UCL and Moorfields Eye Hospital AI tool for detecting leading cause of childhood blindness

A new study led by researchers from UCL and Moorfields Eye Hospital, has found a new AI model could be an effective way of identifying retinopathy of prematurity, the leading cause of childhood blindness.

The tool been developed to help identify which at-risk children have retinopathy of prematurity and to improve access to screening.

The algorithm was trained on a sample of 7,414 images of the eyes of 1,370 newborns, who had been admitted to the Homerton Hospital, London, and assessed for retinopathy of prematurity by ophthalmologists. On its performance, the tool was assessed on another 200 images and compared to the assessments of senior ophthalmologists. Researchers then employed the tool on datasets sourced from Brazil, Egypt and the US – with an aim to further validate the efficacy of the technology.

It’s been developed as a code-free deep learning platform, which the authors said “means it could also be implemented in new settings by people without prior coding experience”.

The authors highlighted that the initial findings from this study justify further testing and are now validating the tool in hospitals across the UK to understand how it could be incorporated into a clinical setting.  

Lead author Dr Konstantinos Balaskas (Director, Moorfields Ophthalmic Reading Centre, Moorfields Eye Hospital and Associate Professor, UCL Institute of Ophthalmology) said: “Retinopathy of prematurity is becoming increasingly common as survival rates of premature babies improve across the globe, and it is now the leading cause of childhood blindness in middle-income countries and in the US.

“As many as 30% of premature newborns in sub-Saharan Africa have some degree of retinopathy of prematurity and, while treatments are now readily available, it can cause blindness if not detected and treated quickly. This is often due to a lack of eye care specialists.

“As it becomes more common, many areas do not have enough trained ophthalmologists to screen all at-risk children; we hope that our technique to automate diagnostics of retinopathy of prematurity will improve access to care in underserved areas and prevent blindness in thousands of newborns worldwide.”

The study was hosted by an international team of scientists and clinicians in the UK, Brazil, Egypt and the US, supported by the National Institute for Health and Care Research Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology. The results of the study were recently published in The Lancet Digital Health.