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IMPACT OF OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY REVIEW STRATEGY ON DETECTION OF CHOROIDAL NEOVASCULARIZATION

Babiuch, Amy S. MD*,†; Uchida, Atsuro MD PhD; Figueiredo, Natalia MD; Hu, Ming PhD†,‡; Khan, Mehnaz MD*; Srivastava, Sunil K. MD*,†; Singh, Rishi P. MD*; Rachitskaya, Aleksandra MD*; Kaiser, Peter K. MD*; Reese, Jamie L. BSN; Ehlers, Justis P. MD*,†

doi: 10.1097/IAE.0000000000002443
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Purpose: To compare optical coherence tomography angiography (OCTA) review strategies for optimizing choroidal neovascularization (CNV) detection.

Methods: Eyes with CNV in the differential diagnosis were imaged with the Avanti RTVue XR HD (Optovue, Fremont, CA). Three modalities of review for CNV presence were used in each case: a single report generated using automated segmentation within Avanti software; a continuous slab descent video OCTA export; and a manual segmentation approach using cross-sectional OCT with decorrelation signal overlay. Scans were reviewed by two masked expert reviewers; a third reviewer was used for discrepancies.

Results: The study included 421 eyes, and 350 eyes had reports deemed sufficient quality for interpretation. Choroidal neovascularization was in the differential diagnosis in 107 of 350 patients. Overall CNV was identified in 55% (59/107) eyes. In those eyes with CNV, the automated segmentation identified CNV in 56% (33/59) of cases, continuous slab descent method identified CNV in 53% (31/59) of cases, and the manual segmentation group identified CNV in 92% (54/59) of cases.

Conclusion: Review strategies for detection of CNV on OCTA were highest using the manual segmentation method as compared to both the automated report and continuous slab descent methods. Although the manual segmentation method had a higher rate of detection, the practical aspects of the time required for segmentation make this method challenging in routine clinical practice.

Review strategies for detection of choroidal neovascularization on optical coherence tomography angiography reveal vast differences in overall rates of identification. Detection of CNV was significantly higher using the manual segmentation with decorrelation overlay method as compared to both the automated report and continuous slab descent methods.

*Vitreoretinal Service, Cleveland Clinic Foundation, Cole Eye Institute, Cleveland, Ohio;

The Tony and Leona Campane Center for Excellence in Image-guided Surgery and Advanced Imaging Research, Cleveland Clinic Foundation, Cole Eye Institute, Cleveland, Ohio; and

Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Lerner Research Institute, Cleveland, Ohio.

Reprint requests: Justis P. Ehlers, Norman C and Donna L. Harbert Endowed Chair for Ophthalmic Research, Cleveland Clinic Foundation, Cole Eye Institute, 9500 Euclid Avenue/i32, Cleveland, OH 44195; e-mail: ehlersj@ccf.org

Unrestricted travel grant from Alcon Novartis Hida Memorial Award 2015 funded by Alcon Japan Ltd (A.U.); NIH/NEI K23-EY022947-01A1 (J.P.E.); Ohio Department of Development TECH-13-059 (J.P.E., S.K.S.); Research to Prevent Blindness (Cole Eye Institutional Grant).

A. S. Babiuch: Allergan (R), Johnson & Johnson (R). S. K. Srivastava: Allergan (R), Bausch and Lomb (C), Bioptigen (P), Zeiss (C), Leica (C), Santen (C), Synergetics (P). R. P. Singh: Zeiss (C), Genentech (C), Regeneron (C), Thrombogenics (C), Alcon (C). J. P. Ehlers: Bioptigen/Leica (P, C), Zeiss (C), Thrombogenics (C, R); Regeneron (R), Genentech (C, R), Santen (C), Novartis (C), Aerpio (C, R), Boerhinger-Ingelheim (R), Allergan (C), Alcon (C, R), and Roche (C). The remaining authors have no conflicting interests to disclose.

© 2019 by Ophthalmic Communications Society, Inc.