Robotic Autonomy for Magnetic Endoscope Biopsy.

Magnetically actuated endoscopes are currently transitioning in to clinical use for procedures such as colonoscopy, presenting numerous benefits over their conventional counterparts. Intelligent and easy-to-use control strategies are an essential part of their clinical effectiveness due to the un-intuitive nature of magnetic field interaction. However, work on developing intelligent control for these devices has mainly been focused on general purpose endoscope navigation. In this work, we investigate the use of autonomous robotic control for magnetic colonoscope intervention via biopsy, another major component of clinical viability. We have developed control strategies with varying levels of robotic autonomy, including semi-autonomous routines for identifying and performing targeted biopsy, as well as random quadrant biopsy. We present and compare the performance of these approaches to magnetic endoscope biopsy against the use of a standard flexible endoscope on bench-top using a colonoscopy training simulator and silicone colon model. The semi-autonomous routines for targeted and random quadrant biopsy were shown to reduce user workload with comparable times to using a standard flexible endoscope.

Enabling the future of colonoscopy with intelligent and autonomous magnetic manipulation.

Early diagnosis of colorectal cancer significantly improves survival. However, over half of cases are diagnosed late due to demand exceeding the capacity for colonoscopy - the "gold standard" for screening. Colonoscopy is limited by the outdated design of conventional endoscopes, associated with high complexity of use, cost and pain. Magnetic endoscopes represent a promising alternative, overcoming drawbacks of pain and cost, but struggle to reach the translational stage as magnetic manipulation is complex and unintuitive. In this work, we use machine vision to develop intelligent and autonomous control of a magnetic endoscope, for the first time enabling non-expert users to effectively perform magnetic colonoscopy in-vivo. We combine the use of robotics, computer vision and advanced control to offer an intuitive and effective endoscopic system. Moreover, we define the characteristics required to achieve autonomy in robotic endoscopy. The paradigm described here can be adopted in a variety of applications where navigation in unstructured environments is required, such as catheters, pancreatic endoscopy, bronchoscopy, and gastroscopy. This work brings alternative endoscopic technologies closer to the translational stage, increasing availability of early-stage cancer treatments.

Macro-Scale Tread Patterns for Traction in the Intestine.

GOAL: Tread patterns are widely used to increase traction on different substrates, with the tread scale, geometry and material being tailored to the application. This work explores the efficacy of using macro-scale tread patterns for a medical application involving a colon substrate - renowned for its low friction characteristics. METHODS: Current literature was first summarized before an experimental approach was used, based on a custom test rig with ex vivo porcine colon, to assess different macro-scale tread patterns. Performance was based on increasing traction while avoiding significant trauma. Repeated testing (n = 16) was used to obtain robust results. RESULTS: A macro-scale tread pattern can increase the traction coefficient significantly, with a static traction coefficient of 0.74 ± 0.22 and a dynamic traction coefficient of 0.35 ± 0.04 compared to a smooth (on the macro-scale) Control (0.132 ± 0.055 and 0.054 ± 0.015, respectively). Decreasing the scale and spacing between the tread features reduced apparent trauma but also reduced the traction coefficient. CONCLUSION: Significant traction can be achieved on colon tissue using a macro-scale tread but a compromise between traction (large feature sizes) and trauma (small feature sizes) may have to be made. SIGNIFICANCE: This work provides greater insight into the complex frictional mechanisms of the intestine and gives suggestions for developing functional tread surfaces for a wide range of clinical applications.

Adaptive Dynamic Control for Magnetically Actuated Medical Robots.

In the present work we discuss a novel dynamic control approach for magnetically actuated robots, by proposing an adaptive control technique, robust towards parametric uncertainties and unknown bounded disturbances. The former generally arise due to partial knowledge of the robots' dynamic parameters, such as inertial factors, the latter are the outcome of unpredictable interaction with unstructured environments. In order to show the application of the proposed approach, we consider controlling the Magnetic Flexible Endoscope (MFE) which is composed of a soft-tethered Internal Permanent Magnet (IPM), actuated with a single External Permanent Magnet (EPM). We provide with experimental analysis to show the possibility of levitating the MFE - one of the most difficult tasks with this platform - in case of partial knowledge of the IPM's dynamics and no knowledge of the tether's behaviour. Experiments in an acrylic tube show a reduction of contact of the 32% compared to non-levitating techniques and 1.75 times faster task completion with respect to previously proposed levitating techniques. More realistic experiments, performed in a colon phantom, show that levitating the capsule achieves faster and smoother exploration and that the minimum time for completing the task is attained by the proposed approach.

Intelligent magnetic manipulation for gastrointestinal ultrasound.

Diagnostic endoscopy in the gastrointestinal tract has remained largely unchanged for decades and is limited to the visualization of the tissue surface, the collection of biopsy samples for diagnoses, and minor interventions such as clipping or tissue removal. In this work, we present the autonomous servoing of a magnetic capsule robot for in-situ, subsurface diagnostics of microanatomy. We investigated and showed the feasibility of closed-loop magnetic control using digitized microultrasound (µUS) feedback; this is crucial for obtaining robust imaging in an unknown and unconstrained environment. We demonstrated the functionality of an autonomous servoing algorithm that uses µUS feedback, both on benchtop trials as well as in-vivo in a porcine model. We have validated this magnetic-µUS servoing in instances of autonomous linear probe motion and were able to locate markers in an agar phantom with 1.0 ± 0.9 mm position accuracy using a fusion of robot localization and µUS image information. This work demonstrates the feasibility of closed-loop robotic µUS imaging in the bowel without the need for either a rigid physical link between the transducer and extracorporeal tools or complex manual manipulation.

Magnetic Levitation for Soft-Tethered Capsule Colonoscopy Actuated With a Single Permanent Magnet: A Dynamic Control Approach.

The present letter investigates a novel control approach for magnetically driven soft-tethered capsules for colonoscopy-a potentially painless approach for colon inspection. The focus of this work is on a class of devices composed of a magnetic capsule endoscope actuated by a single external permanent magnet. Actuation is achieved by manipulating the external magnet with a serial manipulator, which in turn produces forces and torques on the internal magnetic capsule. We propose a control strategy which, counteracting gravity, achieves levitation of the capsule. This technique, based on a nonlinear backstepping approach, is able to limit contact with the colon walls, reducing friction, avoiding contact with internal folds, and facilitating the inspection of nonplanar cavities. The approach is validated on an experimental setup, which embodies a general scenario faced in colonoscopy. The experiments show that we can attain 19.5% of contact with the colon wall, compared to the almost 100% of previously proposed approaches. Moreover, we show that the control can be used to navigate the capsule through a more realistic environment-a colon phantom-with reasonable completion time.