Predicting muscle tissue response from calibrated component models and histology-based finite element models

Area of Science:

• Biomechanics
• Biomaterials Science
• Tissue Engineering

Background:

• Skeletal muscle is a complex, anisotropic soft biological tissue.
• Hierarchical organization of muscle fibers and extracellular matrix (ECM) influences mechanical properties.
• Previous work established 3D finite element models and experimental data on decellularized ECM properties.

Purpose of the Study:

• To calibrate a constitutive model of the skeletal muscle ECM using an inverse finite element procedure.
• To validate the predictive model through supplementary biaxial tensile tests on fresh and decellularized tissues.
• To assess the predictability of composite tissue response from individual component characteristics.

Main Methods:

• Development of 3D finite element models from histological sections.
• Decellularization of fresh tissue samples to obtain ECM properties.
• Inverse finite element analysis to calibrate ECM constitutive model.
• Biaxial tensile testing of fresh and decellularized tissues for validation.

Main Results:

• The predictive strategy matched orders of magnitude of tissue response.
• Qualitative mechanical behavior across various load cases was largely captured.
• Deviations between predicted and experimental results were observed, indicating limitations.

Conclusions:

• Predicting skeletal muscle tissue response from individual cell and ECM characteristics is feasible but limited.
• Existing models may lack crucial components or require more comprehensive experimental data.
• Bottom-up multiscale modeling approaches for skeletal muscle require further refinement.