Modelling and Simulation of Energy Cutting Tool for Soft Tissue Using a Novel extended Finite Element Method

Area of Science:

• Biomedical Engineering
• Surgical Technology
• Computational Mechanics

Background:

• Energy-based surgical tools offer combined cutting and hemostasis capabilities, widely used in various procedures.
• Precise prediction of tissue deformation during energy cutting is crucial for surgical navigation and improved outcomes.
• Existing models for surgical cutting often focus on blade-based tools and cannot accurately predict deformation from energy-based instruments.

Purpose of the Study:

• To develop a novel computational model for predicting tissue deformation during energy-based cutting.
• To investigate the model's performance across different cutting trajectories.
• To enhance computational efficiency for real-time surgical applications.

Main Methods:

• A stratified discontinuity mechanism-based modeling approach for energy cutting.
• Development of a parameterized impact zone model to represent complex surgical manipulations.
• Implementation of an incremental cutting computation algorithm with a novel void enrichment function.

Main Results:

• The developed model achieved mean absolute deformation errors below 1 mm when compared to experimental results across various cutting trajectories.
• Validation of the model's computational efficiency and convergence properties.
• Demonstrated robust accuracy in predicting cutting deformation.

Conclusions:

• The novel energy cutting model achieves the desired accuracy for predicting tissue deformation.
• The model maintains computational efficiency, making it suitable for surgical applications.
• This research advances the capabilities of energy-based surgical tools through improved predictive modeling.