Assessing the impact of the mechanical parameters on the estimation of myocardial passive stiffness.

Abstract

Passive myocardial stiffness of the left ventricle is a promising biomarker for the early detection of cardiotoxicity and heart failure. It can be estimated non-invasively through inverse optimization, using patient-specific finite element models, derived from Magnetic Resonance Imaging. A key step is defining the myocardium's constitutive law. Guccione transversely-isotropic Fung-type law is widely used. It includes a global stiffness parameter to be estimated, and three anisotropy parameters (b_f, b_t, b_ft) whose values vary significantly across studies, complicating parameters selection. This study investigates how anisotropy parameters influence myocardial stiffness estimation. First, biaxial extension and triaxial shear tests were simulated using finite element models, to analyze each parameter's effect on tissue behavior and compare published parameter sets. Then their impact on the displacement fields was studied using an idealized left ventricle geometry. Finally, the impact of the parameter sets on stiffness estimation was evaluated using six patient-specific finite element models. Results showed that varying the anisotropy parameters significantly affected both local tissue behavior and global ventricular mechanics. Within the studied range of variation, b_t had the most pronounced impact, and b_ft had the least impact. Parameter set choice also affected significantly the estimation of stiffness, though no set led to a significantly lower residual error. These findings help clarify how variability in constitutive parameters affects myocardial stiffness estimates. They represent a key step in the methodological framework by guiding parameter selection and interpretation, thereby supporting a more consistent and informed use of stiffness metrics in future research.