Automated Quantification of Capillary Nonperfusion Using Optical Coherence Tomography Angiography in Diabetic Retinopathy

Abstract

Importance: Macular ischemia is a key feature of diabetic retinopathy (DR). Quantification of macular ischemia has potential as a biomarker for DR.

Objective: To assess the feasibility of automated quantification of capillary nonperfusion as a potential sign of macular ischemia using optical coherence tomography (OCT) angiography.

Design, setting, and participants: An observational study conducted in a tertiary, subspecialty, academic practice evaluated macular nonperfusion with 6 × 6-mm OCT angiography obtained with commercially available 70-kHz OCT and fluorescein angiography (FA). The study was conducted from January 22 to September 18, 2014. Data analysis was performed from October 1, 2014, to April 7, 2015. Participants included 12 individuals with normal vision serving as controls and 12 patients with various levels of DR.

Main outcomes and measures: Preplanned primary measures were parafoveal and perifoveal vessel density, total avascular area, and foveal avascular zone as detected with 6 × 6-mm OCT angiography and analyzed using an automated algorithm. Secondary measures included the agreement of the avascular area between the OCT angiogram and FA.

Results: Compared with the 12 healthy controls (11 women; mean [SD] age, 54.2 [14.2] years), the 12 participants with DR (4 women; mean [SD] age, 55.1 [12.1] years) had reduced parafoveal and perifoveal vessel density by 12.6% (95% CI, 7.7%-17.5%; P < .001) and 10.4% (95% CI, 6.8%-14.1%; P < .001), respectively. Total avascular area and foveal avascular zone area were greater in eyes with DR by 0.82 mm2 (95% CI, 0.65-0.99 mm2; P = .02) and 0.16 mm2 (95% CI, 0.05-0.28 mm2; P < .001). The agreement between the vascular areas in the OCT angiogram and FA had a κ value of 0.45 (95% CI, 0.21-0.70; P < .001). Total avascular area in the central 5.5-mm-diameter area distinguished eyes with DR from control eyes with 100% sensitivity and specificity.

Conclusions and relevance: Avascular area analysis with an automated algorithm using OCT angiography, although not equivalent to FA, detected DR reliably in this small pilot study. Further study is necessary to determine the usefulness of the automated quantification in clinical practice.

Conflict of interest statement

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Drs Jia and Huang have a significant financial interest in Optovue, Inc. a company that may have a commercial interest in the results of this research and technology. Dr Huang also has a financial interest in Carl Zeiss Meditec, Inc. Dr Lauer reported being a paid consultant for Oxford Biomedica. These potential conflicts of interest have been reviewed and managed by Oregon Health & Science University. No other disclosures were reported.

Figures

Figure 1. Automated Avascular Area Detection in Optical Coherence Tomography (OCT) Angiography

Example images of normal (control). nonproliferative diabetic retinopathy (DR), and proliferative DR. FA indicates fluorescein angiography. Dotted circles in the first row indicate sectors for perifovea (green circles) and parafovea (blue circles). In the third column, light blue corresponds to automatically detected areas of nonperfusion (highlighted by dashed box in the first row).

Figure 2. Nonperfusion as Seen on Optical Coherence Tomography (OCT) Angiography vs Fluorescein Angiography (FA)

A, An OCT angiogram showing nonperfuson area detected in an eye with diabetic retinopathy in light blue. B, The corresponding FA. Yellow arrowheads disclose an area of capillary dropout seen on OCT but not FA. Red arrowheads point to an area of nonperfusion seen on FA that was not detected by the aIgorithm.