Background: The presence of plus disease is important in determining when to treat retinopathy of prematurity (ROP), but the diagnosis of plus disease is subjective. Semiautomated computer programs (eg, ROPtool) can objectively measure retinal vascular characteristics in retinal images, but are limited by image quality. The purpose of this study was to evaluate whether ROPtool can accurately identify pre-plus and plus disease in narrow-field images of varying qualities using a new methodology that combines quadrant-level data from multiple images of a single retina. Methods: This was a cross-sectional study of previously collected narrow-field retinal images of infants screened for ROP. Using one imaging session per infant, we evaluated the ability of ROPtool to analyze images using our new methodology and the accuracy of ROPtool indices (tortuosity index [TI], maximum tortuosity [Tmax], dilation index [DI], maximum dilation [Dmax], sum of adjusted indices [SAI], and tortuosity-weighted plus [TWP]) to identify pre-plus and plus disease in images compared to clinical examination findings. Results: Of 198 eyes (from 99 infants) imaged, 769/792 quadrants (98%) were analyzable. Overall, 98% of eyes had 3-4 analyzable quadrants. For plus disease, area under the curves (AUCs) of receiver operating characteristic curves were: TWP (0.98) > TI (0.97) = Tmax (0.97) > SAI (0.96) > DI (0.88) > Dmax (0.84). For pre-plus or plus disease, AUCs were: TWP (0.95) > TI (0.94) = Tmax (0.94) = SAI (0.94) > DI (0.86) > Dmax (0.83). Conclusions: Using a novel methodology combining quadrant-level data, ROPtool can analyze narrow-field images of varying quality to identify pre-plus and plus disease with high accuracy.
ASJC Scopus subject areas
- Pediatrics, Perinatology, and Child Health