Discriminating pituitary from glaucomatous visual fields
Research type
Research Study
Full title
Using machine learning to explore automated discrimination between visual field loss caused by pituitary pathology and glaucoma.
IRAS ID
232104
Contact name
Peter Thomas
Contact email
Sponsor organisation
Cambridge University Hospitals Foundation Trust
Duration of Study in the UK
0 years, 9 months, 1 days
Research summary
Many diseases of the eye and brain can cause patients to lose areas of vision in one or both eyes. We assess these by performing a visual field test. Different diseases cause different, often characteristic, patterns of visual field loss. The most common disease affecting visual fields is glaucoma. However, it is a known clinical pitfall that some patients with non-glaucoma diseases can end up being treated for glaucoma.
In this study, we aim to apply machine learning (artificial intelligence) techniques to train computers to discriminate visual field defects caused by glaucoma from visual field defects caused by diseases (generally tumours) of the pituitary gland. This could allow automatic detection of visual field loss related to non-glaucoma diseases, and thus enhance patient safety.
REC name
South West - Cornwall & Plymouth Research Ethics Committee
REC reference
17/SW/0197
Date of REC Opinion
16 Aug 2017
REC opinion
Favourable Opinion