276. AI NAVIGATION SURGERY FOR ESOPHAGEAL CANCER

Abstract With recent technological innovations, artificial intelligence (AI) has begun to be used not only in endoscopic diagnosis and pathology diagnosis but also in the field of surgery. AI enables objective and consistent recognition and evaluation, making it suitable for surgical assistance in surgical operations as well as for the evaluation of surgical techniques and learning curves. First, an AI-assisted surgical procedure recognition system for robotic esophagectomy was developed. By focusing on surgical procedures, the system automatically recognizes surgical procedures with 84% accuracy using AI. In particular, more than 90% of accuracy was obtained in the phase for Left RLN lymph node dissection and Post-dissection to completion of surgery. In addition, as intraoperative navigation, a system for automatic recognition of critical organs such as the recurrent laryngeal nerve, trachea, and subclavian artery was developed, and its recognition accuracy is gradually improving, enabling organ recognition in real time. Currently, with data from more than 100 cases, the system is able to predict Intersection over Union (IoU) with an accuracy of 0.3-0.4. Similar developments are underway in other areas, such as automatic recognition of the surgical process in robotic distal gastrectomy, and a surgical difficulty prediction system is being built using this technology. This system is expected to make it possible to automatically determine the degree of difficulty of surgery during the operation, leading to the decision to change the surgical team during the operation and the prediction of the operation completion time. These technologies can be useful not only for intraoperative navigation, but also surgical education and postoperative care. Using them, young surgeons have the opportunity to dive into authentic scenarios and acquire practical experience safely, bypassing the dangers inherent in real-life surgeries. Through the use of AI-powered interactive simulations, they can deeply grasp surgical methods, establishing the groundwork of crucial practical abilities needed for performing successful operations. In the future, we intend to verify the external validity of these systems using data from multiple facilities, and further work on the development of a surgical support system that transcends fields, with the aim of obtaining regulatory approval as a medical device. In addition to the potential clinical applications of the systems under development, we would like to discuss the current status and future of AI-based surgical support systems in the surgical field.