An eye exam may be all that is needed to diagnose Parkinson’s disease, new research shows.
Using an advanced machine-learning algorithm and fundus eye images, which depict the small blood vessels and more at the back of the eye, investigators are able to classify patients with Parkinson’s disease compared against a control group. “We discovered that micro blood vessels decreased in both size and number in patients with Parkinson’s,” Maximillian Diaz, a PhD student at the University of Florida in Gainesville, told Medscape.
The simple eye examination may offer a way to diagnose Parkinson’s early in the disease progression.
Diaz said the test could be incorporated to a patient’s annual physical examination not only to look for Parkinson’s but also for other neurological diseases. A team in his lab is also looking at whether the same technique can diagnose Alzheimer’s disease.
The beauty of this is that “the technique is simple,” he said. “What surprised us is that we can do this with fundus images, which can be taken in a clinical setting with a lens that attaches to your smartphone.”
“It’s affordable and portable and it takes less than a minute,” he added.
Machine Learning on Fundus Eye Images
Researchers, under the direction of Ruogu Fang, PhD, director of the J. Crayton Pruitt Department of Biomedical Engineering’s Smart Medical Informatics Learning and Evaluation Lab (SMILE), collected fundus eye images from 476 age- and gender-matched individuals, 238 diagnosed with Parkinson’s and 238 control group images. Another set of 100 images were collected from the University of Florida database using green color channels (UKB-Gree