一种量化正常眼和炎症后眼脉络膜毛细血管的新方法。
A Novel Method of Quantifying the Choriocapillaris in Normal and Post-inflammatory Eyes.
机构信息
Ophthalmology Department, SEHHAT Foundation, Gilgit, Pakistan.
Advance Eye Care, Gilgit, Pakistan.
出版信息
Ocul Immunol Inflamm. 2022 Feb 17;30(2):417-423. doi: 10.1080/09273948.2020.1800047. Epub 2020 Aug 18.
OBJECTIVE
To assess the reliability and validity of gray level co-occurrence matrices (GLCM) in the quantification of choriocapillaris and describe GLCM features in normal and eyes with resolved acute posterior multifocal placoid pigment epitheliopathy (APMPPE) and serpiginous choroiditis (SC).
METHODS
In this, multicenter, reliability, validity and comparative study; OCTA was performed on eyes with resolved APMPPE and SC and normal individuals. CC texture classification, low flow area measurements and GLCM feature extraction were performed.
RESULTS
A total of 13 normal, 8 APMPPE and 15 SC eyes were analyzed. All GLCM parameters demonstrated an excellent reliability. GLCM parameters were differently distributed across the three groups. Decision-tree based on the random forest predictive model provided an overall accuracy of 86% in classifying the three groups using GLCM features.
CONCLUSION
These data demonstrated an excellent reliability and validity of GLCM features in quantifying the choriocapillaris in healthy and diseased eyes.
目的
评估灰度共生矩阵（GLCM）在脉络膜毛细血管量化中的可靠性和有效性，并描述正常眼和已缓解的急性后部多灶性-placoid 色素上皮病变（APMPPE）及匐行性脉络膜炎（SC）眼中的 GLCM 特征。
方法
在这项多中心可靠性、有效性和对比研究中，对已缓解的 APMPPE 和 SC 眼以及正常个体进行了 OCTA 检查。进行了脉络膜毛细血管纹理分类、低血流区测量和 GLCM 特征提取。
结果
共分析了 13 只正常眼、8 只 APMPPE 眼和 15 只 SC 眼。所有 GLCM 参数均表现出极好的可靠性。GLCM 参数在三组之间的分布不同。基于随机森林预测模型的决策树使用 GLCM 特征对三组进行分类，总体准确率为 86%。
结论
这些数据表明 GLCM 特征在量化健康和患病眼中脉络膜毛细血管方面具有极好的可靠性和有效性。
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