Beyond tessellation: AI-derived choroidal vessel density on multi-channel cSLO as a surrogate biomarker for OCT choroidal parameters.

Authors

Yuou Yao, Xi Wang, Tengfei Long, Chaohong Li, Saiguang Ling, Enzhong Jin, Yaoyao Sun, Shirong Su, Jianyu Xiong, Jiyang Tang, Xiang Meng, Yi Cai, Qiaozhu Zeng, Heng Li, Heng Miao

Published in

Frontiers in medicine. Volume 13. Pages 1884151. Epub Oct 07, 2026.

Abstract

To develop an AI-based method for quantifying choroidal vessel density (CVD) from ultra-widefield confocal scanning laser ophthalmoscopy (UWF-cSLO) and to validate this metric against swept-source optical coherence tomography (SS-OCT) choroidal parameters.
In this retrospective cross-sectional study, 633 eyes from 354 participants underwent simultaneous UWF-cSLO and SS-OCT imaging on an integrated platform, ensuring precise spatial co-registration. A TransUNet deep-learning model segmented choroidal vessels from red-channel (R; 665 nm) and infrared-channel (IR; 785 nm) images, yielding channel-specific metrics (R-CVD and IR-CVD) and a combined metric (IR + R CVD). Eight SS-OCT parameters-including choroidal thickness (CT), choroidal vascularity index (CVI), luminal area, stromal area (SA), total choroidal area (TCA), and vessel volume index (VVI)-served as reference measures. Associations were evaluated using Spearman correlations with participant-level clustered bootstrap confidence intervals, multivariable generalised estimating equations (GEE) adjusted for age and sex, and receiver operating characteristic (ROC) analysis.
Segmentation accuracy exceeded 0.95 (Dice coefficient) in both channels. R-CVD exhibited the strongest inverse correlations with structural and volumetric OCT parameters (SA: ρ = -0.619; CT: ρ = -0.615; TCA: ρ = -0.615; all q < 0.001), whereas IR + R CVD correlated most closely with proportion-based indices (VVI: ρ = -0.34; CVI: ρ = -0.29). These channel-dependent patterns persisted after adjustment for age and sex in multivariable GEE models. On ROC analysis, R-CVD discriminated thin from thick choroids with an area under the curve (AUC) of 0.789 (sensitivity 72.5%; specificity 74.8%), whereas IR-CVD alone showed near-chance performance (AUC 0.517).
AI-derived CVD from UWF-cSLO correlates strongly with SS-OCT choroidal parameters in a wavelength-dependent manner and may serve as an accessible surrogate for choroidal structural assessment in settings without OCT.

PMID:
42909305
Bibliographic data and abstract were imported from PubMed on 23 Oct 2026.

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