June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
A theoretical assessment of changes in blood flow and oxygen extraction fraction during flicker stimulation
Author Affiliations & Notes
  • Simone Cassani
    Mathematics, Indiana University Purdue Univ, Indianapolis, IN
  • Alon Harris
    Ophthalmology, Indiana University School of Medicine, Indianapolis, IN
  • Giovanna Guidoboni
    Mathematics, Indiana University Purdue Univ, Indianapolis, IN
    Ophthalmology, Indiana University School of Medicine, Indianapolis, IN
  • Brent A Siesky
    Ophthalmology, Indiana University School of Medicine, Indianapolis, IN
  • Julia Concetta Arciero
    Mathematics, Indiana University Purdue Univ, Indianapolis, IN
  • Footnotes
    Commercial Relationships Simone Cassani, None; Alon Harris, AdOM (I), Alcon (R), Biolight (C), Isarna Therapeutics (C), Isarna Therapeutics (R), Nano Retina (C), Ono (C), Science Based Health (C); Giovanna Guidoboni, None; Brent Siesky, None; Julia Arciero, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 2738. doi:
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      Simone Cassani, Alon Harris, Giovanna Guidoboni, Brent A Siesky, Julia Concetta Arciero; A theoretical assessment of changes in blood flow and oxygen extraction fraction during flicker stimulation. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):2738.

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

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Abstract
 
Purpose
 

Accurately assessing tissue oxygenation during altered metabolic demand is essential for identifying key vascular factors that contribute to ocular diseases. In this study, a theoretical model of the retinal vasculature is used to predict changes in blood flow and oxygen extraction fraction (OEF = (O2A-O2v)/O2A, where O2A and O2v are the oxygen content of arterioles and venules) as tissue oxygen demand (M0) varies due to flicker stimulation.

 
Methods
 

The model accounts for the nonlinear effects of intraocular pressure (IOP), blood flow autoregulation mechanisms, and IOP-induced compression of the lamina cribrosa. Baseline (healthy) conditions are established in the model by choosing a level of M0 (2.65 cm3 O2/100 cm3/min) that will yield a venous oxygen saturation of 0.6 (Hammer et al. 2011). The level of M0 is varied between 1-5 cm3 O2/100 cm3/min, representing flicker studies at varying frequencies. Model predictions of blood flow and OEF are compared with data from humans, rats, and monkeys for multiple combinations of autoregulation mechanisms (myogenic, shear, metabolic, and CO2).

 
Results
 

When all autoregulation mechanisms are active, the model predicts blood flow values that are in good agreement with data collected from humans (Garhofer et al. 2004) at baseline and during flicker stimulation (Fig. 1A). The model predicts a 22% increase in retinal blood flow above baseline due to flicker stimulation, which is compared with flow changes in multiple experimental studies (Fig. 1B). Model predictions of OEF before and during flicker stimulation are shown in Fig. 1C.

 
Conclusions
 

The capability of the model to predict blood flow and OEF under various conditions (e.g., impaired autoregulation) highlights the role of theoretical modeling in analyzing data and guiding future clinical directions. The slight underestimate of the model prediction compared with experimental data shown in Fig. 1B is likely due to the absence of capillary recruitment or of the passive contribution of retinal venules in the model. Nevertheless, this study provides an important step in modeling blood flow alterations with changing metabolic demand, which will help to elucidate vascular contributions to ophthalmic disease.  

 
Figure 1. Model predictions, clinical and experimental data for: A) blood flow in one arteriole; B) percentage increase in blood flow during flicker; C) retinal oxygen extraction fraction.
 
Figure 1. Model predictions, clinical and experimental data for: A) blood flow in one arteriole; B) percentage increase in blood flow during flicker; C) retinal oxygen extraction fraction.

 
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