Evaluation of an assistant diagnosis system for gastric neoplastic lesions under white light endoscopy based on artificial intelligence
10.3760/cma.j.cn321463-20220221-00659
- VernacularTitle:基于人工智能的白光内镜下胃瘤性病变辅助诊断系统研究
- Author:
Junxiao WANG
1
;
Zehua DONG
;
Ming XU
;
Lianlian WU
;
Mengjiao ZHANG
;
Yijie ZHU
;
Xiao TAO
;
Hongliu DU
;
Chenxia ZHANG
;
Xinqi HE
;
Honggang YU
Author Information
1. 武汉大学人民医院消化内科 消化系统疾病湖北省重点实验室 湖北省消化疾病微创诊治医学临床研究中心，武汉430060
- Keywords:
Artificial intelligence;
Gastric neoplasms;
White light;
Gastric neoplastic lesions
- From:
Chinese Journal of Digestive Endoscopy
2023;40(4):293-297
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To assess the diagnostic efficacy of upper gastrointestinal endoscopic image assisted diagnosis system (ENDOANGEL-LD) based on artificial intelligence (AI) for detecting gastric lesions and neoplastic lesions under white light endoscopy.Methods:The diagnostic efficacy of ENDOANGEL-LD was tested using image testing dataset and video testing dataset, respectively. The image testing dataset included 300 images of gastric neoplastic lesions, 505 images of non-neoplastic lesions and 990 images of normal stomach of 191 patients in Renmin Hospital of Wuhan University from June 2019 to September 2019. Video testing dataset was from 83 videos (38 gastric neoplastic lesions and 45 non-neoplastic lesions) of 78 patients in Renmin Hospital of Wuhan University from November 2020 to April 2021. The accuracy, the sensitivity and the specificity of ENDOANGEL-LD for image testing dataset were calculated. The accuracy, the sensitivity and the specificity of ENDOANGEL-LD in video testing dataset for gastric neoplastic lesions were compared with those of four senior endoscopists.Results:In the image testing dataset, the accuracy, the sensitivity, the specificity of ENDOANGEL-LD for gastric lesions were 93.9% (1 685/1 795), 98.0% (789/805) and 90.5% (896/990) respectively; while the accuracy, the sensitivity and the specificity of ENDOANGEL-LD for gastric neoplastic lesions were 88.7% (714/805), 91.0% (273/300) and 87.3% (441/505) respectively. In the video testing dataset, the sensitivity [100.0% (38/38) VS 85.5% (130/152), χ2=6.220, P=0.013] of ENDOANGEL-LD was higher than that of four senior endoscopists. The accuracy [81.9% (68/83) VS 72.0% (239/332), χ2=3.408, P=0.065] and the specificity [ 66.7% (30/45) VS 60.6% (109/180), χ2=0.569, P=0.451] of ENDOANGEL-LD were comparable with those of four senior endoscopists. Conclusion:The ENDOANGEL-LD can accurately detect gastric lesions and further diagnose neoplastic lesions to help endoscopists in clinical work.
