Semiautomated segmentation of the choroid in spectral-domain optical coherence tomography volume scans

Changes in the choroid, in particular its thickness, are believed to be of importance in the pathophysiology of a number of retinal diseases. The purpose of this study was to adapt the graph search algorithm to semiautomatically identify the choroidal layer in spectral-domain optical coherence tomography (SD-OCT) volume scans and compare its performance to manual delineation.

A graph-based multistage segmentation approach was used to identify the choroid, defined as the layer between the outer border of the RPE band and the choroid-sclera junction. Thirty randomly chosen macular SD-OCT (1024 × 37 × 496 voxels, Heidelberg Spectralis) volumes were obtained from 20 healthy subjects and 10 subjects with non-neovascular AMD. The positions of the choroidal borders and resultant thickness were compared with consensus manual delineation performed by two graders. For consistency of the statistical analysis, the left eyes were horizontally flipped in the x-direction.

The algorithm-defined position of the outer RPE border and choroid-sclera junction was consistent with the manual delineation, resulting in highly correlated choroidal thickness values with r = 0.91 to 0.93 for the healthy subjects and 0.94 for patients with non-neovascular AMD. Across all cases, the mean and absolute differences between the algorithm and manual segmentation for the outer RPE boundary was -0.74 ± 3.27 μm and 3.15 ± 3.07 μm; and for the choroid-sclera junction was -3.90 ± 15.93 μm and 21.39 ± 10.71 μm.

Excellent agreement was observed between the algorithm and manual choroidal segmentation in both normal eyes and those with non-neovascular AMD. The choroid was thinner in AMD eyes. Semiautomated choroidal thickness calculation may be useful for large-scale quantitative studies of the choroid.