Physics-based simulation of surgical fields for preoperative strategic planning

Area of Science:

• Computational physics and medical simulation
• Surgical planning and decision support systems

Background:

• Conventional surgical planning tools lack the capability to simulate complex soft tissue behaviors during procedures.
• Accurate simulation of cutting and deformation is crucial for detailed preoperative planning and discussion.

Purpose of the Study:

• To propose an adaptive physics-based framework for simulating interactive cutting and deformation of virtual bodies.
• To develop a strategic planning system for preoperative decision-making using 3D surgical field representations.
• To enhance discussion of patient-specific surgical approaches.

Main Methods:

• Developed an adaptive framework integrating particle-based and Finite Element Method (FEM)-based models.
• Utilized FEM-based deformation for accurate simulation of surgical incisions and fields.
• Integrated a 3D representation system for strategic surgical approach planning.

Main Results:

• The framework successfully simulates interactive cutting and accurate soft tissue deformation.
• FEM-based deformation accurately models surgical incisions and resulting surgical fields.
• Experiments and usability tests confirmed the system's utility in understanding 3D anatomy and planning surgical approaches.

Conclusions:

• The proposed physics-based framework and planning system significantly improve preoperative surgical planning.
• The system facilitates detailed, patient-specific discussions on surgical strategies.
• Enhanced understanding of 3D anatomy and target organ location aids in surgical decision-making.