ArticleInvestigative ophthalmology & visual science2025
Retinal OCT-Derived Texture Features as Potential Biomarkers for Early Diagnosis and Progression of Diabetic Retinopathy.
Article in Investigative ophthalmology & visual science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- The role of serum miR-28-5p in predicting diabetic retinopathy onset in type 2 diabetes.BMC endocrine disorders · 2026Article
- Porcine Corneal Models as Translational Platforms for Innovative Therapies: Current Insights and Future Directions.Journal of functional biomaterials · 2025Review
- Early retinal changes in type 2 diabetes detected by texture-based OCT analysis: potential approach for subclinical diabetic retinopathy diagnosis.Eye and vision (London, England) · 2025Article
- Berberine attenuates the expression of NLRP3 and downstream inflammasome effectors in diabetic retinopathy.Journal of natural medicines · 2025Article
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10 authors.
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Abstract
Purpose: Diabetic retinopathy (DR) is usually diagnosed many years after diabetes onset. Indeed, an early diagnosis of DR remains a notable challenge, and, thus, developing novel approaches for earlier disease detection is of utmost importance. We aim to explore the potential of texture analysis of optical coherence tomography (OCT) retinal images in detecting retinal changes in streptozotocin (STZ)-induced diabetic animals at "silent" disease stages when early retinal molecular and cellular changes that cannot be clinically detectable are already occurring. Methods: Volume OCT scans and electroretinograms were acquired before and 1, 2, and 4 weeks after diabetes induction. Automated OCT image segmentation was performed, followed by retinal thickness and texture analysis. Blood-retinal barrier breakdown, glial reactivity, and neuroinflammation were also assessed. Results: Type 1 diabetes induced significant early changes in several texture metrics. At week 4 of diabetes, autocorrelation, correlation, homogeneity, information measure of correlation II (IMCII), inverse difference moment normalized (IDN), inverse difference normalized (INN), and sum average texture metrics decreased in all retinal layers. Similar effects were observed for correlation, homogeneity, IMCII, IDN, and INN at week 2. Moreover, the values of those seven-texture metrics described above decreased throughout the disease progression. In diabetic animals, subtle retinal thinning and impaired retinal function were detected, as well as an increase in the number of Iba1-positive cells (microglia/macrophages) and a subtle decrease in the tight junction protein immunoreactivity, which did not induce any physiologically relevant effect on the blood-retinal barrier. Conclusions: The effects of diabetes on the retina can be spotted through retinal texture analysis in the early stages of the disease. Changes in retinal texture are concomitant with biological retinal changes, thus unlocking the potential of texture analysis for the early diagnosis of DR. However, this requires to be proven in clinical studies.
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