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Measuring retinal vessel tortuosity in 10-year-old children: validation of the Computer-Assisted Image Analysis of the Retina (CAIAR) program

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Owen, C. G., Rudnicka, A. R., Mullen, R., Barman, S. A., Monekosso, Dorothy, Whincup, P. H., Ng, J. and Paterson, C. (2009) Measuring retinal vessel tortuosity in 10-year-old children: validation of the Computer-Assisted Image Analysis of the Retina (CAIAR) program. Investigative ophthalmology & visual science, 50 (5). pp. 2004-2010. [Journal article]

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Abstract

PURPOSE: To examine the agreement of a novel computer program measuring retinal vessel tortuosity with subjective assessment of tortuosity in school-aged children. METHODS: Cross-sectional study of 387 retinal vessels (193 arterioles, 194 veins) from 28 eyes of 14 children (aged 10 years). Retinal digital images were analyzed using the Computer Assisted Image Analysis of the Retina (CAIAR) program, including 14 measures of tortuosity. Vessels were graded (from 0 = none; to 5 = tortuous) independently by two observers. Interobserver agreement was assessed by using kappa statistics. Agreement with all 14 objective measures was assessed with correlation/regression analyses. Intersession repeatability (comparing morning and afternoon sessions) of tortuosity indices was calculated. RESULTS: Interobserver agreement of vessel tortuosity within one grade was high (kappa = 0.97), with total agreement in 56% of grades and 42% differing by +/-1 grade. Tortuosity indices based on subdivided chord length methods showed strong log-linear associations with agreed subjective grades (typically r > 0.6; P

Item Type:Journal article
Keywords:Arterioles/pathology; Child; Cross-Sectional Studies; Humans; Image Processing, Computer-Assisted/methods; Observer Variation; Reproducibility of Results; Retinal Diseases/diagnosis; Retinal Vessels/pathology; Venules/pathology
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
ID Code:9805
Deposited By:Dr Dorothy Monekosso
Deposited On:29 Jan 2010 12:40
Last Modified:14 Mar 2013 09:35

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