Abstract
To determine age-related changes in choroidal thickness and the volume of choroidal vessels and stroma using automated algorithms based on structural swept-source OCT (SS-OCT) scans.
Prospective and observational study.
The study included 144 normal participants with ages ranging from 20 to 88 years.
A previously reported strategy was used to automatically segment the choroid using SS-OCT structural images. Attenuation correction was applied on B-scans to enhance the choroidal contrast and facilitate more accurate automatic segmentation of the 3-dimensional choroidal vessel and stroma. The parameters that we investigated included mean choroidal thickness (MCT), choroidal vessel volume (CVV), choroidal stroma volume (CSV), choroid vascularity index (CVI), and the choroidal stroma-to-vessel volume ratio (CSVR). Correlations between MCT and choroidal vessel metrics of CVV, CSV, CVI, and CSVR were studied. Regional distributions of MCT and CVI were analyzed using a grid centered on the fovea. Age-related changes in MCT, CVV, CSV, and CVI were studied in the entire scanning region, as well as in the subregions of the grids.
Age-related changes in MCT, CVV, CSV, and CVI using 6×6-mm and 12×12-mm SS-OCT scans.
The automated choroid segmentations were validated against manual segmentations, and MCT measurements were shown to be in good agreement (P < 0.0001). Choroidal vessel volume and CSV showed significant correlations with MCT (all P < 0.0001). Interestingly, CVI and CSVR were constant, with little variation among all participants regardless of age and MCT (61.1±1.8% and 0.64±0.05, respectively). Measurements on 12×12-mm and 6×6-mm scans showed excellent agreement in all scan regions (all P < 0.0001). While choroidal thickness and choroidal volume, which includes both choroidal vessels and stroma, decrease with age (all P < 0.0001), the CVI and CSVR vary little among all ages in all regions.
Whereas MCT, CVV, and CSV decrease with age, the CVI and CSVR remain constant in all regions with age. Ongoing studies are using these automated algorithms on SS-OCT structural datasets to investigate the diagnostic usefulness of these choroidal parameters in a myriad of ocular and systemic diseases.
