Presence of plus disease in retinopathy of prematurity (ROP) is an important criterion for identifying treatment-requiring ROP. Plus disease is defined by a standard published photograph selected over 20 years ago by expert consensus. However, diagnosis of plus disease has been shown to be subjective and qualitative. Computer-based image analysis, using quantitative methods, has potential to improve the objectivity of plus disease diagnosis. The objective was to review the published literature involving computer-based image analysis for ROP diagnosis. The PubMed and Cochrane library databases were searched for the keywords “retinopathy of prematurity” AND “image analysis” AND/OR “plus disease.” Reference lists of retrieved articles were searched to identify additional relevant studies. All relevant English-language studies were reviewed. There are four main computer-based systems, ROPtool (AU ROC curve, plus tortuosity 0.95, plus dilation 0.87), RISA (AU ROC curve, arteriolar TI 0.71, venular diameter 0.82), Vessel Map (AU ROC curve, arteriolar dilation 0.75, venular dilation 0.96), and CAIAR (AU ROC curve, arteriole tortuosity 0.92, venular dilation 0.91), attempting to objectively analyze vessel tortuosity and dilation in plus disease in ROP. Some of them show promise for identification of plus disease using quantitative methods. This has potential to improve the diagnosis of plus disease, and may contribute to the management of ROP using both traditional binocular indirect ophthalmoscopy and image-based telemedicine approaches.
Purpose To examine the impact of retinal field of view and magnification on inter-expert reliability of plus disease diagnosis in retinopathy of prematurity (ROP). Methods 15 wide-angle images from infants with ROP were cropped and adjusted in magnification to create two additional image categories: medium-angle (40–50°) and narrow-angle (20–30°). These 45 images were uploaded to a web-based system and interpreted independently by 13 ROP experts using a 3-level (plus, pre-plus, neither) and 2-level (plus, not plus) classification. Absolute agreement and kappa statistics were calculated to compare inter-expert reliability. Results In the 3-level classification, ≥70% experts agreed on the same diagnosis in 8/15 (53%) wide-angle images, but only in 3/15 (20%) medium-angle and 3/15 (20%) narrow-angle images. In the 2-level classification, ≥80% experts agreed on the same diagnosis in 11/15 (73%) wide-angle images, but only in 9/15 (60%) medium-angle and 3/15 (20%) narrow angle images. Mean kappa of each expert compared to all other experts was 0.40–0.59 in 8/13 (62%) experts using wide-angle images, was 0–0.19 in 7/13 (54%) experts using medium-angle images, and was 0.20–0.39 in 9/13 (69%) experts using narrow-angle images. Conclusions Inter-expert agreement in plus disease diagnosis in wide-angle images is higher than from medium-angle and narrow-angle images. Plus disease is defined using a narrow-angle standard published photograph, yet this study suggests that peripheral findings also contribute to diagnosis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.