Digitalization of surgical features improves surgical accuracy via surgeon guidance and robotization - Xiaoyun Chen; Jiali Liu; Hongli Liang; Zelin Chen; Zitian Liu; Yingfeng Zheng; Zhangkai Lian; Lixia Luo; Weirong Chen; Mingxing Wu; Danying Zheng; Xialin Liu; et al. (npj Digital Medicine)
Abstract The evolution of surgical techniques aims to augment surgeons’ capabilities through digital guidance and robotization for higher precision and consistency. Currently, surgeries heavily rely on surgeon’s experience and visual judgment, causing operation variations. Artificial intelligence (AI) offers a solution by extracting and digitizing surgical trajectories and features from videos to provide digital guidance. In this study, we collected 17,538 videos of capsulorhexis, a crucial step in cataract surgery, to create an AI-driven system named Meta Surgery (MetaS). MetaS evaluates and identifies ideal cases, extracts their digital characteristics, and fits an optimal capsulorhexis path in real-time during surgery. Surgeons performed capsulorhexis benefited from MetaS’s guidance and a lens caliper, which increased the rate of ideal capsulorhexis by ~40%. Additionally, these digital features enabled a surgical robot to perform precise capsulorhexis autonomously in porcine eyes. This approach augments surgeons’ surgical skills and paves the way for the autonomous operation of surgical robots.