Medical

Retinal imaging can improve Alzheimer’s detection

24th August 2017
Enaie Azambuja
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A team of researchers at Cedars-Sinai Medical Center in Los Angeles and NeuroVision Imaging, a Sacramento, California firm, have developed a retinal imaging system that could allow early detection of Alzheimer’s disease. One of the hallmarks of Alzheimer’s disease is the accumulation of beta-amyloid protein in the brain. There are numerous ways to monitor levels of beta-amyloid in the nervous system, including cerebrospinal fluid analysis, or imaging techniques like positron emission tomography.

However, these techniques are invasive and expensive, meaning that they are unsuitable for routine screening to assess disease progression.

“We know that Alzheimer’s begins as many as 10 or 20 years before cognitive decline becomes evident, and we believe that potential treatments may be more effective if they can be started early in the process. Therefore, screening and early detection may be crucial to our efforts to turn the tide against the growing threat of this devastating disease,” says Keith Black, a researcher who was involved in the study.

The team developed a new method to detect beta-amyloid protein in the retina by using a specialised ophthalmic camera and sophisticated image-processing software to conduct fluorescence imaging. The technique is much less invasive than other methods of measuring beta-amyloid concentrations and may end up helping tremendously in the fight against Alzheimer’s.

“As a developmental outgrowth of the central nervous system that shares many of the brain’s characteristics, the retina may offer a unique opportunity for us to easily and conveniently detect and monitor Alzheimer’s disease,” said Black.

In a recent study, published in journal JCI Insight, the team conducted a small clinical trial to see if they could identify beta-amyloid in the retina using the technique. They found an average 4.7-fold increase in beta-amyloid plaques in the retinas of patients with Alzheimer’s, suggesting the technique could be useful to find people at risk of the disease, or to monitor those who already have it.

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