A Quantitative Severity Scale for Retinopathy of Prematurity Using Deep Learning to Monitor Disease Regression After Treatment

摘要

Key PointsQuestionCan a quantitative measurement of retinopathy of prematurity severity be used over time to monitor disease regression after treatment? FindingsIn this cohort study of at-risk infants using data collected for the Imaging and Informatics in Retinopathy of Prematurity study, the quantitative retinopathy of prematurity vascular severity score developed using an automated deep learning-based plus disease classifier consistently reflected clinical disease posttreatment regression in 46 included eyes with laser or bevacizumab treatment. MeaningTracking quantitative measurements of retinopathy of prematurity severity may be an effective method of following disease regression and identifying patients at risk for recurrence after retinopathy of prematurity treatment.