June 2020
Volume 61, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2020
Vessel Density and Caliber Discriminate between Normal Retina and Clinical Stages of Diabetic Retinopathy
Author Affiliations & Notes
  • Sam Kushner-Lenhoff
    Ophthalmology, USC Roski Eye Institute, California, United States
  • Kaitlin Kogachi
    Ophthalmology, USC Roski Eye Institute, California, United States
  • Melissa Mert
    Preventative Medicine, Southern California Clinical and Translational Science Institute, University of Southern California, California, United States
  • Zhongdi Chu
    Bioengineering, University of Washington, Washington, United States
  • Neal V. Palejwala
    Retinal Consultants of Arizona, Arizona, United States
  • Jeremy D Wolfe
    Associated Retinal Consultants, Oakland University William Beaumont School of Medicine, Michigan, United States
  • Sujit Itty
    Retinal Consultants of Arizona, Arizona, United States
  • Kimberly A Drenser
    Associated Retinal Consultants, Oakland University William Beaumont School of Medicine, Michigan, United States
  • Antonio Capone
    Associated Retinal Consultants, Oakland University William Beaumont School of Medicine, Michigan, United States
  • Pravin U Dugel
    Retinal Consultants of Arizona, Arizona, United States
  • Andrew A Moshfeghi
    Ophthalmology, USC Roski Eye Institute, California, United States
  • Hossein Ameri
    Ophthalmology, USC Roski Eye Institute, California, United States
    USC Ginsberg Institute for Biomedical Therapeutics, California, United States
  • Ruikang K Wang
    Bioengineering, University of Washington, Washington, United States
  • Amir H Kashani
    Ophthalmology, USC Roski Eye Institute, California, United States
    USC Ginsberg Institute for Biomedical Therapeutics, California, United States
  • Footnotes
    Commercial Relationships   Sam Kushner-Lenhoff, None; Kaitlin Kogachi, None; Melissa Mert, None; Zhongdi Chu, None; Neal Palejwala, None; Jeremy Wolfe, Allergan (C), Allergan (F), Allergan (S), Carl Zeiss Meditec, Inc (C), Genentech (C), Genentech (S), Regeneron (C), Regeneron (S); Sujit Itty, None; Kimberly Drenser, None; Antonio Capone, None; Pravin Dugel, Annidis (C), Annidis (I), DigiSight (C), DigiSight (I), Optovue (C), PanOptica (C), Pentavision (C), TopCon (C); Andrew Moshfeghi, None; Hossein Ameri, Spark Therapeutics (C); Ruikang Wang, Carl Zeiss Meditec, Inc (C), Carl Zeiss Meditec, Inc (P), Insight Photonics (C), Kowa (P); Amir Kashani, Carl Zeiss Meditec, Inc (F), Carl Zeiss Meditec, Inc (R)
  • Footnotes
    Support  NIH R01EY030564, NIH K08EY027006, Unrestricted Departmental Grant From Research To Prevent Blindness, Research Grants from Carl Zeiss Meditec
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 4107. doi:
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    • Get Citation

      Sam Kushner-Lenhoff, Kaitlin Kogachi, Melissa Mert, Zhongdi Chu, Neal V. Palejwala, Jeremy D Wolfe, Sujit Itty, Kimberly A Drenser, Antonio Capone, Pravin U Dugel, Andrew A Moshfeghi, Hossein Ameri, Ruikang K Wang, Amir H Kashani; Vessel Density and Caliber Discriminate between Normal Retina and Clinical Stages of Diabetic Retinopathy. Invest. Ophthalmol. Vis. Sci. 2020;61(7):4107.

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

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Abstract

Purpose : To assess the utility of SD-OCTA derived metrics to determine diabetic retinopathy (DR) severity.

Methods : We carried out a multicenter, retrospective, cross-sectional study using OCTA (AngioPlexTM Carl Zeiss Meditec, Inc). A total of 538 eyes in 349 subjects [102 non-diabetic, 103 mild non-proliferative DR (NPDR), 41 moderate NPDR, 32 severe NPDR, and 71 proliferative DR] were classified according to DR status. Vessel skeletal density (VSD) and vessel diameter index (VDI) were calculated on the superficial retinal layer (SRL). The subjects were divided into initial (227 patients) and validation cohorts (122 patients) for modeling. Multinomial logistic regression models were generated, and the performance of each model was quantified by calculating its area under the curve (AUC).

Results : There is a significant increase in the odds of DR for every 0.001 unit decrease in VSD. Specifically, the odds of having mild, moderate, severe NPDR, and PDR compared to normal subjects increased by 12% (95% CI: 8-19%), 25% (95% CI: 18-33%), 27% (95% CI: 19-35%), and 32% (95% CI: 25-41%) [all p<0.001] respectively, after adjusting for comorbidities from past medical history. In addition, there is a significant increase in the odds of DR for every 0.01 unit increase in VDI. The odds of having mild, moderate, severe NPDR, and PDR compared to normal subjects increased by 5% (95% CI: 1-10%), 17% (95% CI: 11-23%), 16% (95% CI: 10-23%), and 21% (95% CI: 15-28%), respectively [p=0.02 for mild, p<0.001 for moderate, severe, and PDR]. The AUC graphs in both cohorts showed excellent discrimination of normal subjects vs. any DR for the covariate model (AUC =.89 and AUC =.80 for the initial and validation cohort respectively) and furthermore the models containing VSD and VSD with VDI significantly contributed to the discrimination as seen in Figure 1. For mild vs. more severe DR and for mild/moderate/severe vs PDR, we also confirmed excellent discrimination, but the VSD or VDI did not significantly increase the AUC compared to the covariate only model in the validation cohort.

Conclusions : VSD and VDI are significantly correlated with the presence or absence of DR and DR severity. These values may be used with other clinically relevant variables to determine DR severity.

This is a 2020 ARVO Annual Meeting abstract.

 

Figure 1: AUC of all diabetic retinopathy vs. normal in the initial and validation cohort models. Model 1 refers to a covariate only model.

Figure 1: AUC of all diabetic retinopathy vs. normal in the initial and validation cohort models. Model 1 refers to a covariate only model.

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