ABSTRACT
To better understand the impact of valvular heart disease (VHD) on the hemodynamics of the circulatory system, investigations can be carried out using a model of the cardiovascular system. In this study, a previously developed hybrid (hydro-numerical) simulator of the cardiovascular system (HCS) was adapted and used. In our HCS Björk-Shiley mechanical heart valves were used, playing the role of mitral and aortic ones. In order to simulate aortic stenosis (AS) and mitral regurgitation (MR), special mechanical devices have been developed and integrated with the HCS. The simulation results proved that the system works correctly. Namely, in the case of AS - the mean pulmonary arterial pressure was increased due to increased preload of the left ventricle and the decrease in right ventricular preload was caused by a decrease in systemic arterial pressure. The severity of AS was performed based on the transaortic pressure gradient as well as using the Gorlin and Aaslid equations. In the case of severe AS, when the mean gradient was above 40 mmHg, the aortic valve orifice area was 0.5 cm2, which is in line with ACC/AHA guidelines. For the case of MR - with increasing severity of MR, there was a decrease in the left ventricular pressure and an increase in left atrial pressure. Using mechanical heart valves to simulate VHD by the HCS can be a valuable tool for biomedical research, providing a safe and controlled environment to study and understand the pathophysiology of VHD.
ABSTRACT
A promising treatment for congestive heart failure is the implementation of a left ventricular assist device (LVAD) that works as a mechanical pump. Modern LVADs work with adjustable constant rotor speed and provide therefore continuous blood flow; however, recently undertaken efforts try to mimic pulsatile blood flow by oscillating the pump speed. This work proposes an algorithmic framework to construct and evaluate optimal pump speed policies with respect to generic objectives. We use a model that captures the atrioventricular plane displacement, which is a physiological indicator for heart failure. We employ mathematical optimization to adapt this model to patient specific data and to find optimal pump speed policies with respect to ventricular unloading and aortic valve opening. To this end, we reformulate the cardiovascular dynamics into a switched system and thereby reduce nonlinearities. We consider system switches that stem from varying the constant pump speed and that are state dependent such as valve opening or closing. As a proof of concept study, we personalize the model to a selected patient with respect to ventricular pressure. The model fitting results in a root-mean-square deviation of about 6 mmHg. The optimization that considers aortic valve opening and ventricular unloading results in speed modulation akin to counterpulsation. These in silico findings demonstrate the potential of personalized hemodynamical optimization for the LVAD therapy.
