Development and reliability of retinal arteriolar central light reflex quantification system: a new approach for severity grading.

Journal Article (Journal Article)

PURPOSE: To describe the methodology and assess the reliability of novel computer-based semiautomated software that quantifies retinal arteriolar central light reflex (CR) from digital retinal photographs. METHODS: A total of 150 optic disc-centered digital color retinal photographs were selected from a population-based cross-sectional study of persons aged 40 to 80 years (the Singapore Malay Eye Study [SiMES]). Computer-assisted software was developed to quantify retinal arteriolar CR by selecting vessel edge points semiautomatically. This software then automatically computes the CR, vessel diameter, and the CR-to-vessel diameter ratio (CRR). Reliability was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plots. Multiple linear regression analyses were performed to assess the associations between CRR and systemic and ocular factors, to further validate the novel software. RESULTS: The ICCs for the intergrader and intragrader CRR measurement were 0.76 (95% confidence interval [CI] 0.53-0.89) and 0.86 (95% CI 0.67-0.94), respectively. The ICC for intravisit repeatability was 0.87 (95% CI 0.71-0.95). In the multivariate model, a higher CRR was associated with elevated mean arterial blood pressure (per 10 mm Hg increase) (β = 0.017, P < 0.001). CONCLUSIONS: Quantitative assessment of retinal arteriolar wall opacification is a reliable method using a new computer-assisted system. This new CRR measurement system is a potentially useful tool to study retinal arteriolar abnormalities with systemic diseases.

Full Text

Duke Authors

Cited Authors

  • Bhuiyan, A; Cheung, CY; Frost, S; Lamoureux, E; Mitchell, P; Kanagasingam, Y; Wong, TY

Published Date

  • October 30, 2014

Published In

Volume / Issue

  • 55 / 12

Start / End Page

  • 7975 - 7981

PubMed ID

  • 25358734

Electronic International Standard Serial Number (EISSN)

  • 1552-5783

Digital Object Identifier (DOI)

  • 10.1167/iovs.14-14125


  • eng

Conference Location

  • United States