Temporospatial characterization of ventricular wall motion with real-time cardiac magnetic resonance imaging in health and disease.

Cardiac magnetic resonance imaging (MRI) has been largely dependent on retrospective cine for data acquisition. Real-time imaging, although inferior in image quality to retrospective cine, is more informative about motion dynamics. We herein developed a real-time cardiac MRI approach to temporospatial characterization of left ventricle (LV) and right ventricle (RV) wall motion. This approach provided two temporospatial indices, temporal periodicity and spatial coherence, for quantitative assessment of ventricular function. In a cardiac MRI study, we prospectively investigated temporospatial characterization in reference to standard volumetric measurements with retrospective cine. The temporospatial indices were found to be effective for evaluating the difference of ventricular performance between the healthy volunteers and the heart failure (HF) patients (LV temporal periodicity 0.24 ± 0.037 vs. 0.14 ± 0.021; RV temporal periodicity 0.18 ± 0.030 vs. 0.10 ± 0.014; LV spatial coherence 0.52 ± 0.039 vs. 0.38 ± 0.040; RV spatial coherence 0.50 ± 0.036 vs. 0.35 ± 0.035; all in arbitrary unit). The HF patients and healthy volunteers were well differentiated in the scatter plots of spatial coherence and temporal periodicity while they were mixed in those of end-systolic volume (ESV) and ejection fraction (EF) from volumetric measurements. This study demonstrated the potential of real-time cardiac MRI for intricate analysis of ventricular function beyond retrospective cine.

Real-time exercise stress cardiac MRI with Fourier-series reconstruction from golden-angle radial data.

Magnetic resonance imaging (MRI) can measure cardiac response to exercise stress for evaluating and managing heart patients in the practice of clinical cardiology. However, exercise stress cardiac MRI have been clinically limited by the ability of available MRI techniques to quantitatively measure fast and unstable cardiac dynamics during exercise. The presented work is to develop a new real-time MRI technique for improved quantitative performance of exercise stress cardiac MRI. This technique seeks to represent real-time cardiac images as a sparse Fourier-series along the time. With golden-angle radial acquisition, parallel imaging and compressed sensing can be integrated into a linear system of equations for resolving Fourier coefficients that are in turn used to generate real-time cardiac images from the Fourier-series representation. Fourier-series reconstruction from golden-angle radial data can effectively address data insufficiency due to MRI speed limitation, providing a real-time approach to exercise stress cardiac MRI. To demonstrate the feasibility, an exercise stress cardiac MRI experiment was run to investigate biventricular response to in-scanner biking exercise in a cohort of sixteen healthy volunteers. It was found that Fourier-series reconstruction from golden-angle radial data effectively detected exercise-induced increase in stroke volume and ejection fraction in a healthy heart. The presented work will improve the applications of exercise stress cardiac MRI in the practice of clinical cardiology.

Real-time cardiac MRI with radial acquisition and k-space variant reduced-FOV reconstruction.

This work aims to demonstrate that radial acquisition with k-space variant reduced-FOV reconstruction can enable real-time cardiac MRI with an affordable computation cost. Due to non-uniform sampling, radial imaging requires k-space variant reconstruction for optimal performance. By converting radial parallel imaging reconstruction into the estimation of correlation functions with a previously-developed correlation imaging framework, Cartesian k-space may be reconstructed point-wisely based on parallel imaging relationship between every Cartesian datum and its neighboring radial samples. Furthermore, reduced-FOV correlation functions may be used to calculate a subset of Cartesian k-space data for image reconstruction within a small region of interest, making it possible to run real-time cardiac MRI with an affordable computation cost. In a stress cardiac test where the subject is imaged during biking with a heart rate of >100 bpm, this k-space variant reduced-FOV reconstruction is demonstrated in reference to several radial imaging techniques including gridding, GROG and SPIRiT. It is found that the k-space variant reconstruction outperforms gridding, GROG and SPIRiT in real-time imaging. The computation cost of reduced-FOV reconstruction is ~2 times higher than that of GROG. The presented work provides a practical solution to real-time cardiac MRI with radial acquisition and k-space variant reduced-FOV reconstruction in clinical settings.