Intelligent surgical workflow recognition for endoscopic submucosal dissection with real-time animal study

Jianfeng Cao, Hon-Chi Yip (), Yueyao Chen, Markus Scheppach, Xiaobei Luo, Hongzheng Yang, Ming Kit Cheng, Yonghao Long, Yueming Jin, Philip Wai-Yan Chiu (), Yeung Yam (), Helen Mei-Ling Meng () and Qi Dou ()
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Jianfeng Cao: The Chinese University of Hong Kong
Hon-Chi Yip: The Chinese University of Hong Kong
Yueyao Chen: The Chinese University of Hong Kong
Markus Scheppach: University Hospital of Augsburg
Xiaobei Luo: Southern Medical University
Hongzheng Yang: The Chinese University of Hong Kong
Ming Kit Cheng: The Chinese University of Hong Kong
Yonghao Long: The Chinese University of Hong Kong
Yueming Jin: National University of Singapore
Philip Wai-Yan Chiu: Multi-scale Medical Robotics Center and The Chinese University of Hong Kong
Yeung Yam: The Chinese University of Hong Kong
Helen Mei-Ling Meng: Centre for Perceptual and Interactive Intelligence and The Chinese University of Hong Kong
Qi Dou: The Chinese University of Hong Kong

Nature Communications, 2023, vol. 14, issue 1, 1-14

Abstract: Abstract Recent advancements in artificial intelligence have witnessed human-level performance; however, AI-enabled cognitive assistance for therapeutic procedures has not been fully explored nor pre-clinically validated. Here we propose AI-Endo, an intelligent surgical workflow recognition suit, for endoscopic submucosal dissection (ESD). Our AI-Endo is trained on high-quality ESD cases from an expert endoscopist, covering a decade time expansion and consisting of 201,026 labeled frames. The learned model demonstrates outstanding performance on validation data, including cases from relatively junior endoscopists with various skill levels, procedures conducted with different endoscopy systems and therapeutic skills, and cohorts from international multi-centers. Furthermore, we integrate our AI-Endo with the Olympus endoscopic system and validate the AI-enabled cognitive assistance system with animal studies in live ESD training sessions. Dedicated data analysis from surgical phase recognition results is summarized in an automatically generated report for skill assessment.

Date: 2023
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DOI: 10.1038/s41467-023-42451-8

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