Purchase this article with an account.
Arezoo Miraftabi, Navid Amini, Jeff Gornbein, Sharon Henry, Pablo Romero, Anne L. Coleman, Joseph Caprioli, Kouros Nouri-Mahdavi; Local Variability of Macular Thickness Measurements With SD-OCT and Influencing Factors. Trans. Vis. Sci. Tech. 2016;5(4):5. doi: https://doi.org/10.1167/tvst.5.4.5.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
To compare the intrasession variability of spectral-domain optical coherence tomography (SD-OCT)-derived local macular thickness measures and explore influencing factors.
One hundred two glaucomatous eyes (102 patients) and 21 healthy eyes (21 subjects) with three good quality macular images during the same session were enrolled. Thickness measurements were calculated for 3° superpixels for the inner plexiform (IPL), ganglion cell (GCL), or retinal nerve fiber layers (mRNFL), GC/IPL, ganglion cell complex, and full macular thickness. Spatial distribution and magnitude of measurement errors (ME; differences between the 3 individual superpixel values and their mean) and association between MEs and thickness, age, axial length, and image quality were explored.
MEs had a normal distribution with mostly random noise along with a small fraction of outliers (1.2%–6.6%; highest variability in mRNFL and on the nasal border) based on M-estimation. Boundaries of 95% prediction intervals for variability reached a maximum of 3 μm for all layers and diagnostic groups after exclusion of outliers. Correlation between proportion of outliers and thickness measures varied among various parameters. Age, axial length, or image quality did not influence MEs (P > 0.05 for both groups).
Local variability of macular SD-OCT measurements is low and uniform across the macula. The relationship between superpixel thickness and outlier proportion varied as a function of the parameter of interest.
Given the low and uniform variability within and across eyes, definition of an individualized ‘variability space' seems unnecessary. The variability measurements from this study could be used for designing algorithms for detection of glaucoma progression.
This PDF is available to Subscribers Only