Quantitative artery-vein analysis in optical coherence tomography angiography of diabetic retinopathy

Diabetic retinopathy (DR) and other eye diseases can affect artery and vein differently. Therefore, differential artery-vein analysis can improve disease detection and treatment assessment. This study aims to establish color fundus image analysis guided artery-vein differentiation in OCTA, and to verify that differential artery-vein analysis can improve the sensitivity of OCTA detection and classification of DR. Briefly, optical density ratio (ODR) analysis and blood vessel tracking were combined to identify artery-vein in color fundus images. The fundus artery-vein map was used to register arteries and veins in corresponding OCTA images. Based on the fundus image guided artery-vein differentiation, quantitative analysis of arteries and veins in control and NPDR OCTA images were performed. The sensitivities of traditional mean blood vessel caliber (m-BVC) and artery-vein ratio of BVC (AVR-BVC) were quantitatively compared for DR classification. One way, multi-label analysis of variance (ANOVA) with Bonferroni's test and Student t-test was employed for evaluating classification performance. Images from 20 eyes of 18 control subjects and 48 eyes of 35 NPDR patients (18 mild, 16 moderate and 14 severe NPDR) were used for this study. Compared to m-BVC, AVR-BVC provided enhanced sensitivity in differentiating NPDR stages. AVR-BVC was able to differentiate among control and three different NPDR groups. AVR-BVC could also differentiate control from mild NPDR, promising a unique OCTA biomarker for detecting early onset of NPDR.