A doctor takes fundus photos (right) with the MII Retcam system (top) and the Keeler MIO system (bottom). Both systems use a smartphone camera to produce images that can help diagnose retinopathy of prematurity. Image courtesy of JAMA Network.
An inexpensive, smartphone-based camera can help doctors identify premature infants needing treatment for retinopathy of prematurity (ROP), according to a new study funded by the National Eye Institute (NEI). The study also showed that an artificial intelligence (AI)-based system was effective in assessing those same smartphone images to accurately flag babies needing ROP care. Prompt treatment of ROP in newborns can prevent retinal damage and permanent vision loss or blindness. The findings could potentially be used to improve access to ROP screening and treatment for thousands of babies worldwide through a telemedicine approach to care. NEI is part of the National Institutes of Health.
ROP is usually diagnosed by ophthalmologists or trained ophthalmic technicians using specialized, wide-field cameras that can view a large portion of the retina at the back of babies’ eyes. However, each of these cameras can cost up to $150,000 and require trained technicians to take and evaluate the images. Narrow-view cameras, such as those used in this study, are significantly less expensive (at $500 to $1500), but they produce images that show a smaller portion of the retina.
“We found that even though smartphone images captured less information than a wide-field camera, both ROP clinicians reading the images remotely and the AI algorithm were able to accurately identify all babies with severe ROP,” said Peter Campbell, M.D., Oregon Health Sciences University, Portland, the lead author of the study. “If the results of this study can be replicated in other telemedicine programs, it may be possible to rapidly improve access to care in regions where traditional ROP cameras are not available or affordable.”
The study enrolled 156 infants in an ROP telemedicine program at Aravind Eye Hospital in India. The babies were screened for ROP using a conventional wide-field camera, as well as one of two smartphone-based imaging devices: the Make-In-India Retcam or the Keeler Monocular Indirect Ophthalmoscope. The images were used to determine if the baby had ROP, and if so, whether the ROP required treatment. The collaborative research team, which included scientists from the U.S., India, and Singapore, also trained an AI system to use the smartphone-based images to diagnose ROP.
Both human graders and the AI system were able to accurately diagnose ROP requiring treatment 100% of the time from the smartphone-based images. The AI system was less accurate at detecting mild ROP; however, the authors note that as a screening tool for urgent ROP care, these smartphone-based images paired with an AI detection algorithm could help healthcare teams in low-resource settings provide time-sensitive, critical ROP care for newborn babies.
The study was supported by NEI, Research to Prevent Blindness, the US Agency for International Development, and the Seva Foundation, as well as by Oregon Health Sciences University.
Reference: Young BK, Cole ED, Shah PK, Ostmo S, Subramaniam P, Venkatapathy N, Tsai ASH, Coyner AS, Gupta A, Singh P, Chiang MF, Kalpathy-Cramer J, Chan RVP, and Campbell JP. Efficacy of Smartphone-Based Telescreening for Retinopathy of Prematurity with and Without Artificial Intelligence in India. JAMA Ophthalmology. May 11, 2023. doi:10.1001/jamaophthalmol.2023.1466
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NEI leads the federal government’s research on the visual system and eye diseases. NEI supports basic and clinical science programs to develop sight-saving treatments and address special needs of people with vision loss. For more information, visit https://www.nei.nih.gov.
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