August 2021
Volume 62, Issue 11
Open Access
ARVO Imaging in the Eye Conference Abstract  |   August 2021
Comparative feature analysis in OCT and OCT angiography of diabetic retinopathy
Author Affiliations & Notes
  • David Le
    Bioengineering, University of Illinois at Chicago, Chicago, Illinois, United States
  • Xiang Li
    Bioengineering, University of Illinois at Chicago, Chicago, Illinois, United States
  • Taeyoon Son
    Bioengineering, University of Illinois at Chicago, Chicago, Illinois, United States
  • Jennifer Lim
    Ophthalmology & Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, United States
  • Xincheng Yao
    Bioengineering, University of Illinois at Chicago, Chicago, Illinois, United States
    Ophthalmology & Visual Sciences, University of Illinois at Chicago, Chicago, Illinois, United States
  • Footnotes
    Commercial Relationships   David Le, None; Xiang Li, None; Taeyoon Son, None; Jennifer Lim, Adverum (F), Aldeyra Therapeutics (F), Allergan (C), Chengdu Kanghong (F), Clearside (F), Cognition (C), Eyenuk (C), Genentech (F), Genentech (C), Greybug (F), Iveric (C), Kodiak (C), Luxa (C), NGM (F), Novartis (C), Opthea (C), pSivida (C), Quark (C), Regeneron (F), Santen (C); Xincheng Yao, None
  • Footnotes
    Support  T32 Institutional Training Grant for a training program in the biology and translational research on Alzheimer’s disease and related dementias (T32AG057468)
Investigative Ophthalmology & Visual Science August 2021, Vol.62, 36. doi:
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    • Get Citation

      David Le, Xiang Li, Taeyoon Son, Jennifer Lim, Xincheng Yao; Comparative feature analysis in OCT and OCT angiography of diabetic retinopathy. Invest. Ophthalmol. Vis. Sci. 2021;62(11):36.

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

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Abstract

Purpose : Diabetic retinopathy (DR) causes both vascular and photoreceptor abnormalities. This study is to test if photoreceptor change occurs before detectable vascular abnormality in early DR.

Methods : OCTA and OCT images were acquired from normal eyes, and diabetic eyes with no DR and with mild DR. Four OCTA features were quantified, including vessel diameter index (VDI), tortuosity index (VTI), perimeter index (VPI), and complexity index (VCI). Analogously, four OCT features from outer retina were quantified, including intensities of the external limiting membrane (ELM), inner segment ellipsoid (ISe), retinal pigment epithelium (RPE), and the normalized ISe/RPE intensity ratio. Quantitative OCTA features were analyzed on the superficial vascular plexus (Fig. 1a) including corresponding vessel, skeleton, and perimeter (Fig. 1b-d), and OCT features were analyzed using averaged A-line intensities from the OCT B-scans (Fig. 1e) in the parafoveal and perifoveal regions.

Results : Two quantitative OCTA features, VDI and VCI, were observed to have significant differences (p<0.05) among the healthy and diabetic eyes (no DR and mild DR). However, OCTA features did not reveal any significant differences between no DR and mild eyes. In contrast, for OCT features, the ISe intensity revealed significant differences (p<0.05) between non-diabetic eyes (healthy and no DR) and mild DR eyes. Quantification of ISe/RPE intensity ratio improved the sensitivity for differentiation among cohorts (p<0.001) in the parafoveal region.

Conclusions : Quantitative OCT analysis revealed higher sensitivity for differentiation of healthy, no DR, and mild DR eyes compared to OCTA features. This study suggests that abnormalities of the outer retina occur before vascular abnormalities in early DR. The normalized ISe/RPE measurement promises a sensitive biomarker for objective detection of early DR.

This is a 2021 Imaging in the Eye Conference abstract.

 

Figure 1. Illustration of OCT and OCTA feature analysis. A) Enface OCTA image, the yellow box represents the area examined in B-D. B) Segmented vessel map. C) Skeletonized map, with example vessel endpoints used for vessel tortuosity quantification. D) Vessel perimeter map. E) OCT B-scan used for OCT feature quantification. ILM: inner limiting membrane, IPL-INL: inner plexiform layer – inner nuclear layer; OPL-ONL: outer plexiform layer – outer nuclear layer; ELM: external limiting membrane; ISe: inner segment ellipsoid; RPE: retinal pigment epithelium.

Figure 1. Illustration of OCT and OCTA feature analysis. A) Enface OCTA image, the yellow box represents the area examined in B-D. B) Segmented vessel map. C) Skeletonized map, with example vessel endpoints used for vessel tortuosity quantification. D) Vessel perimeter map. E) OCT B-scan used for OCT feature quantification. ILM: inner limiting membrane, IPL-INL: inner plexiform layer – inner nuclear layer; OPL-ONL: outer plexiform layer – outer nuclear layer; ELM: external limiting membrane; ISe: inner segment ellipsoid; RPE: retinal pigment epithelium.

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