Optical Coherence Tomography versus Optic Disc Photo Assessment in Glaucoma Screening.

Abstract

This review article examines the strengths and limitations of optical coherence tomography (OCT) and optic disc photography in glaucoma screening. A comprehensive literature review was conducted, focusing on the accuracy, feasibility, cost-effectiveness, and technological advancements in OCT and optic disc photography for glaucoma screening. OCT is highly accurate and reproducible but faces limitations due to its cost and less portable nature, making widespread screening challenging. On the other hand, optic disc photos are more accessible and cost-effective but are hindered by subjective interpretation and inconsistent grading reliability. A critical challenge in glaucoma screening is achieving a high positive predictive value, particularly given the low prevalence of the disease, which can lead to a significant number of false positives. The advent of artificial intelligence and deep learning models shows potential in improving the diagnostic accuracy of optic disc photos by automating the detection of glaucomatous optic neuropathy (GON) and reducing subjectivity. However, the effectiveness of these AI models hinges on the quality of training data. Using subjective gradings as training data, will carry the limitations of human assessment into the AI system, leading to potential inaccuracies. Conversely, training AI models using objective data from OCT, such as retinal nerve fiber layer thickness, may offer a promising direction. Both OCT and optic disc photography present valuable but distinct capabilities for glaucoma screening. An approach integrating AI technology might be key in optimizing these methods for effective, large-scale screening programs.