An automatic, intercapillary area based algorithm for quantifying diabetes related capillary dropout using OCT angiography
Name
nihms806453.pdf
Description
Accepted version
Size
1.32 MB
Format
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Author(s)
Schottenhamml, Julia Jennifer
Moult, Eric Michael
Ploner, Stefan B
Lee, ByungKun
Lu, Chen David
Fujimoto, James G
Date Issued
December 2016
Journal
Retina
Publisher
Ovid Technologies (Wolters Kluwer Health)
Citation
Schottenhamml, Julia et al. "An Automatic, Intercapillary Area-Based Algorithm for Quantifying Diabetes-Related Capillary Dropout Using Optical Coherence Tomography Angiography." Retina 36 (December 2016): S93-S101 © 2017 The Author(s)
Version
Author's final manuscript
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 areabased metric in patients having various stages of diabetic retinopathy. Intercapillary areabased approaches are likely more sensitive to early stage capillary dropout than vascular density-based methods.
MIT Department
Massachusetts Institute of Technology. Research Laboratory of Electronics
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1097/IAE.0000000000001288
