A numerical simulation study of soft tissue resection for low-damage precision cancer surgery

Area of Science:

• Biomechanical Engineering
• Surgical Oncology
• Computational Modeling

Background:

• Precision cancer surgery strives to minimize tissue damage during tumor removal.
• Understanding the influence of surgical parameters on tissue fracture is crucial for developing less invasive techniques.

Purpose of the Study:

• To investigate the impact of surgical parameters on tissue damage during resection.
• To establish optimal parameters for precision cancer surgical procedures.
• To validate a novel simulation model for soft tissue resection.

Main Methods:

• Mechanical tensile testing of a 3D-printed kidney model to determine biomechanical properties.
• Development of an advanced soft tissue resection simulation model with automated parameter selection.
• Experimental validation of the simulation model through resection tests.

Main Results:

• The simulation model reduced modeling time by approximately 40% compared to traditional methods.
• Analysis revealed that minimal tissue damage occurred at a resection speed of 30 mm/s, with smaller depths and a 15° angle for horizontal cutting.
• Higher resection speeds increase fracture toughness, while smaller cutting angles reduce fiber breakage and energy dissipation.

Conclusions:

• Optimizing resection parameters (speed, depth, angle) significantly minimizes tissue damage.
• Findings provide insights for refining precision cancer surgical techniques.
• The study contributes to developing improved resection strategies for reduced collateral tissue damage.