[Paper Review] A Novel Shaft-to-Tissue Force Model for Safer Motion Planning of Steerable Needles.

Michael Bentley, D. Caleb Rucker+3 more|arXiv (Cornell University)|Jan 6, 2021

Soft Robotics and Applications47 references4 citations

TL;DR

This paper proposes a novel Cosserat string-based force model that predicts shaft-to-tissue normal and frictional forces during steerable needle insertion, integrating it into an asymptotically near-optimal motion planner to minimize tissue damage. The method successfully plans safer, curved needle paths that reduce shearing forces while maintaining target accuracy in simulated lung tumor biopsy scenarios.

ABSTRACT

Steerable needles are capable of accurately targeting difficult-to-reach clinical sites in the body. By bending around sensitive anatomical structures, steerable needles have the potential to reduce the invasiveness of many medical procedures. However, inserting these needles with curved trajectories increases the risk of tissue shearing due to large forces being exerted on the surrounding tissue by the needle's shaft. Such shearing can cause significant damage to surrounding tissue, potentially worsening patient outcomes. In this work, we derive a tissue and needle force model based on a Cosserat string formulation, which describes the normal forces and frictional forces along the shaft as a function of the planned needle path, friction parameters, and tip piercing force. We then incorporate this force model as a cost function in an asymptotically near-optimal motion planner and demonstrate the ability to plan motions that consider the tissue normal forces from the needle shaft during planning in a simulated steering environment and a simulated lung tumor biopsy scenario. By planning motions for the needle that aim to minimize the tissue normal force explicitly, our method plans needle paths that reduce the risk of tissue shearing while still reaching desired targets in the body.

Motivation & Objective

• To address the risk of tissue shearing caused by high normal and frictional forces exerted by curved needle shafts during insertion.
• To develop a physics-based force model that quantifies shaft-tissue interactions as a function of needle path, friction, and tip force.
• To integrate the force model into a motion planner that explicitly minimizes tissue damage during trajectory generation.
• To validate the method in simulated environments, including a clinically relevant lung tumor biopsy scenario.

Proposed method

• Derives a force model using Cosserat string theory to describe normal and tangential (frictional) forces along the needle shaft during curved insertion.
• Models the normal force as a function of the needle's curvature, path geometry, and tissue mechanical properties.
• Incorporates the frictional force component dependent on the normal force and a coefficient of friction.
• Uses the tip piercing force as a key input to scale the overall shaft force distribution.
• Introduces the derived force model as a cost function in an asymptotically near-optimal motion planner.
• Employs numerical simulation to evaluate needle paths that minimize the integrated tissue force along the shaft.

Experimental results

Research questions

• RQ1 How can the normal and frictional forces between a curved needle shaft and surrounding tissue be accurately modeled during insertion?
• RQ2 Can a physics-based force model be integrated into a motion planner to reduce tissue damage during steerable needle navigation?
• RQ3 To what extent can minimizing shaft-induced tissue forces improve safety in needle insertion without compromising target accuracy?
• RQ4 How does the proposed method perform in a realistic simulation of a lung tumor biopsy procedure?

Key findings

• The Cosserat string-based force model accurately predicts shaft-to-tissue forces as a function of path curvature, friction, and tip force.
• Incorporating the force model into the motion planner enables the generation of needle trajectories that explicitly minimize tissue normal forces.
• The method successfully reduces predicted tissue shearing risk while maintaining accurate targeting in simulated environments.
• The simulated lung tumor biopsy scenario demonstrated that the planner could generate safe, curved paths that avoid excessive tissue loading.