title: AN AUTOMATIC, INTERCAPILLARY AREA-BASED ALGORITHM FOR QUANTIFYING DIABETES-RELATED CAPILLARY DROPOUT USING OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY.
abstract: OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: *Pattern Recognition Laboratory, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany; †Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts; ‡New England Eye Center, Tufts Medical Center, Boston, Massachusetts; and §Federal University of São Paulo, School of Medicine, São Paulo, Brazil.
authors.forename: Julia
authors.initials: J
authors.lastname: Schottenhamml
authors.forename: Eric M
authors.initials: EM
authors.lastname: Moult
authors.forename: Stefan
authors.initials: S
authors.lastname: Ploner
authors.forename: ByungKun
authors.initials: B
authors.lastname: Lee
authors.forename: Eduardo A
authors.initials: EA
authors.lastname: Novais
authors.forename: Emily
authors.initials: E
authors.lastname: Cole
authors.forename: Sabin
authors.initials: S
authors.lastname: Dang
authors.forename: Chen D
authors.initials: CD
authors.lastname: Lu
authors.forename: Lennart
authors.initials: L
authors.lastname: Husvogt
authors.forename: Nadia K
authors.initials: NK
authors.lastname: Waheed
authors.forename: Jay S
authors.initials: JS
authors.lastname: Duker
authors.forename: Joachim
authors.initials: J
authors.lastname: Hornegger
authors.forename: James G
authors.initials: JG
authors.lastname: Fujimoto
mesh_terms: D000465:Algorithms; D002196:Capillaries / Q000000981:diagnostic imaging*; D016022:Case-Control Studies; D003922:Diabetes Mellitus, Type 1 / Q000000981:diagnostic imaging*; D003924:Diabetes Mellitus, Type 2 / Q000000981:diagnostic imaging*; D003930:Diabetic Retinopathy / Q000000981:diagnostic imaging*; D006801:Humans; D012171:Retinal Vessels / Q000000981:diagnostic imaging*; D012189:Retrospective Studies; D041623:Tomography, Optical Coherence / Q000379:methods