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Title: Functional and Structural Reliability of Optic Nerve Head Measurements in Healthy Eyes by Means of Optical Coherence Tomography Angiography. Author: Mastropasqua R, D'Aloisio R, Agnifili L, Zuppardi E, Di Marzio G, Di Nicola M, Porreca A, Guarini D, Totta M, Brescia L, Di Antonio L. Journal: Medicina (Kaunas); 2020 Jan 20; 56(1):. PubMed ID: 31968630. Abstract: Background and Objectives: the aim of the study was to evaluate the repeatability and reproducibility of optical microangiography (OMAG)-based optical coherence tomography angiography (OCTA) in the optic nerve head (ONH) and radial peripapillary capillary (RPC) perfusion assessment of healthy eyes. Materials and Methods: in this observational study, a total of 40 healthy subjects underwent ONH evaluation, using an OMAG-based OCTA system at baseline (T0), after 30 min (T1), and after 7 days (T2). The main outcome measures were the vessel density (VD) and flux index (FI) of the RPCs, as well as peri-papillary retinal nerve fibre layer (pRNFL) thickness. The analysis was performed by two observers independently. The coefficient of repeatability (CR), within the subject coefficient of variation (CVw) and intrasession correlation coefficient (ICC), to evaluate intrasession repeatability of measurements was calculated for each observer. Results: the high intrasession and intersession repeatability and reproducibility were assessed in the two observers for all three outcome measures. Of note, the CRs for the first and the second observer were 0.011 (95% confidence interval (CI) 0.009-0.014) and 0.016 (95% CI 0.013-0.020) for FI, 0.016 (95% CI 0.013-0.021) and 0.017 (95% CI 0.014-0.021) for VD, and 2.400 (95% CI 1.948-3.092) and 3.732 (95% CI 3.064-4.775) for pRNFL thickness, respectively. The agreement between them was excellent for pRNFL assessment and very good for FI and VD. Conclusion: OCTA has a great potential in the accurate assessment of ONH and peri-papillary microcirculation. It allows for repeated and reproducible measurements without multiple scans-related bias, thus guaranteeing an independent operator analysis with good reproducibility and repeatability.[Abstract] [Full Text] [Related] [New Search]