A computer model of engineered cardiac monolayers.

Area of Science:

• Computational biology
• Cardiac electrophysiology
• Tissue engineering

Background:

• Engineered cardiac monolayers offer simplified models for studying electrical propagation.
• Classical continuous models fail to capture cell shape, orientation, and cleft space variability.
• Understanding these factors is crucial for accurate simulation of wavefront conduction.

Purpose of the Study:

• To develop a novel computational methodology for modeling cardiac tissue monolayers with spatially random cellular properties.
• To simulate wavefront propagation in a manner analogous to experimental engineered monolayer tissues.
• To compare simulation results with existing experimental data and investigate the impact of cellular architecture on electrical properties.

Main Methods:

• Developed a discrete modeling approach treating cell shape, coupling, and cleft space as random variables.
• Simulated wavefront propagation in engineered cardiac monolayers.
• Compared simulation outcomes with published experimental data on conduction velocities and anisotropy ratios.
• Estimated electrical properties from simulated networks and analyzed the effects of cellular architecture variations.

Main Results:

• Simulations support the use of continuous models for uniform tissues, deriving conductivity from discrete architecture.
• Local estimates of tissue properties may inadequately predict discrete propagation at sites with abrupt cell orientation changes.
• Variations in discrete cellular architecture significantly affect macroscopic conductivities.

Conclusions:

• The novel discrete modeling approach accurately simulates wavefront propagation in engineered cardiac monolayers.
• Continuous models are suitable for uniform tissues, but discrete models are necessary for complex architectures.
• Understanding cellular architecture's role is vital for accurate cardiac electrophysiology modeling.