Automated Analysis of Choroidal Sublayer Morphologic Features in Myopic Children Using EDI-OCT by Deep Learning

Purpose The purpose of this study was to analyze the choroidal sublayer morphologic features in emmetropic and myopic children using an automatic segmentation model, and to explore the relationship between choroidal sublayers and spherical equivalent refraction (SER). Methods We collected data on 92 healthy children (92 eyes) from the Ophthalmology Department of Peking University First Hospital. The data were allocated to three groups: emmetropia (+0.50 diopters [D] to -0.50 D), low myopia (-0.75 D to -3.00 D), and moderate myopia (-3.25 D to -5.75 D). We performed standardized optical coherence tomography (OCT) and developed a new segmentation technique to measure choroidal thickness (CT), large-vessel choroidal layer (LVCL), medium-vessel choroidal layer (MVCL), and small-vessel choroidal layer thickness (SVCL), and evaluated the choroidal vascular system (choroidal vascular volume [VV], choroidal vascular index [CVI], and choroidal vascular density [CVD]). Results All choroidal sublayers (LVCL, MVCL, and SVCL) were significantly thinner in myopic than in emmetropic eyes (P 0.050) and MVCL (with the exception being the temporal inner subfield, P = 0.011). Conclusions Thickness of choroidal sublayers was reduced with higher myopic SER, whereas changes in thickness ratio varied between sublayers. No significant correlations between CVI and SER suggested that both choroidal stromal and vascular volume decreases proportionately. Translational Relevance Automatic segmentation model will be helpful for future clinical trials to quantify choroidal sublayer morphologic features in myopia.