Researchers have developed an innovative metric for objectively classifying pigmentation in a retinal image, rather than using subjective social constructs like ethnicity or other demographic variables, as is currently the case when building health datasets.
Called the Retinal Pigment Score (RPS), the open-source measurement system will enable more equitable artificial intelligence (AI) algorithms for detecting and managing eye conditions, such as diabetic retinopathy.
As described in Nature Communications, the RPS was created by a team of international researchers using deep learning to assess more than 70,000 colour fundus photographs of the retina from UK Biobank.
The international study, led by Moorfields Eye Hospital NHS Foundation Trust, UCL Institute of Ophthalmology and University of Washington, successfully validated the metric on cohorts in Tanzania, China, and Australia. Researchers found that retinal pigmentation varies significantly within ethnic groups with substantial overlap between ethnic groups, making traditional ethnicity-based classification unreliable, in the same way that hair, eye and skin colour overlap between ethnic groups.
If widely adopted, the RPS would overcome the problem of AI models being trained on patient data and labelled for ethnicity, which may be incomplete or missing and not reflect the biological state of the eye. The RPS could enable ophthalmology AI developers and medical product regulators to objectively evaluate whether training data includes adequate diversity and ensure efficacy after clinical deployment on a wide range of patients.
The findings also have potential implications for studying systemic diseases, such as Alzheimer’s and cardiovascular disease, with retinal images serving as a biomarker — a rapidly growing scientific field known as Oculomics.
Co-lead author Abraham Olvera-Barrios, Moorfields clinical research fellow, said: “RPS is a game-changer for both clinical research and AI development. It provides a precise, unbiased measure of retinal pigmentation, ensuring more inclusive and accurate healthcare solutions. If widely adopted, the RPS could overcome the limitations of subjective categorisation, or missing, ethnicity data.”
Fellow lead author Anand E. Rajesh said: “We are excited by the potential of this new metric to transform the way researchers and regulators think about eye data classification. By incorporating RPS, researchers can evaluate and improve AI model performance across varied biological backgrounds, fostering algorithmic fairness in medical AI”.
Senior author Cathy Egan said: “This novel approach challenges the reliance on ethnicity as a surrogate marker for biological variability and addresses the critical challenge of phenotypic diversity within retinal imaging datasets, a key concern in developing equitable and effective AI algorithms. With the global epidemic of diabetes, diabetic retinopathy is overwhelming the medical workforce and AI presents a potential solution. The RPS will be an important metric to demonstrate that these models work safely and fairly for all people with diabetes.”
The RPS algorithm has been made publicly available in hopes of encouraging other researchers to use it for the development of AI systems that are inclusive and unbiased.
4 March 2025
Additional information
To access the RPS algorithm, visit the project repository at GitHub.
Access the Nature Communications publication here.
For more information, please contact alex.black3@nhs.net
About Moorfields Eye Hospital NHS Foundation Trust
Moorfields Eye Hospital NHS Foundation Trust is one of the leading providers of eye health services in the UK and a world class centre of excellence for ophthalmic research and education. Moorfields main focus is the treatment and care of NHS patients with a wide range of eye problems, from common complaints to rare conditions that require treatment not available elsewhere in the UK. Moorfields unique patient case-mix in serving 23 locations across Greater London combined with the number of people treated means that the hospital’s clinicians have expertise in discrete ophthalmic sub-specialties. The Trust also operates commercial divisions that provide care to private patients in both London and the Middle East. Together with the UCL Institute of Ophthalmology, Moorfields is recognised as a leading centre of excellence in eye and vision research.
Moorfields is the lead NHS Foundation Trust for the INSIGHT Health Data Research Hub, the world’s largest bioresource of routinely collected ophthalmic data linked to clinical records. INSIGHT provides approved researchers with access to eye datasets, supported by data curation expertise, AI infrastructure, and patient involvement.
About UCL Institute of Ophthalmology
UCL Institute of Ophthalmology is one of the foremost eye and vision research institutes in the world. It operates at the cutting edge of translational research, delivering new therapies, diagnostic tools and preventive measures to patients suffering from visual impairment or blinding conditions. The combination of the Institute’s research resource with Moorfields Eye Hospital, which has the largest ophthalmic patient population in the western world, opens the way for further advances in vision research. Close collaboration with other academic partners and with industry extends its impact. The Institute has been named as the best place to study ophthalmology in the 2017 Centre for World University Rankings (CWUR). For further information, please visit www.ucl.ac.uk/ioo.