Expected value of artificial intelligence in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement
Expected value of artificial intelligence in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement
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DOI：
10.1055/a-1950-5694
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发表时间：
2022-10-21
期刊：
影响因子：
9.3
通讯作者：
Dinis-Ribeiro, Mario
中科院分区：
文献类型：
--
作者：
Messmann, Helmut;Bisschops, Raf;Dinis-Ribeiro, Mario
本ESGE立场声明定义了人工智能（AI）在ESGE已定义的绩效指标框架内诊断和管理胃肠道肿瘤的预期价值。这是基于预期任务的临床相关性以及人工或临床环境中人工智能的初步证据。主要建议：（1）对于接受AI评估上消化道内窥镜检查的完整性，AI的粘膜检查水平应与经验丰富的内窥镜医师评估的水平相当。(2)为了接受AI评估上消化道内窥镜检查的完整性，应在>= 90%的程序中获得相关解剖标志的自动识别和照片记录。(3)为了接受AI在检测Barrett高度上皮内瘤变或癌症中的应用，针对靶向活检的可疑病变的AI辅助检测率应与有经验的内窥镜医师（使用或不使用先进的成像技术）的检测率相当。(4)为了接受AI在巴雷特瘤的管理，AI辅助选择病变适合内镜切除术应与经验丰富的内镜医师。(5)为了接受AI在胃癌前病变诊断中的应用，萎缩和肠上皮化生的AI辅助诊断应与已建立的活检方案提供的诊断相当，包括程度估计和随后分配到正确的内镜监测间隔。(6)为了接受人工智能用于小肠胶囊式内窥镜（SBCE）中的自动病变检测，AI辅助阅读的性能应与经验丰富的内窥镜医师进行病变检测的性能相当，不会增加但可能减少操作员的阅读时间。(7)为了接受AI在结直肠息肉检测中的应用，AI辅助的腺瘤检测率应与经验丰富的内窥镜医师相当。(8)为了接受小型息肉（≥ 6 mm）的AI光学诊断（计算机辅助诊断[CADx]），在选择适合内镜切除的病变时，AI辅助表征应与经验丰富的内镜医师的表征相当。
This ESGE Position Statement defines the expected value of artificial intelligence (AI) for the diagnosis and management of gastrointestinal neoplasia within the framework of the performance measures already defined by ESGE. This is based on the clinical relevance of the expected task and the preliminary evidence regarding artificial intelligence in artificial or clinical settings. Main recommendations: (1) For acceptance of AI in assessment of completeness of upper GI endoscopy, the adequate level of mucosal inspection with AI should be comparable to that assessed by experienced endoscopists. (2) For acceptance of AI in assessment of completeness of upper GI endoscopy, automated recognition and photodocumentation of relevant anatomical landmarks should be obtained in >= 90% of the procedures. (3) For acceptance of AI in the detection of Barrett's high grade intraepithelial neoplasia or cancer, the AI-assisted detection rate for suspicious lesions for targeted biopsies should be comparable to that of experienced endoscopists with or without advanced imaging techniques. (4) For acceptance of AI in the management of Barrett's neoplasia, AI-assisted selection of lesions amenable to endoscopic resection should be comparable to that of experienced endoscopists. (5) For acceptance of AI in the diagnosis of gastric precancerous conditions, AI-assisted diagnosis of atrophy and intestinal metaplasia should be comparable to that provided by the established biopsy protocol, including the estimation of extent, and consequent allocation to the correct endoscopic surveillance interval. (6) For acceptance of artificial intelligence for automated lesion detection in small-bowel capsule endoscopy (SBCE), the performance of AI-assisted reading should be comparable to that of experienced endoscopists for lesion detection, without increasing but possibly reducing the reading time of the operator. (7) For acceptance of AI in the detection of colorectal polyps, the AI-assisted adenoma detection rate should be comparable to that of experienced endoscopists. (8) For acceptance of AI optical diagnosis (computer-aided diagnosis [CADx]) of diminutive polyps (= 6 mm, AI-assisted characterization should be comparable to that of experienced endoscopists in selecting lesions amenable to endoscopic resection.