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Dean A VanNasdale, Amanda Eilerman; Radial symmetry of the foveal pit curvature assessed with optical coherence tomography. Invest. Ophthalmol. Vis. Sci. 2016;57(12):4243.
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© ARVO (1962-2015); The Authors (2016-present)
To acquire cross sectional optical coherence tomography (OCT) images of the fovea and measure foveal pit curvature using custom curve fitting software. To compare the radius of curvature along different meridians centered on the foveal pit as a metric of foveal pit symmetry.
10 cinically normal subjects were imaged using spectral domain OCT (Heidelberg Engineering, Carlsbad, CA). Radial scans centered on the fovea were acquired in the right eye, with the horizontal and vertical scans used for analysis. Raw images were exported and the retinal surface was manually segmented in Photoshop (Adobe, San Jose, CA). The segmented images were imported into custom curve fitting software (Matlab, Mathworks, Natick, MA) used to determine the radius of curvature of the foveal pit based on the best fitting circle aligned to the central 500 microns of the foveal pit in both meridians. The radius of curvature was compared between the two meridians using a paired t-test to assess for symmetry of the foveal pit.
A circle fit to 500 microns of the central fovea provided a good representation of the foveal pit curvature in all 10 normal subjects. In 7 of the 10 subjects, the horizonatal meridian was flatter than the vertical meridian. The average radius of curvature was 1151 and 913 microns in the horizontal and vertical meridian, respectively. There was no statistically significant difference in radius of curvature between the two meridians (p=0.14).
Curve fitting allows for quantifiable characterization of the foveal pit. In this small sample of clinically normal subjects, the foveal pit curvature was found to be symmetric between the horizontal and vertical meridians. Curve fitting of the central fovea could be useful in assessing subjects with diseases that have asymmetric affects on the macular region.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.
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