Detection of Anterior Segment Disease - V1
Research type
Research Study
Full title
Analysis of Multiple Source Data for the Detection of Disease of the Anterior Segment of the Eye
IRAS ID
296006
Contact name
Lauren Leitch-Devlin
Contact email
Sponsor organisation
Moorfields Eye Hospital
Duration of Study in the UK
2 years, 11 months, 31 days
Research summary
Diseases of the anterior segment of the eye (the part of the eye anterior to the iris) is an important cause for visual loss. The most common conditions are inherited corneal diseases such as keratoconus and Fuchs endothelial corneal dystrophy, or corneal infection. In both of these groups, investigation and imaging are important both for making the diagnosis of disease and also for monitoring for progression of the disease over time. Accurate imaging can also be a valuable aid for determining disease subsequent management to prevent further progression and visual loss.
Moorfields Eye Hospital has a very large database of images taken for the diagnosis of disease and for monitoring disease progression. A comparison with normal eyes is important, and there is also a large database from individuals who have had laser refractive surgery, and had scans to confirm that their eyes have a normal shape. Thirdly, a previous linked study of inherited corneal disease has produced a database of genomic data from some of these individuals with keratoconus and Fuchs endothelial corneal dystrophy.
The purposes of this study are twofold:
1. To examine the stored database of demographic data (e.g. gender, age, self-declared ethnicity) and corresponding images of the cornea and anterior segment, to determine whether statistical analysis of the data from each image can lead to a more accurate way to diagnose the disease or identify changes of disease progression. The data from images from candidates for laser refractive surgery will act as control images for comparison.
2. To link the genomic data from individuals with keratoconus and Fuchs endothelial corneal dystrophy to their image data. This is to identify if any genomic signals correlate with disease severity or the likelihood of disease progression.
REC name
London - London Bridge Research Ethics Committee
REC reference
22/PR/0249
Date of REC Opinion
10 Mar 2022
REC opinion
Favourable Opinion