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连字符彩色成像有益于远端胃部疾病的内镜诊断。

Linked colour imaging benefits the endoscopic diagnosis of distal gastric diseases.

机构信息

Department of Gastroenterology, the 307 Hospital of Academy of Military Medical Science, Beijing, 100071, China.

Department of Internal Medicine, Clinic of August First Film Studio, Beijing, 100161, China.

出版信息

Sci Rep. 2017 Jul 17;7(1):5638. doi: 10.1038/s41598-017-05847-3.

Abstract

Gastric diseases are common in China, and gastroduodenoscopy could provide accurate diagnoses. Our previous study verified that linked colour imaging (LCI) can improve endoscopic diagnostic accuracy. This study aimed for the first time to establish an LCI-based endoscopic model called colour-microstructure-vessel (CMV) criteria and validated its clinical feasibility for detecting distal gastric diseases manifested as red mucosal lesions under endoscopy in a cohort of 62 patients. Colour features were extracted from the endoscopic images and categorized into 3 types. Colour type 1 was a typical red; Colour type 2 was red ringed with purple and Colour type 3 was red with yellow in the centre and purple around the periphery, allowing for predicting chronic nonatrophic gastritis, chronic atrophic gastritis and gastric cancer. The sensitivity, specificity and Youden index of Colour type 3 with abnormal M or V for gastric cancer were 100.0%, 98.2% and 98.2%. The kappa values for intra-observer and inter-observer agreement for predicting the pathology were 0.834 and 0.791 for experienced endoscopists and 0.788 and 0.732 for endoscopy learners, and these values were comparable regardless of the experience of the endoscopists (P > 0.05). These findings support that the CMV criteria are a promising model for accurate endoscopic diagnosis.

摘要

胃部疾病在中国很常见,而胃十二指肠镜检查可以提供准确的诊断。我们之前的研究已经证实,联合色彩成像(LCI)可以提高内镜诊断的准确性。本研究首次建立了一种基于 LCI 的内镜模型,称为色彩-微观结构-血管(CMV)标准,并在 62 名患者的队列中验证了其用于检测内镜下表现为红色黏膜病变的远端胃部疾病的临床可行性。从内镜图像中提取颜色特征,并将其分为 3 种类型。颜色类型 1 为典型红色;颜色类型 2 为红色伴有紫色环;颜色类型 3 为中心红色伴有黄色,周围紫色,可预测慢性非萎缩性胃炎、慢性萎缩性胃炎和胃癌。颜色类型 3 对异常 M 或 V 的胃癌的敏感性、特异性和 Youden 指数分别为 100.0%、98.2%和 98.2%。经验丰富的内镜医师和内镜学习者预测病理的观察者内和观察者间一致性的kappa 值分别为 0.834 和 0.791,以及 0.788 和 0.732,无论内镜医师的经验如何,这些值都相当(P > 0.05)。这些发现支持 CMV 标准是一种用于准确内镜诊断的有前途的模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f727/5514041/85d928380031/41598_2017_5847_Fig1_HTML.jpg

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