Technology Transfer Provides Useful Insight
Dr Tom Margrain with the Retinal Densitometer. Picture credit Cardiff University

News

Technology Transfer Provides Useful Insight

30 Jul, 2013

Published over 12 years ago. See the latest and most current information on News.

Engineers used to designing instruments for ground and space based telescopes are now applying their expertise to the development of a diagnostic test for the developed world’s most common form of sight loss in adults, Age-Related Macular Degeneration (AMD).

Engineers at the UK Astronomy Technology Centre (UK ATC), part of the Science and Technology Facilities Council (STFC) are currently collaborating with scientists from Cardiff University’s School of Optometry and Vision Sciences to develop a unique instrument, a retinal densitometer, which can pick up the earliest stages of AMD by measuring, in the minutest of detail, how the eye responds to light.

AMD affects a small part of the retina at the back of the eye, the macula, which is used to see detail and colour. One of the earliest signs of AMD is a change in the way that the light sensitive pigments in the macula regenerate after exposure to light. The densitometer can assess this change by measuring, over time, the very small changes in the amount of light reflected by the retina after exposure to light.

Cardiff University’s Dr Tom Margrain, said: “The benefits to patients here are huge, but the benefit is not just societal, it is also economic. We may be living longer but this in turn increases the pressure on healthcare services. Our next steps will now be to get the densitometer ready for official clinical testing and then to take this through to full commercialisation. Ultimately our densitometer could be used in any optician’s clinic.”

Early tests already carried out by the project team, on 10 patients with early stage AMD and 10 controls, indicate that the light changes on the macula can be highly accurately measured using this patented technology, and that it has a high ability to distinguish between affected and non-affected groups.

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