Department of Ophthalmology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States.
Department of Ophthalmology, Alexandria Faculty of Medicine, Alexandria, Egypt.
Invest Ophthalmol Vis Sci. 2018 Aug 1;59(10):4292-4298. doi: 10.1167/iovs.18-24142.
To determine whether combining quantitative optical coherence tomography angiography (OCTA) parameters can achieve high sensitivity and specificity to distinguish eyes with nonproliferative diabetic retinopathy (NPDR) from those with proliferative diabetic retinopathy (PDR) as well as eyes with diabetes and no DR (NoDR) from those with clinical DR (any DR).
This cross-sectional study included 28 eyes (17 patients) with NoDR, 54 eyes (34 patients) with NPDR, and 56 eyes (36 patients) with PDR. OCTA images were processed to quantify the foveal avascular zone (FAZ) area, acircularity, vessel density, skeletonized vessel density, fractal dimension, and intersections and average vessel diameter for the superficial (SCP) and the deep capillary plexus (DCP). Binary logistic regression models were used to identify the OCTA parameters that best distinguished DR severity groups. The area (AUC) under the receiver operating characteristic (ROC) curves, and sensitivity and specificity were calculated for each model.
The regression model identified the SCP FAZ area, DCP vessel density, and acircularity as parameters that best distinguished between DR severity groups. ROC curves for NPDR versus PDR had an AUC of 0.845 (P < 0.001) and sensitivity and specificity of 86% and 70%, respectively. ROC curves for NoDR versus any DR showed an AUC of 0.946 (P < 0.001) with sensitivity of 89% and specificity of 96%, with comparable results when explored in males and females separately.
We identified a set of OCTA parameters with high sensitivity and specificity for distinguishing between groups based on DR severity, suggesting potential clinical application for OCTA as a screening tool for DR.
确定定量光学相干断层扫描血管造影（OCTA）参数的组合是否可以实现高灵敏度和特异性，以区分非增殖性糖尿病视网膜病变（NPDR）和增殖性糖尿病视网膜病变（PDR）的眼睛，以及糖尿病无DR（NoDR）和有临床 DR（任何 DR）的眼睛。
本横断面研究纳入了 28 只眼（17 例患者）的 NoDR、54 只眼（34 例患者）的 NPDR 和 56 只眼（36 例患者）的 PDR。对 OCTA 图像进行处理，以定量测量黄斑无血管区（FAZ）面积、非圆度、血管密度、骨架血管密度、分形维数以及浅层毛细血管丛（SCP）和深层毛细血管丛（DCP）的交叉点和平均血管直径。采用二元逻辑回归模型确定区分 DR 严重程度组的最佳 OCTA 参数。计算每个模型的接收者操作特征（ROC）曲线下面积（AUC）以及灵敏度和特异性。
回归模型确定 SCP FAZ 面积、DCP 血管密度和非圆度是区分 DR 严重程度组的最佳参数。NPDR 与 PDR 的 ROC 曲线 AUC 为 0.845（P<0.001），灵敏度和特异性分别为 86%和 70%。NoDR 与任何 DR 的 ROC 曲线 AUC 为 0.946（P<0.001），灵敏度为 89%，特异性为 96%，分别在男性和女性中进行探索时，结果相似。
我们确定了一组 OCTA 参数，具有区分 DR 严重程度组的高灵敏度和特异性，提示 OCTA 作为 DR 筛查工具具有潜在的临床应用价值。
