吲哚青绿
医学
解剖(医学)
放射科
内镜黏膜下剥离术
人工智能
外科
结缔组织
内窥镜检查
生物医学工程
影像引导手术
方向(向量空间)
鉴定(生物学)
作者
Yoshihiko Tashiro,Takeshi Aoki,Ryohei Watanabe,Kimiyasu Yamazaki,Hiromi Date,Tetsuya Kitajima,Shodai Nagaishi,Takahisa YAMAZAKI,Kodai Tomioka,Hideki Shibata,Kazuhiro Matsuda,Makoto Watanabe,Hidekazu Yasunaga,Shinji Ando
出处
期刊:American Surgeon
[SAGE Publishing]
日期:2026-07-28
卷期号:: 31348261472840-31348261472840
标识
DOI:10.1177/00031348261472840
摘要
This preliminary study evaluated the feasibility of a dual-navigation strategy that integrates artificial intelligence (AI)-assisted identification of safe dissection planes with indocyanine green (ICG)-dyed gauze-based localization of anatomical targets during minimally invasive gastrointestinal surgery. Fluorescence imaging is widely used for intraoperative guidance, and artificial intelligence-assisted prediction can contribute to enhancing surgical decision-making and reducing adverse events. The feasibility of this system was evaluated in 39 patients undergoing laparoscopic or robot-assisted gastrointestinal surgery. Data from the Eureka surgical AI system, used in conjunction with indocyanine green-dyed gauze, were retrospectively analyzed to identify loose connective tissue, indicating a safe dissection plane. Eureka successfully predicted loose connective tissue to identify safe dissection planes during tissue separation. In 23 cases, the gauze was more readily detected under near-infrared fluorescence than under white light, thereby serving as a precise intraoperative marker. These preliminary findings suggest that combining AI-assisted dissection-plane recognition with fluorescence-guided target localization is feasible and may support real-time orientation during minimally invasive gastrointestinal surgery.
科研通智能强力驱动
Strongly Powered by AbleSci AI