Artificial intelligence for automatic surgical phase recognition of laparoscopic gastrectomy in gastric cancer

doi:10.1007/s11548-023-03027-5

CORC > 自动化研究所 > 中国科学院自动化研究所 > 紫东太初大模型研究中心

	Artificial intelligence for automatic surgical phase recognition of laparoscopic gastrectomy in gastric cancer
	Zhai, Yuhao 4,5; Chen, Zhen 3; Zheng, Zhi 4,5; Wang, Xi 4,5; Yan, Xiaosheng 4,5; Liu, Xiaoye 4,5; Yin, Jie 4,5; Wang, Jinqiao 1,2,3; Zhang, Jun 4,5
刊名	INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
	2023-11-02
页码	9
关键词	Artificial intelligence Gastric cancer Surgical phase
ISSN号	1861-6410
DOI	10.1007/s11548-023-03027-5
通讯作者	Wang, Jinqiao(jqwang@nlpr.ia.ac.cn) ; Zhang, Jun(zhangjun5986@ccmu.edu.cn)
英文摘要	PurposeThis study aimed to classify laparoscopic gastric cancer phases. We also aimed to develop a transformer-based artificial intelligence (AI) model for automatic surgical phase recognition and to evaluate the model's performance using laparoscopic gastric cancer surgical videos.MethodsOne hundred patients who underwent laparoscopic surgery for gastric cancer were included in this study. All surgical videos were labeled and classified into eight phases (P0. Preparation. P1. Separate the greater gastric curvature. P2. Separate the distal stomach. P3. Separate lesser gastric curvature. P4. Dissect the superior margin of the pancreas. P5. Separation of the proximal stomach. P6. Digestive tract reconstruction. P7. End of operation). This study proposed an AI phase recognition model consisting of a convolutional neural network-based visual feature extractor and temporal relational transformer.ResultsA visual and temporal relationship network was proposed to automatically perform accurate surgical phase prediction. The average time for all surgical videos in the video set was 9114 +/- 2571 s. The longest phase was at P1 (3388 s). The final research accuracy, F1, recall, and precision were 90.128, 87.04, 87.04, and 87.32%, respectively. The phase with the highest recognition accuracy was P1, and that with the lowest accuracy was P2.ConclusionAn AI model based on neural and transformer networks was developed in this study. This model can identify the phases of laparoscopic surgery for gastric cancer accurately. AI can be used as an analytical tool for gastric cancer surgical videos.
资助项目	National Key R&D Program of China[2022ZD0160601] ; National Natural Science Foundation of China[62276260] ; National Natural Science Foundation of China[61976210] ; National Natural Science Foundation of China[62076235] ; National Natural Science Foundation of China[62176254] ; National Natural Science Foundation of China[62006230] ; National Natural Science Foundation of China[62206283] ; National Natural Science Foundation of China[82300646] ; Beijing Natural Science Foundation[7232334] ; Beijing Municipal Science & Technology Commission[D17100006517003] ; Beijing Municipal Administration of Hospitals Incubating Program[PX2020001] ; Beijing Municipal Administration of Hospitals Incubating Program[PX20240103] ; InnoHK program
WOS关键词	WORKFLOW RECOGNITION
WOS研究方向	Engineering ; Radiology, Nuclear Medicine & Medical Imaging ; Surgery
语种	英语
出版者	SPRINGER HEIDELBERG
WOS记录号	WOS:001091527600001
资助机构	National Key R&D Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Beijing Municipal Science & Technology Commission ; Beijing Municipal Administration of Hospitals Incubating Program ; InnoHK program
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54442]
专题	紫东太初大模型研究中心
通讯作者	Wang, Jinqiao; Zhang, Jun
作者单位	1.Wuhan AI Res, Wuhan, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, 95 Zhongguancun East Rd, Beijing, Peoples R China 3.Chinese Acad Sci, Hong Kong Inst Sci & Innovat, Ctr Artificial Intelligence & Robot CAIR, Hong Kong, Peoples R China 4.State Key Lab Digest Hlth, Beijing, Peoples R China 5.Capital Med Univ, Beijing Friendship Hosp, Dept Gen Surg, 95 Yongan Rd, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhai, Yuhao,Chen, Zhen,Zheng, Zhi,et al. Artificial intelligence for automatic surgical phase recognition of laparoscopic gastrectomy in gastric cancer[J]. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY,2023:9.
APA	Zhai, Yuhao.,Chen, Zhen.,Zheng, Zhi.,Wang, Xi.,Yan, Xiaosheng.,...&Zhang, Jun.(2023).Artificial intelligence for automatic surgical phase recognition of laparoscopic gastrectomy in gastric cancer.INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY,9.
MLA	Zhai, Yuhao,et al."Artificial intelligence for automatic surgical phase recognition of laparoscopic gastrectomy in gastric cancer".INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY (2023):9.