Non-Invasive Quantification of Cardiovascular Flow Metrics in Vertebrates

Cancer and cardiac diseases are the major causes of morbidity and mortality in the western world. Cardiovascular hemodynamics is increasingly being used to understand the pathophysiological progression of these diseases. Advancements in imaging modalities and development of multiscale numerical models have opened avenues for innovative quantification of flow metrics that may potentially aid in clinical diagnosis. The motivation behind this dissertation is to investigate three different physiological flow phenomena and develop new flow specific parameters as explained in the following paragraphs. Drug transport efficacy in treating breast tumors has a strong correlation with tissue architecture, nanoparticle transport parameters and hemodynamic metrics that varies from one patient to another. The exact time interval between nanoparticle introduction and drug release must be accurately determined to achieve therapeutic efficacy. The first chapter of the current work implements a numerical model based on mixture theory equations to investigate effect of varying inter-capillary separation on solute transport in dual-channel tissues for various solute sizes (0.5-15 nm) and molecular weights (0.1-70 kDa). The predictive capability of the numerical model is validated by measurements of dextran transport in an invitro tumor platform containing multiple blood vessels. The main contribution of this work is in reporting a unique non-dimensional time at which solute concentration peaks in any location in the tissue in absence of pharmacokinetics. The second chapter focuses on the development of a physics-based metric from color-m-mode (CMM) echocardiography scans to correctly diagnose different stages of left ventricle diastolic dysfunction (LVDD). Current practice of diagnosing LVDD involves calculating a combination of parameters like intraventricular pressure difference (IVPD) and propagation velocity (Vp) from the CMM scans. The conventional Vp measurement is based on heuristics. This definition does not utilize the entire information from the spatio-temporal velocity distribution of the ventricle filling cycle. The present work challenges the underlying assumption of the early ventricle filling wave moving with a constant velocity. The proposed method in this chapter uses wavelets to analyze the early diastolic ventricle filling wave and introduces a wavelet based peak propagation velocity (Peak-Vw). Peak-Vw is free of the inherent assumptions of the subjective selection of an iso-contour in the scan and measuring a slope from it. The novelty of the Peak-Vw measurement can provide new insights for understanding the complicated pathophysiology of the left ventricle (LV) diastolic function. The final focus of this dissertation is to investigate the evolving hemodynamics of the cardiovascular system of Japanese medaka while it is growing from embryonic state to larval stages. Cross-correlation of red blood cell patterns from 2D micro-particle image velocimetry (µPIV) images provide measurements of velocity fields in the fish heart and vessels. Accurate velocity gradient measurements are required to further derive flow quantities like wall shear stress (WSS), pressure drop across valves and cardiac strain. WSS experienced by endocardial cells and vascular endothelial cells are linked to changes in cardiac specific gene expressions. Previous studies with other vertebrate models investigating mechano-genetic correlations were focused on mutating genes or introducing some perturbation in the blood circulation. In the third chapter of this dissertation, a baseline longitudinal study tracking the change in cardiovascular WSS and gene expressions with natural progression of fish age is presented for the first time