AN AUTOMATIC, INTERCAPILLARY AREA-BASED ALGORITHM FOR QUANTIFYING DIABETES-RELATED CAPILLARY DROPOUT USING OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY. (December 2016)

• Record Type: Journal Article
• Authors: Schottenhamml, Julia; Moult, Eric M.; Ploner, Stefan; Lee, ByungKun; Novais, Eduardo A.; Cole, Emily; Dang, Sabin; Lu, Chen D.; Husvogt, Lennart; Waheed, Nadia K.; Duker, Jay S.; Hornegger, Joachim; Fujimoto, James G.
• Is Part Of: Retina. Volume 36(2016)Supplement 1
• Publication Date: 2016-12
• Subjects: diabetic retinopathy -- intercapillary area -- capillary dropout -- optical coherence tomography -- optical coherence tomography angiography; Retina -- Diseases -- Periodicals; Retinal Diseases; Vitreous Body; 617.735
• DOI: 10.1097/IAE.0000000000001288
• Languages: English
• ISSNs: 0275-004X

Abstract

Abstract : Purpose: To develop a robust, sensitive, and fully automatic algorithm to quantify diabetes-related capillary dropout using optical coherence tomography (OCT) angiography (OCTA). Methods: A 1, 050-nm wavelength, 400 kHz A-scan rate swept-source optical coherence tomography prototype was used to perform volumetric optical coherence tomography angiography imaging over 3 mm × 3 mm fields in normal controls (n = 5), patients with diabetes without diabetic retinopathy (DR) (n = 7), patients with nonproliferative diabetic retinopathy (NPDR) (n = 9), and patients with proliferative diabetic retinopathy (PDR) (n = 5); for each patient, one eye was imaged. A fully automatic algorithm to quantify intercapillary areas was developed. Results: Of the 26 evaluated eyes, the segmentation was successful in 22 eyes (85%). The mean values of the 10 and 20 largest intercapillary areas, either including or excluding the foveal avascular zone, showed a consistent trend of increasing size from normal control eyes, to eyes with diabetic retinopathy but without diabetic retinopathy, to nonproliferative diabetic retinopathy eyes, and finally to PDR eyes. Conclusion: Optical coherence tomography angiography-based screening and monitoring of patients with diabetic retinopathy is critically dependent on automated vessel analysis. The algorithm presented was able to automatically extract an intercapillary area-based metric in patients having various stages of diabetic retinopathy. Intercapillary area-based approaches are likely more sensitive to early stage capillary dropout than vascular density-based methods. Abstract : The authors present an automatic, area-based algorithm for quantifying diabetes-related capillary dropout using OCT angiography.