Retinopathy of Prematurity (ROP) is a vascular disease affecting the retinas (back of the eye) of low birth weight infants. Although it can be treated effectively if diagnosed early, it continues to be a leading cause of childhood blindness in the United States and throughout the world. The investigators feel that this study will result in specific knowledge discovery about ROP, as well as general knowledge about how image-based data and genetic data can be combined to better understand clinical disease. Participants will be recruited from the neonatal intensive care unit (NICU) at OHSU, along with 4 collaborating institutions (William Beaumont Hospital, Stanford University, University of Illinois Chicago and University of Utah). Hospitalized infants who receive ROP screening examinations for routine care will be eligible for this study, and will be offered the opportunity to participate. Subjects who provide informed consent will have clinical data from routine care collected along with demographic characteristics, results from routine ROP screening examinations, presence of systemic disease or risk factors. Retinal photographs will be taken during these routine eye exams, using a commercially-available camera that has been FDA-cleared for taking pictures from retinas of premature infants. These retinal pictures do not contain any identifiable patient information, and are taken as routine standard of care. The long-term goal of this research is to establish a quantitative framework for retinopathy of prematurity (ROP) care based on clinical, imaging, genetic, and informatics principles. The investigators have previously recruited and rigorously phenotyped and genotyped a large study cohort, including implementation of a novel reference standard diagnosis; and built a world-class research consortium for image, genetic, and bioinformatics analysis.
Age range
1 Year
Sex
ALL
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A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Evaluate diagnostic accuracy of an AI system for ROP diagnosis
Timeframe: 4 years