Abstract
The heart is one of the greatest examples of engineering principles manifested in biology. Through coordinated electrical and mechanical signals, the heart continually pumps vital blood and nutrients to the entire body. However, the heart is susceptible to injury through disruptions of its own blood supply, which causes myocardial infarction, and through severe alterations of hemodynamics, such as hypertension and aortic stenosis, among other perturbations. These conditions can lead to a progressive deterioration of cardiac function and overall increased demand on the heart to pump sufficient blood. The heart can compensate for the effects of injury through a process of growth and remodeling, which can cause cardiac muscle hypertrophy as an adaptation to increase pump function and efficiency. However, hypertrophy can also become maladaptive in the long term and contribute to the development of heart failure.
Cardiovascular disease (CVD), which encompasses the initial perturbations and eventual heart failure, is a critical health problem, responsible for the majority of all deaths worldwide. Given current trends of increasing incidence of CVD, it is imperative to develop and optimize new therapies to treat CVD. For this purpose, computational modeling offers the unique advantage of allowing us to not only better understand disease, from the effects of acute injury to the development of subsequent hypertrophy, but to also test and design different therapeutic approaches for treating CVD. The overall objective of my work, presented in this dissertation, has been to create computational models of the heart that can help us better understand how different manifestations of CVD affect the heart and how various therapies can lead to improvements in cardiac function and attenuation of the long-term effects of hypertrophy. I have focused on two specific projects: 1) constructing a finite-element model of local, anisotropic mechanical reinforcement of acute myocardial infarction, to understand how this therapy leads to increased pump function by altering mechanics; and 2) constructing a multiscale computational model of cardiac concentric hypertrophy – as is caused by hypertension and aortic stenosis – that incorporates realistic organ-level mechanics and intracellular signaling and captures how changes to both the mechanical and hormonal environments can induce growth and how specific genetic and pharmacologic interventions can attenuate this hypertrophy.
