Alzheimer’s disease has rightly been characterised as a ‘silent pandemic’, with the number of Americans over 65 who are living with Alzheimer’s projected to double by 2060 as the population ages, to 13.8 million.
More broadly, dementia affects over 55 million people worldwide and the economic impact is extensive as well, with the burden of dementia estimated at $2.8tn globally and US costs for health and hospice payments alone estimated at $360bn, in addition to billions of hours of free care provided by over 11 million relatives and unpaid caregivers. The silver lining is that this affords us an impactful way to use artificial intelligence (AI) to make healthcare better, by detecting Alzheimer’s disease – and, eventually, other diseases too – at earlier stages, in a non-invasive and low-cost way that can be as simple as an eye exam.
Current methods for detecting asymptomatic Alzheimer’s, like a lumbar puncture to analyse patients’ cerebrospinal fluid, or PET or MRI imaging, tend to be expensive, invasive or have limited availability. Researchers have been investigating other methods as well, but this one is exciting: what if someone could walk into an ophthalmologist’s office for a routine check-up and receive an eye exam that also screens for Alzheimer’s disease – and ultimately for other significant but silent conditions, like cardiovascular disease.
The good news is that the technology for AI-supported retina scans that can detect Alzheimer’s is already mature. Now it’s time to lay the groundwork to start deploying this technology at doctors’ offices, healthcare clinics and hospitals.
In the world of metaphor, the eyes are the windows to the soul. In the world of science, the retina is the window to human vasculature and neural connections. It’s the only place on the body that doesn’t require advanced imaging equipment or invasive procedures in order to get a glimpse of the blood vessels. As such, the retina holds a great deal of potential as an entry point for the detection of systemic diseases like neurological disorders and heart disease.
In October 2024, an article in the scholarly journal npj Digital Medicine reported that the deep learning framework Eye-AD excelled at detecting early-onset Alzheimer’s disease and mild cognitive impairment, using a combination of retinal imaging and artificial intelligence. The multi-centre study involved 1,671 participants, forming by far the largest data set for use of the non-invasive imaging procedure known as optical coherence tomography angiography (OCTA) in detecting Alzheimer’s and mild cognitive impairment.
‘Retinal imaging is less expensive, simpler and faster, and has greater feasibility for smaller hospitals or community screening programmes, when compared with a conventional [Alzheimer’s disease] diagnosis protocol,’ the study found, while a literature review published last year reported that ‘the growing application of AI in medicine promises its future position in processing different aspects of patients with [Alzheimer’s disease]’.
The merits of non-invasive retinal scans bolstered by AI capabilities go beyond the lower cost, greater convenience and lack of pain or side effects. Another big benefit is that the detection is opportunistic, meaning that it doesn’t require a patient to specifically come in for an Alzheimer’s diagnosis, but can be performed on any patient who goes for an eye exam – which is particularly important for those at an early stage who are asymptomatic.
At the same time, there are multiple challenges that the medical community still needs to work on in order to turn the technology from functional viability to common practice.
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