In vivo estimation of murine iris stiffness using finite element modeling

Chanyoung Lee, Guorong Li, W. Daniel Stamer, C. Ross Ethier

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


The iris plays an important role in certain types of glaucoma, including primary angle-closure glaucoma and pigmentary glaucoma. Iris mechanics are also important in influencing trabecular meshwork deformation in response to intraocular pressure changes in some animal species. Although mice are widely used to study ocular disease, including glaucoma, the in vivo biomechanical properties of the murine iris are unknown. Thus, the primary objective of this study was to estimate murine iris biomechanical stiffness. We used optical coherence tomography (OCT) images of the anterior segment of living mice (n = 13, age = 7.3 ± 3.2 [mean ± SD] months) at sequentially increasing IOP levels, observing IOP-dependent iris deformations. We then used an inverse finite element model to predict iris deformations under the same conditions, estimating iris stiffness by maximizing agreement between OCT data and numerical simulations. Our results show an in vivo murine iris stiffness of 96.1 ± 54.7 kPa (mean ± SD), which did not correlate with age but was dependent on gender. Our results further showed strong evidence of reverse pupillary block, with mean posterior chamber pressure remaining at approximately 12 mmHg even as anterior chamber pressure was set to much higher levels. Our approach to monitoring iris stiffness in vivo is applicable to study potential changes of iris stiffness in various pathophysiological conditions and thus has significant potential for clinical care of ocular disease involving iris biomechanics.

Original languageEnglish (US)
Article number108374
JournalExperimental eye research
StatePublished - Jan 2021
Externally publishedYes


  • Biomechanical properties
  • Glaucoma
  • Inverse finite element modeling
  • Iris
  • OCT

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience


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