Research showing robots performing surgery on pigs may lead to fully automated surgery

Future studies may see the STAR system autonomously detect and adjust missed stitches

Ben Wodecki, Jr. Editor

January 28, 2022

3 Min Read

Future studies may see the STAR system autonomously detect and adjust missed stitches

Researchers from John Hopkins University successfully oversaw a robot performing surgery on pigs– without human aid.

The Smart Tissue Autonomous Robot (Star) conducted a series of laparoscopic to connect two ends of an intestine in pigs, with results showing the unit performed well.

A paper published in Science Robotics suggests the results “demonstrate that surgical robots exhibiting high levels of autonomy have the potential to improve consistency, patient outcomes, and access to a standard surgical technique.”

The robot was built to improve upon a 2016 model and is a vision-guided system designed to suture soft tissue.

“Autonomous soft tissue surgery in unstructured environments requires accurate and reliable imaging systems for detecting and tracking the target tissue, complex task planning strategies that take tissue deformation into consideration, and precise execution of plans via dexterous robotic tools and control algorithms that are adaptable to dynamic surgical situations,” the paper reads.

“In the robotic laparoscopic anastomosis experiments, the developed system outperformed surgeons using LAP and RAS surgical techniques in metrics, including the consistency of suture spacing and bite depth and the number of suture hesitancy events, that directly affect the quality of a leak-free end-to-end anastomosis.”

The STAR system “encapsulates the autonomous control functionality and reduces the involvement of the human operator, with the robot reacting to tissue deformation and various test condition changes,” the researchers wrote.


Image: The results of in vivo experiments. (A) Representative histology examples from each anastomosis tissue operated on with STAR (n = 4), and manual laparoscopic control test (n = 1). The approximate location of each anastomosis is indicated with an arrow. Squares near each anastomosis represent the location of the magnified images. (B) PMN cell as a surrogate measure of inflammation for each sample. Source: Science Robotics

AI-assisted surgery is a growing AI application in the healthcare space. The likes of California-based Theator have developed artificial intelligence and computer vision tools to improve the efficiency and safety of surgical procedures.

But researchers have sought to bring robotics into the surgery theatre. In 2016,

Simon Leonard, a Johns Hopkins University computer scientist, published findings that showed a robot surgeon can adjust to the subtle movement and deformation of soft tissue to execute precise and consistent suturing

In the earlier instance, Leonard and his team used a STAR system to perform anastomosis procedures, where a surgeon would suture two structures, such as blood vessels.

A common surgery practice, the researchers found that robots like STAR took considerably longer to perform anastomosis compared to humans – around 35 to 57 minutes compared to just eight minutes – however, the robot's performance was comparable or better than that of the surgeons.

The latest experiment showed the robot surpassing the human’s work, showing a clear improvement on the efforts from six years ago.

And the researchers behind the latest efforts see their work as a step towards fully automated surgery.

Later efforts may include works where the STAR system autonomously detects, adjusts and repeats a missed stitch to result in a completely autonomous anastomosis procedure, the paper suggests.

About the Author(s)

Ben Wodecki

Jr. Editor

Ben Wodecki is the Jr. Editor of AI Business, covering a wide range of AI content. Ben joined the team in March 2021 as assistant editor and was promoted to Jr. Editor. He has written for The New Statesman, Intellectual Property Magazine, and The Telegraph India, among others. He holds an MSc in Digital Journalism from Middlesex University.

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