June 2023
Volume 64, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2023
Simulated impact of vascular network structure heterogeneity on retinal tissue oxygenation
Author Affiliations & Notes
  • Gal Antman
    Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
    Ophthalmology, Rabin Medical Center, Petah Tikva, Central, Israel
  • Alon Harris
    Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Brendan Fry
    Department of Mathematics and Statistics, Metropolitan State University of Denver, Denver, Colorado, United States
  • Amanda Albright
    Department of Mathematical Sciences, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States
  • Louis R Pasquale
    Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Ingrida Januleviciene
    Lithuanian University of Health Sciences, Kaunas, Lithuania
  • Giedre Pakuliene
    Lithuanian University of Health Sciences, Kaunas, Lithuania
  • Alice Chandra Verticchio Vercellin
    Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Brent A Siesky
    Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • George Eckert
    Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Francesco Oddone
    Glaucoma Unit, IRCCS Fondazione Bietti, Rome, Italy
  • Julia Arciero
    Department of Mathematical Sciences, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States
  • Footnotes
    Commercial Relationships   Gal Antman None; Alon Harris AdOM, Qlaris, Luseed, Cipla , Code C (Consultant/Contractor), AdOM, Luseed, Oxymap, Qlaris, Phileas Pharma, SlitLed, QuLent , Code I (Personal Financial Interest), AdOM, Qlaris, Phileas Pharma , Code S (non-remunerative); Brendan Fry None; Amanda Albright None; Louis Pasquale to Eyenovia, Twenty Twenty, Skye Biosciences, Code C (Consultant/Contractor); Ingrida Januleviciene Santen, Thea, Code C (Consultant/Contractor), Santen, Code R (Recipient); Giedre Pakuliene None; Alice Chandra Verticchio Vercellin None; Brent Siesky None; George Eckert None; Francesco Oddone None; Julia Arciero None
  • Footnotes
    Support  NIH grant (R01EY030851); NSF DMS (1853222/2021192); NYEE Foundation grants; in part by a Challenge Grant award from Research to Prevent Blindness, NY; NSF DMS-1654019, NSF DMS-1852146, NSF DMS-2150108; EY015473; EY032599
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 2378. doi:
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    • Get Citation

      Gal Antman, Alon Harris, Brendan Fry, Amanda Albright, Louis R Pasquale, Ingrida Januleviciene, Giedre Pakuliene, Alice Chandra Verticchio Vercellin, Brent A Siesky, George Eckert, Francesco Oddone, Julia Arciero; Simulated impact of vascular network structure heterogeneity on retinal tissue oxygenation. Invest. Ophthalmol. Vis. Sci. 2023;64(8):2378.

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

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Abstract

Purpose : A theoretical model of the human retina is simulated using two different vascular network geometries to predict the impact of heterogeneity in vascular network structure on retinal tissue oxygenation.

Methods : Two different branches (Branch 1) and (Branch 2) from a published theoretical model of the human retinal vasculature are used to investigate the role of vessel network geometry on tissue oxygenation. The vascular network is modeled as a combined heterogeneous representation of retinal arterioles and compartmental representation of capillaries, small venules, and large venules. A Green’s function method is used to model oxygen transport in the arterioles, and a Krogh cylinder model is used in the capillaries and venules. Identical input arterial blood saturation (0.92), arteriolar pressure drop (16 mmHg), and arteriolar diameters by vessel order (117, 73, 44, 32, and 22 µm) are assumed for both branches. Given these inputs, we created a mathematical model to predict blood vessel and arteriolar tissue PO2 for both retinal vascular networks.

Results : Figure 1 depicts the model-predicted levels of vessel and arteriolar tissue PO2 for each network. In Figure 1 (bottom), the percentage of arteriolar tissue exhibiting a PO2 level less than a given value (PO2 threshold) is given for Branch 1 (blue) and Branch 2 (red). As indicated by points A and B, 20% of the arteriolar tissue in Branch 1 has a PO2 less than 20 mmHg, while only 6% of the arteriolar tissue in Branch 2 has a PO2 less than 20 mmHg. The model also predicts a higher oxygen extraction fraction in Branch 2 than Branch 1 (Figure 1, top and middle). The difference in mean arteriolar tissue PO2 between the two networks is predicted to increase as the level of oxygen demand is increased (not depicted).

Conclusions : The mathematical model used in this study demonstrates the impact of heterogeneity of vascular network structure on the oxygenation of retinal tissue. Even with identical initial conditions for saturation, pressure drop, and diameter, variations in network geometry lead to significantly different regions of low PO2, indicating a wide range of potential oxygenation outcomes for individual patients. This study therefore demonstrates that regional heterogeneity in vessel branching architecture may significantly impact oxygen saturation and ultimately retinal ganglion cell health and functionality.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.

 

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