However, new retinal research has found that these changes can be measured earlier than previously thought with specialised optical techniques and computer analysis.
‘Early detection of retinal damage from diabetes is possible to obtain with painless methods and might help identify undiagnosed patients early enough to diminish the consequences of uncontrolled diabetes. ’
The ability to detect biomarkers for this sight-threatening condition may lead to the early identification of people at risk for diabetes or a visual impairment, as well as improve physicians’ ability to manage these patients.
The new study is part of the current widespread emphasis on the detection of diabetic retinopathy through AI applied to retinal images. However, some of these algorithms provide detection based on features that occur much later than the changes found in this study.
The IU-led method advances earlier detection because of the retinal image processing algorithms described in the study.
For the study, published in the journal PLOS One, the team conducted the retinal image analysis in a lab. They used data collected from volunteers with diabetes, along with healthy control subjects.A
Additional data were also collected from a diabetic retinopathy screening of members of the underserved community.
The computer analysis was performed on retinal image data commonly collected in well-equipped clinics, but much of the information used in this study is often ignored for diagnosis or management of patients.
Source: IANS
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