Estimation of Needle Deflection in Layered Soft Tissue for Robotic Needle Steering

Abstract

Precise needle tip placement is important in robotic needle steering but it is challenging to estimate the behavior of the flexible needle when it interacts with the soft tissue. Numerous studies have been focused on a needle deflection model in homogeneous tissue. However, human soft tissues generally have layered structure which has various mechanical properties and geometries. In this paper, we proposed a needle deflection model in a layered elastic medium considering variable needle–tissue interaction forces such as friction of needle surface, needle tip force, and lateral stiffness of soft tissue. For validation, needle steering experiment was performed to a layered tissue phantom and porcine meat which has a skin layer and muscle layer. Using the forces measured from the needle base in the experiment, the needle tip position was simulated. The simulated needle tip trajectory was then compared to the measured needle tip trajectory. The average needle tip estimation error was 1.78 \(\pm \) 0.84 mm for tissue phantom and 1.85 \(\pm \) 0.73 mm for porcine tissue. The proposed model could be applied to the robotic needle steering in layered tissue.