July 2019
Volume 60, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2019
Theoretical predictions of oxygenation in a heterogeneous vascular network of the retina
Author Affiliations & Notes
  • Lucas Rowe
    Ophthalmology, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Alon Harris
    Ophthalmology, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Brendan C. Fry
    Mathematical and Computer Sciences, Metropolitan State University of Denver, Denver, Colorado, United States
  • Alice Chandra Verticchio Vercellin
    Ophthalmology, University of Pavia, Pavia, Italy
    IRCCS - Fondazione Bietti, Rome, Italy
  • Brent A Siesky
    Ophthalmology, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Julia Arciero
    Mathematical Sciences, IUPUI, Indianapolis, Indiana, United States
  • Footnotes
    Commercial Relationships   Lucas Rowe, None; Alon Harris, AdOM (C), AdOM (I), CIPLA (C), Oxymap (I), Shire (C); Brendan Fry, None; Alice Chandra Verticchio Vercellin, None; Brent Siesky, None; Julia Arciero, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 5728. doi:
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      Lucas Rowe, Alon Harris, Brendan C. Fry, Alice Chandra Verticchio Vercellin, Brent A Siesky, Julia Arciero; Theoretical predictions of oxygenation in a heterogeneous vascular network of the retina. Invest. Ophthalmol. Vis. Sci. 2019;60(9):5728.

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

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Abstract

Purpose : This study uses theoretical modeling to predict blood and tissue oxygenation in a heterogeneous vascular network of the mouse retina for different levels of tissue oxygen demand.

Methods : Confocal microscopy images of the mouse retina have revealed a very complex and non-uniform distribution of blood vessels supplying the retina. Here, a realistic model of oxygen transport is adopted which explicitly represents the interactions among vessels and tissue in a vascular network with non-uniform geometry. By the conservation of mass, oxygen diffusion in tissue is equated to oxygen consumption in tissue, which is assumed to follow Michaelis-Menten kinetics. Vessels are modeled as discrete oxygen sources, and the tissue regions are considered as oxygen sinks. The resulting oxygen concentration at any tissue point is calculated by summing the oxygen fields produced by each of the surrounding blood vessels.

Results : Figure 1 (Panel A) shows the model-predicted contour map of the oxygenation of the arteriolar network and surrounding tissue under well-oxygenated conditions (incoming arterial saturation to all branches is 96%). In Panel B, the inflow saturation in one of the six arteriolar branches is reduced to 33%. As a result of this simulated oxygen impairment, average tissue PO2 in the entire network decreased from 67.2 mmHg to 61.7 mmHg. Importantly, the minimum tissue PO2 dropped from 18.7 mmHg to 8.1 mmHg. Thus, tissue oxygenation in one branch of the retina is predicted to decrease by nearly 56% following a 66% reduction in arterial blood saturation.

Conclusions : By incorporating a realistic model of oxygen transport within the multi-layer and heterogeneous geometry of the retina, this model allows, for the first time, more accurate predictions of retinal oxygenation in response to changes in oxygen demand, arterial saturation, viscosity, or hematocrit. The results of this study highlight the critical point that the average value of PO2 in the retina is a poor indicator of network oxygenation. Many terminal arteriolar vessels will have abnormally low PO2 levels despite reasonable average values in the overall network, which can lead to areas at risk of hypoxia—an effect that would not be observed in a non-heterogeneous description of the network.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

 

Predicted contour maps of oxygenation in the arteriolar network. (A) Normal conditions. (B) Reduced inflow saturation in one branch. Red: High PO2. Blue: Low PO2.

Predicted contour maps of oxygenation in the arteriolar network. (A) Normal conditions. (B) Reduced inflow saturation in one branch. Red: High PO2. Blue: Low PO2.

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