Imagine a routine patient consultation. You carry out the standard eye examination, then use your optical coherence tomography (OCT) device to scan the patient’s retina. A few minutes later, you provide a printout that tells the patient that they have a raised risk of developing heart disease in the next five years, and you recommend they consult their GP. You haven’t seen visible cardiovascular structural change; rather real-time OCT analysis has utilised an artificial intelligence (AI) review of the vessels to predict a clinically significant increased risk profile.

This scenario is – potentially – just a few years away, thanks to the new discipline of oculomics. The term was coined as recently as 2019 by Professor Alastair Denniston, Consultant Ophthalmologist at University Hospitals Birmingham NHS Foundation Trust, and a pioneer in the field.

Oculomics combines a number of technologies, including high-resolution imaging such as OCT and fundus photography, AI and large-scale datasets such as INSIGHT and UK Biobank. By training algorithms on databases of millions of eye images and comparing them with images of other organs, as well as data from patient records, it is possible to observe a correlation between changes in the eye and particular health conditions. 

As Alastair says: “The power of oculomics is that we can look into your eye and see signals of your present and future health. We’ve been able to do this to some extent for more than 100 years, seeing changes in blood pressure and diabetes, but technology is enabling us to see things that were previously invisible.” These include early signs of diseases such as stroke and Alzheimer’s.