Abstract
AbstractEvery year approximately 200,000 human heart valves are replaced worldwide. Although prosthetic heart valves are widely accepted, their performance is far from ideal, especially when compared to natural and healthy heart valves. There is a need to develop more accurate methods of characterizing the performance and efficiency of prosthetic heart valves. Currently, though, heart valves are clinically evaluated based on transvalvular pressure characteristics and left ventricular ejection fraction. These current assessment methods overlook the complex flow field downstream of these valves and inside the left ventricle which if understood can provide valuable insight on valvular and cardiac performance. Thus, our research focuses on flow characterization past heart valves. Namely, we are interested in characterizing vortex ring formation, resulting from the roll-up of the shear layers shedding past heart valves, which has been shown by previous studies to be important and to provide insight into left ventricle energy losses. Having designed a flow loop to enable the visualization of vortex ring formation past various mechanical and biological heart valves, we tested four prosthetic valves (three mechanical and one biological). The use of a high speed camera enabled us to capture vortex ring formation past the various prosthetic valve designs. Important flow parameters were estimated, such as vortex ring propagation speed which has been shown to be an important diagnostic parameter. Comparative analysis across valves revealed important differences between biological and mechanical heart valves. The potential of this research is that it can aid researchers and practitioners to determine the effectiveness of all types of valves (natural, diseased, prosthetic, tissue engineered, percutaneous) and also serve as ground work leading towards clinical translation.KeywordsParticle Image VelocimetryHeart ValveVortex RingPropagation SpeedProsthetic Heart ValveThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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