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Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
Modelling coronary flow and myocardial perfusion by integrating a structured-tree coronary flow model and a
1School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom.
Insights
This study introduces a new computational model integrating coronary blood flow and heart motion for accurate simulations. The model accurately predicts coronary flow and myocardial perfusion, aiding in diagnosing insufficient blood flow to the heart.
Area of Science:
- Computational modeling in cardiovascular science.
- Integration of fluid dynamics and solid mechanics in cardiac research.
Background:
- Growing demand for integrated computational models of coronary circulation in health and disease.
- Trend towards personalized medicine in cardiology necessitates patient-specific models.
- Absence of structured-tree models in existing integrated coronary circulation models.
Purpose of the Study:
- Develop a novel computational framework combining a 1D structured-tree coronary flow model with a 3D left ventricle model.
- Achieve physiologically accurate simulation of coronary flow dynamics.
- Explore interactions between coronary flow dynamics and myocardial motion.
Main Methods:
- Utilized detailed geometric data for coronary vasculature and left ventricle models.
- Expanded the structured-tree model to include time-varying intramyocardial pressure effects.
- Employed a one-way coupling framework for evaluating coronary flow and myocardial perfusion.
Main Results:
- Predicted coronary flow waveforms closely matched experimental data.
- Model accurately captured systolic flow patterns, including impeded or reversed flow.
- Demonstrated that elevated intramyocardial pressure impedes coronary flow.
- Simulated myocardial blood flow aligned with MRI perfusion data.
Conclusions:
- The integrated model offers a novel, physiologically accurate simulation of coronary flow and myocardial perfusion.
- The model shows promise for clinical applications in diagnosing myocardial perfusion insufficiency.
Background And Objective:
There is an increasing demand to establish integrated computational models that facilitate the exploration of coronary circulation in physiological and pathological contexts, particularly concerning interactions between coronary flow dynamics and myocardial motion. The field of cardiology has also demonstrated a trend toward personalised medicine, where these integrated models can be instrumental in integrating patient-specific data to improve therapeutic outcomes. Notably, incorporating a structured-tree model into such integrated models is currently absent in the literature, which presents a promising prospect. Thus, the goal here is to develop a novel computational framework that combines a 1D structured-tree model of coronary flow in human coronary vasculature with a 3D left ventricle model utilising a hyperelastic constitutive law, enabling the physiologically accurate simulation of coronary flow dynamics.
Methods:
We adopted detailed geometric information from previous studies of both coronary vasculature and left ventricle to construct the coronary flow model and the left ventricle model. The structured-tree model for coronary flow was expanded to encompass the effect of time-varying intramyocardial pressure on intramyocardial blood vessels. Simultaneously, the left ventricle model served as a robust foundation for the calculation of intramyocardial pressure and subsequent quantitative evaluation of myocardial perfusion. A one-way coupling framework between the two models was established to enable the evaluation and examination of coronary flow dynamics and myocardial perfusion.
Results:
Our predicted coronary flow waveforms aligned well with published experimental data. Our model precisely captured the phasic pattern of coronary flow, including impeded or even reversed flow during systole. Moreover, our assessment of coronary flow, considering both globally and regionally averaged intramyocardial pressure, demonstrated that elevated intramyocardial pressure corresponds to increased impeding effects on coronary flow. Furthermore, myocardial blood flow simulated from our model was comparable with MRI perfusion data at rest, showcasing the capability of our model to predict myocardial perfusion.
Conclusions:
The integrated model introduced in this study presents a novel approach to achieving physiologically accurate simulations of coronary flow and myocardial perfusion. It holds promise for its clinical applicability in diagnosing insufficient myocardial perfusion.
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