Linked Color Imaging and Color Analytic Model Based on Pixel Brightness for Diagnosing H. Pylori Infection in Gastric Antrum

Yang Xu
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Abstract

Objectives: Linked color imaging (LCI) helps to differentiate minor mucosal changes, which can be objectively judged by red–green–blue pixel brightness. However, whether this color analytic model based on pixel brightness can be applied to diagnose Helicobacter pylori infection remains unknown. Methods: Consecutive adult patients with indications and underwent esophagogastroduodenoscopy for the 1 st time were enrolled in the training (n=166) and validation (n=79) set. Demographic and clinical characteristics were recorded. Target region in gastric antrum was pictured before biopsy for rapid urea test, and pixel brightness was calculated by MATLAB software. Results: In training set, 25 patients had H. pylori infection. Pixel brightness for R and B in patients with H. pylori infection was greatly higher than those in patients without H. pylori infection (R: 210.203±27.233 vs. 196.401±29.018, p=0.043; B: 127.621±26.112 vs. 125.334±27.812, p=0.025). At the cut off of R = 210 and B = 127, the specificity and sensitivity were 0.696 and 0.701. In validation set, 10 patients had H. pylori infection and the findings were consistent with those in training set. Conclusion: Color analytic model based on pixel brightness under LCI was useful in diagnosing H. pylori infection in gastric antrum.
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基于像素亮度的链接彩色成像和颜色分析模型诊断胃窦幽门螺杆菌感染
目的:联色成像(LCI)有助于区分轻微的粘膜变化,可通过红绿蓝像素亮度客观判断。然而,这种基于像素亮度的颜色分析模型能否应用于幽门螺杆菌感染的诊断仍是未知的。方法:将有适应证且首次行食管胃十二指肠镜检查的连续成年患者纳入训练组(n=166)和验证组(n=79)。记录人口学和临床特征。活检前对胃窦靶区进行快速尿素检测,并通过MATLAB软件计算像素亮度。结果:训练集中有25例患者发生幽门螺杆菌感染。幽门螺杆菌感染患者R、B的像素亮度显著高于未感染患者(R: 210.203±27.233 vs. 196.401±29.018,p=0.043;B: 127.621±26.112 vs. 125.334±27.812,p=0.025)。在R = 210和B = 127的截点处,特异性和敏感性分别为0.696和0.701。验证组中有10例患者存在幽门螺杆菌感染,与训练组结果一致。结论:LCI下基于像素亮度的颜色分析模型可用于胃窦幽门螺杆菌感染的诊断。
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