Enhanced learning and play with AI. Image byTim Sandle
Mount Sinai researchers have demonstrated the effectiveness of teaching surgical trainees a difficult procedure using artificial intelligence algorithms and an extended-reality headset without the presence of an instructor.
In terms of outcomes, each of the 17 trainees in the study achieved surgical success. As a qualitative measure, the process drew highly favourable reviews from student participants who tested the deep learning model. The results carry significant implications for future training of residents and surgeons, as well as for the even broader field of autonomous learning within medicine.
Surgical training of residents has traditionally required the presence of a teaching proctor alongside the student physician in the operating room, which can result in inconsistent skills acquisition. The AI tool provides a functional alternative.
The alternative AI programs, including ESIST (educational system for instructionless surgical training) coupled deep learning methodology, offer a faster rate of learning. The technology includes a custom-designed extended-reality headset to stream surgical instructions and video content before the eyes of the wearer. This allows the trainee medics to keep their hands free to practice intricate procedures.
In the trial, the operation simulated a partial nephrectomy procedure designed to remove a cancerous portion of a kidney, including placing a clamp on the renal artery. For this replication, researchers created a “phantom” kidney from 3D printed casts of an anonymized patient’s computerized tomography (CT) scans.
The casts were filled with water-based polymers and assembled to create a partial nephrectomy model with kidney tumours. While students practiced, the system’s sophisticated first-person camera continuously monitored their training, providing real-time feedback and projecting corrective prompts as part of its skills assessment capability.
Commenting on the AI innovation, researcher Nelson Stone states: “For the first time, we created an AI model linked to an extended-reality headset to prove that a critical step in a kidney cancer procedure could be done with 99.9 percent accuracy…We believe our study offers early proof that AI programs that substitute for proctors, who teach resident physicians, can reduce training costs and ultimately improve the quality, efficiency, and standardization of that instruction.”
Stone continues: “Our study proved that a complex procedure like a partial nephrectomy could be effectively taught to surgical trainees using a simulated model, without the presence of an instructor
He adds: “This finding addresses an urgent need resulting from the shortage of trainers and supervisors to educate physicians on new medical devices and techniques, and from the severe time constraints on attending physicians to train residents pursing surgical careers.”
The study has been published in the Journal of Medical Extended Reality. The research paper is titled “Autonomous Educational System for Surgical Training Utilizing Deep Learning Combined with Extended Reality.”