It’s an exciting time for medical diagnostics. Imagine getting a regular eye check-up and discovering, almost a decade in advance, that you may be at risk for Parkinson’s disease. Recent research suggests this could soon be a reality.
Eye scans, specifically those in 3D, are standard offerings at eye clinics and even some high-street opticians. What’s groundbreaking is the claim that these scans could potentially identify the early signs of Parkinson’s disease up to seven years before the symptoms become clinically evident.
While it’s not groundbreaking to use eye data to pinpoint health conditions, the combination of new advancements in ocular health technology and the ever-increasing power of computing has dramatically expanded the horizon for early disease diagnosis.
Enter the Optical Coherence Tomography (OCT) scan. This isn’t just any regular 3D eye scan. The OCT scan offers an impressively detailed cross-section of the retina – that’s the back part of our eyes. And how detailed, you ask? We’re talking about precision down to a thousandth of a millimetre. All this, in under sixty seconds! It’s the only non-invasive technique available to peek into the cell layers beneath our skin.
A team of researchers at UCL, in collaboration with the Moorfields Eye Hospital in London, saw potential in this technology. Leveraging the power of artificial intelligence, they embarked on a study analysing OCT scans from two massive databases – the AlzEye and the UK Biobank dataset, with a whopping total of over 220,000 individuals.
Their findings? They reinforced earlier research that showed patients with Parkinson’s had a noticeably thinner ganglion cell–inner plexiform layer (GCIPL). Additionally, there was evidence of atrophies in the inner nuclear layer (INL). Crucially, these changes in thickness in both layers appeared to be linked with the disease’s progression.
Dr Siegfried Wagner, the study’s lead author, exudes hope. He envisions a world where these findings could transform the OCT scan into a preliminary screening tool for those at potential risk of Parkinson’s. “The early signs of various diseases might offer people a precious window to make lifestyle modifications,” Wagner noted. Such advancements could enable medical professionals to delay or even prevent the onset of severe neurodegenerative conditions, providing a transformative impact on patients’ lives.
The study’s ripple effects are already visible. Under the leadership of the senior author, Professor Pearse Keane, a team has secured funding from the UK Research and Innovation body. Their mission? To further refine and validate this foundational model.
Beyond just Parkinson’s, this is a significant leap for the burgeoning domain of “oculomics.” Here, the prowess of machine learning is combined with eye scan data, unlocking clues to various diseases, including formidable foes like Alzheimer’s and multiple sclerosis.
