A Multi-Domain Simulation Study of a Pulsatile-Flow Pump Device for Heart Failure With Preserved Ejection Fraction

Acausal Modelling of Advanced-Stage Heart Failure and the Istanbul Heart Ventricular Assist Device Support with Patient Data

BACKGROUND

In object-oriented or acausal modelling, components of the model can be connected topologically, following the inherent structure of the physical system, and system equations can be formulated automatically. This technique allows individuals without a mathematics background to develop knowledge-based models and facilitates collaboration in multidisciplinary fields like biomedical engineering. This study conducts a preclinical evaluation of a ventricular assist device (VAD) in assisting advanced-stage heart failure patients in an acausal modelling environment.

METHODS

A comprehensive object-oriented model of the cardiovascular system with a VAD is developed in MATLAB/SIMSCAPE, and its hemodynamic behaviour is studied. An analytically derived pump model is calibrated for the experimental prototype of the Istanbul Heart VAD. Hemodynamics are produced under healthy, diseased, and assisted conditions. The study features a comprehensive collection of advanced-stage heart failure patients' data from the literature to identify parameters for disease modelling and to validate the resulting hemodynamics.

RESULTS

Regurgitation, suction, and optimal speeds are identified, and trends in different hemodynamic parameters are observed for the simulated pathophysiological conditions. Using pertinent parameters in disease modelling allows for more accurate results compared to the traditional approach of arbitrary reduction in left ventricular contractility to model dilated cardiomyopathy.

CONCLUSION

The current research provides a comprehensive and validated framework for the preclinical evaluation of cardiac assist devices. Due to its object-oriented nature, the featured model is readily modifiable for other cardiovascular diseases for studying the effect of pump operating conditions on hemodynamics and vice versa in silico and hybrid mock circulatory loops. The work also provides a potential teaching tool for understanding the pathophysiology of heart failure, diagnosis rationale, and degree of assist requirements.

Soft robotics-enabled large animal model of HFpEF hemodynamics for device testing

Heart failure with preserved ejection fraction (HFpEF) is a major challenge in cardiovascular medicine, accounting for approximately 50% of all cases of heart failure. Due to the lack of effective therapies for this condition, the mortality associated with HFpEF remains higher than that of most cancers. Despite the ongoing efforts, no medical device has yet received FDA approval. This is largely due to the lack of an in vivo model of the HFpEF hemodynamics, resulting in the inability to evaluate device effectiveness in vivo prior to clinical trials. Here, we describe the development of a highly tunable porcine model of HFpEF hemodynamics using implantable soft robotic sleeves, where controlled actuation of a left ventricular and an aortic sleeve can recapitulate changes in ventricular compliance and afterload associated with a broad spectrum of HFpEF hemodynamic phenotypes. We demonstrate the feasibility of the proposed model in preclinical testing by evaluating the hemodynamic response of the model post-implantation of an interatrial shunt device, which was found to be consistent with findings from in silico studies and clinical trials. This work addresses several of the limitations associated with previous models of HFpEF, such as their limited hemodynamic fidelity, elevated costs, lengthy development time, and low throughput. By showcasing exceptional versatility and tunability, the proposed platform has the potential to revolutionize the current approach for HFpEF device development and selection, with the goal of improving the quality of life for the 32 million people affected by HFpEF worldwide.

A numerical study of a left ventricular expander for heart failure with preserved ejection fraction

Increased cardiac stiffness hinders proper left ventricular (LV) expansion, resulting in decreased volume and diastolic dysfunction. LV expanders are spring-like devices designed to improve diastolic function by facilitating mechanical outward expansion. Implantations in animals and humans have shown promising results, yet further evaluation is needed to assess a range of functions and the risk of use. In this computational study, the effectiveness and potential use of a generic LV expander were assessed by using previously generated finite-element models of induced heart failure with preserved ejection fraction (HFpEF). Following implantation, the treated models were compared to the corresponding untreated and healthy pre-induction models. The influence of device orientation and its material properties was also examined. Our results demonstrated a reduction in LV pressure and a volumetric improvement. Computed LV stresses have shown no gross irregularities. The device contributed to stress elevation during diastole while having a minor effect during systole, supporting a basic safety profile. This is the first study to use numerical analysis to assess LV expanders' performance on different HFpEF phenotypes. Improvement in heart function was demonstrated in both subjects, suggesting its potential use in various HFpEF manifestations, yet customization and optimal deployment are essential to improve heart performance.

Framework for patient-specific simulation of hemodynamics in heart failure with counterpulsation support

Despite being responsible for half of heart failure-related hospitalizations, heart failure with preserved ejection fraction (HFpEF) has limited evidence-based treatment options. Currently, a substantial clinical issue is that the disease etiology is very heterogenous with no patient-specific treatment options. Modeling can provide a framework for evaluating alternative treatment strategies. Counterpulsation strategies have the capacity to improve left ventricular diastolic filling by reducing systolic blood pressure and augmenting the diastolic pressure that drives coronary perfusion. Here, we propose a framework for testing the effectiveness of a soft robotic extra-aortic counterpulsation strategy using a patient-specific closed-loop hemodynamic lumped parameter model of a patient with HFpEF. The soft robotic device prototype was characterized experimentally in a physiologically pressurized (50–150 mmHg) soft silicone vessel and modeled as a combination of a pressure source and a capacitance. The patient-specific model was created using open-source software and validated against hemodynamics obtained by imaging of a patient (male, 87 years, HR = 60 bpm) with HFpEF. The impact of actuation timing on the flows and pressures as well as systolic function was analyzed. Good agreement between the patient-specific model and patient data was achieved with relative errors below 5% in all categories except for the diastolic aortic root pressure and the end systolic volume. The most effective reduction in systolic pressure compared to baseline (147 vs. 141 mmHg) was achieved when actuating 350 ms before systole. In this case, flow splits were preserved, and cardiac output was increased (5.17 vs. 5.34 L/min), resulting in increased blood flow to the coronaries (0.15 vs. 0.16 L/min). Both arterial elastance (0.77 vs. 0.74 mmHg/mL) and stroke work (11.8 vs. 10.6 kJ) were decreased compared to baseline, however left atrial pressure increased (11.2 vs. 11.5 mmHg). A higher actuation pressure is associated with higher systolic pressure reduction and slightly higher coronary flow. The soft robotic device prototype achieves reduced systolic pressure, reduced stroke work, slightly increased coronary perfusion, but increased left atrial pressures in HFpEF patients. In future work, the framework could include additional physiological mechanisms, a larger patient cohort with HFpEF, and testing against clinically used devices.