Emerging Role of optical coherence tomography in the Diagnosis of diabetic retinopathy
DOI:
https://doi.org/10.5281/zenodo.22812176Keywords:
optical coherence tomography, OCT angiography, diabetic retinopathy, diabetic macular edema, deep learningAbstract
Background: Diabetic retinopathy remains a leading cause of preventable vision loss, and optical coherence tomography (OCT) has become central to detecting its structural and vascular changes earlier and more objectively than clinical examination alone [2,3].
Objective: This review synthesizes the published evidence on structural OCT and OCT angiography (OCTA) in the diagnosis, staging, and monitoring of diabetic retinopathy and diabetic macular edema.
Methods: We synthesized landmark OCT validation studies, randomized treatment trials using OCT-based endpoints, quantitative OCTA cohort studies, and papers on automated and deep-learning-assisted OCT/OCTA interpretation.
Findings: Structural OCT reliably detects and quantifies diabetic macular edema and underpins the primary endpoints of major treatment trials [6,8,9], while OCTA reveals microvascular non-perfusion and foveal avascular zone changes that precede clinically apparent retinopathy and predict disease progression [23,25]; deep-learning systems applied to OCT and OCTA are increasingly able to detect referable disease at accuracy approaching human graders [28,32].
Conclusions: OCT and OCTA have moved from adjunct imaging tools toward central components of diabetic retinopathy diagnosis and screening, though cross-device standardization and prospective outcome validation remain needed before algorithm-assisted interpretation sees uniform clinical adoption [13,30].
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