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Minhaj Alam, Jennifer I. Lim, Devrim Toslak, Xincheng Yao; Differential Artery–Vein Analysis Improves the Performance of OCTA Staging of Sickle Cell Retinopathy. Trans. Vis. Sci. Tech. 2019;8(2):3. doi: https://doi.org/10.1167/tvst.8.2.3.
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We test if differential artery–vein analysis can increase the performance of optical coherence tomography angiography (OCTA) detection and classification of sickle cell retinopathy (SCR).
This observational case series was conducted in a tertiary-retina practice. Color fundus and OCTA images were collected from 20 control and 48 SCR subjects. Fundus data were collected from fundus imaging devices, and SD-OCT and corresponding OCTA data were acquired using a spectral-domain OCT (SD-OCT) angiography system. For each patient, color fundus image-guided artery–vein classification was conducted in the OCTA image. Traditional mean blood vessel tortuosity (m-BVT) and mean blood vessel caliber (m-BVC) in OCTA images were quantified for control and SCR groups. Artery BVC (a-BVC), vein BVC (v-BVC), artery BVT (a-BVT), and vein BVT (v-BVT) were calculated; and then the artery–vein ratio of BVC (AVR–BVC) and artery–vein ratio of BVT (AVR–BVT) were quantified for comparative analysis.
We evaluated 40 control and 85 SCR images in this study. The color fundus image-guided artery–vein classification had 97.02% accuracy for differentiating arteries and veins in OCTA. Differential artery–vein analysis provided significant improvement (P < 0.05) in detecting and classifying SCR stages compared to traditional mean blood vessel analysis. AVR–BVT and AVR–BVC showed significant (P < 0.001) correlation with SCR severity.
Differential artery–vein analysis can significantly improve the performance of OCTA detection and classification of SCR. AVR–BVT is the most sensitive feature that can classify control and mild SCR.
SCR and other retinovascular diseases result in changes to the caliber and tortuosity appearance of arteries and veins separately. Differential artery–vein analysis can improve the performance of SCR detection and stage classification.
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