Subjects

Thirty healthy subjects were recruited from among university employees and their families at the Shiley Eye Center, University of California, San Diego. Subjects with current ocular disease, previous ocular surgery, myopia of more than 5 diopters, or hyperopia of more than 3 diopters were excluded. All subjects had normal visual field testing results (using Statpac II, Swedish interactive thresholding algorithm 24-2, Zeiss-Humphrey Field Analyzer; Carl Zeiss Meditec, Inc, Dublin, California, USA), an IOP of 21 mmHg or less on Goldmann applanation tonometry, and no clinical signs of eye disease on slit-lamp anterior segment and fundus examination.

Swept-Source Optical Coherence Tomography

Images of the optic disc and the macular region were obtained using a prototype SS OCT system (Topcon, Inc, Tokyo, Japan). The SS OCT has an acquisition rate of 100,000 A-scans per second operated at the 1-μm wavelength region. This instrument uses a wavelength-sweeping laser with a tuning range of approximately 100 nm as light source and has a center wavelength of 1050 nm, yielding an 8-μm axial resolution in tissue. These features allow penetration of deeper tissue through the retinal pigment epithelium into the choroid. The device has been described in more detail elsewhere.

Four different scan protocols were used for evaluation of choroidal thickness. First, a 3-dimensional (3D) imaging data set was acquired with a 6 × 6-mm raster scan centered on the optic disc (optic disc protocol) composed of 256 B-scans, each consisting of 256 A-scans (total, 65,536 axial scans/volume) with an acquisition time of approximately 0.66 seconds. The resulting scan provides a 3D image of the optic disc and surrounding area. Second, the same 3D imaging data set was obtained covering an area of 6 × 6-mm centered on the fovea (macula protocol). Third, a radial scan protocol centered on the optic disc (12 lines, each composed of 32 B-scans, with each B-scan composed of 1024 A-scans) with an acquisition time of 4 seconds was obtained ( Supplemental Figure 1 , available at AJO.com ). Fourth, a 12-mm horizontal line scan protocol, centered between the optic disc and the fovea and composed of 1024 A-scans for each of 96 B-scans, was obtained (acquisition time, 1 second; Supplemental Figure 2 , available at AJO.com ).

All scan protocols were acquired in the described order. Each scan protocol was repeated 3 times consecutively on the same visit. Participant and device were repositioned after each scan. The choroidal reference position was used for all scans. The centering of scans was achieved by internal fixation and confirmed by a fundus camera integrated in the instrument. Two experienced examiners (A.J.T., N.M.) scanned all participants. Measurements of both eyes of each study participant were obtained through undilated pupils. To be included in the analysis, all images had to have an image quality score of 45 (of 160) or more, according to manufacturer recommendation. The detailed image quality calculation is generated by a proprietary algorithm that produces an image quality score in the range of 0 to 160, which corresponds to an estimate of the signal-to-noise ratio specifically for the retinal signal. A score of 160 indicates that the all-retinal signal is of greater intensity than the estimated background, whereas a score of 0 indicates that the all-retinal signal is indistinguishable from the estimated background signal. In a 3D scan, only a single score is assigned, representing the average of all individual frames’ image quality scores.

Classification of Artifacts

The following sources of artifacts were defined: motion artifact, signal loss resulting from blinking, and segmentation failure. Quality assurance checks were carried out at the conclusion of the study by an independent grader not involved in the image acquisition process. The number of scans with an artifact, the type of the artifact, and whether the artifact affected the calculated retinal and choroidal measurements were recorded.

Motion artifacts were defined as displacement of major retinal vessels by more than 1 vessel diameter ( Figure 1 ). Scans with blink-related signal losses were excluded automatically from the averaging process for the line scan and radial scan protocols. Information on the averaging success is available during image acquisition. In the present study, only images with a minimum 50% averaging success were considered good quality and were saved during acquisition. The used averaging technique relies on correlation statistics to determine whether to accept a newly registered image into the composite average image. A registration operation that results in a relatively low interimage correlation is rejected, and those poorly matched image frames are not accepted into the final composite average. The displayed success rate information serves as an indication of the number of the number of frames that were included in the final composite average image. With the 3D scan protocols, blink-related signal loss is not readily visible during image acquisition ( Figure 2 ). Therefore, postacquisition quality controls were performed, and scans with a signal loss of more than 10% (by manual measurement) of the scan area were excluded from the analysis. Failure of a segmentation line was defined when corroboration with visual inspection differed in more than 25% of the 2D scan area (3D scan protocol), in more than 25% of the scan area in more than 25% of scan lines (eg, fewer than 3 lines, radial scan protocol), and in more than 25% of the line area (line scan protocol; Figure 3 ). These cutoffs were chosen arbitrarily; however, other investigators have used similar cutoffs (eg, 85% concordance between manual and automated identification of posterior surface). Post hoc analysis was conducted to evaluate whether reproducibility results changed significantly when all scans with the presence of blink artifacts (including less than 10%) were excluded.

Retinal and choroidal thickness by swept-source optical coherence tomography: demonstration of blink artifact with the 3-dimensional (3D) macula scan protocol. (Top left) Fundus image demonstrating area of the 3D scan (green square). The blackened area in the superior part of the image corresponds to signal loss resulting from blinking. The green line indicates the area of the B-scan. (Top center) Corresponding B-scan. Note the continued use of retinal and choroidal segmentation lines despite absence of signal. (Bottom left) Fundus image demonstrating position of measurement outside the area of signal loss (green line). (Bottom center) Corresponding B-scan with correct segmentation of choroidal boundaries and outer retinal layers. (Right) Resulting 3D macula tomograph illustrating continued application of segmentation lines despite absence of signal in the superior macular region. In the intact inferior region, accurate segmentation of choroidal borders can be visualized (color lines).

Example of a swept-source optical coherence tomography scan demonstrating segmentation failure on a 12-mm horizontal line scan. (Top left) Fundus image demonstrating area and orientation of the line scan (green line, temporal scan direction). (Top right) Outer choroid misidentification: in approximately 50% of the scan area, the segmentation line does not follow the retinal pigment epithelium (RPE) with subsequent displacement of chorioscleral interface (CSI) segmentation (indicated by dashed line). (Bottom left) Fundus image from repeat scan obtained at the same location (green line, temporal scan direction). (Bottom right) Correct identification of RPE and CSI.

Demonstration of segmentation failure on a 12-line radial scan protocol using swept-source optical coherence tomography (SS OCT). (Top left) Fundus image demonstrating plane and orientation of the line scan (green line). (Top right) The SS OCT software failed to recognize a less well-demarcated posterior choroidal surface and instead identified the posterior scleral interface as chorioscleral interface (CSI) in approximately 75% of the scan area. (Bottom left) Fundus image of the adjacent clock hour scan of the same eye. (Bottom right) The CSI was identified correctly by the segmentation software.

Choroidal and Retinal Thickness Measurement

Segmentation data were produced using the SS OCT segmentation software (version 1.43) and exported using the manufacturer’s OCT batch (version 4.3.0.118) utility. The resulting data files consisted of the boundary depth information for 9 layers for each A-scan, with the values for each B-scan in a separate file. A script was developed that combined the B-scans of each examination into a single thickness file—converted from pixel space to micrometers—and, using the boundary depth of the first layer, computed the depth thicknesses of each subsequent layer for each B-scan. The thickness information then was processed using MATLAB (version 2012a; MathWorks, Inc, Natick, Massachusetts, USA) to compute the average thickness for each B-scan. Additionally, for each radial scan, the average thickness over all 12 B-scans was calculated for each layer. For each 3D scan, the average thickness and the total volume over the entire scan area was calculated for each layer. The SS OCT segmentation software outputs 0 for the boundary depths when scanning over the optic disc. We used this information to exclude the optic disc region in the average thickness calculations. Automated measurements of choroidal thickness and choroidal volume thus were obtained for all subjects. Supplemental Figure 3 (available at AJO.com ) demonstrates segmentation of retina and choroid at the optic disc.

Statistical Analysis

Data are presented as means and standard deviations. The repeatability within each scan protocol was assessed using 3 repeated measurements. Interscan repeatability was evaluated by computing intraclass correlation coefficients (ICC) and 95% confidence intervals. Because measurements from both eyes of the same subject are likely to correlate, statistical methods are required that account for the fact that both eyes of an individual were included in the analysis. For this purpose, we used generalized estimating equations with robust standard errors (Huber-White sandwich variance estimator) to adjust for potential correlations. All tests were 2-sided, and a P value of less than .05 was considered statistically significant. All statistical analyses were performed with commercially available software (Stata version 10.0; StataCorp, College Station, Texas, USA).