Optical coherence tomography imaging (OCT) rapidly produces 3 dimensional images of the macula (the sensitive part of the retina used for central vision). Abnormalities of macular thickness and structure on OCT imaging are the hallmark of both diabetic retinopathy (commonest cause of vision loss in working aged individuals in the UK) and age-related macular degeneration (commonest cause of vision loss in the elderly). OCT imaging can also provide information about the thickness of the macular nerve fibre layer, which may be thinned in glaucoma (commonest cause of irreversible vision loss worldwide) and in neurodegenerative diseases.
Our proposed analysis falls into 3 components: (1) use high speed computer algorithms to generate automated macular thickness measurements from OCT images captured from the 78,880 UKBiobank participants who underwent OCT imaging; (2) subject 5% of the analysed images and images which failed automated analysis to a manual grading process (3) use automated approaches to determine retinal sublayer thicknesses.
We are requesting access to OCT images and data on lifestyle and medical history. This will allow us to report the distribution of macular thickness across the sampled Biobank population and enable us to gain a clearer understanding of factors that influence macular thickness in health and disease.
The proposed analysis is well aligned with UK biobank objectives as deriving macular thickness measurements from the stored OCT data could help improve the diagnosis and treatment of a wide-range of serious and life-threatening diseases including eye diseases (age-related macular degeneration and glaucoma) and systemic disease (diabetes and neurodegenerative diseases).
