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

Precision cancer surgery aims to minimize tissue damage while ensuring effective tumor removal. The paper presented a numerical simulation study and its experimental validation to reveal the influence of surgical parameters on tissue fracture towards establishing precision cancer surgical procedure for achieving low tissue damage.

A mechanical tensile test was conducted on a clinically certified 3D-printed kidney model to characterize its biomechanical properties and determine constitutive model parameters. Based on these findings, we developed an advanced soft tissue resection simulation model, which can accurately capture the contact interactions between surgical tools and biological soft tissue. Additionally, we implemented a computational program that automates the selection of viscoelastic and hyperelastic properties, significantly reducing the need for repeated manual modeling. The accuracy of this simulation was validated through experimental resection tests.

This method saves about 40 % of time compared to traditional simulation methods. The study analyzed the effects of different resection angles, depths, and velocities on tissue damage. The results indicate that minimal tissue damage occurs at a higher resection speed (30 mm/s), a smaller depth, and an angle of 15° for horizontal cutting.

Higher resection speeds enhance fracture toughness, making tissue easier to fracture with less internal deformation, while smaller cutting angles reduce fiber breakage and energy dissipation, leading to minimal tissue damage. These findings suggest that optimizing resection parameters can significantly reduce tissue damage. The study provides insights into refining precision cancer surgical techniques and contributes to developing improved resection strategies that minimize collateral tissue damage.