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Scanning the eye to identify Alzheimer’s
SACRAMENTO, Calif.—The eyes are said to be the windows to the soul; could it be they are also the windows to dementia? Researchers at Cedars-Sinai and NeuroVision Imaging LLC recently led a study that they say provides the scientific basis for using noninvasive eye imaging to detect the pathological hallmarks of Alzheimer’s disease.
Accumulations of neurotoxic beta-amyloid protein can be detected with positron emission tomography (PET) scans and analysis of cerebrospinal fluid, but because both routes are invasive, inconvenient and costly, they are impractical for routine screening and follow-up evaluation. The experimental technology developed by Cedars-Sinai and NeuroVision, however, scans the retina using techniques that can identify beta-amyloid protein deposits that mirror those in the brain.
“This is the first study demonstrating the potential to image and quantify retinal findings related to beta-amyloid plaques noninvasively in living patients using a retinal scan with high resolution,” said Dr. Maya Koronyo-Hamaoui, an associate professor of neurosurgery and biomedical sciences and a research scientist at the Maxine Dunitz Neurosurgical Institute at Cedars-Sinai, as well as a co-founder, inventor and scientist at NeuroVision. “This clinical trial is reinforced by an in-depth exploration of the accumulation of beta-amyloid in the retina of Alzheimer’s patients versus matched controls, and a comparison analysis between retina and brain pathologies. Findings from this study strongly suggest that retinal imaging can serve as a surrogate biomarker to investigate and monitor Alzheimer’s disease.”
“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,” added Dr. Keith L. Black, chairman of NeuroVision and also chair of the Department of Neurosurgery and director of the Maxine Dunitz Neurosurgical Institute at Cedars-Sinai. “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.”
Steven Verdooner, NeuroVision’s CEO, said the imaging system leverages the company’s expertise in autofluorescence imaging of the retina using a specialized ophthalmic camera and sophisticated image processing software, adding: “It’s exciting to see these studies demonstrating the power of the technology applied to the Alzheimer’s field. Our goal is to develop a product that is easy to use, affordable and widely accessible. We look forward to the potential of retinal imaging playing a vital role in solving the problem of Alzheimer’s, both in identifying and monitoring those who may be affected by the disease. Our next step is to continue with clinical trials, building upon the existing pharmaceutical company collaborations, to ensure our technology is ready for the medical community to help manage this disease.”
The study’s first author, Yosef Koronyo, a research associate at Cedars-Sinai and a scientist and inventor at NeuroVision, said the latest findings cap a decade of study that has produced several landmark discoveries. “In 2010, our research group published an article providing the first evidence for the existence of Alzheimer’s-specific plaques in the human retina, and we demonstrated the ability to detect individual plaques in live mouse models using a modified ophthalmic device.”
Among key findings, the researchers reported a 4.7-fold increase in retinal plaque burden in patients with Alzheimer’s, compared to controls, and they provide observations regarding geometric distribution and layer location of amyloid pathology in the retina. With the imaging technology’s ability to detect autofluorescence signal related to retinal beta-amyloid, these findings may lead to a practical approach for large-scale identification of the at-risk population and monitoring of Alzheimer’s, the researchers say.