Related Experiment Video
Updated: Jul 19, 2025

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
Benchtop Models of Patient-Specific Intraventricular Flow During Heart Failure and LVAD Support
Vi Vu1, Lorenzo Rossini2, Juan C Del Alamo3
1Bioengineering Program, Department of Mechanical Engineering, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182; Division of Biomedical Physics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993.
Abstract:
The characterization of intraventricular flow is critical to evaluate the efficiency of fluid transport and potential thromboembolic risk but challenging to measure directly in advanced heart failure (HF) patients with left ventricular assist device (LVAD) support. The study aims to validate an in-house mock loop (ML) by simulating specific conditions of HF patients with normal and prosthetic mitral valves (MV) and LVAD patients with small and dilated left ventricle volumes, then comparing the flow-related indices result of vortex parameters, residence time (RT), and shear-activation potential (SAP). Patient-specific inputs for the ML studies included heart rate, end-diastolic and end-systolic volumes, ejection fraction, aortic pressure, E/A ratio, and LVAD speed. The ML effectively replicated vortex development and circulation patterns, as well as RT, particularly for HF patient cases. The LVAD velocity fields reflected altered flow paths, in which all or most incoming blood formed a dominant stream directing flow straight from the mitral valve to the apex. RT estimation of patient and ML compared well for all conditions, but SAP was substantially higher in the LVAD cases of the ML. The benchtop system generated comparable and reproducible hemodynamics and fluid dynamics for patient-specific conditions, validating its reliability and clinical relevance. This study demonstrated that ML is a suitable platform to investigate the fluid dynamics of HF and LVAD patients and can be utilized to investigate heart-implant interactions.

