Hill's force-velocity relationship is integrated into a 3D left-ventricular finite element model to enhance myocardial contraction dynamics alongside the Frank-Starling mechanism. Hypertensive conditions were simulated by adjusting arterial resistance and compliance to mimic varying afterload, with damping applied on velocity as an alternative stabilization method for numerical stability. Hill's relationship reduced peak systolic pressures (6.3%-7.2%) as hypertension progressed, moderated shortening velocities (1.61-1.69 s-1), and prevented velocity overshoot. Cardiac output was preserved, and ejection fraction remained unaffected. These findings highlight Hill's role in regulating systolic function, optimizing myocardial response under elevated afterload, and improving predictive capabilities for hypertensive heart disease.
Aortic stenosis, hypertension, and left ventricular hypertrophy often coexist in the elderly, causing a detrimental mismatch in coupling between the heart and vasculature known as ventricular-vascular (VA) coupling. Impaired left VA coupling, a critical aspect of cardiovascular dysfunction in aging and disease, poses significant challenges for optimal cardiovascular performance. This systematic review aims to assess the impact of simulating and studying this coupling through computational models. By conducting a comprehensive analysis of 34 relevant articles obtained from esteemed databases such as Web of Science, Scopus, and PubMed until July 14, 2022, we explore various modeling techniques and simulation approaches employed to unravel the complex mechanisms underlying this impairment. Our review highlights the essential role of computational models in providing detailed insights beyond clinical observations, enabling a deeper understanding of the cardiovascular system. By elucidating the existing models of the heart (3D, 2D, and 0D), cardiac valves, and blood vessels (3D, 1D, and 0D), as well as discussing mechanical boundary conditions, model parameterization and validation, coupling approaches, computer resources and diverse applications, we establish a comprehensive overview of the field. The descriptions as well as the pros and cons on the choices of different dimensionality in heart, valve, and circulation are provided. Crucially, we emphasize the significance of evaluating heart-vessel interaction in pathological conditions and propose future research directions, such as the development of fully coupled personalized multidimensional models, integration of deep learning techniques, and comprehensive assessment of confounding effects on biomarkers.