Purpose:
To determine the repeatability of macular thickness measurements from eyes with various retinal diseases using a Cirrus HD-OCT with retinal tracking capability.
Methods:
Fifty six (56) eyes with various diseases including age-related macular degeneration (AMD), epiretinal membrane (ERM), diabetic retinopathy (DR), and cystoid macular edema (CME) were imaged twice in one session with the Macular 512x128 volume cube scan protocol. The imaging was performed using a prototype Cirrus HD-OCT instrument with retinal tracking capability to compensate for retinal motion during scans. The Internal Limiting Membrane (ILM) and the Retinal Pigment Epithelium (RPE) layers were automatically segmented from the data cubes using the segmentation algorithms in the Cirrus HD-OCT instrument. The fovea was automatically segmented from the cube and measurements were obtained from an ETDRS grid centered on the fovea. For this study, the central subfield thickness measurement from the ETDRS grid was used as the measurement parameter of interest. Outliers due to segmentation failures and errors in fovea detection were excluded from further analysis. Analysis of variance (ANOVA) was used to determine repeatability standard deviation (SD) for the measurement parameter.
Results:
The repeatability standard deviation obtained with the new tracking prototype software for the overall cohort including all diseases was 1.54 microns (Table 1). The table also shows the repeatability standard deviation of the software without tracking for various retinal diseases. Eyes with AMD appeared to have the highest variability between scans, particularly when compared with eyes with vitreo-retinal interface disease.
Conclusions:
Tracking improves the repeatability of Cirrus HD-OCT Central Subfield Macular Thickness measurements in eyes with disease. The benefit may be most striking for diseases such as AMD and diabetic retinopathy which may have poor vision and poor fixation.
Keywords: imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • imaging/image analysis: clinical • retina