Quantifying Contributions of Cellular Mechanical Myocardial Properties on Left Ventricular Contractile Function in Aortic Banded Rats

Abstract

Left ventricular (LV) contractile dysfunction is known to be associated with altered cellular myocardial properties. Quantitative translation from cellular mechanical properties to whole-organ cardiomyopathy phenotype, however, is an ongoing challenge. To quantitatively map cell-level pathophysiology to whole-organ contractile function in aortic banded (AB) 6-weeks post-surgery rats (Røe et al. 2017), we consider an in silicomodel of LV hypertrophy which combines mathematical models of cellular electrophysiology and calcium dynamics, sarcomere contraction and whole-organ mechanics solved over geometries derived from control and AB rat hearts. The resulting multi-scale computationally expensive model is regulated by >100 parameters. To assess parameters impact on the model outputs we developed a computationally effective approach for global sensitivity analysis (GSA) of rat cardiac mechanics based on Gaussian process (GP) emulation. We identified eight key parameters regulating ventricular mechanics such as myofilament calcium sensitivity (Ca50), and described the LV contractile function using eleven measurements including ejection fraction (EF) and pressure-volume loop. We found Ca50 to be the most significant parameter in explaining the total variance in both the control and AB rat (56%, 53%, 56%, 57% of the total variance of EF, isovolumetric relaxation time, peak pressure and maximum pressure rise rate, respectively, in control, and 65%, 47%, 58%, 56%, respectively, in AB rat). Calcium unbinding rate from Troponin C and maximal cellular tension yielded, respectively, the second and the third highest impact on the above LV features' total variances. Tissue stiffness and cross-bridge cycling rate impacted EF, ejection time, diastolic time and peak and end-systolic pressure features in the AB rat only. Our GP-based GSA approach enables computationally efficient identification of key components in 3D ventricular mechanics models, a potential path towards discovering new targets for heart failure treatment.