Left ventricular diastolic dysfunction (LVDD) is any abnormality in the filling of the left ventricle (LV).  Despite the prevalence of this disease, it remains difficult to diagnose, mainly due to inherent compensatory mechanisms and a limited physical understanding of the filling process.  LV filling can be non-invasively imaged using color m-mode echocardiography which provides a spatio-temporal map of inflow velocity.  These filling patterns, or waves, are conventionally used to qualitatively assess the filling pattern, however, this work aims to physically quantify the filling waves to improve understanding of diastole and develop robust, reliable, and quantitative parameters. This work reveals that LV filling waves in a normal ventricle act as dispersive waves and not only propagate along the length of the LV but also spread and disperse in the direction of the apex.  In certain diseased ventricles, this dispersion is limited due to changes in LV geometry and wall motion.  This improved understanding could aid LVDD diagnostics not only for determining health and disease, but also for distinguishing between progressing disease states. This work also identifies a limitation in a current LVDD parameter, intra ventricular pressure difference (IVPD), and presents a new methodology to address this limitation.  This methodology is also capable of synthesizing velocity information from a series of heartbeats to generating one representative heartbeat, addressing inaccuracies due to beat-to-beat variations.  This single beat gives a comprehensive picture of that specific patient's filling pattern.  Together, these methods improve the clinical utility of IVPD, making it more robust and limiting the chance for a misdiagnosis. / Master of Science

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.