Analysis of datasets of eye scans with the help of artificial intelligence (AI) has enabled doctors to identify subtle markers that indicate the presence of Parkinson’s disease on average seven years before clinical presentation. 

The study, conducted by a UCL and Moorfields Eye Hospital research team and published in the medical journal Neurology®, has detected very early signs of Parkinson’s by observing signs and changes in the INL (inner nuclear layer) of the retina that are too subtle for humans to see.

"We hope that this method could soon become a pre-screening tool for people at risk of the disease," said lead author Dr Siegfried Wagner of UCL Institute of Ophthalmology and Moorfields Eye Hospital. 

"Finding such signs means that, in the future, people will have the time to make lifestyle changes to prevent the conditions arising, and clinicians could delay the onset and impact of life-changing neurodegenerative disorders,” he said. 

A high-resolution 3D scan of the retina, known as ‘optical coherence tomography’ (OCT) produces a cross-section of the retina down to a thousandth of a millimeter. Using a type of AI known as ‘machine learning’, computers are now able to uncover hidden information about the whole body from these images alone.

The study has confirmed that a reduced thickness of the INL (inner nuclear layer) of the retina was associated with an increased risk of developing Parkinson’s disease. Detecting signs of Parkinson’s this early opens up a world of possibilities for the treatment of the dreaded disease.