March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
Determining The Mechanical Properties Of Human Lamina Cribrosa Using A Computational Optimization Algorithm
Author Affiliations & Notes
  • Jonathan P. Vande Geest
    Aerospace and Mechanical Engineering, University of Arizona, Tucson, Arizona
    Graduate Interdisciplinary Program of Biomedical Engineering, University of Arizona, Arizona
  • Avinash Ayyalasomayajula
    Aerospace and Mechanical Engineering, University of Arizona, Tucson, Arizona
  • Jonathan P. Vande Geest
    Biomedical Engineering, University of Arizona, Arizona
    BIO5, University of Arizona, Arizona
  • Footnotes
    Commercial Relationships  Jonathan P. Vande Geest, None; Avinash Ayyalasomayajula, None; Jonathan P. Vande Geest, None
  • Footnotes
    Support  NIH (NEI) Grant 1R01EY020890 - 01A1
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 2831. doi:
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      Jonathan P. Vande Geest, Avinash Ayyalasomayajula, Jonathan P. Vande Geest; Determining The Mechanical Properties Of Human Lamina Cribrosa Using A Computational Optimization Algorithm. Invest. Ophthalmol. Vis. Sci. 2012;53(14):2831.

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

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Abstract

Purpose: : It is well known that elevated IOP is a major factor leading to primary open-angle glaucoma. Studies have indicated that increased IOP can have a deleterious effect on the optic nerve head (ONH) via strains in the lamina cribrosa (LC). Thus, a better understanding of the LC mechanical properties could provide new insights into the progressive damage of the ONH. The purpose of this work is to develop a technique to determine the mechanical properties of the LC using a finite element optimization procedure in which LC deformations are mapped from multiphoton image datasets.

Methods: : A computational mesh was generated from multiphoton microscopy images of the LC. The entire mesh was assigned a predetermined and homogeneous value of neohookean hyperelastic stiffness. This model, which was assumed to be incompressible, was then loaded in biaxial tension using a load boundary condition equivalent to that for a normal eye using the law of Laplace. The displacements of this model represent a set of mock experimental data. An automated Matlab-Abaqus algorithm was then used, along with an appropriate initial estimate of stiffness, to optimize for the value of LC stiffness that minimized the sum of the squares of the residual between the mock experimental displacements and those obtained in sequential Abaqus calls within the optimization algorithm.

Results: : From the final optimized solution, the displacements at a randomly chosen set of mesh points compared well with those in the mock experimental data. The results showed an average percent relative error of 2.3% in the material property values across the mesh.

Conclusions: : Our developed method is an effective technique to obtain LC mechanical properties. Experimentally measured displacements in a pressurized eye, which can be obtained from digital image correlation, will be used in the future to arrive at the mechanical properties of the LC using this technique. The broader goal of this study is to use this technique to investigate differences in LC mechanical properties for different ages and ethnicities.

Keywords: lamina cribrosa • image processing • computational modeling 
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