Erandi Chandrasekera1,2,3, Evan N Wong1,2, Danuta M Sampson1,2, David Alonso-Caneiro1,4, Fred K Chen1,2,5. 1. Centre for Ophthalmology and Visual Science, The University of Western Australia, Perth, Australia. 2. Ocular Tissue Engineering Laboratory, Lions Eye Institute, Perth, Australia. 3. Save Sight Institute, The University of Sydney, Sydney, Australia. 4. Contact Lens and Visual Optics Laboratory, Queensland University of Technology, Brisbane, Australia. 5. Department of Ophthalmology, Royal Perth Hospital, Perth, Australia.
Abstract
Purpose: To determine the influence of choroidal boundary morphology on the accuracy of automated measurements of subfoveal choroidal thickness (SFCT) in swept source optical coherence tomography (SSOCT). Methods: A retrospective image analysis of foveal-centered horizontal line scans from normal and diseased eyes using the Topcon DRI OCT-1 Atlantis SSOCT was conducted. Subfoveal choroid-scleral junction (CSJ) and retina-choroidal junction (RCJ) morphologies were graded by two observers. Automated SFCT (A-SFCT) was compared with manual SFCT (M-SFCT) measurements from Bruch's membrane to the posterior limits of choroidal vessel, hyperreflective stroma, and hyporeflective lamina fusca. Agreement in boundary grading was assessed by Cohen's kappa. A-SFCT and M-SFCT were compared using Bland-Altman analysis and paired t-tests. Results: A total of 200 eyes of 100 patients with a mean (SD) age of 62 (18) years were included. The choroidal vessel, stromal, and lamina fusca boundaries were visible in 100%, 58%, and 38% of the eyes, respectively. Interobserver agreement in RCJ and CSJ grading was high (kappa = 0.974 and 0.851). Mean A-SFCT differed from M-SFCT by only 2 μm at posterior choroidal vessel boundary (P = 0.801). A-SFCT overestimated SFCT at the posterior vessel wall boundary by 17 μm (P = 0.026) and 23 μm (P = 0.001) in the presence of a visible posterior choroidal stroma and lamina fusca, respectively. Conclusions: Automated outer choroidal boundary segmentation tends to identify the posterior limit of the choroidal vessel. Agreement between A-SFCT and M-SFCT is reduced by the presence of posterior stromal layer and lamina fusca. A-SFCT should be interpreted with RCJ and CSJ boundary grading.
Purpose: To determine the influence of choroidal boundary morphology on the accuracy of automated measurements of subfoveal choroidal thickness (SFCT) in swept source optical coherence tomography (SSOCT). Methods: A retrospective image analysis of foveal-centered horizontal line scans from normal and diseased eyes using the Topcon DRI OCT-1 Atlantis SSOCT was conducted. Subfoveal choroid-scleral junction (CSJ) and retina-choroidal junction (RCJ) morphologies were graded by two observers. Automated SFCT (A-SFCT) was compared with manual SFCT (M-SFCT) measurements from Bruch's membrane to the posterior limits of choroidal vessel, hyperreflective stroma, and hyporeflective lamina fusca. Agreement in boundary grading was assessed by Cohen's kappa. A-SFCT and M-SFCT were compared using Bland-Altman analysis and paired t-tests. Results: A total of 200 eyes of 100 patients with a mean (SD) age of 62 (18) years were included. The choroidal vessel, stromal, and lamina fusca boundaries were visible in 100%, 58%, and 38% of the eyes, respectively. Interobserver agreement in RCJ and CSJ grading was high (kappa = 0.974 and 0.851). Mean A-SFCT differed from M-SFCT by only 2 μm at posterior choroidal vessel boundary (P = 0.801). A-SFCT overestimated SFCT at the posterior vessel wall boundary by 17 μm (P = 0.026) and 23 μm (P = 0.001) in the presence of a visible posterior choroidal stroma and lamina fusca, respectively. Conclusions: Automated outer choroidal boundary segmentation tends to identify the posterior limit of the choroidal vessel. Agreement between A-SFCT and M-SFCT is reduced by the presence of posterior stromal layer and lamina fusca. A-SFCT should be interpreted with RCJ and CSJ boundary grading.
Authors: Jason Kugelman; David Alonso-Caneiro; Scott A Read; Jared Hamwood; Stephen J Vincent; Fred K Chen; Michael J Collins Journal: Sci Rep Date: 2019-09-16 Impact factor: 4.379