. Typically, a 3D slab covering the myocardium is scanned within a single breath-hold. However, 3D LGE with sufficient resolution and slice coverage requires a long scan time and is challenging in cardiac patients with limited breath-hold capability. Recently, compressed sensing (CS) [1] has demonstrated the ability to further accelerate MRI on top of parallel imaging (PI) and has demonstrated promising results for 3D LGE [2]. This work intended to evaluate the feasibility of a CS-PI method based on ESPIRiT [3-5] and optimize its data acquisition for improving the robustness of 3D LGE with high acceleration.

Background Single-shot (SSH) pulse sequences in CMR are beneficial for rapid image acquisition that is robust to motion, especially in arrhythmic patients or poor breath-holders. However, this fast scanning technique trades scan time for a lower signal-to-noise ratio compared to conventional multi-shot acquisitions. Here we propose a motion-compensated denoising technique that improves the image quality from multiple free-breathing singleshot acquisitions.

Background Recently, 3D cine has gained attention due to its capability for single breath-hold volumetric measurement [1]. Nonetheless, conventional 2D cine maintains two intrinsic advantages, namely, its superior blood-myocardium contrast owing to blood in-flow effects and reduced SSFP banding artifacts with more localized slice-by-slice shimming. These advantages are more prominent at high field. This work intends to optimize a k-t acceleration method, kat ARC [2], for 2D cine and preliminarily investigate its performance vs. 3D cine at 3T.

Background Late Gadolinium Enhancement (LGE) allows imaging of infarction and cardiomyopathies by measuring the accumulation of contrast agent within the myocardium. The shortened T1 relaxation time compared to healthy myocardium is imaged by an inversion recovery (IR) prepared segmented fast gradient echo sequence in which pathology and fat show as bright signal. The fat signal can lead to misinterpretation and poor visualization of epicardial enhancement. In previous work fat was suppressed by using two appropriately timed fat-selective RF pulses which re-invert and invert fat signal [Foo et al., JMRI, 2007] but this technique was sensitive to off-resonance and heart rate variations. The goal of the present work is to make two improvements to fat-saturated LGE: (1) increase robustness against B0 and B1 variations by using asymmetric adiabatic RF pulses, and (2) increase robustness against heart rate variations through dynamic timing of fat-selective RF pulses.

Background Recently, 3D CINE phase-contrast MRI (4D Flow) has demonstrated potential for quantitative measurement of blood flow of the cardiovascular systems in the entire thoracic trunk [1]. However, the needs of 4D flow for high resolution, large volume coverage & respiratory gating render very long scan time. This work intended to improve the data acquisition efficiency of free-breathing cardiac 4D flow.

Background Residual background phase in cardiac phase-contrast (PC) imaging introduces velocity errors that bias quantitative flow measurements [1]. While the bias can be offset using static phantoms [2], improved workflow is realized if self-calibrated correction is performed by fitting the phase of static tissue from the in vivo images. However, the residual phase can be nonlinear in space and the vessels of interest, e.g. great vessels, are often far from any static tissue in the image. This means that a linear fit [3] can sometimes result in under-fitting, while fitting with higher spatial-orders can result in over-fitting. Methods We propose a nonlinear self-calibrated approach, which assumes a nonlinear shape. This follows observations that the residual phase is similar in shape to that of the concomitant field. Therefore as compared to linear fitting that uses 4 terms (constant + XYZ), the nonlinear-fit has 5 terms that also include the concomitant field. Further steps are taken to improve the fit, which include iterative removal of outliers that frequently occur at tissue boundaries, and weighting velocities from the quiescent cardiac phase more heavily to reduce effects from flow artifacts at systole. To prevent over