Optometry Research Today is a free monthly online journal that collates and summarizes the latest research about Optometry, including details on myopia, optometric practice, therapy.

Computerized Analysis of Retinal Vessel Width and Tortuosity in Premature Infants.

Wilson CM, Cocker KD, Moseley MJ, Paterson C, Clay ST, Schulenburg WE, Mills MD, Ells A, Parker K, Quinn G, Fielder A, Ng J

Dept of Optometry and Visual Science, City University, City University, London, CE1V 0HB, United Kingdom; St Marys Hospital, London, United Kingdom.

PURPOSE To determine using novel software the feasibility of measuring the tortuosity and width of retinal veins and arteries from digital retinal images of infants at risk of retinopathy of prematurity (ROP). METHODS The Computer Assisted Image Analysis of the Retina (CAIAR) program was developed to enable semiautomatic detection of retinal vasculature and measurement of vessel tortuosity and width from digital images. CAIAR was tested for accuracy and reproducibility of tortuosity and width measurements using computer generated vessel-like lines of known frequency, amplitude and width. CAIAR was then tested using clinical digital retinal images for correlation of vessel tortuosity and width readings as compared to expert ophthalmologist gradings. RESULTS When applied to 16 computer generated sinusoidal vessels, the tortuosity measured by CAIAR correlated very well with the known values. Width measures also increased as expected. When CAIAR readings were compared to 5 expert ophthalmologist gradings of 75 vessels on 10 retinal images, moderate correlation was found in 10 of the 14 tortuosity output calculations, Spearman's rho ranging from 0.618 to 0.673. Width was less well correlated, rho = 0.415. CONCLUSIONS The measures of tortuosity and width in CAIAR were validated using sequential model vessel analysis. On comparison of CAIAR output to assessments made by expert ophthalmologists, CAIAR correlates moderately with tortuosity grades, but less well with width grades. CAIAR offers the opportunity for developing an automated image analysis system for detecting the vascular changes at the posterior pole which are becoming increasingly important in diagnosing treatable ROP.

Published 14 April 2008 in Invest Ophthalmol Vis Sci.
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