Cardiovascular diseases are among the leading causes of deaths worldwide, but the fluid mechanics of many of these conditions and the devices used to treat them are only partially understood. This goal of this dissertation was to develop new experimental techniques that would enable translational research into two of these conditions. The first set of experiments examined <i>in-vitro</i> the changes in Wall Shear Stress (WSS) and Oscillatory Shear Index (OSI) caused by the implantation of coronary stents into the arteries of the heart using Particle Image Velocimetry. These experiments featured one-to-one scaling, commercial stents, and realistic flow and pressure waveforms, and are believed to be the most physiologically accurate stent experiments to date. This work revealed distinct differences in WSS and OSI between the different stent designs tested, and showed that changes in implantation configuration also affected these hemodynamic parameters. Also, the production of vortices near the stent struts during flow reversal was noted, and an inverse correlation between WSS and OSI was described. The second set of experiments investigated Left Ventricular Diastolic Dysfunction (LVDD) using phase contrast magnetic resonance imaging (pcMRI). Using this technique, ten patients with and without LVDD were scanned and a 2D portrait of blood flow through their heart was obtained. To augment this data, pressure fields were calculated from the velocity data using an omni-directional pressure integration scheme coupled with a proper-orthogonal decomposition-based smoothing. This technique was selected from a variety of methods from the literature based on an extensive error analysis and comparison. With this coupled information, it was observed that healthy patients exhibited different flow patterns than diseased patients, and had stronger pressure differences during early filling. In particular, the ratio of early filling pressure to late filling pressure was a statistically significant predictor of diastolic dysfunction. Based on these observations, a novel hypothesis was presented that related the motion of the heart walls to the observed flow patterns and pressure gradients, which may explain the differences observed clinically between healthy and diseased patients. / Ph. D.

Heart valve tissue engineering (HVTE) stands as a potential intervention that could reduce the prevalence of congenital heart valve disease in juvenile patients. Prior studies in our laboratory have utilized mechanobiological testing to quantify the forces involved in the development of heart valve tissue, utilizing a Flow-Stretch-Flexure (FSF) bioreactor to condition bone marrow stem cells (BMSCs)-derived valve tissue. Simulations have demonstrated that certain sets of flow conditions can introduce specific levels of oscillatory shear stress (OSS)-induced stimuli, augmenting the growth of engineered valves as well as influencing collagen formation, extracellular matrix (ECM) composition and gene expression. The computational findings discussed in this thesis outline the methods in which flow conditions, when physiologically relevant, induce specific oscillatory shear stresses which could not only lead to an optimized valve tissue phenotype (at 0.18≤ OSI≤ 0.23), but could identify native valve tissue remodeling indicative of aortic valve disease.