Investigative Ophthalmology & Visual Science Cover Image for Volume 61, Issue 9
July 2020
Volume 61, Issue 9
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ARVO Imaging in the Eye Conference Abstract  |   July 2020
Retinal capillary perfusion heterogeneity in diabetic retinopathy detected by optical coherence tomography angiography
Author Affiliations & Notes
  • Po Hsiang (Shawn) Yuan
    Department of Ophthalmology and Visual Sciences, University of British Columbia Faculty of Medicine , Vancouver, British Columbia, Canada
  • Arman Athwal
    School of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada
    Lions Eye Institute, Center for Ophthalmology and Visual Science, The University of Western Australia, Perth, Western Australia, Australia
  • Julian Lo
    School of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada
  • Dao-Yi Yu
    Lions Eye Institute, Center for Ophthalmology and Visual Science, The University of Western Australia, Perth, Western Australia, Australia
  • Marinko Sarunic
    School of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada
  • Eduardo Navajas
    Department of Ophthalmology and Visual Sciences, University of British Columbia Faculty of Medicine , Vancouver, British Columbia, Canada
  • Footnotes
    Commercial Relationships   Po Hsiang (Shawn) Yuan, None; Arman Athwal, None; Julian Lo, None; Dao-Yi Yu, None; Marinko Sarunic, Seymour Vision (I); Eduardo Navajas, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2020, Vol.61, PB0020. doi:
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      Po Hsiang (Shawn) Yuan, Arman Athwal, Julian Lo, Dao-Yi Yu, Marinko Sarunic, Eduardo Navajas; Retinal capillary perfusion heterogeneity in diabetic retinopathy detected by optical coherence tomography angiography. Invest. Ophthalmol. Vis. Sci. 2020;61(9):PB0020.

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

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Abstract

Purpose : To investigate the ability of a commercially available optical coherence tomography angiography (OCTA) machine to describe retinal capillary perfusion heterogeneity in diabetic retinopathy (DR) patients.

Methods : Ten consecutive en face 6x6mm foveal OCTA images were obtained from both eyes of 13 DR patients and 5 healthy controls using a Zeiss PLEX Elite 9000. Fifteen DR and eight healthy eyes met the inclusion criteria: a centered fovea, little motion artifacts, and a signal of at least 8/10 in all frames. Each eye was analysed for capillary perfusion changes between frames in the superficial and deep capillary plexuses (SCP and DCP respectively). The ten en face images of each eye of the SCP and DCP were aligned into temporal stacks and the vessels were segmented in each frame with a neural network. The coefficient of variation (CV) was calculated at each pixel to map spatiotemporal perfusion heterogeneity. During analysis care was taken to ignore areas with signs of artifact including motion, segmentation error, and large intensity variations due to floaters and inter-frame OCTA focus differences.

Results : Inter-frame intensity changes suggest retinal capillary perfusion variation in some regions of both DR and healthy patients. The variation ranged from narrowing of capillaries to flow voids that occurred intermittently. In DR patients, there were variations in microaneurysm morphology with some even disappearing between frames.

Conclusions : Preliminary analysis of OCTA images suggests perfusion heterogeneity in normal and DR eyes. Variations in pixel intensity were shown qualitatively as CV maps and in some regions indicates potential vessel perfusion and density heterogeneity. Clinicians should be wary of relying on a single OCTA image as serially acquired images demonstrate discrepancies between frames. Further studies are necessary to determine the source of the capillary flow variation in the retina.

This is a 2020 Imaging in the Eye Conference abstract.

 

(A) Averaged stack of 10 serially acquired macular OCTA images from the deep capillary plexus of a severe diabetic retinopathy patient. (B) Two frames of the stack in which the intensity of a microaneurysm changes significantly despite the surrounding region’s intensity profile remaining mostly consistent. (C) A coefficient of variation map which shows variations in pixel intensity. The colour bar indicates the variation from blue (no variation) to red (most variation).

(A) Averaged stack of 10 serially acquired macular OCTA images from the deep capillary plexus of a severe diabetic retinopathy patient. (B) Two frames of the stack in which the intensity of a microaneurysm changes significantly despite the surrounding region’s intensity profile remaining mostly consistent. (C) A coefficient of variation map which shows variations in pixel intensity. The colour bar indicates the variation from blue (no variation) to red (most variation).

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