AI Model Uses Retinal Scans to Detect Alzheimer's Disease

Artificial intelligence (AI) or machine learning that interprets a combination of retinal images was able to successfully identify Alzheimer's disease patients, stated a study from Duke University.

Artificial intelligence approach could one day be used as a predictive tool. The findings of the study are published in the British Journal of Ophthalmology.

‘Machine learning analysis of certain types of retinal images has the potential to offer a non-invasive way to detect Alzheimer's disease in symptomatic individuals.’

The machine learning software looks at retinal structure and blood vessels on images of the inside of the eye that have been correlated with cognitive changes.

"Diagnosing Alzheimer's disease often relies on symptoms and cognitive testing," said senior author Sharon Fekrat, M.D., retina specialist at the Duke Eye Center. "Additional tests to confirm the diagnosis are invasive, expensive, and carry some risk. Having a more accessible method to identify Alzheimer's could help patients in many ways, including improving diagnostic precision, allowing entry into clinical trials earlier in the disease course, and planning for necessary lifestyle adjustments."

Researchers trained a machine learning model, known as a convolutional neural network (CNN), using four types of retinal scans as inputs to teach a computer to discern relevant differences among images.

Scans from 159 study participants were used to build the CNN; 123 patients were cognitively healthy, and 36 patients were known to have Alzheimer's.

"We tested several different approaches, but our best-performing model combined retinal images with clinical patient data," said lead author C. Ellis Wisely, M.D., a comprehensive ophthalmologist at Duke. "Our CNN differentiated patients with symptomatic Alzheimer's disease from cognitively healthy participants in an independent test group."

Co-author Dilraj S. Grewal, M.D., Duke retinal specialist said additional studies will also determine how well the AI approach compares to current methods of diagnosing Alzheimer's disease, which often include expensive and invasive neuroimaging and cerebral spinal fluid tests.

"Links between Alzheimer's disease and retinal changes -- coupled with non-invasive, cost-effective, and widely available retinal imaging platforms -- position multimodal retinal image analysis combined with artificial intelligence as an attractive additional tool, or potentially even an alternative, for predicting the diagnosis of Alzheimer's," Fekrat said.

Artificial Intelligence in Healthcare

Integrating AI into the healthcare system allows for a multitude of benefits:

• Automates administrative tasks at a lower cost.
• Analyzes big patient data sets to deliver better healthcare services.
• Helps in early diagnosis.
• Supports people with mental health issues.

Source: Medindia