Abstract
This paper details a multi-scale model computational model of myocardial energetics---oxidative ATP synthesis, ATP hydrolysis, and phosphate metabolite kinetics---and myocardial mechanics used to analyze data from a rat model of cardiac decompensation and failure. Combined, these two models simulate cardiac mechano-energetics: the coupling between metabolic production of ATP and hydrolysis of ATP to generate mechanical work. The model is used to predict how differences in energetic metabolic state found in failing versus control hearts causally contribute to systolic mechanical dysfunction in heart failure. This Physiome paper describes how to access, run, and manipulate these computer models, how to parameterize the models to match data, and how to compare model predictions to data.
Highlights
The cardiac energetics model takes as an input the myocardial ATP consumption rate, the measured metabolite pools levels, and the measured mitochondrial ATP synthesis capacity, and outputs the cytoplasm concentrations of phosphate metabolites
The cardiac mechanics code takes as an input the cytoplasmic concentrations of phosphate metabolites and computes as an output the ventricular end-systolic and end-diastolic volumes and arterial pressures to compare to measured data, and the myocardial ATP hydrolysis rate to use in the energetics module
The energetics and mechanics models are iteratively run until they simultaneously converge to a steady state at fit the target cardiovascular data
Summary
The cardiac metabolic energetic model component is parameterized to match data from individual animals based on the oxidative capacity and cytoplasmic metabolite pools obtained from Lopez et al (2020). Wall volumes and anatomic parameters associated with the Lumens et al (2009) heart model are identified based on anatomical data obtained from echocardiography and ex-vivo gross morphological measurements on individual animals from Lopez et al (2020). The simple lumped parameter circulatory model is identified based on cardiovascular state variables measured under resting conditions. The resulting integrated model is used to predict the in vivo mechanical function and energetic state of the myocardium under resting conditions in each animal
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