Adaptive finite element eye model for the compensation of biometric influences on acoustic tonometry.
Corneal vibration
Eye model
FEM
Glaucoma
Intraocular pressure
Transient simulation
Journal
Computer methods and programs in biomedicine
ISSN: 1872-7565
Titre abrégé: Comput Methods Programs Biomed
Pays: Ireland
ID NLM: 8506513
Informations de publication
Date de publication:
Mar 2021
Mar 2021
Historique:
received:
02
07
2020
accepted:
04
01
2021
pubmed:
25
1
2021
medline:
15
5
2021
entrez:
24
1
2021
Statut:
ppublish
Résumé
Glaucoma is currently a major cause for irreversible blindness worldwide. A risk factor and the only therapeutic control parameter is the intraocular pressure (IOP). The IOP is determined with tonometers, whose measurements are inevitably influenced by the geometry of the eye. Even though the corneal mechanics have been investigated to improve accuracy of Goldmann and air pulse tonometry, influences of geometric properties of the eye on an acoustic self-tonometer approach are still unresolved. In order to understand and compensate for measurement deviations resulting from the geometric uniqueness of eyes, a finite element eye model is designed that considers all relevant eye components and is adjustable to all physiological shapes of the human eye. The general IOP-dependent behavior of the eye model is validated by laboratory measurements on porcine eyes. The difference between simulation and measurement is below 8 µm for IOP levels from 5 to 40 mmHg. The adaptive eye model is then used to quantify systematic uncertainty contributions of a variation of eye length and central corneal thickness based on input statistics of a clinical trial series. The adaptive eye model provides the required relation between biometric eye parameters and the corneal deflection amplitude, which here is the measured quantity to trace back to the IOP. Implementing the relations provided by the eye model in a Gaussian uncertainty propagation calculation now allows the quantification of the uncertainty contributions of the biometric parameters on the overall measurement uncertainty of the acoustic self-tonometer. As a result, a systematic uncertainty contribution resulting from deviations in eye length dominate stochastic deviations of the sensor equipment by a factor of 3.5. As perspective, the proposed adaptive eye model provides the basis to compensate for systematic deviations of (but not only) the acoustic self-tonometer.
Sections du résumé
BACKGROUND AND OBJECTIVE
OBJECTIVE
Glaucoma is currently a major cause for irreversible blindness worldwide. A risk factor and the only therapeutic control parameter is the intraocular pressure (IOP). The IOP is determined with tonometers, whose measurements are inevitably influenced by the geometry of the eye. Even though the corneal mechanics have been investigated to improve accuracy of Goldmann and air pulse tonometry, influences of geometric properties of the eye on an acoustic self-tonometer approach are still unresolved.
METHODS
METHODS
In order to understand and compensate for measurement deviations resulting from the geometric uniqueness of eyes, a finite element eye model is designed that considers all relevant eye components and is adjustable to all physiological shapes of the human eye.
RESULTS
RESULTS
The general IOP-dependent behavior of the eye model is validated by laboratory measurements on porcine eyes. The difference between simulation and measurement is below 8 µm for IOP levels from 5 to 40 mmHg. The adaptive eye model is then used to quantify systematic uncertainty contributions of a variation of eye length and central corneal thickness based on input statistics of a clinical trial series. The adaptive eye model provides the required relation between biometric eye parameters and the corneal deflection amplitude, which here is the measured quantity to trace back to the IOP. Implementing the relations provided by the eye model in a Gaussian uncertainty propagation calculation now allows the quantification of the uncertainty contributions of the biometric parameters on the overall measurement uncertainty of the acoustic self-tonometer. As a result, a systematic uncertainty contribution resulting from deviations in eye length dominate stochastic deviations of the sensor equipment by a factor of 3.5.
CONCLUSION
CONCLUSIONS
As perspective, the proposed adaptive eye model provides the basis to compensate for systematic deviations of (but not only) the acoustic self-tonometer.
Identifiants
pubmed: 33486338
pii: S0169-2607(21)00004-3
doi: 10.1016/j.cmpb.2021.105930
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
105930Informations de copyright
Copyright © 2021 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest Authors declare that they have no conflicts of interest.