June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
A sublamina-based approach to retinal vessel analysis using OCT angiography in glaucoma and glaucoma suspect eyes
Author Affiliations & Notes
  • Rolake Alabi
    Ophthalmology, University of California San Francisco, San Francisco, California, United States
  • Opeyemi Alabi
    Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, United States
  • Alan W Kong
    Ophthalmology, University of California San Francisco, San Francisco, California, United States
  • Mohit Jethi
    Ophthalmology, University at Buffalo, Buffalo, New York, United States
  • Luca Della Santina
    Ophthalmology, University of California San Francisco, San Francisco, California, United States
  • Yvonne Ou
    Ophthalmology, University of California San Francisco, San Francisco, California, United States
  • Footnotes
    Commercial Relationships   Rolake Alabi None; Opeyemi Alabi None; Alan Kong None; Mohit Jethi None; Luca Della Santina None; Yvonne Ou None
  • Footnotes
    Support  Supported by NEI R01 Grant (R01EY028148), NEI P30 Grant (EY002162) - Core Grant for Vision Research, That Man May See, and an unrestricted grant from Research to Prevent Blindness
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 4260. doi:
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    • Get Citation

      Rolake Alabi, Opeyemi Alabi, Alan W Kong, Mohit Jethi, Luca Della Santina, Yvonne Ou; A sublamina-based approach to retinal vessel analysis using OCT angiography in glaucoma and glaucoma suspect eyes. Invest. Ophthalmol. Vis. Sci. 2022;63(7):4260.

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

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Abstract

Purpose : To compare macular vessel density across inner plexiform layer (IPL) depths in glaucoma suspects and patients with glaucoma

Methods : This is a retrospective cross-sectional study from a glaucoma clinic at a single center. 6 by 6 mm2 en face OCT angiography (OCTA) macular images centered on the fovea were collected. 6 to 7 mm thick sections spanning the internal limiting membrane to the IPL/inner nuclear layer (IPL/INL) border (the outer IPL border) were extracted for each eye. A custom-written MATLAB code was used to distinguish small and large vessels in image stacks. Small and large vessel density (VD) were computed for each stack. A linear mixed effects (LME) model was used for statistical analysis. When comparing macular VD within stacks of a specific thickness in suspect versus glaucoma eyes, the LME model included a random effect for each patient (to account for multiple eyes per patient) and a fixed effect for glaucoma. Multivariable models included the potential confounding factors of age, history of hypertension, and/or history of diabetes.

Results : In the study, there were a total of 87 eyes (56 patients) that met criteria for analysis. Analysis using a LME model revealed glaucoma was associated with decreased small vessel density (SVD) starting 25μm above the IPL/INL border (effect size from -1.31 to -0.39, p=3.6x10-4 to 0.045 with a peak negative effect size of -1.20 to -1.31 from 31 to 48μm above the IPL/INL border). To account for the contribution of confounders in the study population, a multivariate analysis that also included age, history of hypertension, and history of diabetes was completed. In this analysis, glaucoma was associated with decreased SVD specifically from 31 to 66μm (-1.17 to -0.54, p= 0.002 to 0.03) and from 79 to 96μm (-0.54 to -0.47, p=9.2x10-4 to 0.002) above the IPL/INL border. Of the included confounders, only age demonstrated an effect on VD. Compared to glaucoma, the effect size of age on SVD was smaller in magnitude (-0.08 to -0.04 from 0-12μm and 25-30μm).

Conclusions : We quantified small and large vessel density across IPL depths using OCTA. In this analysis, glaucoma patients exhibited decreased SVD in the inner IPL compared to glaucoma suspects. How variable VD across IPL depths may result from or reflect differences in retinal ganglion cell resiliency and/or susceptibility in glaucoma are important questions for future study.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

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