A computational model of microcirculatory network structure and transient coronary microcirculation

Area of Science:

• Cardiovascular Physiology
• Biomedical Engineering
• Computational Fluid Dynamics

Background:

• Understanding coronary microcirculation is crucial for diagnosing and treating cardiovascular diseases.
• Existing models often lack the biophysical detail to accurately represent microvascular blood flow dynamics.

Purpose of the Study:

• To develop a comprehensive mathematical and computational model of the coronary microcirculation.
• To incorporate non-Newtonian blood properties and their effects on flow within microvessels.

Main Methods:

• Constructed a network model of coronary microcirculation using porcine morphometric data.
• Solved Poiseuille flow equations for capillaries and coupled them with a finite difference model for arterioles/venules.
• Integrated empirical models for phase separation and the Fahraeus-Lindqvist effect to simulate non-Newtonian blood viscosity.

Main Results:

• Successfully coupled steady-state capillary flow with transient arteriole/venule flow using a non-linear root-finding algorithm.
• Achieved rapid convergence in small-scale network simulations.
• The model accurately assesses transient flow in spatially heterogeneous networks while maintaining computational efficiency.

Conclusions:

• The developed model provides a robust biophysical framework for studying coronary microcirculation.
• This approach enhances the understanding of blood flow dynamics in microvessels, considering complex non-Newtonian behaviors.
• The model's efficiency and biophysical basis make it valuable for future research in cardiovascular science.