July 2018
Volume 59, Issue 9
ARVO Annual Meeting Abstract  |   July 2018
Relationship between intraocular pressure, blood pressure and cerebrospinal fluid pressure: a theoretical approach
Author Affiliations & Notes
  • Giovanna Guidoboni
    Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, United States
  • Fabrizia Salerni
    Physics, University of Parma, Parma, Italy
  • Rodolfo Repetto
    Civil, Chemical and Environmental Engineering, University of Genova, Genova, Italy
  • Marcela Szopos
    Université de Strasbourg, CNRS, IRMA UMR 7501, Strasbourg, France
  • Alon Harris
    Glick Eye Institute, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Footnotes
    Commercial Relationships   Giovanna Guidoboni, None; Fabrizia Salerni, None; Rodolfo Repetto, None; Marcela Szopos, None; Alon Harris, AdOM (C), AdOM (I), CIPLA (C), Nano Retina (I), Oxymap (I)
  • Footnotes
    Support  This work has been partially supported by NSF DMS-1224195, LabEx IRMIA (France), a grant from Research to Prevent Blindness (RPB, NY, USA).
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 1665. doi:
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      Giovanna Guidoboni, Fabrizia Salerni, Rodolfo Repetto, Marcela Szopos, Alon Harris; Relationship between intraocular pressure, blood pressure and cerebrospinal fluid pressure: a theoretical approach. Invest. Ophthalmol. Vis. Sci. 2018;59(9):1665.

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

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Purpose : Intraocular pressure (IOP), arterial blood pressure (PA) and cerebrospinal fluid pressure (CSFp) have been identified as major players in several ocular pathologies, including glaucoma, central vein occlusion and papilledema to name a few. However, IOP, PA and CSFp are not independent from each other. For example, aqueous humor and CSF flows, whose mechanics contribute to establish IOP and CSFp levels, originate from blood flow, which is driven by PA. As a consequence, it is difficult to isolate experimentally IOP, PA and CSFp and to disentangle their effect in pathological conditions. Here we utilize a theoretical approach to address this issue.

Methods : A mathematical model is developed to simulate fluid flow in the eyes and brain within a simplified description of the whole-body circulation (Fig.1). The model accounts for: (i) the flows of blood and aqueous humor in the eyes; (ii) the flows of blood, cerebrospinal fluid and interstitial fluid in the brain; and (iii) their interactions. The flow is driven by PA, which is given as a variable input, while the venous pressure PV is kept constant. Model parameters have been calibrated on published data. The model is used to simulate changes in IOP, CSFp, flow and pressure distributions across the whole system induced by changes in PA. Results are compared those reported in clinical studies.

Results : Model predicted relationships between IOP, PA and CSFp are within the same range as those reported in clinical studies (Fig2a,b,c). In addition, choroidal venous pressure in the vortex veins computed by the model from flow and pressure distribution within the body results to be approximately equal to IOP over a wide range of values (Fig2c), confirming the findings by A. Bill (The uveal venous pressure. Archives of Ophthalmology, 69(6):780-782. (1963)).

Conclusions : Simulation results validate the predictive capability of the model, which provides a powerful virtual laboratory where the relationships between IOP, PA, CSFp could be assessed based on patient's conditions. Thus, our model may have an important clinical role as medicine is moving in the direction of tailoring treatments for specific patients.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.


Model of fluid flow in eyes and brain connected to a simplified whole-body circulation

Model of fluid flow in eyes and brain connected to a simplified whole-body circulation


Comparisons between model prediction and clinical data

Comparisons between model prediction and clinical data


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