X-ray physics-based CT-to-composition conversion applied to a tissue engineering scaffold, enabling multiscale...

Area of Science:

• Biomaterials Science
• Mechanical Engineering
• Computational Modeling

Background:

• Tissue engineering scaffolds require robust mechanical property assessment.
• Finite Element (FE) analysis is a key computational tool for this purpose.
• Micro-computed tomography (microCT) provides essential structural data for FE models.

Purpose of the Study:

• To develop and validate a novel FE model for a ternary composite scaffold (PHBV/PLGA/TCP).
• To accurately determine the mechanical competence of rapid prototyped scaffolds.
• To investigate the impact of material heterogeneity on scaffold mechanical behavior.

Main Methods:

• MicroCT data was used to define the FE model's geometry and material properties.
• A two-step micromechanical homogenization scheme was employed to upscale constituent stiffness.
• Simulations of uniaxial compression were performed to analyze stress and strain distribution.
• Voxel-specific material composition was calculated from microCT grey values.

Main Results:

• The FE model successfully predicted stress and strain fields under uniaxial compression.
• Fiber junctions were identified as the most mechanically stressed regions.
• Neglecting material heterogeneity led to significant underestimation of stresses and strains.
• The microCT-based analysis demonstrated conceptual superiority over simplified strategies.

Conclusions:

• The developed FE model provides a reliable method for assessing the mechanical competence of complex composite scaffolds.
• Accurate modeling of material heterogeneity is crucial for predicting scaffold performance.
• This approach enhances the design and optimization of tissue engineering scaffolds.