A-EYE Study
Research type
Research Study
Full title
A-EYE: A mixed quantitative and qualitative study to develop and evaluate the application of Artificial Intelligence (AI) methods using retinal imaging for the identification of adverse retinal changes associated with cancer therapies
IRAS ID
283212
Contact name
Tariq Aslam
Contact email
Sponsor organisation
The University of Manchester
Duration of Study in the UK
0 years, 8 months, 30 days
Research summary
Many cancer patients with advanced disease enter clinical trials when they have exhausted all available standard treatments. These early phase clinical trials involve giving innovative new drugs with unknown side effects to cancer patients. These include side effects, or toxicities, which impact the eyes. In some cases these can lead to visual changes, including blindness, that may indicate how toxic these new drugs are, or a potential response to treatment. In many cases, there is very little preplanning or management plans put in place for the detection of eye toxicities in advance of patients commencing on a clinical trial. Additionally, the expertise of eye specialists is not always available to all patients undergoing cancer treatment, and they may only be referred to eye specialists when symptoms and signs of eye toxicity become more apparent and advanced. This leads to delays in identification, treatment and follow-up management. Access to this expertise would help in detecting these often unpredictable eye toxicities, however, current demands on resources means that this expertise is not readily available. Developing an artificial intelligence (AI) algorithm trained in the detection of cancer related eye toxicities will go a significant way in easing the burden on the health care system, and improving side effects from new cancer therapies.
This study, sponsored by The University of Manchester, will involve the collection of patient data and copies of the images produced when patients undergo an Optical Coherence Tomography (OCT) scan of the eyes at Manchester Royal Eye Hospital. This data and the copy images will be used to develop and assess AI methods to detect eye abnormalities associated with cancer treatment, and to compare these methods with the assessments of ophthalmologists, to assess if the AI methods give similar results.
REC name
London - West London & GTAC Research Ethics Committee
REC reference
21/PR/0021
Date of REC Opinion
18 Mar 2021
REC opinion
Further Information Favourable Opinion