An Anatomy-specific Guidewire Shaping Robot for Improved Vascular Navigation

TL;DR

This paper introduces a robotic system for shaping guidewires in neuroendovascular procedures, enabling standardized, autonomous wire shaping tailored to specific vascular anatomies, thus reducing reliance on surgeon expertise.

Contribution

The authors develop a model and robotic system capable of producing clinically relevant wire shapes with high accuracy, including 3D configurations, for improved vascular navigation.

Findings

Robot can produce common clinical tip geometries with 0.56mm RMS error

Model accurately predicts wire shape from robot actions

Demonstrated successful navigation in complex vascular anatomy

Abstract

Neuroendovascular access often relies on passive microwires that are hand-shaped at the back table and then used to track a microcatheter to the target. Neuroendovascular surgeons determine the shape of the wire by examining the patient pre-operative images and using their experience to identify anatomy specific shapes of the wire that would facilitate reaching the target. This procedure is particularly complex in convoluted anatomical structures and is heavily dependent on the level of expertise of the surgeon. Towards enabling standardized autonomous shaping, we present a bench-top guidewire shaping robot capable of producing navigation-specific desired wire configurations. We present a model that can map the desired wire shape into robot actions, calibrated using experimental data. We show that the robot can produce clinically common tip geometries (C, S, Angled, Hook) and validate them with respect to the model-predicted shapes in 2D. Our model predicts the shape with a Root Mean Square (RMS) error of 0.56mm across all shapes when compared to the experimental results. We also demonstrate 3D tip shaping capabilities and the ability to traverse complex endoluminal navigation from the petrous Internal Carotid Artery (ICA) to the Posterior Communicating Artery (PComm).