Estimation of Left Ventricular Motion from Cardiac Gated Tagged MRI Using an Image-Matching Deformable Mesh Model

In this paper, we propose a deformable mesh model (DMM) method for left-ventricular (LV) motion-estimation from cardiac-gated tagged magnetic resonance imaging (MRI). DMM starts by partitioning short-axis (SA) and long-axis (LA) images at end-diastole (ED) in a collection of non-overlapping mesh elements (triangles). Next, mesh elements are deformed attempting to track temporal changes in pixel intensities by minimizing an image-matching cost function from frame to frame. Finally, dense motion fields can be obtained at any frame from the displacement of mesh nodes, without any additional user interaction. For validation, 23 human tagged MRI studies were used, allocated as 7 normal, 9 hypertensive (HTN), and 7 with mitral regurgitation (MR). DMM end-systolic (ES) motion and strains were quantitatively compared to a “gold-standard” feature-based (FB) motion analysis method that includes manual tagline editing. DMM motion achieves subpixel average displacement error of SA landmarks with respect to FB. 3-D ES strains obtained from DMM correlate well with FB method ( $\rho $ ranging from 0.79 to 0.97). Finally, we show temporal curves for several DMM strain components, grouped according to the condition of patients (normal and diseased). These curves are qualitatively compared to a strain from unwrapped harmonic phase motion estimation algorithm. DMM produces robust temporal curves, which capture strain fluctuations reported in medical literature for HTN and MR conditions. This makes it a viable alternative to analyze motion from images at phases suffering from low contrast-to-noise ratio that may convey important information about the presence of certain cardiac pathologies.