Finite element analysis for evaluating liver tissue damage due to mechanical compression.

Area of Science:

• Biomedical Engineering
• Computational Mechanics
• Surgical Technology

Background:

• Robotic-assisted minimally invasive surgery (RMIS) demands methods to quantify tissue damage.
• Current tissue damage assessment often requires time-consuming bench work.
• Improving surgeon training and patient safety in RMIS is critical.

Purpose of the Study:

• To develop and validate a novel nonlinear finite element (FE) analysis methodology for predicting tissue damage during RMIS.
• To investigate the influence of boundary conditions and material properties on FE model simulations.
• To identify an efficient FE model for accurate tissue damage prediction.

Main Methods:

• Nonlinear finite element analysis (FEA) was employed to simulate mechanical compression on liver tissue.
• Four FE models were evaluated: 2D plane strain, 2D plane stress, full 3D, and 3D thin membrane.
• Material properties were derived from in vivo and in vitro experimental data.

Main Results:

• The 3D thin membrane model closely approximated full 3D analysis results for stress and damage.
• The 3D thin membrane model required significantly less computational time (0.2% of full 3D).
• FE model boundary conditions and material properties influenced stress and necrosis distributions.

Conclusions:

• The 3D thin membrane FE model provides an efficient and accurate approach for predicting tissue damage in RMIS.
• This methodology can enhance the design of surgical instruments and improve the realism of surgical simulators.
• Findings contribute to advancing surgeon training and patient safety in robotic surgery.