In Silico Tissue Engineering: A Coupled Agent-Based Finite Element Approach.

Area of Science:

• Biomedical Engineering
• Computational Biology
• Tissue Engineering

Background:

• Cardiovascular diseases drive the need for advanced tissue-engineered vascular grafts (TEVGs).
• Current TEVGs face challenges with compliance mismatch and suboptimal mechanical properties.
• Understanding collagen fiber deposition and orientation is crucial for TEVG development.

Purpose of the Study:

• To investigate the impact of various loading modes and culture conditions on TEVG growth and remodeling.
• To analyze the influence of mechanical stimuli on collagen fiber deposition and orientation in smooth muscle cell-populated TEVGs.
• To utilize a coupled agent-based finite element analysis (AB-FEA) model for efficient simulation of TEVG mechanobiology.

Main Methods:

• Employed a coupled agent-based finite element analysis (AB-FEA) modeling approach.
• Simulated TEVGs under different loading modes (uniaxial, biaxial, equibiaxial), boundary conditions, stretch magnitudes, and serum concentrations.
• Focused on predicting collagen fiber deposition and orientation over a 12-week simulated culture period.

Main Results:

• Biaxial cyclic loading, unlike uniaxial or equibiaxial loading, promoted collagen fiber alignment in physiological directions.
• Axial boundary conditions significantly influenced the orientation of collagen fibers within the TEVG.
• Reduced serum concentration (5% or 1%) slowed growth and remodeling; only 1% serum impacted fiber orientation.

Conclusions:

• Computational modeling (in silico tissue engineering) offers an efficient approach to study complex mechanobiological interactions in TEVGs.
• Biaxial loading and specific axial boundary conditions are critical for achieving desired collagen fiber organization in TEVGs.
• The developed AB-FEA model accurately predicted collagen fiber orientation in TEVGs within 8 hours.