Eye Exam Could Help Diagnose Parkinson's Disease Early

Eye exam along with machine learning technology helps identify Parkinson's disease earlier, according to research at the annual meeting of the Radiological Society of North America (RSNA). Parkinson's disease, a progressive disorder of the central nervous system is diagnosed based on symptoms like tremors, muscle stiffness, and impaired balance--an approach that has significant limitations.

"The issue with that method is that patients usually develop symptoms only after prolonged progression with a significant injury to dopamine brain neurons," said study lead author Maximillian Diaz, a biomedical engineering Ph.D. student at the University of Florida in Gainesville, Florida. "This means that we are diagnosing patients late in the disease process."

Nerve cell decay thins the walls of the retina in Parkinson's. It also affects the microscopic blood vessels, or microvasculature, of the retina. These features provide an opportunity to leverage the power of AI to examine images of the eyes for signs of Parkinson's disease.

For the new study, Diaz collaborated with graduate student Jianqiao Tian and University of Florida neurologist Adolfo Ramirez-Zamora, M.D., under the direction of Ruogu Fang, Ph.D., director of the J. Crayton Pruitt Department of Biomedical Engineering's Smart Medical Informatics Learning and Evaluation Lab (SMILE).

The researchers deployed AI-based support vector machine (SVM) learning. Using pictures of the back of the eye from both patients with Parkinson's disease and control participants, they trained the SVM to detect signs on the images suggestive of disease.

The results concluded that machine learning networks can classify Parkinson's disease based on retina vasculature.

Advertisement

"The single most important finding of this study was that a brain disease was diagnosed with a basic picture of the eye," Diaz said. "This is very different from traditional approaches where to find a problem with the brain you look at different brain images."

Diaz noted that those traditional imaging approaches with MRI, CT, and nuclear medicine techniques can be very costly. In contrast, the new approach uses basic photography with equipment commonly available in eye clinics to get an image. The images can even be captured by a smartphone with a special lens.

Advertisement

"It's just a simple picture of the eye, you can have it done in less than a minute, and the cost of the equipment is much less than a CT or MRI machine," Diaz said. "If we can make this a yearly screening, then the hope is that we can catch more cases sooner, which can help us better understand the disease and find a cure or a way to slow the progression."

The approach may also have applications in identifying other diseases that affect the structure of the brain, such as Alzheimer's disease and multiple sclerosis, Diaz said.



Source-Medindia