Integrating Multiscale FE2M Simulations and Experiments to Predict Microcrack Damage in Cartilage.

Area of Science:

• Biomedical Engineering
• Computational Mechanics
• Tissue Engineering

Background:

• Articular cartilage is susceptible to microdamage from impacts, potentially leading to osteoarthritis (OA).
• Understanding collagen network mechanics is crucial for predicting cartilage failure.
• Existing models often lack multiscale integration for accurate damage prediction.

Purpose of the Study:

• To develop and validate a multiscale computational framework (FE2M) for predicting microdamage initiation and propagation in articular cartilage.
• To couple macroscale cartilage deformation with microscale fibril mechanics.
• To investigate the role of stress versus stretch in cartilage failure.

Main Methods:

• Utilized the Finite Elements of Multiscale Mixtures (FE2M) framework within FEBio.
• Generated Statistically Equivalent Representative Volume Elements (SERVEs) to model anisotropic collagen architecture.
• Simulated impact and cyclic compression loading conditions, validated against experimental data.

Main Results:

• FE2M predictions of fiber failure fractions strongly agreed with experimentally measured microcrack fractions.
• High-impact simulations showed stress, not stretch, as a more reliable predictor of failure.
• Model demonstrated robustness to variations in fibril stiffness parameters.

Conclusions:

• The validated FE2M framework accurately captures multiscale mechanical behavior and microdamage trends in articular cartilage.
• This approach offers a predictive tool for understanding cartilage degeneration.
• Potential applications include injury risk assessment and OA prevention strategies.