Purpose:
To measure the reproducibility of retinal thickness measurements from Cirrus Spectral Domain Optical Coherence Tomography (CirrusTM HD-OCT), and to determine if inter-visit or inter-instrument variability contribute significantly to overall variance.
Methods:
First, a single operator scanned one eye of fifteen (15) healthy subjects using the Cirrus HD-OCT (Carl Zeiss Meditec, Inc., Dublin, CA) Macula 200x200 scan. Subjects were imaged twice per system during a single visit on five systems. Instrument order was randomized for each subject. Then, the same operator scanned one eye of seventeen (17) healthy subjects using the Macula 200x200 scan and the Macula 512x128 scan three times per visit on three different visits. All scans for both phases were acquired within one week. Average retinal thickness measurements in nine subfields were calculated for both scan types. An analysis of variance (ANOVA) using a random effects model without interactions was performed and the calculated variance components were used to estimate the reproducibility of the measurement for each of the subfields for each scan type.
Results:
The inter-visit component was not statistically significant for any of the parameters for either scan type. The inter-instrument component was statistically significant for all parameters (P < 0.05) except the Inner Superior subfield (P = 0.056), but the component was small, contributing less than 1 µm2 to total variance in all cases. The intervisit repeatability standard deviation (SD) appeared similar for the two scan types. Reproducibility SD was calculated from the inter-system study by summing the inter-system and random variance components.
Conclusions:
We observed minimal inter-visit variability, and only a small inter-instrument variability in this study. The small overall non-subject variance corresponds to a high degree of reproducibility for all retinal subfields measured by the Cirrus HD-OCT.
Keywords: imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • macula/fovea • imaging/image analysis: clinical