Resolution-Optimal Motion Planning for Steerable Needles
This work addresses the challenge of minimizing patient trauma in minimally invasive medical procedures, though it appears incremental as it builds on existing steerable needle motion planning with new theoretical guarantees.
The paper tackled the problem of automating motion planning for medical steerable needles to improve accuracy, precision, speed, and safety in procedures like lung biopsy, resulting in a planner that is faster and generates higher-quality plans compared to state-of-the-art methods.
Medical steerable needles can follow 3D curvilinear trajectories inside body tissue, enabling them to move around critical anatomical structures and precisely reach clinically significant targets in a minimally invasive way. Automating needle steering, with motion planning as a key component, has the potential to maximize the accuracy, precision, speed, and safety of steerable needle procedures. In this paper, we introduce the first resolution-optimal motion planner for steerable needles that offers excellent practical performance in terms of runtime while simultaneously providing strong theoretical guarantees on completeness and the global optimality of the motion plan in finite time. Compared to state-of-the-art steerable needle motion planners, simulation experiments on realistic scenarios of lung biopsy demonstrate that our proposed planner is faster in generating higher-quality plans while incorporating clinically relevant cost functions. This indicates that the theoretical guarantees of the proposed planner have a practical impact on the motion plan quality, which is valuable for computing motion plans that minimize patient trauma.