Bi-ventricular elastic material parameters estimation using 3D CMR myocardial strains in rheumatic heart disease patients

Abstract

Understanding the elastic material behavior of myocardium during the diastolic phase is critical for evaluating cardiac function and improving treatments for diastolic abnormalities. This study introduces a novel multi-objective optimization framework that incorporates both strain and volume measurements to enhance the accuracy of myocardial property assessments in Rheumatic Heart Disease (RHD) patients and healthy controls. By employing global volume and strain measurements instead of segmented strains from the sixteen AHA regions, we achieve a robust alignment with the Klotz curve across all groups, indicating an accurate simulation of end-diastolic pressure–volume relationships (EDPVRs). Our approach uniquely integrates combinations of longitudinal, circumferential, and radial strains, resulting in an unprecedented reduction in errors between clinical and simulated strain values, with less than one percent difference for targeted parameters. The results demonstrate that the alignment between computational predictions and clinical measurements depends significantly on the choice of optimization target. The study reveals significant differences in tissue mechanics between RHD patients and healthy controls, with notable variations in ventricular stiffness and fiber orientations across optimization targets, confirmed through rigorous statistical analyses. The observed variations in fiber angles, particularly the smaller angles for longitudinal strains and steeper angles for circumferential strains, underscore the intricate relationship between myocardial fiber architecture and cardiac deformation, offering deeper insights into ventricular biomechanics. By presenting qualitative and quantitative differences in stress and strain distributions, this research advances the understanding of myocardial mechanics, highlighting the clinical relevance of fiber orientation and material properties in modeling cardiac mechanics and distinguishing diseased from healthy myocardial behavior.