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

Evaluation of an assistant diagnosis system for gastric neoplastic lesions under white light endoscopy based on artificial intelligence

摘要:

目的 评估基于人工智能的上消化道内镜影像辅助诊断系统（以下简称ENDOANGEL‑LD）在白光下诊断胃病变和胃瘤性病变的效能。方法 使用图片测试集和视频测试集分别测试ENDOANGEL‑LD的诊断能力。图片测试集来自2019年6月—2019年9月武汉大学人民医院191例患者的805张胃病变（300张胃瘤性病变、505张非瘤性病变）图片和990张正常胃对照图片；视频测试集来自2020年11月—2021年4月武汉大学人民医院存储的78例患者的83个病灶视频（38个胃瘤性病变和45个非瘤性病变）。计算ENDOANGEL‑LD诊断图片测试集的准确率、灵敏度和特异度等指标。比较ENDOANGEL‑LD与4名内镜专家在视频测试集中诊断胃瘤性病变的准确率、灵敏度和特异度。结果 在图片测试集中，ENDOANGEL‑LD诊断胃病变的准确率、灵敏度和特异度分别为93.9%（1 685/1 795）、98.0%（789/805）和90.5%（896/990）；诊断胃瘤性病变的准确率、灵敏度和特异度分别为88.7%（714/805）、91.0% （273/300）和87.3% （441/505）。在视频测试集中，ENDOANGEL‑LD和4名专家总体诊断胃瘤性病变的准确率分别为81.9%（68/83） 和72.0% （239/332），灵敏度分别为100.0%（38/38）和 85.5%（130/152），特异度分别为66.7%（30/45） 和 60.6% （109/180）。ENDOANGEL‑LD的灵敏度优于4名专家（χ2=6.220，P=0.013），准确率（χ2=3.408，P=0.065）和特异度（χ2=0.569，P=0.451）与4名专家相当。结论 ENDOANGEL‑LD辅助诊断系统能够准确检测出胃病变并进一步诊断出胃瘤性病变，可在临床工作中辅助内镜医师。

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.