Abstract
Purpose: :
To characterize the geometry of the normal fovea using spectral-domain optical coherence tomography (SD-OCT). In particular direct measurements of the principal curvatures at the fovea center are obtained and analyzed.
Methods: :
A Spectral-domain Optical Coherence Tomography (Cirrus HD-OCT, from Carl Zeiss Meditec, Inc) system was used to obtain three-dimensional data sets covering a 6x6 mm region of the macula in normal subjects. Each eye was scanned using a 200x200 cube protocol. Custom-designed software was used to analyze the scans. Our software segments the inner limiting membrane (ILM), automatically locates the fovea and builds a very accurate parametric fitting of the foveal pit. This is used to generate measurements including principal curvatures and principal directions.
Results: :
One-hundred eyes of fifty normal volunteers were scanned as part of this study. The range of measured curvatures varied between 0.39 and 1.45. If k1 is the principal curvature at the foveal pit associated with a principal direction closer to the horizontal (roughly the axis between the optic disc and the fovea) than the vertical axis and k2 is the other principal curvature, we find that the curvature difference k2-k1 has a positive mean (0.22) and it is significantly different from zero (p<0.001). This means that the foveal curvature tends to be larger along the inferior-superior axis. The radius of mean curvature is defined as r=1/H, where H is the mean curvature. We obtain a mean value of 1.34 mm for r (range 0.81 to 2.36 mm). This values obtained by direct measurement compare well to the data available in the literature and derived from a reflectance technique. The distribution of the radius of mean curvature shows a significant positive correlation with age (R=0.33, p=0.02).
Conclusions: :
Using SD-OCT datasets it is possible to obtain very detailed information about the geometry of the foveal pit. A deeper understanding of the geometry of the normal fovea could be useful in building better normative databases.
Keywords: imaging/image analysis: clinical • macula/fovea • retina