A robot has performed laparoscopic surgery on the soft tissue of a pig
without the guiding hand of a human—a significant step in robotics toward
fully automated surgery on humans. Designed by a team of Johns Hopkins
University researchers, the Smart Tissue Autonomous Robot (STAR) is
described today in Science Robotics.
"Our findings show that we can automate one of the most intricate and
delicate tasks in surgery: the reconnection of two ends of an intestine. The
STAR performed the procedure in four animals and it produced significantly
better results than humans performing the same procedure," said senior
author Axel Krieger, an assistant professor of mechanical engineering at
Johns Hopkins' Whiting School of Engineering.
The robot excelled at intestinal anastomosis, a procedure that requires a
high level of repetitive motion and precision. Connecting two ends of an
intestine is arguably the most challenging step in gastrointestinal surgery,
requiring a surgeon to suture with high accuracy and consistency. Even the
slightest hand tremor or misplaced stitch can result in a leak that could
have catastrophic complications for the patient.
Working with collaborators at the Children's National Hospital in
Washington, D.C. and Jin Kang, a Johns Hopkins professor of electrical and
computer engineering, Krieger helped create the robot, a vision-guided
system designed specifically to suture soft tissue. Their current iteration
advances a 2016 model that repaired a pig's intestines accurately, but
required a large incision to access the intestine and more guidance from
humans.
The team equipped the STAR with new features for enhanced autonomy and
improved surgical precision, including specialized suturing tools and
state-of-the art imaging systems that provide more accurate visualizations
of the surgical field.
Soft-tissue surgery is especially hard for robots because of its
unpredictability, forcing them to be able to adapt quickly to handle
unexpected obstacles, Krieger said. The STAR has a novel control system that
can adjust the surgical plan in real time, just as a human surgeon would.
"What makes the STAR special is that it is the first robotic system to plan,
adapt, and execute a surgical plan in soft tissue with minimal human
intervention," Krieger said.
A structural-light based three-dimensional endoscope and machine
learning-based tracking algorithm developed by Kang and his students guides
STAR. "We believe an advanced three-dimensional machine vision system is
essential in making intelligent surgical robots smarter and safer," Kang
said.
As the medical field moves towards more laparoscopic approaches for
surgeries, it will be important to have an automated robotic system designed
for such procedures to assist, Krieger said.
"Robotic anastomosis is one way to ensure that surgical tasks that require
high precision and repeatability can be performed with more accuracy and
precision in every patient independent of surgeon skill," Krieger said. "We
hypothesize that this will result in a democratized surgical approach to
patient care with more predictable and consistent patient outcomes."
The team from Johns Hopkins also included Hamed Saeidi, Justin D. Opfermann,
Michael Kam, Shuwen Wei, and Simon Leonard. Michael H. Hsieh, director of
Transitional Urology at Children's National Hospital, also contributed to
the research.
Reference:
Hamed Saeidi et al, Autonomous Robotic Laparoscopic Surgery for Intestinal
Anastomosis, Science Robotics (2022).
DOI: 10.1126/scirobotics.abj2908.