Artificial Intelligence breakthrough in the diagnosis of geographic atrophy at Moorfields & UCL
A team led by Dr Konstantinos Balaskas at Moorfields Eye Hospital Ophthalmic Reading Centre and Clinical A.I. hub has developed a fully automated, deep-learning model (algorithm) that can detect and quantify geographic atrophy using standard eye scans.
Developed entirely in-house by the artificial intelligence (A.I.) team at Moorfields, this will be hugely beneficial to clinicians caring for patients with GA, providing a reliable and fast way to assess the severity of geographic atrophy, how quickly it progresses and how well it is responding to treatment.
The study has been published here in The Lancet Digital Health.
The reading centre at Moorfields Eye Hospital NHS Foundation Trust is a state-of-the-art image grading centre for clinical trials and diagnostics in ophthalmology and is the informatics hub of Moorfields, analysing data in order to gain clinical insights.
They then tested the algorithm using a completely different set of eye scans from patients at Moorfields Eye Hospital. The new A.I. system is able to match, and even outperform, predictions made by specialist human graders, all in a fraction of a second. The team also hope that further research will yield an A.I. that can predict progression to GA in otherwise healthy patients, to allow future treatments to be administered at the earliest opportunity.
Section b in diagram
The video shows the algorithm reading the segmented OCT images in real time.
The algorithm consists of separate models looking at different aspects of Geographic Atrophy, one is predicting disease progression and the other is determining specific features of the disease. It was developed using 5049 individual segments taken from 984 OCT scans of 200 patients. The scans were part of the FILLY study into a novel treatment for GA and taken from patients based in the USA, Australia and New Zealand . The results were validated using 884 manually graded segments from 192 OCT scans, collected as part of routine patient assessment from 110 patients at Moorfields.
Konstantinos Balaskas, Director of the Reading Centre and Clinical Trials and Digital Eye Health Lead at Moorfields Ophthalmic Reading Centre, said:
“At the Moorfields Reading Centre and Clinical A.I. Hub, we are working to pave the way for the safe and user-centric deployment of clinical A.I. for the benefit of patients and healthcare systems. I am particularly proud of our team of brilliant A.I. software engineers who developed a state-of-the-art deep-learning model to support the care of patients with a severe form of dry AMD, Geographic Atrophy. A particular challenge for the management of GA at-scale is the need to reliably, objectively and rapidly quantify and monitor growth of area of GA on the retina using OCT scans and assess its response to potential treatments. We are the first academic/reading centre to develop an A.I. tool to do this. Critically, we tested our AI system rigorously on a separate dataset from real-life clinical practice to ensure it performs reliably. We hope it is a major step towards an effective treatment pathway for GA, which affects millions of people worldwide and often leads to debilitating sight loss”
This research also heralds an exciting future for the INSIGHT Health Data Research Hub, which aims to make the de-identified, manually graded OCT scans used to test the GA algorithm available to other researchers.
INSIGHT, an NHS-led partnership, was set up to provide access to anonymous patient data for approved research in a safe and efficient way, within a robust governance structure. The data available through INSIGHT, comes from Moorfields Eye Hospital and University Hospitals Birmingham, and includes millions of routinely collected retinal images, scans, eye test results and related hospital records. INSIGHT encourages research that improves eye care and healthcare in general, and ensures it is carried out to the benefit of patients and the NHS in an ethical and transparent way.