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M. K. Garvin, M. Sonka, R. H. Kardon, X. Wu, Y. H. Kwon, S. R. Russell, M. D. Abramoff; Three-Dimensional Analysis of SD OCT: Thickness Assessment of Six Macular Layers in Normal Subjects. Invest. Ophthalmol. Vis. Sci. 2008;49(13):1879.
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© ARVO (1962-2015); The Authors (2016-present)
Develop a method for 3-D segmentation of multiple retinal layers from macular spectral OCT data. Perform a pilot analysis of localized thickness and thickness variability of six layers of the macula in normal subjects.
15 macula-centered 3-D OCT volumes (200×200×1024 voxels, 6×6×2 mm3) were obtained from the right eye of 15 normal subjects (mean age of 39.4 ± 8.2 years) using a CirrusTM HD-OCT machine (Carl Zeiss Meditec, Inc., Dublin, CA). Seven surfaces were automatically segmented in 3-D using an extended version of our previously reported algorithm (Haeker et al., IPMI 2007: 207-218) corresponding to roughly the following six anatomical layers: 1) retinal nerve fiber layer (RNFL), 2) ganglion cell layer + inner plexiform layer (GCL+IPL), 3) inner nuclear layer (INL), 4) outer plexiform layer (OPL), 5) outer nuclear layer + the photoreceptor inner segments (ONL+IS), and 6) the photoreceptor outer segments (OS). For each location in the en-face plane, the mean and standard deviation of the thickness of each layer were computed. Observed nasal-temporal regional differences of selected surfaces were tested for statistical significance using a paired t-test (p < 0.05 considered significant).
The included figure summarizes the resulting thickness and thickness variability values (displayed as color-coded maps). The standard deviation of the localized thickness averaged 8.1 µm. As expected, the nasal side of the RNFL was significantly thicker than the temporal side (mean difference of 26.2 µm, p < 0.001). However, other layers showed differences as well. For example, the ONL+IS was significantly thicker temporally (mean difference of 2.6 µm, p = 0.003).
With an average overall thickness variability of less than 10 µm, these preliminary results indicate good reproducibility across individuals. Furthermore, such an approach allows for a more localized quantification of properties of interest than available with time-domain OCT.
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