Abstract
Optical coherence tomography (OCT) is a widely used tool to diagnose and monitor glaucoma by objectively measuring the ganglion cell layer and the retinal nerve fiber layer (RNFL) thickness. The presence of RNFL thinning raises suspicion for glaucoma progression. Therefore, this review aims to discuss current approaches to using OCT for detecting glaucomatous change, limitations, and recent advancements. Previously established approaches to determining glaucomatous progression on OCT include quantitative and qualitative methods. The most common quantitative methods include event-based and trend-based analysis. Decreasing RNFL thickness or loss of the ganglion cell layer are indicative of glaucomatous changes. However, interpretation of OCT scans is strongly impacted by artifacts, which can be because of epiretinal membrane or posterior vitreous detachment. Race and aging also may impact interpretation of RNFL progression. More recent research focuses on loss of the RNFL because of the effects of systemic conditions. Given the limitations in the current approaches, recent advancements indicate a promising role for artificial intelligence in determining true glaucomatous progression. This review highlights current approaches to identifying glaucoma progression on OCT, limitations to these approaches, and the potential role for artificial intelligence.
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