Why the study?
Mock circulatory loops reduce animal testing costs and complexity, and novel platforms provide preclinical testing flexibility to emulate human physiology for ventricular assist devices.
A novel hardware-in-the-loop platform successfully emulated advanced heart failure hemodynamics to evaluate the iHeart-II LVAD, demonstrating hemodynamic normalization at ~3500 rpm.
May reduce animal testing for LVAD evaluation; leaves open in vivo and regulatory validation.
BACKGROUND AND OBJECTIVES: The cost and complexity associated with animal testing are significantly reduced by using mock circulatory loops prior. Novel mock circulatory loops allow us to test biomedical devices preclinically due to their flexibility, scalability, and cost-effectiveness. The presented work describes the development of a hardware-in-the-loop platform to emulate human physiology for the Istanbul Heart (iHeart-II) LVAD. METHODS: A closed-loop system is developed whereby the effect of the LVAD on the heart and vice versa can be studied. An acausal model of the cardiovascular system is calibrated to emulate advanced-stage heart failure. A new prototype of the iHeart-II LVAD is connected between two air-actuated chambers emulating the left ventricle and aortic chambers with PID controllers tracking numerically modeled pressures from the in silico model. A lead-lag compensator is used to maintain fluid level. Controllers are tuned using nonlinear Hammerstein-Weiner models identified using open-loop data. The iHeart-II LVAD is operated at various speeds in its operational range, and the resulting hemodynamics are visualized in real time. RESULTS: Hemodynamic variables, such as LVAD flow rate, aortic, left ventricular, and pulse pressure, demonstrate trends similar to clinical observations. The iHeart-II LVAD achieves hemodynamic normalization at ~3500 rpm for the emulated condition. CONCLUSIONS: A novel evaluation methodology is adopted to study the performance of the iHeart LVAD under advanced-stage heart failure emulation. The models and controllers used in the platform are readily replicable to facilitate VAD research, pedagogy, design, and development.
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Rahman et al. (2024) studied this question.
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