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Duan Y, Ling J, Feng Z, Ye T, Sun T, Zhu Y. A Survey of Needle Steering Approaches in Minimally Invasive Surgery. Ann Biomed Eng 2024; 52:1492-1517. [PMID: 38530535 DOI: 10.1007/s10439-024-03494-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 03/08/2024] [Indexed: 03/28/2024]
Abstract
In virtue of a curved insertion path inside tissues, needle steering techniques have revealed the potential with the assistance of medical robots and images. The superiority of this technique has been preliminarily verified with several maneuvers: target realignment, obstacle circumvention, and multi-target access. However, the momentum of needle steering approaches in the past decade leads to an open question-"How to choose an applicable needle steering approach for a specific clinical application?" This survey discusses this question in terms of design choices and clinical considerations, respectively. In view of design choices, this survey proposes a hierarchical taxonomy of current needle steering approaches. Needle steering approaches of different manipulations and designs are classified to systematically review the design choices and their influences on clinical treatments. In view of clinical consideration, this survey discusses the steerability and acceptability of the current needle steering approaches. On this basis, the pros and cons of the current needle steering approaches are weighed and their suitable applications are summarized. At last, this survey concluded with an outlook of the needle steering techniques, including the potential clinical applications and future developments in mechanical design.
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Affiliation(s)
- Yuzhou Duan
- College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China
| | - Jie Ling
- College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
| | - Zhao Feng
- School of Power and Mechanical Engineering, Wuhan University, Wuhan, 430072, China
- Wuhan University Shenzhen Research Institute, Shenzhen, 518057, China
| | - Tingting Ye
- Industrial and Systems Engineering Department, The Hong Kong Polytechnic University, Hong Kong SAR, 999077, China
| | - Tairen Sun
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China
| | - Yuchuan Zhu
- College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China
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2
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Kuntz A, Emerson M, Ertop TE, Fried I, Fu M, Hoelscher J, Rox M, Akulian J, Gillaspie EA, Lee YZ, Maldonado F, Webster RJ, Alterovitz R. Autonomous medical needle steering in vivo. Sci Robot 2023; 8:eadf7614. [PMID: 37729421 PMCID: PMC11182607 DOI: 10.1126/scirobotics.adf7614] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 08/21/2023] [Indexed: 09/22/2023]
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.
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Affiliation(s)
- Alan Kuntz
- Kahlert School of Computing and Robotics Center, University of Utah; Salt Lake City, UT 84112, USA
| | - Maxwell Emerson
- Department of Mechanical Engineering, Vanderbilt University; Nashville, TN 37235, USA
| | - Tayfun Efe Ertop
- Department of Mechanical Engineering, Vanderbilt University; Nashville, TN 37235, USA
| | - Inbar Fried
- Department of Computer Science, University of North Carolina at Chapel Hill; Chapel Hill, NC 27599, USA
| | - Mengyu Fu
- Department of Computer Science, University of North Carolina at Chapel Hill; Chapel Hill, NC 27599, USA
| | - Janine Hoelscher
- Department of Computer Science, University of North Carolina at Chapel Hill; Chapel Hill, NC 27599, USA
| | - Margaret Rox
- Department of Mechanical Engineering, Vanderbilt University; Nashville, TN 37235, USA
| | - Jason Akulian
- Department of Medicine, Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina School of Medicine; Chapel Hill, NC 27599, USA
| | - Erin A. Gillaspie
- Department of Medicine and Thoracic Surgery, Vanderbilt University Medical Center; Nashville, TN 37232, USA
| | - Yueh Z. Lee
- Department of Radiology, University of North Carolina School of Medicine; Chapel Hill, NC 27599, USA
| | - Fabien Maldonado
- Department of Medicine and Thoracic Surgery, Vanderbilt University Medical Center; Nashville, TN 37232, USA
| | - Robert J. Webster
- Department of Mechanical Engineering, Vanderbilt University; Nashville, TN 37235, USA
| | - Ron Alterovitz
- Department of Computer Science, University of North Carolina at Chapel Hill; Chapel Hill, NC 27599, USA
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3
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Fu M, Solovey K, Salzman O, Alterovitz R. Toward certifiable optimal motion planning for medical steerable needles. Int J Rob Res 2023; 42:798-826. [PMID: 37905207 PMCID: PMC10613120 DOI: 10.1177/02783649231165818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Medical steerable needles can follow 3D curvilinear trajectories to avoid anatomical obstacles and reach clinically significant targets inside the human body. Automating steerable needle procedures can enable physicians and patients to harness the full potential of steerable needles by maximally leveraging their steerability to safely and accurately reach targets for medical procedures such as biopsies. For the automation of medical procedures to be clinically accepted, it is critical from a patient care, safety, and regulatory perspective to certify the correctness and effectiveness of the planning algorithms involved in procedure automation. In this paper, we take an important step toward creating a certifiable optimal planner for steerable needles. We present an efficient, resolution-complete motion planner for steerable needles based on a novel adaptation of multi-resolution planning. This is the first motion planner for steerable needles that guarantees to compute in finite time an obstacle-avoiding plan (or notify the user that no such plan exists), under clinically appropriate assumptions. Based on this planner, we then develop the first resolution-optimal motion planner for steerable needles that further provides theoretical guarantees on the quality of the computed motion plan, that is, global optimality, in finite time. Compared to state-of-the-art steerable needle motion planners, we demonstrate with clinically realistic simulations that our planners not only provide theoretical guarantees but also have higher success rates, have lower computation times, and result in higher quality plans.
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Affiliation(s)
- Mengyu Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kiril Solovey
- Department of Electrical and Computer Engineering, Technion-Israel Institute of Technology, Haifa, Israel
| | - Oren Salzman
- Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel
| | - Ron Alterovitz
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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4
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Berthet-Rayne P, Yang GZ. Navigation with minimal occupation volume for teleoperated snake-like surgical robots: MOVE. Front Robot AI 2023; 10:1211876. [PMID: 37377630 PMCID: PMC10291266 DOI: 10.3389/frobt.2023.1211876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 05/16/2023] [Indexed: 06/29/2023] Open
Abstract
Master-Slave control is a common mode of operation for surgical robots as it ensures that surgeons are always in control and responsible for the procedure. Most teleoperated surgical systems use low degree-of-freedom (DOF) instruments, thus facilitating direct mapping of manipulator position to the instrument pose and tip location (tip-to-tip mapping). However, with the introduction of continuum and snake-like robots with much higher DOF supported by their inherent redundant architecture for navigating through curved anatomical pathways, there is a need for developing effective kinematic methods that can actuate all the joints in a controlled fashion. This paper introduces the concept of navigation with Minimal Occupation VolumE (MOVE), a teleoperation method that extends the concept of follow-the-leader navigation. It defines the path taken by the head while using all the available space surrounding the robot constrained by individual joint limits. The method was developed for the i 2 Snake robot and validated with detailed simulation and control experiments. The results validate key performance indices such as path following, body weights, path weights, fault tolerance and conservative motion. The MOVE solver can run in real-time on a standard computer at frequencies greater than 1 kHz.
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Affiliation(s)
- Pierre Berthet-Rayne
- The Hamlyn Centre for Robotic Surgery, Imperial College London, London, United Kingdom
| | - Guang-Zhong Yang
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China
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5
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Feng S, Wang S, Jiang W, Gao X. Planning of Medical Flexible Needle Motion in Effective Area of Clinical Puncture. SENSORS (BASEL, SWITZERLAND) 2023; 23:671. [PMID: 36679469 PMCID: PMC9867150 DOI: 10.3390/s23020671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/20/2022] [Accepted: 01/04/2023] [Indexed: 06/17/2023]
Abstract
Lung cancer is the leading cause of cancer deaths worldwide. Although several lung cancer diagnostic methods are available for lung nodule biopsy, there are limitations in terms of accuracy, safety, and invasiveness. Transbronchial needle aspiration (TBNA) is a common method for diagnosing and treating lung cancer that involves a robot-assisted medical flexible needle moving along a curved three-dimensional trajectory, avoiding anatomical barriers to achieve clinically meaningful goals in humans. Inspired by the puncture angle between the needle tip and the vessel in venipuncture, we suggest that different orientations of the medical flexible needle puncture path affect the cost of the puncture trajectory and propose an effective puncture region based on the optimal puncture direction, which is a strategy based on imposing geometric constraints on the search space of the puncture direction, and based on this, we focused on the improved implementation of RCS*. Planning within the TBNA-based lung environment was performed using the rapidly exploring random tree (RRT), resolution-complete search (RCS), and RCS* (a resolution-optimal version of RCS) within an effective puncture region. The experimental results show that the optimal puncture direction corresponding to the lowest cost puncture trajectory is consistent among the three algorithms and RCS* is more efficient for planning. The experiments verified the feasibility and practicality of our proposed minimum puncture angle and puncture effective region and facilitated the study of the puncture direction of flexible needle puncture.
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Affiliation(s)
| | - Shigang Wang
- Correspondence: (S.W.); (X.G.); Tel.: +86-1857-726-2003 (S.W.); +86-1880-772-7899 (X.G.)
| | | | - Xueshan Gao
- Correspondence: (S.W.); (X.G.); Tel.: +86-1857-726-2003 (S.W.); +86-1880-772-7899 (X.G.)
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6
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Hoelscher J, Fried I, Fu M, Patwardhan M, Christman M, Akulian J, Webster RJ, Alterovitz R. A Metric for Finding Robust Start Positions for Medical Steerable Needle Automation. PROCEEDINGS OF THE ... IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS. IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS 2022; 2022:9526-9533. [PMID: 37153690 PMCID: PMC10162587 DOI: 10.1109/iros47612.2022.9982227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Steerable needles are medical devices with the ability to follow curvilinear paths to reach targets while circumventing obstacles. In the deployment process, a human operator typically places the steerable needle at its start position on a tissue surface and then hands off control to the automation that steers the needle to the target. Due to uncertainty in the placement of the needle by the human operator, choosing a start position that is robust to deviations is crucial since some start positions may make it impossible for the steerable needle to safely reach the target. We introduce a method to efficiently evaluate steerable needle motion plans such that they are safe to variation in the start position. This method can be applied to many steerable needle planners and requires that the needle's orientation angle at insertion can be robotically controlled. Specifically, we introduce a method that builds a funnel around a given plan to determine a safe insertion surface corresponding to insertion points from which it is guaranteed that a collision-free motion plan to the goal can be computed. We use this technique to evaluate multiple feasible plans and select the one that maximizes the size of the safe insertion surface. We evaluate our method through simulation in a lung biopsy scenario and show that the method is able to quickly find needle plans with a large safe insertion surface.
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Affiliation(s)
- Janine Hoelscher
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Inbar Fried
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Mengyu Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Mihir Patwardhan
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Max Christman
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason Akulian
- Division of Pulmonary Diseases and Critical Care Medicine at the University of North Carolina at Chapel Hill, NC 27599, USA
| | - Robert J Webster
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Ron Alterovitz
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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7
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Fu M, Solovey K, Salzman O, Alterovitz R. Resolution-Optimal Motion Planning for Steerable Needles. IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION : ICRA : [PROCEEDINGS]. IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION 2022; 2022:9652-9659. [PMID: 36337768 PMCID: PMC9629985 DOI: 10.1109/icra46639.2022.9811850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
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.
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Affiliation(s)
- Mengyu Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kiril Solovey
- Computer Science Department, Technion - Israel Institute of Technology, Israel
| | - Oren Salzman
- Computer Science Department, Technion - Israel Institute of Technology, Israel
| | - Ron Alterovitz
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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8
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Fu M, Salzman O, Alterovitz R. Toward Certifiable Motion Planning for Medical Steerable Needles. ROBOTICS SCIENCE AND SYSTEMS : ONLINE PROCEEDINGS 2021; 2021:10.15607/rss.2021.xvii.081. [PMID: 36312204 PMCID: PMC9612400 DOI: 10.15607/rss.2021.xvii.081] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Medical steerable needles can move along 3D curvilinear trajectories to avoid anatomical obstacles and reach clinically significant targets inside the human body. Automating steerable needle procedures can enable physicians and patients to harness the full potential of steerable needles by maximally leveraging their steerability to safely and accurately reach targets for medical procedures such as biopsies and localized therapy delivery for cancer. For the automation of medical procedures to be clinically accepted, it is critical from a patient care, safety, and regulatory perspective to certify the correctness and effectiveness of the motion planning algorithms involved in procedure automation. In this paper, we take an important step toward creating a certifiable motion planner for steerable needles. We introduce the first motion planner for steerable needles that offers a guarantee, under clinically appropriate assumptions, that it will, in finite time, compute an exact, obstacle-avoiding motion plan to a specified target, or notify the user that no such plan exists. We present an efficient, resolution-complete motion planner for steerable needles based on a novel adaptation of multi-resolution planning. Compared to state-of-the-art steerable needle motion planners (none of which provide any completeness guarantees), we demonstrate that our new resolution-complete motion planner computes plans faster and with a higher success rate.
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Affiliation(s)
- Mengyu Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Oren Salzman
- Computer Science Department, Technion - Israel Institute of Technology, Israel
| | - Ron Alterovitz
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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9
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Fried I, Hoelscher J, Fu M, Emerson M, Ertop TE, Rox M, Granna J, Kuntz A, Akulian JA, Webster RJ, Alterovitz R. Design Considerations for a Steerable Needle Robot to Maximize Reachable Lung Volume. IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION : ICRA : [PROCEEDINGS]. IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION 2021; 2021:10.1109/icra48506.2021.9561342. [PMID: 34721939 PMCID: PMC8553157 DOI: 10.1109/icra48506.2021.9561342] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Steerable needles that are able to follow curvilinear trajectories and steer around anatomical obstacles are a promising solution for many interventional procedures. In the lung, these needles can be deployed from the tip of a conventional bronchoscope to reach lung lesions for diagnosis. The reach of such a device depends on several design parameters including the bronchoscope diameter, the angle of the piercing device relative to the medial axis of the airway, and the needle's minimum radius of curvature while steering. Assessing the effect of these parameters on the overall system's clinical utility is important in informing future design choices and understanding the capabilities and limitations of the system. In this paper, we analyze the effect of various settings for these three robot parameters on the percentage of the lung that the robot can reach. We combine Monte Carlo random sampling of piercing configurations with a Rapidly-exploring Random Trees based steerable needle motion planner in simulated human lung environments to asymptotically accurately estimate the volume of sites in the lung reachable by the robot. We highlight the importance of each parameter on the overall system's reachable workspace in an effort to motivate future device innovation and highlight design trade-offs.
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Affiliation(s)
- Inbar Fried
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
| | - Janine Hoelscher
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Mengyu Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Maxwell Emerson
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Tayfun Efe Ertop
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Margaret Rox
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Josephine Granna
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Alan Kuntz
- School of Computing and the Robotics Center, University of Utah, Salt Lake City, UT 84112, USA
| | - Jason A. Akulian
- Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina School of Medicine, Chapel Hill, NC 27514, USA
| | - Robert J. Webster
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Ron Alterovitz
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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10
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Hoelscher J, Fu M, Fried I, Emerson M, Ertop TE, Rox M, Kuntz A, Akulian JA, Webster RJ, Alterovitz R. Backward Planning for a Multi-Stage Steerable Needle Lung Robot. IEEE Robot Autom Lett 2021; 6:3987-3994. [PMID: 33937523 PMCID: PMC8087253 DOI: 10.1109/lra.2021.3066962] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Lung cancer is one of the deadliest types of cancer, and early diagnosis is crucial for successful treatment. Definitively diagnosing lung cancer typically requires biopsy, but current approaches either carry a high procedural risk for the patient or are incapable of reaching many sites of clinical interest in the lung. We present a new sampling-based planning method for a steerable needle lung robot that has the potential to accurately reach targets in most regions of the lung. The robot comprises three stages: a transorally deployed bronchoscope, a sharpened piercing tube (to pierce into the lung parenchyma from the airways), and a steerable needle able to navigate to the target. Planning for the sequential deployment of all three stages under health safety concerns is a challenging task, as each stage depends on the previous one. We introduce a new backward planning approach that starts at the target and advances backwards toward the airways with the goal of finding a piercing site reachable by the bronchoscope. This new strategy enables faster performance by iteratively building a single search tree during the entire computation period, whereas previous forward approaches have relied on repeating this expensive tree construction process many times. Additionally, our method further reduces runtime by employing biased sampling and sample rejection based on geometric constraints. We evaluate this approach using simulation-based studies in anatomical lung models. We demonstrate in comparison with existing techniques that the new approach (i) is more likely to find a path to a target, (ii) is more efficient by reaching targets more than 5 times faster on average, and (iii) arrives at lower-risk paths in shorter time.
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Affiliation(s)
- Janine Hoelscher
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Mengyu Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Inbar Fried
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Maxwell Emerson
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Tayfun Efe Ertop
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Margaret Rox
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Alan Kuntz
- School of Computing and the Robotics Center, University of Utah, Salt Lake City, UT 84112, USA
| | - Jason A Akulian
- Division of Pulmonary Diseases and Critical Care Medicine at the University of North Carolina at Chapel Hill, NC 27599, USA
| | - Robert J Webster
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Ron Alterovitz
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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11
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Rox M, Emerson M, Ertop TE, Fried I, Fu M, Hoelscher J, Kuntz A, Granna J, Mitchell J, Lester M, Maldonado F, Gillaspie EA, Akulian JA, Alterovitz R, Webster RJ. Decoupling Steerability from Diameter: Helical Dovetail Laser Patterning for Steerable Needles. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2020; 8:181411-181419. [PMID: 35198341 PMCID: PMC8863302 DOI: 10.1109/access.2020.3028374] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
The maximum curvature of a steerable needle in soft tissue is highly sensitive to needle shaft stiffness, which has motivated use of small diameter needles in the past. However, desired needle payloads constrain minimum shaft diameters, and shearing along the needle shaft can occur at small diameters and high curvatures. We provide a new way to adjust needle shaft stiffness (thereby enhancing maximum curvature, i.e. "steerability") at diameters selected based on needle payload requirements. We propose helical dovetail laser patterning to increase needle steerability without reducing shaft diameter. Experiments in phantoms and ex vivo animal muscle, brain, liver, and inflated lung tissues demonstrate high steerability in soft tissues. These experiments use needle diameters suitable for various clinical scenarios, and which have been previously limited by steering challenges without helical dovetail patterning. We show that steerable needle targeting remains accurate with established controllers and demonstrate interventional payload delivery (brachytherapy seeds and radiofrequency ablation) through the needle. Helical dovetail patterning decouples steerability from diameter in needle design. It enables diameter to be selected based on clinical requirements rather than being carefully tuned to tissue properties. These results pave the way for new sensors and interventional tools to be integrated into high-curvature steerable needles.
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Affiliation(s)
- Margaret Rox
- Department of Mechanical Engineering and the Vanderbilt Institute for Surgery and Engineering at Vanderbilt University, Nashville, TN 37203, USA
| | - Maxwell Emerson
- Department of Mechanical Engineering and the Vanderbilt Institute for Surgery and Engineering at Vanderbilt University, Nashville, TN 37203, USA
| | - Tayfun Efe Ertop
- Department of Mechanical Engineering and the Vanderbilt Institute for Surgery and Engineering at Vanderbilt University, Nashville, TN 37203, USA
| | - Inbar Fried
- Department of Computer Science at the University of North Carolina at Chapel Hill, NC 27599, USA
| | - Mengyu Fu
- Department of Computer Science at the University of North Carolina at Chapel Hill, NC 27599, USA
| | - Janine Hoelscher
- Department of Computer Science at the University of North Carolina at Chapel Hill, NC 27599, USA
| | - Alan Kuntz
- Robotics Center and the School of Computing at the University of Utah, Salt Lake City, UT 84112, USA
| | - Josephine Granna
- Department of Mechanical Engineering and the Vanderbilt Institute for Surgery and Engineering at Vanderbilt University, Nashville, TN 37203, USA
| | - Jason Mitchell
- Department of Mechanical Engineering and the Vanderbilt Institute for Surgery and Engineering at Vanderbilt University, Nashville, TN 37203, USA
| | - Michael Lester
- Department of Medicine and Thoracic Surgery at the Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Fabien Maldonado
- Department of Medicine and Thoracic Surgery at the Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Erin A Gillaspie
- Department of Medicine and Thoracic Surgery at the Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Jason A Akulian
- Division of Pulmonary Diseases and Critical Care Medicine at the University of North Carolina at Chapel Hill, NC 27599, USA
| | - Ron Alterovitz
- Department of Computer Science at the University of North Carolina at Chapel Hill, NC 27599, USA
| | - Robert J Webster
- Department of Mechanical Engineering and the Vanderbilt Institute for Surgery and Engineering at Vanderbilt University, Nashville, TN 37203, USA
- Department of Medicine and Thoracic Surgery at the Vanderbilt University Medical Center, Nashville, TN 37212, USA
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12
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Ertop TE, Emerson M, Rox M, Granna J, Maldonado F, Gillaspie E, Lester M, Kuntz A, Rucker C, Fu M, Hoelscher J, Fried I, Alterovitz R, Webster R. STEERABLE NEEDLE TRAJECTORY FOLLOWING IN THE LUNG: TORSIONAL DEADBAND COMPENSATION AND FULL POSE ESTIMATION WITH 5DOF FEEDBACK FOR NEEDLES PASSING THROUGH FLEXIBLE ENDOSCOPES. PROCEEDINGS OF THE ASME DYNAMIC SYSTEMS AND CONTROL CONFERENCE. ASME DYNAMIC SYSTEMS AND CONTROL CONFERENCE 2020; 2020:V001T05A003. [PMID: 35284151 PMCID: PMC8916686 DOI: 10.1115/dscc2020-3163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Bronchoscopic diagnosis and intervention in the lung is a new frontier for steerable needles, where they have the potential to enable minimally invasive, accurate access to small nodules that cannot be reliably accessed today. However, the curved, flexible bronchoscope requires a much longer needle than prior work has considered, with complex interactions between the needle and bronchoscope channel, introducing new challenges in steerable needle control. In particular, friction between the working channel and needle causes torsional windup along the bronchoscope, the effects of which cannot be directly measured at the tip of thin needles embedded with 5 degree-of-freedom magnetic tracking coils. To compensate for these effects, we propose a new torsional deadband-aware Extended Kalman Filter to estimate the full needle tip pose including the axial angle, which defines its steering direction. We use the Kalman Filter estimates with an established sliding mode controller to steer along desired trajectories in lung tissue. We demonstrate that this simple torsional deadband model is sufficient to account for the complex interactions between the needle and endoscope channel for control purposes. We measure mean final targeting error of 1.36 mm in phantom tissue and 1.84 mm in ex-vivo porcine lung, with mean trajectory following error of 1.28 mm and 1.10 mm, respectively.
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Affiliation(s)
| | - Maxwell Emerson
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37212
| | - Margaret Rox
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37212
| | - Josephine Granna
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37212
| | | | - Erin Gillaspie
- Vanderbilt University Medical Center, Nashville, TN 37212
| | - Michael Lester
- Vanderbilt University Medical Center, Nashville, TN 37212
| | - Alan Kuntz
- Robotics Center and School of Computing, University of Utah, Salt Lake City, UT 84112
| | - Caleb Rucker
- The Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996
| | - Mengyu Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Janine Hoelscher
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Inbar Fried
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Ron Alterovitz
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Robert Webster
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN 37212
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Fauser J, Seelecke S, Werthschutzky R, Kupnik M, Mukhopadhyay A, Chadda R, Goergen Y, Hessinger M, Motzki P, Stenin I, Kristin J, Klenzner T, Schipper J. Planning for Flexible Surgical Robots via Bézier Spline Translation. IEEE Robot Autom Lett 2019. [DOI: 10.1109/lra.2019.2926221] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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