Validity of Automated Choroidal Segmentation in SS-OCT and SD-OCT

The choroid provides oxygen and nourishment to the outer retinal layers and is crucial for metabolic activity in the retina.1 Choroidal changes are associated with many eye diseases, such as age-related macular degeneration (AMD),2 age-related choroidal atrophy,3 central serous retinopathy,4 and choroiditis. It has been also reported that choroidal thickness increases during childhood and decreases during adulthood.5,6 Accurately and automatically measuring choroidal thickness is therefore of great interest. Spectral-domain optical coherence tomography (SD-OCT) provides a cross-sectional, three-dimensional (3D), microscale depiction of ocular tissues7 and clearly distinguishable retinal layers, as shown in Figure 1. However, without the use of enhanced depth imaging or image enhancement techniques, visualization of the choroid, including choroid–sclera junction, remains challenging (see Fig. 1). Due to the high backscatter by the retinal pigment epithelium layer (RPE), the intensity contrast in the choroid region can be insufficient for applying straightforward image analysis algorithms. Figure 1 In the standard clinically available SD-OCT scans, retinal layer structures are clear (red arrows), but the posterior choroidal boundary is difficult to distinguish (yellow arrow). At right, the surfaces from top to bottom are internal limiting membrane, ... Swept-source OCT (SS-OCT) allows increased scanning speed.8 In many SS-OCT prototype systems, a longer central wavelength (1060 vs. 840 nm in SD-OCT) is adopted to allow deeper penetration through the RPE. Consequently, the choroid–sclera boundary has higher contrast in SS-OCT (see Fig. 2). We and others have previously developed fully automated 3D algorithms for segmenting choroid on standard clinically available SD-OCT scans.9–14 In our approach, choroidal thickness was estimated by defining the Euclidian distance between the enveloping surfaces of a choroidal vasculature segmentation (see Fig. 3). Figure 2 Segmentation results from the previous method on clinically available SD-OCT image (Zeiss Cirrus; EDI mode was not used): (a) Original B-scan; (b) 3D choroidal vasculature segmentation; (c) the outer boundary of choroidal vasculature is estimated using ... Figure 3 Swept-source OCT and spectral-domain OCT show difference of intensity contrast around choroidal–scleral interface. An example of the difference of intensity contrast at the same location from the same eye in (a) SS-OCT image data and in (b) SD-OCT ... The purpose of this study was to develop and evaluate the validity of a fully automated 3D method capable of segmenting the choroid over the entire scan and quantifying choroidal thicknesses of the macula in both SS-OCT and SD-OCT image data of the same subjects, without a preceding vasculature segmentation step, so that choroidal thickness can be measured for each A-scan.