Title: Eye2Gene: accelerating the diagnosis of inherited retinal diseases
Funder: Department of Health and Social Care

Abstract: Background Inherited retinal disease (IRDs) are a leading cause of visual impairment in the working age population. Mutations in over 300 genes are associated with IRDs and a genetic diagnosis, which involves identifying the affected gene in a patient, is the first step towards care and management of the patient. However, genetics diagnosis is currently slow, expensive and not widely accessible: Average time to diagnosis is over 5 years and costs £10,000 per patient. More than 40% of patients are undiagnosed (>10,000 individuals). Aims_and_Objectives We aim to address the evidence gap in IRD diagnosis with an AI algorithm, Eye2Gene, to accelerate and democratise the IRD diagnosis service. Currently Eye2Gene predicts the gene causing the disease from a retinal scan, with a top-5 accuracy of 88% on our internal dataset. As part of this Phase 2 grant we plan to develop Eye2Gene into a medical device by: Validating Eye2Gene on independent datasets from three external sites (Oxford, Liverpool and Tokyo) Providing explainability by identifying specific abnormalities (IRD-specific features) in retinal scans. Work_plan_and_t imelines_for_delivery Year 1 External site onboarding Extension of a deep-learning segmentation algorithm to segment IRD-specific features Datasets preparation for benchmarking against "best-practice" Year 2 Validation in external sites Health economic evaluation Year 3 Application to variant proritisation Regulatory approvals Commercial exploitation Anticipated_Impact_and_Dissemination By increasing the diagnostic rate for IRDs at a decreased cost, and by offering equitable access to a genetic diagnosis, the anticipated impact for patients are: Improved health outcomes Personalised treatment plans (emerging treatments or clinical trials) Better understanding of the condition and its heritability for family planning For the NHS: Improved operational efficiency Increased genetic diagnostic rate at eye hospital. Reduced economic burden Dissemination channels for healthcare professionals will include: High-impact publications Conferences Research networks Professional bodies For patients and public: Patient day Charities Lay summaries Media

Lay abstract: The retina is the light-sensitive tissue at the back of our eyes which transforms light into electrical signals to your brain and is responsible for vision. Unfortunately, over 1 in 3000 people in the UK will have an inherited retinal disease (IRD), a genetic condition which causes a dysfunction of the retina, and the most common cause of blindness in young people in the UK. Accordingly, IRDs account for a leading cause of severe visual impairment in the working age population. Depending on the genetic condition, some may be blind from birth, while others may have their peripheral or central vision progressively deteriorate over several decades. Treatments are emerging for some IRDs but these require identification of the precise causative genetic mutation. Mutations in over 300 genes are associated with IRDs and identifying the affected gene in a patient is the first step towards diagnosis, prognosis and treatment. Currently, IRDs are detected first by community opticians and referred to ophthalmology for retinal imaging and diagnosis with a subsequent referral to specialist eye hospitals, such as Moorfields Eye Hospital, for further imaging and a genetic test. However, because of limitations in the availability of IRD expertise, detection and diagnostic rates remain poor, with most individuals having to wait more than 5 years for a diagnosis. This delays possible treatment pathways and assistance with sight loss. Our plan is to prepare images of historical IRD patient retinal scans (datasets) from four leading eye hospitals, Moorfields Eye Hospital, Oxford, Liverpool and Tokyo (Japan). We will use these retinal scan datasets to benchmark, further train and then test Eye2Gene, a deep-learning algorithm which is able to detect and diagnose IRDs from a patient s retinal scan. If Eye2Gene is successful, we aim to provide detection and diagnosis of IRDs through non-specialist hospitals within months instead of years, thus democratising expert IRD knowledge widely across the NHS for patient benefit, by enabling expertise to be delivered locally.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: EYE