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Towards Autonomous Navigation of Neuroendovascular Tools for Timely Stroke Treatment via Contact-aware Path Planning

Aabha Tamhankar, Giovanni Pittiglio

TL;DR

The paper addresses the critical need for rapid reperfusion in ischemic stroke by enabling semi-autonomous navigation of telescoping neuroendovascular tools inside patient-specific arteries. It introduces a model-based contact-aware planner that combines a static elasticity model of the tools with anatomical constraints derived from pre-operative 3D segmentation and solves via a contact-aware RRT to produce feasible paths. Experimental validation on a realistic aorta phantom demonstrates 50 trials with 100% success to reach the LCCA, with robustness to aorta motion up to 10° and 10 mm misalignment. This approach has the potential to reduce time to reperfusion, support rural centers, and provide actionable semi-autonomous guidance, with future work extending to full cerebral vasculature and closed-loop imaging control.

Abstract

In this paper, we propose a model-based contact-aware motion planner for autonomous navigation of neuroendovascular tools in acute ischemic stroke. The planner is designed to find the optimal control strategy for telescopic pre-bent catheterization tools such as guidewire and catheters, currently used for neuroendovascular procedures. A kinematic model for the telescoping tools and their interaction with the surrounding anatomy is derived to predict tools steering. By leveraging geometrical knowledge of the anatomy, obtained from pre-operative segmented 3D images, and the mechanics of the telescoping tools, the planner finds paths to the target enabled by interacting with the surroundings. We propose an actuation platform for insertion and rotation of the telescopic tools and present experimental results for the navigation from the base of the descending aorta to the LCCA. We demonstrate that, by leveraging the pre-operative plan, we can consistently navigate the LCCA with 100% success of over 50 independent trials. We also study the robustness of the planner towards motion of the aorta and errors in the initial positioning of the robotic tools. The proposed plan can successfully reach the LCCA for rotations of the aorta of up to 10°, and displacement of up to 10mm, on the coronal plane.

Towards Autonomous Navigation of Neuroendovascular Tools for Timely Stroke Treatment via Contact-aware Path Planning

TL;DR

The paper addresses the critical need for rapid reperfusion in ischemic stroke by enabling semi-autonomous navigation of telescoping neuroendovascular tools inside patient-specific arteries. It introduces a model-based contact-aware planner that combines a static elasticity model of the tools with anatomical constraints derived from pre-operative 3D segmentation and solves via a contact-aware RRT to produce feasible paths. Experimental validation on a realistic aorta phantom demonstrates 50 trials with 100% success to reach the LCCA, with robustness to aorta motion up to 10° and 10 mm misalignment. This approach has the potential to reduce time to reperfusion, support rural centers, and provide actionable semi-autonomous guidance, with future work extending to full cerebral vasculature and closed-loop imaging control.

Abstract

In this paper, we propose a model-based contact-aware motion planner for autonomous navigation of neuroendovascular tools in acute ischemic stroke. The planner is designed to find the optimal control strategy for telescopic pre-bent catheterization tools such as guidewire and catheters, currently used for neuroendovascular procedures. A kinematic model for the telescoping tools and their interaction with the surrounding anatomy is derived to predict tools steering. By leveraging geometrical knowledge of the anatomy, obtained from pre-operative segmented 3D images, and the mechanics of the telescoping tools, the planner finds paths to the target enabled by interacting with the surroundings. We propose an actuation platform for insertion and rotation of the telescopic tools and present experimental results for the navigation from the base of the descending aorta to the LCCA. We demonstrate that, by leveraging the pre-operative plan, we can consistently navigate the LCCA with 100% success of over 50 independent trials. We also study the robustness of the planner towards motion of the aorta and errors in the initial positioning of the robotic tools. The proposed plan can successfully reach the LCCA for rotations of the aorta of up to 10°, and displacement of up to 10mm, on the coronal plane.

Paper Structure

This paper contains 11 sections, 13 equations, 7 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. Catheterization Tools Static Model
  3. Single Tool Model
  4. Telescoping Tools Constraints
  5. Anatomical Constraints
  6. Static Equilibrium Solution
  7. RRT Planner for Neuroendovascular Tools
  8. Experimental Validation
  9. Actuation System
  10. Results
  11. Conclusions

Figures (7)

  • Figure 1: Description of robotic platform for autonomous navigation of neuroendovascular catheterization tools.
  • Figure 2: Schematic description of model parameters.
  • Figure 3: Components of the experimental setup. a) Actuation system for controlling guidewire translation and rotation; b) Guidewire and Catheter system inside anatomy; c) Tools configuration parameters.
  • Figure 4: Contact-aware planned path from base of descending aorta to , avoiding . ① Start configuration, ⑥ End configuration.
  • Figure 5: Guidewire navigation in the phantom of the arteries in antero/posterior and lateral views; a) initial configuration; b) guidewire avoiding ; c) guidewire entering ; d) end configuration.
  • ...and 2 more figures