内镜检查已广泛用于诊断胃肠道黏膜病变。然而，仍然缺乏客观的内镜标准。联动成像技术（LCI）是新的内镜技术，可增强色彩对比度。因此，我们调查了LCI的临床应用，并进一步分析了RGB颜色模型的像素亮度。所有病灶均通过白光内镜（WLE）、LCI和蓝光成像（BLI）进行观察。Matlab软件用于计算红色（R）、绿色（G）和蓝色（B）的像素亮度。在病变的内镜图像中，LCI的R显著高于BLI，而G高于WLE（所有P < 0.05）。R/(G + B)在3种技术之间有显著差异，可作为复合LCI标记。我们对内镜诊断与病理的相关性分析表明，LCI与病理诊断一致性高（P=0.000），颜色可以预测某些类型的病变。ROC曲线显示在R/(G + B)=0.646的临界点，曲线下面积为0.646，敏感性和特异性分别为0.514和0.773。 综上所述，LCI 可以提高诊断胃肠道黏膜病变的效率和准确性，并有利于靶向活检。基于像素亮度的R/(G + B)可以引入作为评价内镜图像的客观标准。

Abstract: Endoscopy has been widely used in diagnosing gastrointestinal mucosal lesions. However, there are still lack of objective endoscopic criteria. Linked color imaging (LCI) is newly developed endoscopic technique which enhances color contrast. Thus, we investigated the clinical application of LCI and further analyzed pixel brightness for RGB color model. All the lesions were observed by white light endoscopy (WLE), LCI and blue laser imaging (BLI). Matlab software was used to calculate pixel brightness for red (R), green (G) and blue color (B). Of the endoscopic images for lesions, LCI had significantly higher R compared with BLI but higher G compared with WLE (all P < 0.05). R/(G + B) was significantly different among 3 techniques and qualified as a composite LCI marker. Our correlation analysis of endoscopic diagnosis with pathology revealed that LCI was quite consistent with pathological diagnosis (P = 0.000) and the color could predict certain kinds of lesions. ROC curve demonstrated at the cutoff of R/(G+B) = 0.646, the area under curve was 0.646, and the sensitivity and specificity was 0.514 and 0.773. Taken together, LCI could improve efficiency and accuracy of diagnosing gastrointestinal mucosal lesions and benefit target biopsy. R/(G + B) based on pixel brightness may be introduced as a objective criterion for evaluating endoscopic images.