September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Quantification of retinal microvascular changes in diabetic retinopathy using spectral domain optical coherence tomography angiography (SD-OCTA)
Author Affiliations & Notes
  • Alice Yon Kim
    Ophthalmology, University of Southern California Eye Institute, Los Angeles, California, United States
  • Zhongdi Chu
    Bioengineering and Ophthalmology, University of Washington, Seattle, Washington, United States
  • Anoush Shahidzadeh
    Ophthalmology, University of Southern California Eye Institute, Los Angeles, California, United States
  • Ruikang K Wang
    Bioengineering and Ophthalmology, University of Washington, Seattle, Washington, United States
  • Carmen A Puliafito
    Ophthalmology, University of Southern California Eye Institute, Los Angeles, California, United States
  • Amir H Kashani
    Ophthalmology, University of Southern California Eye Institute, Los Angeles, California, United States
  • Footnotes
    Commercial Relationships   Alice Kim, Carl Zeiss Meditec, Inc. (F); Zhongdi Chu, Carl Zeiss Meditec, Inc. (F); Anoush Shahidzadeh, Carl Zeiss Meditec, Inc. (F); Ruikang Wang, Carl Zeiss Meditec, Inc. (F), Carl Zeiss Meditec, Inc. (C), Carl Zeiss Meditec, Inc. (R), Carl Zeiss Meditec, Inc. (P); Carmen Puliafito, Carl Zeiss Meditec, Inc. (F); Amir Kashani, Carl Zeiss Meditec, Inc. (F), Carl Zeiss Meditec, Inc. (C), Carl Zeiss Meditec, Inc. (R)
  • Footnotes
    Support  Research To Prevent Blindness, University of Southern California Dean’s Scholars Fund, National Eye Institute (R01EY024158)
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 5484. doi:
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      Alice Yon Kim, Zhongdi Chu, Anoush Shahidzadeh, Ruikang K Wang, Carmen A Puliafito, Amir H Kashani; Quantification of retinal microvascular changes in diabetic retinopathy using spectral domain optical coherence tomography angiography (SD-OCTA). Invest. Ophthalmol. Vis. Sci. 2016;57(12):5484.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : To quantify changes in density and morphology of retinal microvasculature in diabetic retinopathy (DR) using SD-OCTA.

Methods : Retrospective, cross-sectional, observational study of healthy and diabetic adult subjects with and without DR. Retinal microvascular changes were assessed using a prototype SD-OCTA (Cirrus, Carl Zeiss Meditec, Dublin, CA) and intensity-based optical microangiography (OMAG) algorithm. A semi-automated program was used to calculate indices of microvascular density and morphology in non-segmented and segmented 3x3 mm SD-OCTA images centered on the fovea. Microvascular density was quantified using skeleton density (SD) and vessel density (VD), while vessel morphology was quantified as fractal dimension (FD) and vessel diameter index (VDI). Statistical analyses were performed using the Student’s t-test or analysis of variance (ANOVA) with post hoc Tukey Honest Significant Difference (HSD) tests for multiple comparisons.

Results : Eighty four eyes of 50 patients with DR and 14 eyes of 8 healthy subjects were studied. All subjects were age- and gender-matched. Spearman’s rank test demonstrated a negative correlation between DR severity and SD, VD, and FD, and a positive correlation with VDI (rho = -0.767, -0.7166, -0.768, and +0.5051, respectively; P < 0.0001). All parameters showed high reproducibility between graders (ICC = 0.971, 0.962, 0.937, and 0.994 for SD, VD, FD, and VDI respectively). Repeatability (κ) was 0.997, 0.996, 0.996, and 0.999 for SD, VD, FD, and VDI, respectively.

Conclusions : Vascular changes in DR can be objectively characterized using SD, VD, FD and VDI. In general, decreasing capillary density (SD and VD), branching complexity (FD), and increasing vascular caliber (VDI) were associated with worsening DR. Capillary density and morphology were significantly correlated with diabetic macular edema.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

 

Non-segmented SD-OCTA images with quantitative image outputs of representative subjects in 3x3 mm areas around the fovea. En face representations of retinal perfusion can be viewed as (A-D) 2D grayscale SD-OCTA images, with selection of noise thresholding marked with yellow in the foveal avascular zone. Contrast-enhanced (E-H) binarized and (I-L) skeletonized images of retinal perfusion around the macula corresponding to the group labeled in each column. Yellow scale bar (A) shows a distance of 500 μm.

Non-segmented SD-OCTA images with quantitative image outputs of representative subjects in 3x3 mm areas around the fovea. En face representations of retinal perfusion can be viewed as (A-D) 2D grayscale SD-OCTA images, with selection of noise thresholding marked with yellow in the foveal avascular zone. Contrast-enhanced (E-H) binarized and (I-L) skeletonized images of retinal perfusion around the macula corresponding to the group labeled in each column. Yellow scale bar (A) shows a distance of 500 μm.

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