Unknown

Dataset Information

0

Simulation of Air Puff Tonometry Test Using Arbitrary Lagrangian-Eulerian (ALE) Deforming Mesh for Corneal Material Characterisation.


ABSTRACT: : Purpose: To improve numerical simulation of the non-contact tonometry test by using arbitrary Lagrangian-Eulerian deforming mesh in the coupling between computational fluid dynamics model of an air jet and finite element model of the human eye.

Methods

Computational fluid dynamics model simulated impingement of the air puff and employed Spallart-Allmaras model to capture turbulence of the air jet. The time span of the jet was 30 ms and maximum Reynolds number was Re=2.3×104, with jet orifice diameter 2.4 mm and impinging distance 11 mm. The model of the human eye was analysed using finite element method with regional hyperelastic material variation and corneal patient-specific topography starting from stress-free configuration. The cornea was free to deform as a response to the air puff using an adaptive deforming mesh at every time step of the solution. Aqueous and vitreous humours were simulated as a fluid cavity filled with incompressible fluid with a density of 1000 kg/m3.

Results

Using the adaptive deforming mesh in numerical simulation of the air puff test improved the traditional understanding of how pressure distribution on cornea changes with time of the test. There was a mean decrease in maximum pressure (at corneal apex) of 6.29 ± 2.2% and a development of negative pressure on a peripheral corneal region 2-4 mm away from cornea centre.

Conclusions

The study presented an improvement of numerical simulation of the air puff test, which will lead to more accurate intraocular pressure (IOP) and corneal material behaviour estimation. The parametric study showed that pressure of the air puff is different from one model to another, value-wise and distribution-wise, based on cornea biomechanical parameters.

SUBMITTER: Maklad O 

PROVIDER: S-EPMC6982245 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC4851392 | biostudies-literature
| S-EPMC5085055 | biostudies-literature
| S-EPMC4618943 | biostudies-literature
| S-EPMC5417684 | biostudies-literature
| S-EPMC8713130 | biostudies-literature
| S-EPMC7447134 | biostudies-literature
| S-EPMC5828335 | biostudies-other
| S-EPMC6890641 | biostudies-literature
| S-EPMC3296536 | biostudies-other
| S-EPMC4950185 | biostudies-literature