Fluid-Structure Interaction Based Algorithms for IOP and Corneal Material Behavior

Purpose: This paper presents and clinically validates two algorithms for estimating intraocular pressure (IOP) and corneal material behavior using numerical models that consider the fluid-structure interaction between the cornea and the air-puff used in non-contact tonometry. Methods: A novel multi-physics fluid-structure interaction model of the air-puff test was employed in a parametric numerical study simulating human eyes under air-puff pressure with a wide range of central corneal thickness (CCT = 445–645 μm), curvature (R = 7.4–8.4 mm), material stiffness and IOP (10–25 mmHg). Models were internally loaded with IOP using a fluid cavity, then externally with air-puff loading simulated using a turbulent computational fluid dynamics model. Corneal dynamic response parameters were extracted and used in development of two algorithms for IOP and corneal material behavior; fIOP and fSSI, respectively. The two algorithms were validated against clinical corneal dynamic response parameters for 476 healthy participants. The predictions of IOP and corneal material behavior were tested on how they varied with CCT, R, and age. Results: The present study produced a biomechanically corrected estimation of intraocular pressure (fIOP) and a corneal material stiffness parameter or Stress-Strain Index (fSSI), both of which showed no significant correlation with R (p > 0.05) and CCT (p > 0.05). Further, fIOP had no significant correlation with age (p > 0.05), while fSSI was significantly correlated with age (p = 0.001), which was found earlier to be strongly correlated with material stiffness. Conclusion: The present study introduced two novel algorithms for estimating IOP and biomechanical material behavior of healthy corneas in-vivo. Consideration of the fluid structure interaction between the cornea and the air puff of non-contact tonometry in developing these algorithms led to improvements in performance compared with bIOP and SSI

Role of impinging jets in the biomechanical correction of the intraocular pressure ( IOP ) measurement

Glaucoma is one of the ocular diseases which develops when the eye internal fluid cannot drain properly and intraocular pressure builds up. This can result in damage to the optic nerve and the nerve fibers from the retina and early diagnosis is very important as any damage to the eyes cannot be reversed [1]–[3]. Non-contact IOP measurement techniques like corneal response analyzers including CorVis-ST are very popular. The technique depends on impingement of an air puff to the cornea and recording the corneal response to the impact force from the puff using high speed Scheimpflug imaging. The aim of this study is to improve the accuracy of the IOP measurements by considering the fluid structure interaction effect between the cornea, the air puff and the eye internal fluid through a parametric study of numerical models and their comparisons with the clinical data

Fluid Structure Interaction (FSI) simulation of the human eye under the air puff tonometry using Computational Fluid Dynamics (CFD)

The air puff test is a non-contact method used in different areas to investigate the material behaviour or the biomechanical properties of biological tissues such as skin, cornea, and soft tissue tumours and also to study fruit firmness or meat tenderness. For the human eye, having a valid and fully coupled numerical simulation of the air puff test is very helpful and can greatly benefit to reduce a lot of time and cost of experimental testing. The gab in research in this area is considering the fluid structure interaction effect between the cornea, the air puff and the eye internal fluid. The simulation of the air puff test on the human eye is a Multi-physics problem which means; coupling between different numerical models and solvers with different governing equations and exchanging the data between them during the solution. A Computational Fluid Dynamics (CFD) model has been generated for an impinging air jet of maximum velocity of 168 m/s over a time span of 30ms and a coupling between the CFD model and the Finite Element (FE) model of the human eye has been successfully achieved for accurate simulation of the Fluid Structure Interaction (FSI) effect on the human eye cornea deformation. The air puff test is a non-contact method used in different areas to investigate the material behaviour or the biomechanical properties of biological tissues such as skin, cornea, and soft tissue tumours and also to study fruit firmness or meat tenderness. For the human eye, having a valid and fully coupled numerical simulation of the air puff test is very helpful and can greatly benefit to reduce a lot of time and cost of experimental testing. The gab in research in this area is considering the fluid structure interaction effect between the cornea, the air puff and the eye internal fluid. The simulation of the air puff test on the human eye is a Multi-physics problem which means; coupling between different numerical models and solvers with different governing equations and exchanging the data between them during the solution. A Computational Fluid Dynamics (CFD) model has been generated for an impinging air jet of maximum velocity of 168 m/s over a time span of 30ms and a coupling between the CFD model and the Finite Element (FE) model of the human eye has been successfully achieved for accurate simulation of the Fluid Structure Interaction (FSI) effect on the human eye cornea deformation

An investigation on transient flow behaviour in pulsating channel flows

DNS has been used to investigate the transient behaviour of turbulence for the pulsating flows. An in-house DNS/LES code, CHAPSim, has been adopted and used for the study. Simulations have been performed for channel flow at Reynolds number of Rem=2800, where Reynolds number is based on the time-averaged bulk velocity and channel half-height. A wide range of pulsating frequencies and amplitudes has been simulated. Turbulence statistics and detailed flow behaviour are examined. Where possible, the simulations are validated against the physical experiments. The preliminarily results show strong similarity between the pulsating and accelerating/decelerating flow for the behaviour of turbulence in the transient period. The transient development of the flow is characterised by a two-stage process resembling pre-transition and transition stages of boundary layer bypass transition (laminar-turbulent) and corresponding stages reported, in the literature, for the individual accelerating/decelerating (turbulent-turbulent) flows. The elongated low- and high-speed streaks are exhibited during the early stages of the transition. This is reflected into immediate but gradual response of the streamwise fluctuating velocities in the near-wall region while it remains almost unchanged in the core region. The wall-normal and spanwise components remain also approximately unchanged during the pre-transition stage and until the onset of transition when the fluctuating velocities and the Reynolds stress exhibit rapid changes

Patient-specific air puff-induced loading using machine learning

Introduction: The air puff test is a contactless tonometry test used to measure the intraocular pressure and the cornea’s biomechanical properties. Limitations that most challenge the accuracy of the estimation of the corneal material and the intraocular pressure are the strong intercorrelation between the intraocular pressure and the corneal parameters, either the material properties that can change from one person to another because of age or the geometry parameters like central corneal thickness. This influence produces inaccuracies in the corneal deformation parameters while extracting the IOP parametric equation, which can be reduced through the consideration of the patient-specific air puff pressure distribution taking into account the changes in corneal parameters. This air puff pressure loading distribution can be determined precisely from the fluid-structure interaction (FSI) coupling between the air puff and the eye model. However, the computational fluid dynamics simulation of the air puff in the coupling algorithm is a time-consuming model that is impractical to use in clinical practice and large parametric studies. Methods: By using a supervised machine learning algorithm, we predict the time-dependent air puff pressure distribution for different corneal parameters via a parametric study of the corneal deformations and the gradient boosting algorithm. Results: The results confirmed that the algorithm gives the time-dependent air puff pressure distribution with an MAE of 0.0258, an RMSE of 0.0673, and an execution time of 93 s, which is then applied to the finite element model of the eye generating the corresponding corneal deformations taking into account the FSI influence. Using corneal deformations, the response parameters can be extracted and used to produce more accurate algorithms of the intraocular pressure and corneal material stress-strain index (SSI). Discussion: Estimating the distribution of air pressure on the cornea is essential to increase the accuracy of intraocular pressure (IOP) measurements, which serve as valuable indicator of corneal disease. We find that the air puff pressure loading is largely influenced by complex changes in corneal parameters unique to each patient case. With our innovative algorithm, we can preserve the same accuracy developed by the CFD-based FSI model, while reducing the computational time from approximately 101000 s (28 h) to 720 s (12 min), which is about 99.2% reduction in time. This huge improvement in computational cost will lead to significant improvement in the parametric equations for IOP and the Stress-Strain Index (SSI)

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

Purpose: To improve numerical simulation of the non-contact tonometry test by using Arbitrary Eulerian-Lagrangian 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 consisted of 25920 wedge6 elements and employed Spallart-Allmaras model to simulate capture turbulence of the air jet. The time span of the jet wais 30 ms and maximum Reynolds numbe

Controlling the properties of the micellar and gel phase by varying the counterion in functionalised-dipeptide systems

The micellar aggregates formed at high pH for dipeptide-based gelators can be varied by using different alkali metal salts to prepare the solutions. The nature of the micellar aggregates directly affects the properties of the resulting gels

Ex-vivo experimental validation of biomechanically-corrected intraocular pressure measurements on human eyes using the CorVis ST

The purpose of this study was to assess the validity of the Corvis ST (Oculus; Wetzlar, Germany) biomechanical correction algorithm (bIOP) in determining intraocular pressure (IOP) using experiments on ex-vivo human eyes. Five ex-vivo human ocular globes (age 69 ± 3 years) were obtained and tested within 3–5 days post mortem. Using a custom-built inflation rig, the internal pressure of the eyes was controlled mechanically and measured using the CorVis ST (CVS-IOP). The CVS-IOP measurements were then corrected to produce bIOP, which was developed for being less affected by variations in corneal biomechanical parameters, including tissue thickness and material properties. True IOP (IOPt) was defined as the pressure inside of the globe as monitored using a fixed pressure transducer. Statistical analyses were performed to assess the accuracy of both CVS-IOP and bIOP, and their correlation with corneal thickness. While no significant differences were found between bIOP and IOPt (0.3 ± 1.6 mmHg, P = 0.989) using ANOVA and Bonferroni Post-Hoc test, the differences between CVS-IOP and IOPt were significant (7.5 ± 3.2 mmHg, P < 0.001). Similarly, bIOP exhibited no significant correlation with central corneal thickness (p = 0.756), whereas CVS-IOP was significantly correlated with the thickness (p < 0.001). The bIOP correction has been successful in providing close estimates of true IOP in ex-vivo tests conducted on human donor eye globes, and in reducing association with the cornea's thickness

Fluid-structure interaction based algorithms for IOP and corneal material behavior

Purpose: This paper presents and clinically validates two algorithms for estimating intraocular pressure (IOP) and corneal material behavior using numerical models that consider the fluid-structure interaction between the cornea and the air-puff used in non-contact tonometry. Methods: A novel multi-physics fluid-structure interaction model of the air-puff test was employed in a parametric numerical study simulating human eyes under air-puff pressure with a wide range of central corneal thickness (CCT = 445–645 μm), curvature (R = 7.4–8.4 mm), material stiffness and IOP (10–25 mmHg). Models were internally loaded with IOP using a fluid cavity, then externally with air-puff loading simulated using a turbulent computational fluid dynamics model. Corneal dynamic response parameters were extracted and used in development of two algorithms for IOP and corneal material behavior; fIOP and fSSI, respectively. The two algorithms were validated against clinical corneal dynamic response parameters for 476 healthy participants. The predictions of IOP and corneal material behavior were tested on how they varied with CCT, R, and age. Results: The present study produced a biomechanically corrected estimation of intraocular pressure (fIOP) and a corneal material stiffness parameter or Stress-Strain Index (fSSI), both of which showed no significant correlation with R (p > 0.05) and CCT (p > 0.05). Further, fIOP had no significant correlation with age (p > 0.05), while fSSI was significantly correlated with age (p = 0.001), which was found earlier to be strongly correlated with material stiffness. Conclusion: The present study introduced two novel algorithms for estimating IOP and biomechanical material behavior of healthy corneas in-vivo. Consideration of the fluid structure interaction between the cornea and the air puff of non-contact tonometry in developing these algorithms led to improvements in performance compared with bIOP and SSI