Toward Continuum Robot Tentacles for Lung Interventions: Exploring Folding Support Disks.

Toward the future goal of creating a lung surgery system featuring multiple tentacle-like robots, we present a new folding concept for continuum robots that enables them to squeeze through openings smaller than the robot's nominal diameter (e.g., the narrow space between adjacent ribs). This is facilitated by making the disks along the robot's backbone foldable. We also demonstrate that such a robot can feature not only straight, but also curved tendon routing paths, thereby achieving a diverse family of conformations. We find that the foldable robot performs comparably, from a kinematic perspective, to an identical non-folding continuum robot at varying deployment lengths. This work paves the way for future applications with a continuum robot that can fold and fit through smaller openings, with the potential to reduce invasiveness during surgical tasks.

Autonomous medical needle steering in vivo.

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.

Backward Planning for a Multi-Stage Steerable Needle Lung Robot.

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.

Design Considerations for a Steerable Needle Robot to Maximize Reachable Lung Volume.

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.

STEERABLE NEEDLE TRAJECTORY FOLLOWING IN THE LUNG: TORSIONAL DEADBAND COMPENSATION AND FULL POSE ESTIMATION WITH 5DOF FEEDBACK FOR NEEDLES PASSING THROUGH FLEXIBLE ENDOSCOPES.

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.

Decoupling Steerability from Diameter: Helical Dovetail Laser Patterning for Steerable Needles.

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.

Design and Control of a Compact, Modular Robot for Transbronchial Lung Biopsy.

Lung cancer is one of the most prevalent and deadly forms of cancer, claiming more than 154,000 lives in the USA per year. Accurate targeting and biopsy of pulmonary abnormalities is key for early diagnosis and successful treatment. Many cancerous lesions originate in the peripheral regions of the lung which are not directly accessible from the bronchial tree, thereby requiring percutaneous approaches to collect biopsies, which carry a higher risk of pneumothorax, hemorrhage, and death in extreme cases. In prior work, our group proposed a concept for accessing the peripheral lung through the airways, via a bronchscope deployed steerable needle. In this paper, we present a more compact, modular, multi-stage robot, designed to deploy a steerable needle through a standard flexible bronchoscope, to retrieve biopsies from lesions in the peripheral regions of the lung. The robot has several stages that can control a steerable biopsy needle, as well as concentric tubes, which act as an aiming conduit. The functionality of this robot is demonstrated via closed-loop lesion targeting in a CT scanner. The steerable needle is controlled using a previously proposed sliding mode controller, based on feedback from a magnetic tracker embedded in the steerable needle's tip. Towards developing a clinically viable platform, this system builds on prior work through its modular, compact form factor, and workflow-conscious design that provides precise homing and the ability to interchange tools as needed.

A 3D-printed modular device for imaging the brain of small birds.

BACKGROUND: One potential barrier to using in vivo imaging in any new animal species is solving the basic problem of how to hold animals safely and securely during scans. NEW METHOD: In this paper, we describe the design, fabrication, use, and positional reproducibility of a 3D-printed plastic device (the Avian Imaging Device, or AID) for imaging the brain of 1 or 2 small songbirds. We designed two different types of head cones to use with this device: one that was not contoured and designed for anesthesia induction, and one contoured to the shape of a house sparrow head, designed to be used with a pre-anesthetized animal. RESULTS: Compared to no holder, using the AID with both contoured and non-contoured head cones significantly reduced the amount of translation necessary to align the head in pairs of CT scans (by 78% and 90%, respectively); using the contoured head cone also significantly reduced the amount of rotation necessary for head alignment in registering pairs of scans (by 90%). COMPARISON WITH EXISTING METHOD(S): Using an animal holder that can not only securely hold animals but which has high positional reproducibility is essential to take advantage of the maximum resolution possible with small animal imaging. 3D-printed materials are also compatible with PET and CT, environmentally stable, and fast and inexpensive to make. CONCLUSIONS: Researchers can learn from the design of the AID and use our CAD models as a starting point for fabricating devices for multiple small-animal imaging needs.