Purpose: To evaluate the sensitivity and specificity for the detection of choroidal neovascularization (CNV) using automatically generated versus manually modified swept-source OCT angiography (SS-OCTA) en face images.
Design: Prospective cohort study.
Participants: Consecutive patients with various chorioretinal diseases and subretinal hyperreflective material (SHRM) or pigment epithelial detachments (PEDs) on OCT possibly corresponding to CNV in at least 1 eye.
Methods: A total of 102 eyes of 63 patients were included in this study. Fluorescein angiography (FA) and SS-OCTA imaging (PLEX Elite 9000, Carl Zeiss Meditec, Dublin, CA) were performed at the same day. OCTA en face images were generated using the "retina," "avascular," "choriocapillaris," and "outer retina to choriocapillaris (ORCC)" slabs automatically provided by the software. In addition, a custom slab was created by manual modification of the automatically provided boundary "retinal pigment epithelium fit" positioned at the level of Bruch's membrane and anterior to any SHRM or PED to ensure that a possible CNV was captured in its entirety. Two graders independently evaluated OCTA en face images for the presence of CNV masked to all other images of the patient.
Main Outcome Measures: Sensitivity and specificity for detection of CNV using FA as the reference.
Results: In 40% of cases (41/102), a CNV was detected on FA. Automatically provided OCTA en face slabs revealed the highest sensitivity for the "ORCC" slab (46.3%), followed by the "retina" slab (22.0%), "avascular" slab (17.1%), and "choriocapillaris" slab (14.6%). Specificity ranged between 93.4% for "ORCC" and 100% for the "retina" and "avascular" slabs. Sensitivity could be increased to 78.1% using the custom slab with a specificity of 88.5%. Concordance between FA and OCTA en face slabs was moderate for the "ORCC" slab (κ = 0.43; range, 0.41-0.60) and substantial for the custom slab (κ = 0.67; range, 0.61-0.80).
Conclusions: Segmentation artifacts and incomplete coverage of CNV on SS-OCTA en face images may impede identification of CNV. Manual modification of the position of automatically generated segmentation lines anterior and posterior to any suspected CNV (SHRM or PED) increases the sensitivity of CNV detection compared with automatically generated slabs.
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