超声内镜 (EUS) 对检测胰腺神经内分泌肿瘤 (pNEN) 非常敏感。然而，pNEN 的内镜诊断依赖于操作者且耗时，因为 pNEN 模仿正常胰腺和其他胰腺病变。我们打算开发一种名为 iEUS 的基于卷积神经网络 (CNN) 的系统，用于通过 EUS 识别 pNEN 和多种类型的胰腺病变。从 pNEN 和非 pNEN 胰腺病变（包括胰腺导管腺癌 (PDAC)）获得的 12,200 张 EUS 图像的回顾性数据）、自身免疫性胰腺炎（AIP）和胰腺囊性肿瘤（PCN）被用于开发 iEUS。它由二类（pNEN/非pNEN胰腺病变）分类模型（CNN1）和四类（pNEN/ PDAC/ AIP/ PCN）分类模型（CNN2）组成。前瞻性地收集连续患者的视频用于人类-iEUS 竞赛，以评估 iEUS 的性能。共有 573 名患者参加了这项研究。在包含 203 个视频的人类-iEUS 竞赛中，CNN1 和 CNN2 诊断 pNEN 的准确率分别为 84.2% 和 88.2%，显着高于新手（75.4%），与中级超声内科医生（85.5%）和专家（85.5%）。此外，CNN2 诊断 PDAC、AIP 和 PCN 的准确率分别为 86.2%、97.0% 和 97.0%。在iEUS的辅助下，三级超声内镜医师诊断pNEN的敏感性均显着提高（分别为64.6% vs. 44.8%、87.5% vs. 71.9%、74.0% vs. 57.6%）。iEUS精准诊断pNEN和其他令人困惑的胰腺病变，因此可以帮助内超声医师通过 EUS 实现更容易和更准确的内窥镜诊断。版权所有 © 2024 美国胃肠内窥镜协会。由爱思唯尔公司出版。保留所有权利。

Endoscopic ultrasound (EUS) is sensitive in detecting pancreatic neuroendocrine neoplasm (pNEN). However, the endoscopic diagnosis of pNEN is operator-dependent and time-consuming since pNEN mimics normal pancreas and other pancreatic lesions. We intended to develop a convolutional neural network (CNN)-based system named iEUS for identifying pNEN and multiple types of pancreatic lesions via EUS.Retrospective data of 12,200 EUS images obtained from pNEN and non-pNEN pancreatic lesions, including pancreatic ductal adenocarcinoma (PDAC), autoimmune pancreatitis (AIP), and pancreatic cystic neoplasm (PCN), were used to develop iEUS. It was composed of a two-category (pNEN/ non-pNEN pancreatic lesion) classification model (CNN1) and a four-category (pNEN/ PDAC/ AIP/ PCN) classification model (CNN2). Videos from consecutive patients were prospectively collected for a human-iEUS contest to evaluate the performance of iEUS.A total of 573 patients were enrolled in this study. In the human-iEUS contest containing 203 videos, CNN1 and CNN2 showed an accuracy of 84.2% and 88.2% for diagnosing pNEN, respectively, which were significantly higher than that of novices (75.4%) and comparable with intermediate endosonographers (85.5%) and experts (85.5%). In addition, CNN2 showed an accuracy of 86.2%, 97.0%, and 97.0% for diagnosing PDAC, AIP, and PCN, respectively. With the assistance of iEUS, the sensitivity of endosonographers at all three levels in diagnosing pNEN has significantly improved (64.6% vs. 44.8%, 87.5% vs. 71.9%, 74.0% vs. 57.6%, respectively).The iEUS precisely diagnosed pNEN and other confusing pancreatic lesions, thus could assist endosonographers in achieving more accessible and accurate endoscopic diagnoses via EUS.Copyright © 2024 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.