Abstract:
This dissertation focuses on the computational modeling of cardiac biomechanics, aiming to develop a realistic and patient-specific model of the heart to aid medical scientists in diagnosing and treating heart diseases. The foundation of this biomechanical approach involves creating a three-dimensional finite element (FE) model of the heart, constructed from magnetic resonance images of a beating pig heart. This model was subjected to physiological loading conditions, specifically the pressure of blood inside the left ventricle, meticulously measured via synchronous catheterization. A critical biomechanical advancement in this work was the incorporation of a recently developed structurally based constitutive model of the myocardium into the finite element solver, enabling accurate representation of the passive mechanical behavior of the left ventricular myocardium. Furthermore, an innovative biomechanical technique involved adapting an unloading algorithm, originally developed for arteries, to precisely estimate the stress-free geometry of the heart from its partially-loaded state captured by magnetic resonance imaging. This step is vital for deriving accurate material parameters and stress distributions in biomechanical models. To expand the model's predictive capabilities in cardiac remodeling, a regionally varying growth module was integrated. This module allows the computational model to predict biomechanical changes like eccentric hypertrophy under various pathological conditions that induce volume overload of the heart. The comprehensive computational model, with its emphasis on capturing the heart's mechanical response, was rigorously validated against experimental data from porcine hearts, including in vivo strains directly measured from magnetic resonance imaging, ensuring its biomechanical fidelity. The study also delved into optimizing material parameters using in-vivo MRI and pressure data, and explored the influence of the Holzapfel and Ogden (H-O) model on end-diastolic pressure-volume relationships, further advancing the understanding of myocardial mechanics. The work underscores the power of computational biomechanics in providing detailed three-dimensional deformation, stress, and strain fields that are crucial for understanding cardiac function and disorder, complementing conventional clinical data.
