A new fast nonlinear modeling of soft tissue for surgical simulation

Area of Science:

• Biomechanics
• Robotic Surgery
• Materials Science

Background:

• Soft tissue deformation is crucial in robotic surgery.
• Accurate modeling of tissue behavior under external forces is needed.
• Understanding tissue failure points is essential for safe surgical interventions.

Purpose of the Study:

• To simulate soft tissue deformation using a nonlinear viscoelastic model.
• To develop a mass-spring-damper system for modeling tissue response to surgical instruments.
• To determine the force and displacement thresholds for soft tissue tearing.

Main Methods:

• A nonlinear viscoelastic model was applied to soft tissue confined in a mold.
• Dynamic equations were derived as ordinary differential equations.
• Bovine sirloin data was collected using an Instron hardness tester for model validation.

Main Results:

• Simulations accurately predicted laboratory findings for tissue deformation.
• Unknown parameters of the nonlinear model were successfully estimated.
• Threshold force and displacement values preceding tissue tearing were identified.

Conclusions:

• The mass-spring-damper model effectively simulates soft tissue deformation.
• The study provides critical data for enhancing safety in robotic surgery.
• Identified tearing thresholds can inform surgical instrument design and control.