Irish National Diabetic RetinaScreen Programme: report on five rounds of retinopathy screening and screen-positive referrals. (INDEAR study report no. 1).

OBJECTIVE: To study the uptake of annual diabetic retinopathy screening and study the 5-year trends in the detection of screen-positive diabetic retinopathy and non-diabetes-related eye disease in a cohort of annually screened individuals. DESIGN: Retrospective retinopathy screening attendance and retinopathy grading analysis. SETTING: Community-based retinopathy screening centres for the Diabetic RetinaScreen Programme. PARTICIPANTS: 171 557 were identified by the screening programme to be eligible for annual diabetic retinopathy screening. 120 048 individuals over the age of 12 consented to and attended at least one screening appointment between February 2013 to December 2018. MAIN OUTCOME MEASURES: Detection rate per 100 000 of any retinopathy, screen-positive referrable retinopathy and nondiabetic eye disease. RESULTS: Uptake of screening had reached 67.2% in the fifth round of screening. Detection rate of screen-positive retinopathy reduced from 13 229 to 4237 per 100 000 screened over five rounds. Detection of proliferative disease had reduced from 2898 to 713 per 100 000 screened. Non-diabetic eye disease detection and referral to treatment centres increased almost eightfold from 393 in round 1 to 3225 per 100 000 screened. The majority of individuals referred to treatment centres for ophthalmologist assessment are over the age of 50 years. CONCLUSIONS: Screening programme has seen a reduced detection rate both screen-positive retinopathy referral in Ireland over five rounds of screening. Management of nondiabetic eye diseases poses a significant challenge in improving visual outcomes of people living with diabetes in Ireland.

A New Smartphone-Based Optic Nerve Head Biometric for Verification and Change Detection.

Purpose: Lens adapted smartphones are being used regularly instead of ophthalmoscopes. The most common causes of preventable blindness in the world, which are glaucoma and diabetic retinopathy, can develop asymptomatic changes to the optic nerve head (ONH) especially in the developing world where there is a dire shortage of ophthalmologists but ubiquitous mobile phones. We developed a proof-of-concept ONH biometric (application [APP]) to use as a routine biometric on a mobile phone. The unique blood vessel pattern is verified if it maps on to a previously enrolled image. Methods: The iKey APP platform comprises three deep neural networks (DNNs) developed from anonymous ONH images: the graticule blood vessel (GBV) and the blood vessel specific feature (BVSF) DNNs were trained on unique blood vessel vectors. A non-feature specific (NFS) baseline ResNet50 DNN was trained for comparison. Results: Verification reached an accuracy of 97.06% with BVSF, 87.24% with GBV and 79.8% using NFS. Conclusions: A new ONH biometric was developed with a hybrid platform of ONH algorithms for use as a verification biometric on a smartphone. Failure to verify will alert the user to possible changes to the image, so that silent changes may be observed before sight threatening disease progresses. The APP retains a history of all ONH images. Future longitudinal analysis will explore the impact of ONH changes to the iKey biometric platform. Translational Relevance: Phones with iKey will host ONH images for biometric protection of both health and financial data. The ONH may be used for automatic screening by new disease detection DNNs.