June 2020
Volume 61, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2020
Influence of low perfusion pressure on the diastolic hemodynamics in central retinal vessels: a data-driven computational study
Author Affiliations & Notes
  • Nicholas Marazzi
    Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, United States
  • Lorenzo Sala
    Department of Mathematics, Imperial College London, United Kingdom
  • Rachel Chong Shujuan
    Singapore National Eye Centre, Singapore
  • Ching-Yu Cheng
    Singapore National Eye Centre, Singapore
  • Alon Harris
    Icahn School of Medicine, Mount Sinai Hospital, New York, New York, United States
  • Giovanna Guidoboni
    Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, United States
    Department of Mathematics, University of Missouri, Missouri, United States
  • Footnotes
    Commercial Relationships   Nicholas Marazzi, None; Lorenzo Sala, None; Rachel Shujuan, None; Ching-Yu Cheng, None; Alon Harris, AdOM (C), AdOM (I), AdOM (S), LuSeed (I), Oxymap (I), Thea (R); Giovanna Guidoboni, Foresite Healthcare LLC (C), Gspace LLC (I)
  • Footnotes
    Support  NSF-DMS 1853222/1853303, NMRC/CIRG/1488/2018, NMRC/CSA-SI/0012/2017
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 614. doi:
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    • Get Citation

      Nicholas Marazzi, Lorenzo Sala, Rachel Chong Shujuan, Ching-Yu Cheng, Alon Harris, Giovanna Guidoboni; Influence of low perfusion pressure on the diastolic hemodynamics in central retinal vessels: a data-driven computational study. Invest. Ophthalmol. Vis. Sci. 2020;61(7):614.

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

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Abstract

Purpose :
High intraocular pressure (IOP) and low systolic and diastolic blood pressures (SP and DP) lead to low perfusion pressure and are considered risk factors for glaucoma. Diastole is the low-pressure part of the cardiac cycle and is likely to be more prone to low perfusion. In this study, we investigate how diastolic hemodynamics change in the central retinal artery and vein (CRA and CRV) as a function of SP, DP and IOP.

Methods : A validated mathematical model (Guidoboni et al, 2014) is used to simulate retinal circulation. A sensitivity analysis is performed to quantify variations in the diastolic flux and vascular resistances in the CRA and CRV (DQcra, DQcrv, DRcra and DRcrv) resulting from variations in SP, DP and IOP, whose distributions are based on data on ocular hypertensive subjects (IOP > 21mmHg) from the Singapore Epidemiology of Eye Diseases Study (Tham et al, 2017), see Fig1[A-C]. The fraction of total output variance associated with a given input when it varies singly or jointly with all the input set is given by the first and total Sobol indices, respectively.

Results : Fig1[D-E] shows the computed distribution of DRcra and DRcrv, while Fig2[A-D] reports the computed Sobol indices . Model results indicate that: (i) the distributions of DQcra and DQcrv are very similar and both follow a normal distribution (N~(2.10e-4, 9.98e-09) , N~(1.78e-4 ± 1.08e-8 ml/s), pvalue < 0.001)(ii) DRcra fits a normal distribution (N~(953,31)), while DRcrv exhibits a skewed and more spread distribution (median = 20207 mmHg s cm3 , mean = 32070 mmHg s cm3); (iii) DQcra and DQcrv present a similar dependency on SP, DP and IOP; (iv) DRcra mainly depends on SP and DP, while DRcrv, depends entirely on IOP.

Conclusions : Results from our model predict that DRcra is mainly controlled by SP and DP, while DRcrv is mainly controlled by IOP. Furthermore, different vascular resistance properties in the CRA and CRV result in a similar response in their diastolic flux. These results may provide insight into why high IOP and low SP and DP are risk factors for glaucoma.

This is a 2020 ARVO Annual Meeting abstract.

 


Probability density function of SP, DP and IOP [A-C], DRcra and DRcrv [D-E]


Probability density function of SP, DP and IOP [A-C], DRcra and DRcrv [D-E]

 


Simulated first order (blue) and total (turquoise) Sobol indices for the diastolic hemodynamic variables.


Simulated first order (blue) and total (turquoise) Sobol indices for the diastolic hemodynamic variables.

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