背景人工智能（AI）在使用深度学习系统的图像识别方面取得了显着进展，并已用于检测食管鳞状细胞癌（ESCC）。然而，之前的所有报告都不是在临床环境中进行研究，而是采用回顾性设计。因此，我们进行了这项试验，以确定人工智能如何帮助内窥镜医师在临床环境中检测食管鳞癌。方法 这是一项前瞻性、单中心、探索性、随机对照试验。接受食管胃十二指肠镜检查或监测的食管鳞癌高危患者被纳入并随机分配到 AI 组或对照组。在AI组中，内窥镜医师同时观看带有注释的检测ESCC的AI监视器和正常监视器，而在对照组中，内窥镜医师仅观看正常监视器。在两组中，内窥镜医师使用白光成像（WLI）观察食道，然后进行窄带成像（NBI）和碘染色。主要终点是非专家使用 AI 提高 ESCC 检出率。检出率定义为WLI/NBI检出的ESCC与碘染色检出的所有ESCC的比率。结果 本次分析共纳入 320 名患者。非专家的 ESCC 检出率，AI 组为 47%，对照组为 45%（p=0.93），无显着差异，与专家相似（87% vs. 57%，p= 0.20）和所有内窥镜医师（57% vs. 50%，p=0.70）。结论 本研究未能证明使用 ESCC.Thieme AI 诊断支持系统可提高食管癌检出率。版权所有。

Background Artificial intelligence (AI) has made remarkable progress in image recognition using deep learning systems and has been used to detect esophageal squamous cell carcinoma (ESCC). However, all previous reports were not investigated in clinical settings, but in a retrospective design. Therefore, we conducted this trial to determine how AI can help endoscopists detect ESCC in clinical settings. Methods This was a prospective, single-center, exploratory, and randomized controlled trial. High-risk patients with ESCC undergoing screening or surveillance esophagogastroduodenoscopy were enrolled and randomly assigned to either the AI or control group. In the AI group, the endoscopists watched both the AI monitor detecting ESCC with annotation and the normal monitor simultaneously, whereas in the control group, the endoscopists watched only the normal monitor. In both groups, the endoscopists observed the esophagus using white-light imaging (WLI), followed by narrow-band imaging (NBI) and iodine staining. The primary endpoint was the enhanced detection rate of ESCC by non-experts using AI. The detection rate was defined as the ratio of WLI/NBI-detected ESCCs to all ESCCs detected by iodine staining. Results A total of 320 patients were included in this analysis. The detection rate of ESCC in non-experts was 47% in the AI group and 45% in the control group (p=0.93), with no significant difference, was similar to that in experts (87% vs. 57%, p=0.20) and all endoscopists (57% vs. 50%, p=0.70). Conclusions This study could not demonstrate an improvement in the esophageal cancer detection rate using the AI diagnostic support system for ESCC.Thieme. All rights reserved.