A novel modeling framework for multilayered soft tissue deformation in virtual orthopedic surgery

Area of Science:

• Biomedical Engineering
• Computer Science
• Orthopedics

Background:

• Realistic modeling of soft tissue deformation is essential for virtual orthopedic surgery simulators, particularly for trauma cases involving complex, layered tissues.
• Existing models often lack the fidelity to accurately represent the heterogeneous, multilayered nature of human soft tissues.

Purpose of the Study:

• To propose a novel modeling framework for multilayered soft tissue deformation to improve orthopedic surgery simulators.
• To enhance the realism and accuracy of virtual surgical simulations by incorporating the layered structure of human organs.

Main Methods:

• A multilayered deformable model was constructed based on segmented data from the Chinese Visible Human (CVH) dataset.
• A 3D mass-spring system was employed for computational efficiency, incorporating a bilinear elasticity scheme to simulate nonlinear biomechanical properties.
• An optimization approach was utilized to accurately configure spring parameters for specific human tissue properties, validated against biomechanics literature.

Main Results:

• The developed framework successfully created a multilayered model reflecting anatomical layering.
• The mass-spring system with bilinear elasticity accurately reproduced nonlinear passive biomechanical properties of skin and skeletal muscle.
• Experiments demonstrated the framework's capability for interactive and realistic soft tissue deformation, validated by benchmark biomechanics data.

Conclusions:

• The proposed framework provides an effective method for simulating multilayered soft tissue deformation in virtual orthopedic surgery.
• The integration of a multilayered mass-spring model, optimization, and advanced visualization offers a feasible platform for realistic and interactive surgical training.