Non-contact artificial intelligence-assisted intraoperative 3D navigation technology prospective application study in lung cancer surgery

作者：Chengrun Li, Jiachun Song, Rui Yan, Bo Zhang, Bin Wang, Jingfan Fan, Y. Tony Yang, Hongxu Yue, Jixing Lin, Ruiji Chen, Leilei Shen, Hengliang Xu, Shurui Wu, Zhengnan Liu, Jie Li · 发表于：Journal of Thoracic Disease · 年份：2025 · DOI：10.21037/jtd-2025-1136 · 被引用次数：1 · 研究领域：Augmented Reality Applications、Lung Cancer Diagnosis and Treatment、Surgical Simulation and Training

Background: Precise minimally invasive lung cancer surgery supported by three-dimensional (3D) reconstruction navigation is currently an important means of treating early-stage lung cancer. In conventional intraoperative 3D reconstruction navigation, the operation of the display requires assistance from an assistant, resulting in suboptimal real-time performance and surgeon autonomy. To overcome the limitations of previous navigation technologies, this study developed a surgeon-autonomous non-contact intraoperative 3D navigation system and conducted a prospective exploration of its clinical application value in lung cancer surgical procedures. Methods: From March 2022 to March 2025, a total of 62 patients with early-stage lung cancer who were eligible for pulmonary segmentectomy were randomly divided into two groups. The experimental group received the assistance of a non-contact 3D navigation system during surgery, while the control group received the assistance of an assistive display after traditional 3D reconstruction. The two groups were compared in terms of blood loss, surgical success rate, operation time, navigation time, operator satisfaction, and other indicators. Results: The experimental group had a shorter navigation time during surgery (50–107 vs. 120–234 s, P<0.001), a faster operation time (84.23±13.18 vs. 101.84±11.01 min, P<0.001) and a higher surgical success rate (96.77% vs. 93.55%), and the surgeons had a higher experience value for non-contact navigation...