Computational simulation of bone fracture healing under inverse dynamisation

Area of Science:

• Biomechanics
• Computational Biology
• Orthopedic Surgery

Background:

• Adaptive finite element models (FEM) are used to study bone fracture healing.
• The predictive power of these models requires validation against experimental data.
• Mechano-biological schemes can simulate fracture healing dynamics.

Purpose of the Study:

• To test the predictive capability of an established mechano-biological finite element model.
• To simulate sheep tibial osteotomy healing under a novel "inverse dynamisation" fixation strategy.
• To compare healing outcomes under different fixation stiffness conditions.

Main Methods:

• Iterative finite element simulation of sheep tibial osteotomy.
• Application of an established mechano-biological scheme.
• Simulation of constant stiff, constant flexible, and "inverse dynamisation" fixation regimes.
• Blind modeling conducted prior to subsequent experimental testing.

Main Results:

• Constant stiff fixation predicted the fastest and most direct bone healing.
• Flexible fixation resulted in the slowest healing, despite initial callus formation.
• Switching to stiffer fixation accelerated bridging, but "inverse dynamisation" showed no overall advantage.
• Callus formation under flexible fixation conferred minimal stiffness in the initial 5 weeks.

Conclusions:

• The study demonstrated the potential of finite element models to predict fracture healing outcomes.
• "Inverse dynamisation" did not show a significant advantage over constant stiff fixation in simulations.
• In vivo data is crucial for validating the model's predictions and the treatment protocol.