Scientists at the University of Leeds said yesterday that they have made a breakthrough in the development of systems for semi-autonomous colonoscopy, in which a robot guides a medical device into the human body.
They said their findings mark progress toward an intelligent robotic system being able to guide instruments to precise locations to examine internal tissues or take biopsies. A doctor or nurse would still be on hand to make clinical decisions, but the demanding task of manipulating the device could be offloaded to a robotic system.
Robots intended to facilitate vital screening
Colorectal cancer is the third most commonly diagnosed malignancy in the world, according to medical journals published by BMJ Publishing Group Ltd.
“Colonoscopy gives doctors a window into the world hidden deep inside the human body, and it provides a vital role in the screening of diseases such as colorectal cancer,” stated Pietro Valdastri, the professor of robotics and autonomous systems at the University of Leeds’ School of Electronic and Electrical Engineering who is leading the research. “But the technology has remained relatively unchanged for decades.”
Conventional colonoscopy is carried out using a semi-flexible tube, which is inserted into the anus in a process some patients find so painful they require an anesthetic.
“What we have developed is a system that is easier for doctors or nurses to operate and is less painful for patients,” Valdastri said. “It marks an important a step in the move to make colonoscopy much more widely available — essential if colorectal cancer is to be identified early.”
Because the system is easier to use, the scientists said they hope this can increase the number of providers who can perform the procedure and allow for greater patient access to colonoscopies.
University of Leeds builds magnetic, flexible scope
The research team at the University of Leeds has developed a smaller, capsule-shaped device that is tethered to a narrow cable and is inserted into the anus and then guided into place — not by the doctor or nurse pushing the colonoscope but by a magnet on a robotic arm positioned over the patient.
The robotic arm moves around the patient as it magnetically maneuvers the capsule. The magnet on the outside of the patient interacts with tiny magnets in the capsule inside the body, navigating it through the colon. The researchers say it will be less painful than having a conventional colonoscopy.
Guiding the robotic arm can be done manually, but it is a technique that is difficult to master. In response, the researchers have developed different levels of robotic assistance. This latest research evaluated how effective the different levels of robotic assistance were in aiding non-specialist staffers to carry out the procedure.
University of Leeds describes levels of robotic assistance
- Direct robot control: This is where the operator has direct control of the robot via a joystick. In this case, there is no assistance.
- Intelligent endoscope teleoperation: The operator focuses on where they want the capsule to be located in the colon, leaving the robotic system to calculate the movements of the robotic arm necessary to get the capsule into place.
- Semi-autonomous navigation: The robotic system autonomously navigates the capsule through the colon, using computer vision — although this can be overridden by the operator.
During a laboratory simulation, 10 non-expert staffers were asked to get the capsule to a point within the colon within 20 minutes. They did that five times, using the three different levels of assistance.
Using direct robot control, the participants had a 58% success rate. That increased to 96% using intelligent endoscope teleoperation — and 100% using semi-autonomous navigation.
In the next stage of the experiment, two participants were asked to navigate a conventional colonoscope into the colon of two anaesthetised pigs — and then to repeat the task with the magnet-controlled robotic system using the different levels of assistance. A veterinarian was in attendance to ensure the animals were not harmed.
The participants were scored on the NASA Task Load Index, a measure of how taxing a task was, both physically and mentally. The NASA Task Load Index revealed that they found it easier to operate the colonoscope with robotic assistance. A sense of frustration was a major factor in operating the conventional colonoscope and where participants had direct control of the robot.
“Operating the robotic arm is challenging,” said James Martin, a Ph.D. researcher at the University of Leeds who co-led the study. “It is not very intuitive, and that has put a brake on the development of magnetic flexible colonoscopes. But we have demonstrated for the first time that it is possible to offload that function to the robotic system, leaving the operator to think about the clinical task they are undertaking — and it is making a measurable difference in human performance.”
Robots could make care more accessible
“Robot-assisted colonoscopy has the potential to revolutionize the way the procedure is carried out,” said Dr. Bruno Scaglioni, a postdoctoral research fellow at the University of Leeds and co-leader of the study. “It means people conducting the examination do not need to be experts in manipulating the device. That will hopefully make the technique more widely available, where it could be offered in clinics and health centers rather than hospitals.”
The other institutions involved in the research are Vanderbilt University in the U.S., Leeds Teaching Hospitals NHS Trust in the U.K., and the University of Torino in Italy. Team RoboFORCE research was named a finalist in the KUKA Innovation Award late last year.
The techniques developed to conduct colonoscopy examinations could be applied to other endoscopic devices in healthcare, such as those used to inspect the upper digestive tract or lungs, said the University of Leeds.
The latest findings — “Enabling the future of colonoscopy with intelligent and autonomous magnetic manipulation” — is the culmination of 12 years of research by an international team of scientists led by the University of Leeds. The research was published today in the scientific journal Nature Machine Intelligence.
Patient trials using the system could begin next year or in early 2022, said the University of Leeds researchers.