Anatomical Location-Specific Normative Quantification of Macular Nonperfusion in Diabetic Retinopathy using Optical Coherence Tomography Angiography (OCTA)

Abstract

Purpose : To evaluate a novel normative-based approach to mapping and quantifying extent of macular nonperfusion in different stages of diabetic retinopathy (DR) using OCTA.

Methods : 19 controls and 45 diabetic eyes (15 no retinopathy - NoDR; 15 nonproliferative diabetic retinopathy - NPDR; and 15 proliferative diabetic retinopathy - PDR) were imaged using a commercial SDOCT system (Avanti RTVue-XR; Optovue). Registered and averaged OCTA images created from 10 sequential 3x3 mm foveal OCTA scans using ImageJ were obtained for each subject (Moet al, ARVO imaging conference 2016) (Fig A1 & B1). All nonperfused perifoveal areas were automatically delineated on the averaged OCTA images using custom software. An eccentricity-specific normative database based upon the control group was used to identify all nonperfused areas that were at least 2 standard deviations (SD) greater than the norm. These regions were classified according to their sizes: 2-3.9, 4-7.9, or ≥8 SDs greater than the mean of the control group. Percentage of nonperfused perifoveal area was computed as the percentage occupied by the total nonperfused area (at least 2 SD greater than the normative means) divided by the area within the 300μm region of interest extending from the FAZ margin (Fig A2 & B2). Values between groups were compared using Kruskal-Wallis and post hoc Mann-Whitney U tests.

Results : The mean±SD of the percentage of nonperfused areas were 4±4%, 5±4%, 20±10%, and 31±11% in the control, noDR, NPDR, and PDR groups respectively. While there were no significant differences between the control and NoDR groups, percentage of nonperfused area differed significantly between all other groups in terms of nonperfused areas of each different size (2-3.9, 4-7.9, and ≥8 SDs), at the 300 μm eccentricity from the FAZ margin (p<0.05).

Conclusions : We have demonstrated a novel technique of automated standard deviation mapping which can quantify the degree of anatomical location-specific nonperfusion on OCTA scans in patients with DR. This technique is sensitive to both focal and global defects which may prove useful for earlier diabetic retinopathy detection and severity grading.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.