J. Terry Ernest Ocular Imaging Center, Department of Ophthalmology and Visual Science, The University of Chicago, Chicago, IL 60637, USA.
Department of Ophthalmology and Visual Science, University of Texas Health Sciences, Houston, TX 77030, USA.
Cells. 2022 Jun 15;11(12):1934. doi: 10.3390/cells11121934.
Computerized texture analysis uses higher-order mathematics to identify patterns beyond what the naked eye can recognize. We tested its feasibility in optical coherence tomography angiography imaging of choriocapillaris. Our objective was to determine sets of parameters that provide coherent and consistent output when applied to a homogeneous, healthy group of patients. This observational cross-sectional study involved 19 eyes of 10 young and healthy Caucasian subjects. En-face macular optical coherence tomography angiography of superficial choriocapillaris was obtained by the RTVue-XR Avanti system. Various algorithms were used to extract texture features. The mean and standard deviation were used to assess the distribution and dispersion of data points in each metric among eyes, which included: average gray level, gray level yielding 70% threshold and 30% threshold, balance, skewness, energy, entropy, contrast, edge mean gradient, root-mean-square variation, and first moment of power spectrum, which was compared between images, showing a highly concordant homology between all eyes of participants. We conclude that computerized texture analysis for en-face optical coherence tomography angiography images of choriocapillaris is feasible and provides values that are coherent and tightly distributed around the mean in a homogenous, healthy group of patients. Homology of blob size among subjects may represent a "repeat pattern" in signal density and thus a perfusion in the superficial choriocapillaris of healthy young individuals of the same ethnic background.
计算机纹理分析使用高阶数学来识别肉眼无法识别的模式。我们测试了它在脉络膜毛细血管光相干断层扫描血管造影成像中的可行性。我们的目的是确定在应用于同质、健康的患者群体时提供一致和一致输出的参数集。本观察性横断面研究涉及 10 名年轻健康白种人受试者的 19 只眼。通过 RTVue-XR Avanti 系统获得浅层脉络膜毛细血管的黄斑面光学相干断层扫描血管造影。使用各种算法提取纹理特征。平均值和标准差用于评估每个指标在眼睛之间的数据点的分布和离散程度，包括：平均灰度、产生 70%阈值和 30%阈值的灰度、平衡、偏度、能量、熵、对比度、边缘平均梯度、均方根变化和功率谱的第一矩，比较图像之间的差异，显示所有参与者的所有眼睛之间具有高度一致的同源性。我们得出结论，用于脉络膜毛细血管的面光学相干断层扫描血管造影图像的计算机纹理分析是可行的，并提供了在同质、健康的患者群体中一致且紧密分布在平均值周围的值。受试者中斑点大小的同源性可能代表信号密度中的“重复模式”，因此代表相同种族背景的健康年轻个体的浅层脉络膜毛细血管的灌注。
