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Glaucoma Ophthalmic Imaging Tools to Detect Glaucoma Progression Tigran Kostanyan, MD 1 and Gadi Wollstein, MD 2 1. Research Fellow; 2. Associate Professor of Ophthalmology, UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, Philadelphia, US Abstract Ocular imaging devices provide objective and reliable structural measurements and estimate structural progression that has important clinical implications in ocular pathologies such as glaucoma. This review describes the working principles and main methods for detection of glaucoma progression used in the leading commercially available ocular imaging. This information allows clinicians to better identify eyes that are suspicious of progression and adjust the clinical management as needed. Keywords Spectral domain optical coherence tomography (SD-OCT), confocal scanning laser ophthalmoscopy (CSLO), scanning laser polarimetry (SLP), glaucoma progression Disclosures: Tigran Kostanyan, MD, and Gadi Wollstein, MD, have no conflicts of interest to declare. No funding was received in the publication of this article. Open Access: This article is published under the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, adaptation, and reproduction provided the original author(s) and source are given appropriate credit. Received: August 30, 2014 Accepted: October 10, 2014 Citation: US Ophthalmic Review, 2015;8(1):37–42 Correspondence: Gadi Wollstein, MD, UPMC Eye Center, Eye and Ear Institute, 203 Lothrop St, Pittsburgh, PA 15213, US. E: wollsteing@upmc.edu Glaucoma is a chronic progressive optic neuropathy, which can lead to irreversible blindness. 1 It is characterized  by loss of retinal nerve tissue that results in visual function deterioration. Structural changes, such as accelerated loss of retinal ganglion cells (RGCs) and their axons, and a specific pattern of damage in the optic nerve head (ONH) associated with visual field (VF) loss, are considered hallmarks of glaucoma. 2 The efficacy of glaucoma management depends mostly on the ability to reliably detect disease progression as early as possible. Detection of progression allows the clinician to initiate or modify treatment, which can slow glaucoma progression and potentially preserve vision. Even though optic disc stereophotographs are considered the gold standard for the evaluation of glaucomatous structural damage, the estimation of structural progression in glaucoma using this tool is challenging due to its subjective nature. 3 The recent evolution of imaging tools noticeably improved the objective and quantitative determination of structural changes and the assessment of progression caused by glaucoma. 4–6 However, the assessment of structural progression in glaucoma still comprises several dilemmas due to difficulties in differentiating between true glaucomatous change and natural age- related loss of retinal nerve tissue, measurement variability, and a lack of widely accepted and efficient gold standard criteria for establishing glaucoma progression. In this review we will summarize the imaging tools that are currently available, namely scanning laser polarimetry (SLP), confocal scanning laser ophthalmoscopy (CSLO), and spectral domain optical coherence tomography (SD-OCT). We will focus Tou ch MEd ica l MEdia particularly on their ability to detect glaucoma progression, as well as the strengths and limitations of each imaging technology. Detection of Glaucoma Progression Progression of glaucoma can be estimated by subjective assessment based on clinical experience and judgment, or by statistical analysis of quantitative measurements. The statistical methods used to detect glaucoma progression can be classified as event- or trend-based analysis. In event-based analysis a series of follow-up measurements are compared with baseline measurements, and progression is defined when measurements exceed a predetermined threshold for change from baseline. This method is highly sensitive to the threshold level, with a higher threshold resulting in fewer cases identified as progressing with only a small number of false positive classifications and vice versa when choosing a lower threshold. The threshold is often selected based on the physical properties of the imaging device (e.g., measurement reproducibility), or by population-based data. The main disadvantage of this method is the effect of erroneous deviating measurements that might be labeled as progression. A confirmatory second test can resolve most of the false progression classifications in this method. Trend-based analysis uses regression analysis or mixed effect regression analysis to estimate the rate of change in the examined parameters. Progression is defined either when the rate of change is significantly different than a no change slope (zero slope), or when the rate is different than population or individually derived slope. This method 37