A robot shows that machines may one day replace human surgeons

Nearly four decades ago, the Defense Advanced Research Projects Agency (DARPA) and NASA began promoting projects that would make it possible to perform surgeries remotely — whether on the battlefield or in space. Out of those initial efforts emerged robotic surgical systems like Da Vinci, which function as an extension of the surgeon, allowing them to carry out minimally invasive procedures using remote controls and 3D vision. But this still involves a human using a sophisticated tool. Now, the integration of generative artificial intelligence and machine learning into the control of systems like Da Vinci are bringing the possibility of autonomous surgical robots closer to reality.

This Wednesday, the journal Science Robotics published the results of a study conducted by researchers at Johns Hopkins and Stanford universities, in which they present a system capable of autonomously performing several steps of a surgical procedure, learning from videos of humans operating and receiving commands in natural language — just like a medical resident would.

Like human learning, the team of scientists had been gradually teaching the robot the necessary steps to complete a surgery. Last year, the Johns Hopkins team, led by Axel Krieger, trained the robot to perform three basic surgical tasks: handling a needle, lifting tissue, and suturing. This training was done through imitation and a machine learning system similar to the one used by ChatGPT, but instead of words and text, it uses a robotic language that translates the machine’s movement angles into mathematical data.

In the new experiment, two experienced human surgeons performed demonstrations of gallbladder removal surgeries on pig tissues outside the animal. They used 34 gallbladders to collect 17 hours of data and 16,000 trajectories, which the machine used to learn. Afterward, the robots, without human intervention and with eight gallbladders they hadn’t seen before, were able to perform some of the 17 tasks required to remove the organ with 100% precision — such as identifying certain ducts and arteries, holding them precisely, strategically placing clips, and cutting with scissors. During the experiments, the model was able to correct its own mistakes and adapt to unforeseen situations.

In 2022, this same team performed the first autonomous robotic surgery on a live animal: a laparoscopy on a pig. But that robot needed the tissue to have special markers, was in a controlled environment, and followed a pre-established surgical plan. In a statement from his institution, Krieger said it was like teaching a robot to drive a carefully mapped-out route. The new experiment just presented would be — for the robot — like driving on a road it had never seen before, relying only on a general understanding of how to drive a car.

José Granell, head of the Department of Otolaryngology and Head and Neck Surgery at HLA Moncloa University Hospital and professor at the European University of Madrid, believes that the Johns Hopkins team’s work “is beginning to approach something that resembles real surgery.”

“The problem with robotic surgery on soft tissue is that biology has a lot of intrinsic variability, and even if you know the technique, in the real world there are many possible scenarios,” explains Granell. “Asking a robot to carve a bone is easy, but with soft tissue, everything is more difficult because it moves. You can’t predict how it will react when you push, how much it will move, whether an artery will tear if you pull too hard,” continues the surgeon, adding: “This technology changes the way we train the sequence of gestures that constitute surgery.”

For Krieger, this advancement takes us “from robots that can perform specific surgical tasks to robots that truly understand surgical procedures.” The team leader behind this innovation, made possible by generative AI, argues: “It’s a crucial distinction that brings us significantly closer to clinically viable autonomous surgical systems, capable of navigating the messy and unpredictable reality of real-life patient care.”

Francisco Clascá, professor of Human Anatomy and Embryology at the Autonomous University of Madrid, welcomes the study, but points out that “it’s a very simple surgery” and is performed on organs from “very young animals, which don’t have the level of deterioration and complications of a 60- or 70-year-old person, which is when this type of surgery is typically needed.” Furthermore, the robot is still much slower than a human performing the same tasks.

Mario Fernández, head of the Head and Neck Surgery department at the Gregorio Marañón General University Hospital in Madrid, finds the advance interesting, but believes that replacing human surgeons with machines “is a long way off.” He also cautions against being dazzled by technology without fully understanding its real benefits, and points out that its high cost means it won’t be accessible to everyone.

“I know a hospital in India, for example, where they have a robot and can perform two surgical sessions per month, operating on two patients. A total of 48 per year. For them, robotic surgery may be a way to practice and learn, but it’s not a reality for the patients there,” says Fernández. He believes we should appreciate technological progress, but surgery must be judged by what it actually delivers to patients. As a contrasting example, he points out that “a technique called transoral ultrasound surgery, which was developed in Madrid and is available worldwide, is performed on six patients every day.”

Krieger believes that their proof of concept shows it’s possible to perform complex surgical procedures autonomously, and that their imitation learning system can be applied to more types of surgeries — something they will continue to test with other interventions.

Looking ahead, Granell points out that, beyond overcoming technical challenges, the adoption of surgical robots will be slow because in surgery, “we are very conservative about patient safety.”

He also raises philosophical questions, such as overcoming Isaac Asimov’s First and Second Laws of Robotics: “A robot may not injure a human being or, through inaction, allow a human being to come to harm,” and “A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.” This specialist highlights the apparent contradiction in the fact that human surgeons “do cause harm, but in pursuit of the patient’s benefit; and this is a dilemma that [for a robot] will have to be resolved.”

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