Next-generation ophthalmoscope to spot signs of disease

To this end, Stephen A. Burns, a professor at Indiana University’s School of Optometry, has been named a principal investigator on a three-year, $4.8m award from the US NIH Venture Program Oculomics Initiative.

“This research is about using the eye as a window on health,” Burns said in a statement. “We want to give health care providers the clearest view they can hope to get into the body, non-invasively.”

Additional researchers on the project include co-principal investigator Amani Fawzi of Northwestern University and co-investigators Alfredo Dubra of Stanford University and Toco Y. P. Chui of the New York Eye and Ear Infirmary of Mount Sinai Hospital.

Burns’ research on using the eye to detect disease goes back to the early 2000s, when he and colleagues at the IU School of Optometry pioneered applying adaptive optics scanning laser systems to the observation of the human eye.

Using the technology developed at the school, the ophthalmoscope in Burns’ lab can observe the back of the human eye at the resolution of two microns, which is a scale small enough to show the real-time movement of red blood cells inside the eye’s arteries and veins. To date, Burns has used the technology to identify biomarkers for diabetes and hypertension in the walls of the eye’s blood vessels.

Project researchers from Northwestern and Mount Sinai have used similar technology to observe the cells outside and inside these blood vessels, including spotting the crescent-shaped red blood cells found in sickle cell aneamia. The Stanford researchers have used adaptive optics to improve observation of the eye’s photoreceptors.

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With support from the US National Institutes of Health (NIH), the research teams will integrate their individual projects into a singular device, as well as apply advanced machine learning and AI. Additionally, they will explore the technology’s potential to spot the early signs of heart disease and Alzheimer’s disease.

“There’s growing evidence of a strong retinal vascular component to Alzheimer’s disease,” said Burns. “You can currently see the signs with PET scans, which require large, multimillion-dollar instruments. If we can see the same signs with an eye scan, it’s a lot less invasive and a lot less costly.”

Co-investigator Eleftherios Garyfallidis, an associate professor of intelligent systems engineering at the IU Luddy School of Informatics, Computing and Engineering, will develop and apply machine learning and AI methods for interpreting the devices’ results. This could reduce diagnosis time from days to minutes by eliminating the need for a human to analyse the imagery.

In the first year of the project, the labs will align their instruments to the same level of sensitivity, said Burns, whose lab will integrate its technology with Northwestern’s instrument. Stanford will focus on similar technological integrations with the instrument at New York Eye and Ear.

Next, the work will shift toward data validation to confirm that the new instruments’ readings align with earlier versions of the technology. The researcher will also compare the new AI system’s interpretation of scans against the conclusions of human analysts to confirm accuracy.

The final year of the project will involve testing the device on clinical volunteers. Much of IU’s data will come from individuals recruited through the Atwater Eye Care Center.