Identifying Cognitive Impairment from Retinal Scans
Researchers at Duke Health have developed a machine learning model that can distinguish normal cognition from mild cognitive impairment using retinal scans from the eye. The model analyzes retinal images and associated data and recognizes specific features to identify individuals with mild cognitive impairment. This model shows the potential for a non-invasive and inexpensive method of identifying early signs of cognitive impairment that could progress to Alzheimer’s disease. The scans which are based on optical coherence tomography (OCT) and OCT angiography (OCTA) detected structural changes in the neurosensory retina and its microvasculature among Alzheimer’s patients. (1) Specifically, the new model identifies specific features in the OCT and OCTA images that signal the presence of cognitive impairment, along with patient data such as age, sex, visual acuity and years of education and quantitative data from the images themselves.
Machine learning algorithms that leverage non-invasive and cost-effective retinal imaging to evaluate neurological health can be a very powerful tool to screen patients at scale.
1) Ophthalmology Science, June 2023
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