Statistical Model of Optical Coherence Tomography Angiography Parameters That Correlate With Severity of Diabetic Retinopathy

与糖尿病视网膜病变严重程度相关的光学相干断层扫描血管造影参数的统计模型

阅读:1

Abstract

PURPOSE: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。