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AI-supported test could predict eye disease years before symptoms

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University College London and Western Eye Hospital have come together to create the new test

A new AI-supported test has the potential to predict eye disease three years before the outbreak of symptoms.

Developed by scientists at University College London in collaboration with the Western Eye Hospital, the test may predict wet AMD, a leading cause of severe sight loss.

Currently the diagnosis of wet AMD relies on a person developing symptoms, which then leads them to seek advice from a clinician. Initially, someone with wet AMD would notice distortion in their vision, normally interfering with their reading. Very quickly, this can progress to complete central vision loss.

Researchers hope their test could be used to identify the disease early enough so that treatment can effectively prevent any vision loss.

The test, called Detection of Apoptosing Retinal Cells (DARC), involves injecting into the bloodstream (via the arm) a fluorescent dye that attaches to retinal cells, and illuminates those that are undergoing stress or in the process of apoptosis, a form of programmed cell death. The damaged cells appear bright white when viewed in eye examinations – the more damaged cells detected, the higher the DARC count.

Using the same technology, the researchers had previously found that they can detect the earliest signs of glaucoma progression. This new study, which forms part of the same ongoing clinical trial of DARC, assessed 19 of the study participants who had already shown signs of AMD, but not necessarily in both eyes. The AI was newly trained to detect the formation of leaking and new blood vessels, which corresponded with the spots that DARC picked up.

The new analysis found that DARC can uniquely highlight endothelial cells (which line our blood vessels) under stress in the retina. These stressed cells then predict future wet AMD activity with the formation of leaking and new blood vessels seen in patients three years later, using conventional eye scans with Optical Coherence Tomography (OCT).

Lead researcher Professor Francesca Cordeiro said: “Our results are very promising as they show DARC could be used as a biomarker for wet AMD when combined with the AI-aided algorithm.

“Our new test was able to predict new wet AMD lesions up to 36 months in advance of them occurring and that is huge – it means that DARC activity can guide a clinician into treating more intensively those patients who are at high risk of new lesions of wet AMD and also be used as a screening tool.”

The study team hope to continue their research with a clinical trial with more participants, and hope to investigate the test in other eye diseases as well.

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