Three-Dimensional Choroidal Vessels Assessment in Fellow Eyes of Patients With Central Serous Chorioretinopathy

To evaluate choroidal vasculature using a novel three-dimensional algorithm in fellow eyes of patients with unilateral chronic central serous chorioretinopathy (cCSC).

Patients with unilateral cCSC were retrospectively included. Automated choroidal segmentation was conducted using a deep-learning ResUNet model. Phansalkar thresholding was applied to binarize choroidal vasculature, and three-dimensional maps were created. Mean choroidal vessel diameter, intervessel distance, choroidal thickness, and choroidal vascularity index (CVI) were measured. Linear mixed models were used for statistical analysis.

Thirty unilateral cCSC eyes, 22 fellow, and 26 controls were included. Both cCSC and fellow eyes exhibited significant higher mean choroidal vessel diameter compared with controls (362.50 ± 83.23 µm, 276.84 ± 26.89 µm, and 233.28 ± 28.18 µm, respectively; P < 0.001), and in choroidal thickness (288.90 ± 64.77 µm, 269.76 ± 71.17 µm, and 223.97 ± 43.40 µm, respectively; P = 0.001). The intervessel distance was reduced in cCSC and fellow eyes compared with controls (196.53 ± 23.58 µm, 225.05 ± 33.72 µm, and 264.13 ± 46.06 µm, respectively; P < 0.001). Although lower, the CVI was not significantly different in cCSC and fellow eyes compared with controls (38.14 ± 5.55%, 37.23 ± 6.41%, and 40.65 ± 3.53%, respectively; P = 0.066), indicating a possible trend toward a lower CVI.

Three-dimensional representation of choroidal vasculature revealed significant changes in both cCSC and fellow eyes, including a larger diameter and reduced spacing compared with healthy controls.

Using a validated deep learning-based three-dimensional method, we observed changes in the choroidal vasculature in both CSC and fellow eyes.