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Validation of Macular Choroidal Thickness Measurements from Automated SD-OCT Image Segmentation

Twa, Michael D.; Schulle, Krystal L.; Chiu, Stephanie J.; Farsiu, Sina; Berntsen, David A.

doi: 10.1097/OPX.0000000000000985

Purpose Spectral domain optical coherence tomography (SD-OCT) imaging permits in vivo visualization of the choroid with micron-level resolution over wide areas and is of interest for studies of ocular growth and myopia control. We evaluated the speed, repeatability, and accuracy of a new image segmentation method to quantify choroid thickness compared to manual segmentation.

Methods Two macular volumetric scans (25 × 30°) were taken from 30 eyes of 30 young adult subjects in two sessions, 1 hour apart. A single rater manually delineated choroid thickness as the distance between Bruch’s membrane and sclera across three B-scans (foveal, inferior, and superior-most scan locations). Manual segmentation was compared to an automated method based on graph theory, dynamic programming, and wavelet-based texture analysis. Segmentation performance comparisons included processing speed, choroid thickness measurements across the foveal horizontal midline, and measurement repeatability (95% limits of agreement (LoA)).

Results Subjects were healthy young adults (n = 30; 24 ± 2 years; mean ± SD; 63% female) with spherical equivalent refractive error of −3.46 ± 2.69D (range: +2.62 to −8.50D). Manual segmentation took 200 times longer than automated segmentation (780 vs. 4 seconds). Mean choroid thickness at the foveal center was 263 ± 24 μm (manual) and 259 ± 23 μm (automated), and this difference was not significant (p = 0.10). Regional segmentation errors across the foveal horizontal midline (±15°) were ≤9 μm (median) except for nasal-most regions closest to the nasal peripapillary margin—15 degrees (19 μm) and 12 degrees (16 μm) from the foveal center. Repeatability of choroidal thickness measurements had similar repeatability between segmentation methods (manual LoA: ±15 μm; automated LoA: ±14 μm).

Conclusions Automated segmentation of SD-OCT data by graph theory and dynamic programming is a fast, accurate, and reliable method to delineate the choroid. This approach will facilitate longitudinal studies evaluating changes in choroid thickness in response to novel optical corrections and in ocular disease.




School of Optometry (MDT), Department of Biomedical Engineering (MDT), University of Alabama at Birmingham, Birmingham, Alabama; College of Optometry, University of Houston, Houston, Texas (KLS, DAB); Department of Biomedical Engineering, Duke University, Durham, North Carolina (SJC, SF); and Department of Ophthalmology, Duke University Medical Center, Durham, North Carolina (SF).

Michael Twa School of Optometry The University of Alabama at Birmingham HPB 515, 1716 University Blvd Birmingham, AL 35294-0010 e-mail:

© 2016 American Academy of Optometry