Investigating the Utility of Near-Infrared Reflectance Imaging for Diabetic Retinopathy Screening

Background and objective: We investigated the reliability of near-infrared reflectance (NIR) imaging as a method of assessing severity of diabetic retinopathy (DR). Patients and methods: One hundred ninety-five NIR images were reviewed by two graders for the number of hyporeflective foci, presence or absence of vascular abnormalities, and presumptive DR stage; these were correlated to fundus photography-defined DR stage. Interrater reliability was confirmed via one-way random effects model of intraclass correlation coefficients. Analysis of variance was used in subgroup analysis, receiver operating characteristic (ROC) curves were created to validate reliability of the model, and logistic regression was used to model foci and vascular abnormalities as predictors for moderate or worse disease. Results: A statistically significant difference in mean number of hyporeflective foci was found between no DR and moderate non-proliferative DR (NPDR; P < 0.0001), no DR and severe NPDR (P < 0.001), no DR and proliferative DR (PDR; P < 0.0001), mild and moderate NPDR (P = 0.008), mild and severe NPDR (P < 0.001), and mild NPDR and PDR (P < 0.001). The area under the ROC curve was 0.849 (CI: 0.792 to 0.905). The threshold for detection of moderate NPDR or worse was 4.75 foci, with a sensitivity of 79.0% and a false positive rate of 20.0%. Multivariate logistic regression model incorporating hyporeflective foci with vascular abnormalities (odds ratio [OR] = 1.592, 95% CI: 1.381 to 1.835; P < 0.001) was able to accurately predict moderate disease or worse, just moderate disease (OR = 1.045, 95% CI: 1.003 to 1.089; P = 0.035), severe disease (OR = 1.050, 95% CI: 1.006 to 1.096; P = 0.027), and proliferative disease (OR = 1.050, 95% CI: 1.008 to 1.095; P = 0.018). Conclusions: NIR imaging may be an adjunct tool in screening for DR.