Autonomous medical needle steering in vivo

Author:

Kuntz Alan1ORCID,Emerson Maxwell2ORCID,Ertop Tayfun Efe2ORCID,Fried Inbar3ORCID,Fu Mengyu3ORCID,Hoelscher Janine3ORCID,Rox Margaret2ORCID,Akulian Jason4,Gillaspie Erin A.5,Lee Yueh Z.6ORCID,Maldonado Fabien5,Webster Robert J.2ORCID,Alterovitz Ron3ORCID

Affiliation:

1. Kahlert School of Computing and Robotics Center, University of Utah, Salt Lake City, UT 84112, USA.

2. Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA.

3. Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

4. Department of Medicine, Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA.

5. Department of Medicine and Thoracic Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA.

6. Department of Radiology, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA.

Abstract

The use of needles to access sites within organs is fundamental to many interventional medical procedures both for diagnosis and treatment. Safely and accurately navigating a needle through living tissue to a target is currently often challenging or infeasible because of the presence of anatomical obstacles, high levels of uncertainty, and natural tissue motion. Medical robots capable of automating needle-based procedures have the potential to overcome these challenges and enable enhanced patient care and safety. However, autonomous navigation of a needle around obstacles to a predefined target in vivo has not been shown. Here, we introduce a medical robot that autonomously navigates a needle through living tissue around anatomical obstacles to a target in vivo. Our system leverages a laser-patterned highly flexible steerable needle capable of maneuvering along curvilinear trajectories. The autonomous robot accounts for anatomical obstacles, uncertainty in tissue/needle interaction, and respiratory motion using replanning, control, and safe insertion time windows. We applied the system to lung biopsy, which is critical for diagnosing lung cancer, the leading cause of cancer-related deaths in the United States. We demonstrated successful performance of our system in multiple in vivo porcine studies achieving targeting errors less than the radius of clinically relevant lung nodules. We also demonstrated that our approach offers greater accuracy compared with a standard manual bronchoscopy technique. Our results show the feasibility and advantage of deploying autonomous steerable needle robots in living tissue and how these systems can extend the current capabilities of physicians to further improve patient care.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Mechanical Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Design of an MRI Compatible Steerable Guide for MRI-Guided Laser Interstitial Thermal Therapy;IEEE Transactions on Medical Robotics and Bionics;2024-02

2. The next generation of robotic surgery is emerging: but is it better than a human?;Nature Medicine;2024-01

3. Soft actuators in surgical robotics: a state-of-the-art review;Intelligent Service Robotics;2023-12-26

4. Landmark Based Bronchoscope Localization for Needle Insertion Under Respiratory Deformation;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

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