Abstract
Cardiac Magnetic Resonance Imaging (MRI) allows quantifying myocardial tissue deformation and strain based on the tagging principle. In this work, we investigate accuracy and precision of strain quantification from synthetic 3D tagged MRI using equilibrated warping. To this end, synthetic biomechanical left-ventricular tagged MRI data with varying tag distance, spatial resolution and signal-to-noise ratio (SNR) were generated and processed to quantify errors in radial, circumferential and longitudinal strains relative to ground truth. Results reveal that radial strain is more sensitive to image resolution and noise than the other strain components. The study also shows robustness of quantifying circumferential and longitudinal strain in the presence of geometrical inconsistencies of 3D tagged data. In conclusion, our study points to the need for higher-resolution 3D tagged MRI than currently available in practice in order to achieve sufficient accuracy of radial strain quantification.
Highlights
The noninvasive assessment of myocardial function represents an important diagnostic tool in the clinic
Nel i1⁄41 i where eavg and estd are the mean and standard deviation in strain error for component s, which is a scalar field, while sireg and siref are the strain values at element i at end-systolic time frame for the registered case and the ground truth, respectively. We investigate both the individual and combined effects of two image characteristics, Tag distance to Pixel size Ratio (TPR) and signal-to-noise ratio (SNR) on images with isotropic (Fig 2) and anisotropic (Fig 3) spatial resolution
We have investigated the effect of image resolution, tag distance and SNR on deformation quantification from 3D tagged images and have illustrated the challenges in quantifying radial strain
Summary
The noninvasive assessment of myocardial function represents an important diagnostic tool in the clinic. Beyond cine Magnetic Resonance Imaging (MRI), a number of dedicated approaches to quantify ventricular tissue motion and strains have been proposed, including phase contrast [1], tissue tagging [2], displacement encoding [3] and strain encoding [4]. A number of improvements have been proposed [5, 7,8,9,10] and the method has been shown to reveal alterations in myocardial function for a variety of pathologies including ischemic heart disease [11, 12], aortic stenosis [13], cardiac hypertrophy [14], left bundle branch block [15], cardiomyopathy [16] and coronary artery disease [17], among others. While direct methods aim to extract tag features using image filtering and segmentation approaches [19], Fourier-based methods
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