Spectral-domain Optical Coherence Tomography Retinal and Choroidal Thickness Metric Repeatability in Age-related Macular Degeneration

PurposeTo determine the intrasession repeatability of spectral-domain OCT (SDOCT)-derived macular retinal and choroidal metrics in patients with neovascular age-related macular degeneration (nAMD) in the Distance of Choroid Study (DOCS).DesignValidity and reliability analysis.MethodsEnrolled patients underwent repeated SDOCT imaging using the Spectralis OCT (Heidelberg Engineering, Heidelberg, Germany). A single technician certified for clinical trials took 3 macular volume scans. Retinal thicknesses were calculated for each of the 9 Early Treatment Diabetic Retinopathy Study (ETDRS) macular subfields. Center point thickness and total macular volume were also included in the analysis. Manual subfoveal choroidal thickness measurements were made by a masked observer.ResultsA total of 40 eyes of 40 patients were included in this analysis (mean [± standard deviation] age: 74.1 [± 7.2] years, 60% male). The coefficient of repeatability (CR) of the central macular subfield was 30.6 μm (95% confidence interval [CI] 29.8-1.4 μm). The CR for the other macular subfields ranged from 7.0 μm to 38.2 μm. The CR for the total macular volume was 0.212 mm3 (95% CI 0.206-0.217 mm3) and the CR for the center point was 47.5 μm (95% CI 46.2-48.7 μm). Images were also reviewed for the presence of segmentation error in the central macular subfield, and after exclusion of these eyes the revised CR for this subfield was 13.7 μm (95% CI 13.3-14.1 μm). The intrasession CR of subfoveal choroidal thickness was 34.7 μm (95% CI 33.7-35.7 μm).ConclusionsThis study suggests that a change of greater than 31 μm in Spectralis SDOCT-derived retinal thickness measurement of the central macular subfield and 35 μm in subfoveal choroidal thickness is necessary to detect true clinical change associated with disease progression or improvement in nAMD with a revised figure of 14 μm for central macular retinal subfield thickness in the absence of segmentation error.