September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Modelling of lens fluid dynamics with additions of different geometrical structures
Author Affiliations & Notes
  • Ho Ting Duncan Wu
    Optometry, University of Auckland, Auckland, New Zealand
  • Paul J Donaldson
    Physiology, University of Auckland, Auckland, New Zealand
  • Ehsan Vaghefi
    Optometry, University of Auckland, Auckland, New Zealand
  • Footnotes
    Commercial Relationships   Ho Ting Duncan Wu, None; Paul Donaldson, None; Ehsan Vaghefi, None
  • Footnotes
    Support  Health Research Council Emerging Scientist First Award
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 5736. doi:
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      Ho Ting Duncan Wu, Paul J Donaldson, Ehsan Vaghefi; Modelling of lens fluid dynamics with additions of different geometrical structures. Invest. Ophthalmol. Vis. Sci. 2016;57(12):5736.

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

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Purpose : Vaghefi produced a 3D computer model of the lens capable to accurately predict its fluid dynamics [1]. However, the geometric domain of this model was not anatomically accurate. We aim to examine the effects geometrical structures such as sutures or the anterior/ posterior chambers of the eye have on the fluid dynamics of the lens and its surroundings.

Methods : The 3D model of the lens developed by Vaghefi using CMISS has been redeveloped using COMSOL. Initially, we created models which included the 3D Y-sutures and also the anterior and posterior chambers of the eye. The complex geometric domain has then been discretised into 97142 elements capable of capturing key information. Next, the governing equations and appropriate boundary conditions of the lens under normal condition were applied and invoked (detailed in Vaghefi et al. [1]). Finally, the fluid dynamics of the lens, including its water content gradient was solved for.

Results : The model was able to predict values and pattern of fluid velocity, pressure, as well as intracellular and extracellular solutes concentration. The fluid appeared to flow from the anterior and posterior chambers respectively to the core of the lens and flows outward around the equatorial region. The velocity appeared to be the highest in the posterior outer cortex and the lowest at the inner anterior cortex. Radially from surface to core, [Na]i ranges from 5.78 to 9.99 mM, [Na]e from 103.44 to 112.65 mM, [Cl]i from 9.80 to 10.48 mM and [Cl]e from 113.94 to 115.43 mM. The intracellular concentrations were highest in the core and lowest in the outer cortex, whilst the extracellular concentrations were reversed. These results are consistent with predictions by Vaghefi’s model.

Conclusions : 3D Y-sutures and anterior/ posterior chambers of the eye were added to a redeveloped fluid dynamics model of the lens. Pattern and values of fluid velocity as well as solutes concentration matches well with predictions from Vaghefi’s model suggesting these geometrical structures have no significant effects on its fluid dynamics. We are now able to build on top of this modelling framework, and be able to calculate water gradient of the lens, which creates its refractive index gradient. This enables us to create links between physiological changes of the lens to its overarching optical performance, through the lenticular fluid dynamics.

[1] E. Vaghefi et al. Biomed.Eng.Online, vol. 11(1),p.1,2012

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.


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