New Clinical Grading Scales and Objective Measurement for Conjunctival Injection
New Clinical Grading Scales and Objective Measurement for Conjunctival Injection
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DOI：
10.1167/iovs.12-10678
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发表时间：
2013-08-01
影响因子：
4.4
通讯作者：
Hwang, Jeong-Min
中科院分区：
文献类型：
--
作者：
Park, In Ki;Chun, Yeoun Sook;Hwang, Jeong-Min
目的.目的：建立一种新的临床分级标准和客观的测量方法来评价结膜注射。本文回顾了429眼各种眼病的结膜注射照片。将三位眼科医生一致的73张图像分为4级和10级主观分级量表，并用作标准照片。每个图像以四种方式量化：每个红-绿-蓝（RGB）像素的红色分量的相对幅度;基于血管占用面积的两种不同算法（采用LAB颜色模型的K均值聚类和对比度限制自适应直方图均衡化[CLAHE]算法）;以及基于Canny边缘检测算法的血管边缘的存在。计算受试者工作特征曲线下面积（AUC）以总结四种算法的诊断准确性。RGB颜色模型、LAB颜色模型的K-means聚类和CLAHE算法与临床10步分级量表（R分别为0.741、0.784、0.919）和临床4步分级量表（R分别为0.645、0.702、0.838）具有良好的相关性。CLAHE法的AUC最大，区分度最好（P < 0.001，ANOVA，Bonferroni多重比较检验），重复性好（R = 0.996）。CLAHE算法与10步和4步主观临床分级量表的相关性最好，具有较高的区分力和重复性。CLAHE算法可以作为一种有效的结膜充血评估方法。
PURPOSE. To establish a new clinical grading scale and objective measurement method to evaluate conjunctival injection.METHODS. Photographs of conjunctival injection with variable ocular diseases in 429 eyes were reviewed. Seventy-three images with concordance by three ophthalmologists were classified into a 4-step and 10-step subjective grading scale, and used as standard photographs. Each image was quantified in four ways: the relative magnitude of the redness component of each red-green-blue (RGB) pixel; two different algorithms based on the occupied area by blood vessels (K-means clustering with LAB color model and contrast-limited adaptive histogram equalization [CLAHE] algorithm); and the presence of blood vessel edges, based on the Canny edge-detection algorithm. Area under the receiver operating characteristic curves (AUCs) were calculated to summarize diagnostic accuracies of the four algorithms.RESULTS. The RGB color model, K-means clustering with LAB color model, and CLAHE algorithm showed good correlation with the clinical 10-step grading scale (R = 0.741, 0.784, 0.919, respectively) and with the clinical 4-step grading scale (R = 0.645, 0.702, 0.838, respectively). The CLAHE method showed the largest AUC, best distinction power (P < 0.001, ANOVA, Bonferroni multiple comparison test), and high reproducibility (R = 0.996).CONCLUSIONS. CLAHE algorithm showed the best correlation with the 10-step and 4-step subjective clinical grading scales together with high distinction power and reproducibility. CLAHE algorithm can be a useful for method for assessment of conjunctival injection.