Automatic versus Manual Segmentation of Choroidal Neovascularization Lesions Using Optical Coherence Tomography

Abstract

Purpose: To measure and quantify choroidal neovascularization (CNV) lesion size in classic lesions visualized on Spectral Domain-Optical Coherence Tomography (SD-OCT) using automated segmentation analysis and confirm whether further refinement improves the accuracy of disease regression after loading dose Anti-VEGF injections.Methodology: A retrospective study of 10 macular degeneration patients diagnosed with CNV. Blinded observers, trained to detect changes on OCT, delineated boundaries of CNV lesions using SD-OCT (Topcon 2000) with automated software and then modified segmentation manually before and after loading dose Ranbizumab injections. Automated measurements were then compared to manual segmentation values. Statistical analysis was performed, taking into account inter-observer variability.Results: Automatic and manual segmentation measurements are similar in 1) retinal area and fovea center values both pre-and post-injection; and 2) retinal volume post-injection. Retinal volume pre-injection is 1) similar between the two blinded observers; 2) varies between automatic measurements and observers in some patients; and 3) underestimated for all patients in the automatic measurements. Overall, automatic segmentation detects a general reduction in CNV lesion size following loading dose injections.Conclusion: SD-OCT automated segmentation software detects CNV lesions and reports size reduction after the third anti-VEGF injection. SD-OCT automatic segmentation using Topcon segmentation analysis in this small cohort is an accurate diagnostic tool to measure CNV surface area and volume as a biomarker of CNV regression.