Anatomically-driven soft-tissue simulation strategy for cranio-maxillofacial surgery using facial muscle template...

Area of Science:

• Biomedical Engineering
• Computational Mechanics
• Surgical Simulation

Background:

• Cranio-maxillofacial (CMF) surgery requires precise soft-tissue simulation.
• Patient-specific model preparation is often time-consuming.
• Accurate simulation of facial muscle mechanics is crucial for realistic outcomes.

Purpose of the Study:

• To develop a computationally efficient and bio-mechanically relevant soft-tissue simulation method for CMF surgery.
• To reduce the effort in patient-specific model preparation.
• To enhance simulation accuracy by integrating advanced modeling techniques.

Main Methods:

• Implemented a template-based facial muscle reconstruction approach.
• Utilized a transversely isotropic mass-tensor model (MTM) for directional muscle properties.
• Incorporated sliding contact simulation for teeth and mucosa interactions.

Main Results:

• The proposed method offers a computationally efficient solution for soft-tissue simulation.
• Template-based muscle reconstruction simplified model preparation.
• The inclusion of MTM and sliding contact improved simulation accuracy in retrospective validation.

Conclusions:

• The developed simulation method is bio-mechanically relevant and computationally efficient for CMF surgery.
• Template-based facial muscle anatomy and sliding contact enhance simulation realism and accuracy.
• This approach shows considerable improvements for surgical planning and outcome prediction.