A Novel Path Planner for Steerable Bevel-Tip Needles to Reach Multiple Targets With Obstacles

Abstract

Steerable bevel-tip needles offer higher maneuverability independent of insertion depth and consequently are preferred for many needle-steering applications compared with symmetric-tip needles. Using these needles, the clinician can reach previously inaccessible targets using traditional stiff needles, thus helping improve the efficiency of needle insertion procedures significantly. However, due to their nonholonomic kinematics inside biological tissue, path planning of these needles is complicated and requires a great deal of care. Rapidly exploring random-tree (RRT)-based approaches are proper candidates for intraoperative planning of needle motion due to their fast computation and simple implementations. They also work well in high-dimensional configuration spaces and under nonholonomic kinematic constraints, both of which are the characteristics of steerable bevel-tip needle motion inside soft tissue. We developed a new heuristic-based RRT planner to reach multiple targets inside soft tissue without having to completely retract, reorient, and reinsert the needle toward each separate target, resulting in significantly less tissue damage compared with the conventional sequential insertion of the needle toward each target. Moreover, the proposed planner can have real clinical applications, where the limited size of the workspace as well as the needle's limited natural curvature imposes significant limitations on the needle path-planning problem inside soft tissue. Simulations demonstrate the efficiency of the proposed planner. The maximum targeting error of all targets is 1 mm and the needle's inserted length is decreased up to 35% compared with the sequential insertion of the needle for each target.