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

Invest Ophthalmol Vis Sci. 2014 Oct 30;55(12):7975-81. doi: 10.1167/iovs.14-14125.

Abstract

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.

Keywords: grading; hypertension; image processing; retinal arteriolar central light reflex; retinal color photograph.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Arterioles / pathology
  • Blood Pressure / physiology
  • Cross-Sectional Studies
  • Diagnosis, Computer-Assisted / methods*
  • Female
  • Humans
  • Hypertension / diagnosis*
  • Light*
  • Male
  • Middle Aged
  • Optic Disk / pathology
  • Photography / methods
  • Regression Analysis
  • Reproducibility of Results
  • Retinal Artery / pathology*
  • Retinal Diseases / diagnosis*
  • Severity of Illness Index
  • Software