Modulation of pressure overload in chronic animal and in vitro models to elucidate associated effects on hemodynamics and left ventricular plasticity

Massachusetts Institute Of Technology, Cambridge MA

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Abstract

PROJECT SUMMARY Cardiac remodeling with loss of left ventricular compliance, impaired filling, and diastolic dysfunction can be secondary to several conditions, including restrictive cardiomyopathies and pressure overload (i.e., aortic stenosis or hypertension). Currently, there is an absence of in vitro and in vivo models of loss of LV compliance and impaired filling representing a major barrier for the development of effective treatments. To date, no validated in vitro model of the biomechanics of loss of LV compliance exists and animal models are limited by high mortality rates and an inability to finely control the degree and dynamics of induced pressure overload. The lack of robust animal models of loss of LV compliance and diastolic dysfunction has hampered the general understanding of the pathophysiology of these conditions. As a result, there are no available strategies that treat the underlying biomechanical manifestations of diastolic function. There is a lack of insight into optimal intervention planning to target and reverse adverse remodeling due to pressure overload. Through this proposal, we aim to leverage tunable dynamic mechanical implants to create disease models of loss of LV compliance and to characterize the plasticity of LV remodeling processes from biomechanical and hemodynamic standpoints, their progression, and potential reversal. We recently developed a soft robotic aortic sleeve to recapitulate the acute hemodynamics of pressure overload in a porcine model. Preliminary data show that we can re-create the hemodynamics of pressure overload and impaired filling in an in vitro model using soft robotic tools. Here, we aim to re-create the chronic biomechanical and hemodynamic manifestations of loss of LV compliance and impaired filling secondary to pressure overload with an enhanced system with sensing and control abilities. Specifically, we aim to: (1) Develop high-fidelity and patient-specific benchtop models of pressure overload loss of ventricular compliance, and impaired filling using tunable soft robotic tools ; (2) Optimize the aortic sleeve for chronic studies through the development of a minimally invasive delivery approach, MRI-safe implantable system, and built-in smart sensing for closed-loop feedback control to re-create patient-specific disease and (3) Develop and evaluate a clinically relevant chronic large animal model of cardiac remodeling due to pressure overload for time-varied degrees of pressure overload and assessment of potential for disease regression. Our proposed work will address limitations with current models to enable studies of the reversibility of the remodeling processes associated with chronic pressure overload, provide insights into the pathophysiological mechanisms, guide the optimal type and timing of intervention, and ultimately serve as a tunable, high-fidelity, and patient-specific platform for training purposes, device development, and hemodynamic outcome prediction for interventional planning in the clinic.