Finite element analysis of determining corneal biomechanical properties in vivo based on Corvis ST_Journal of Biomedical Engineering

Authors：

MENG Qiaoyu ¹ ,  WANG Xiaojun ¹ , CHEN Weiyi ² , LI Xiaona ² , HE Rui ³

1. College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, P.R.China;
2. College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, P.R.China;
3. Department of Excimer Laser, Shanxi Eye Hospital, Taiyuan 030002, P.R.China;

Corresponding author：

WANG Xiaojun, Email: wangxiaojun@tyut.edu.cn

Keywords：

cornea; biomechanics; Corvis ST; finite element model; laser assisted in situ keratomileusis

DOI：

10.7507/1001-5515.201911081

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The decrease of corneal stiffness is the key factor leading to keratoconus, and the corneal collagen fiber stiffness and fiber dispersion are closely related to the corneal biomechanical properties. In this paper, a finite element model of human cornea based on corneal microstructure, namely collagen fiber, was established before and after laser assisted in situ keratomileusis (LASIK). By simulating the Corvis ST process and comparing with the actual clinical results, the hyperelastic constitutive parameters and corneal collagen fiber stiffness modulus of the corneal material were determined before and after refractive surgery. After LASIK, the corneal collagen fiber stiffness modulus increased significantly, and was highly correlated with central corneal thickness (CCT). The predictive relationship between the corneal collagen fiber stiffness modulus and the corresponding CCT before and after surgery was: k_{1 before} = exp(9.14 − 0.009CCT_before), k_{1 after} = exp(8.82 − 0.008CCT_after). According to the results of this study, the central corneal thickness of the patient can be used to estimate the preoperative and postoperative collagen fiber stiffness modulus, and then a personalized corneal model that is more consistent with the actual situation of the patient can be established, providing a theoretical reference for more accurately predicting the safe surgical cutting amount of the cornea.

Citation： MENG Qiaoyu, WANG Xiaojun, CHEN Weiyi, LI Xiaona, HE Rui. Finite element analysis of determining corneal biomechanical properties in vivo based on Corvis ST. Journal of Biomedical Engineering, 2020, 37(4): 608-613. doi: 10.7507/1001-5515.201911081 Copy

1.	王聪聪, 谢永芳, 王国辉. 实验性高度近视眼巩膜胶原及弹性模量的变化. 医用生物力学, 2018, 33(2): 157-162.
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6.	Rohit S, Mathew F, Rushad S, <italic>et al</italic>. Corneal biomechanical changes and tissue remodeling after SMILE and LASIK. Invest Opthalmol Vis Sci, 2017, 58(13): 5703-5712.
7.	Hon Y, Chen G Z, Lu S H, <italic>et al</italic>. <italic>In vivo</italic> measurement of regional corneal tangent modulus. Sci Rep, 2017, 7(1): 14974.
8.	Pandolfi A, Holzapfel G A. Three-dimensional modeling and computational analysis of the human cornea considering distributed collagen fibril orientations. J Biomech Eng, 2008, 130(6): 061006.
9.	Karimi A, Razaghi R, Biglari H, <italic>et al</italic>. Collision of the glass shards with the eye: A computational fluid-structure interaction model. J Chem Neuroanat, 2018, 90: 80-86.
10.	Xu M, Lerner A L, Funkenbusch P D, <italic>et al</italic>. Sensitivity of corneal biomechanical and optical behavior to material parameters using design of experiments method. Comput Meth Biomech Biomed Eng, 2018, 21(3): 287-296.
11.	Wang X J, Li X N, Chen W Y, <italic>et al</italic>. Effects of ablation depth and repair time on the corneal elastic modulus after laser in situ keratomileusis. BioMed Eng OnLine, 2017, 16(1): 20.
12.	Ariza-Gracia M Á, Zurita J F, Piñero D P, <italic>et al</italic>. Coupled biomechanical response of the cornea assessed by non-contact tonometry. A simulation study. PLoS One, 2015, 10(3): e0121486.
13.	Ariza-Gracia M Á, Zurita J, Pi Ero D P, <italic>et al</italic>. Automatized patient-specific methodology for numerical determination of biomechanical corneal response. Ann Biomed Eng, 2016, 44(5): 1753-1772.
14.	Wang L K, Tian L, Zheng Y P. Determining <italic>in vivo</italic>, elasticity and viscosity with dynamic Scheimpflug imaging analysis in keratoconic and healthy eyes. J Biophoton, 2016, 9(5): 454-463.
15.	Zhang H X, Ahmad K M, Zhang D, <italic>et al</italic>. Corneal biomechanical properties after FS-LASIK with residual bed thickness less than 50% of the original corneal thickness. J Ophthalmol, 2018, 2018: 1-10.
16.	Grytz R, Günther M. A computational remodeling approach to predict the physiological architecture of the collagen fibril network in corneo-scleral shells. Biomech Model Mechanobiol, 2010, 9(2): 225-235.
17.	赵科超. 基于 ORA 及 Corvis ST 检测研究手术及病变对角膜生物力学特性的影响. 太原: 太原理工大学, 2019.

1. 王聪聪, 谢永芳, 王国辉. 实验性高度近视眼巩膜胶原及弹性模量的变化. 医用生物力学, 2018, 33(2): 157-162.
2. 董子献, 周行涛. 激光角膜屈光手术生物力学效应的研究进展. 中华眼科杂志, 2012, 48(11): 1053-1056.
3. 陈维毅, 李晓娜, 高志鹏. 眼力学研究进展. 医用生物力学, 2016, 31(4): 340-346.
4. Whitford C, Studer H, Boote C, <italic>et al</italic>. Biomechanical model of the human cornea: Considering shear stiffness and regional variation of collagen anisotropy and density. J Mech Behav Biomed Mater, 2015, 42: 76-87.
5. Sinha Roy A, Dupps W J, Roberts C J. Comparison of biomechanical effects of small-incision lenticule extraction and laser in situ keratomileusis: Finite-element analysis. J Cataract Refr Surg, 2014, 40(6): 971-980.
6. Rohit S, Mathew F, Rushad S, <italic>et al</italic>. Corneal biomechanical changes and tissue remodeling after SMILE and LASIK. Invest Opthalmol Vis Sci, 2017, 58(13): 5703-5712.
7. Hon Y, Chen G Z, Lu S H, <italic>et al</italic>. <italic>In vivo</italic> measurement of regional corneal tangent modulus. Sci Rep, 2017, 7(1): 14974.
8. Pandolfi A, Holzapfel G A. Three-dimensional modeling and computational analysis of the human cornea considering distributed collagen fibril orientations. J Biomech Eng, 2008, 130(6): 061006.
9. Karimi A, Razaghi R, Biglari H, <italic>et al</italic>. Collision of the glass shards with the eye: A computational fluid-structure interaction model. J Chem Neuroanat, 2018, 90: 80-86.
10. Xu M, Lerner A L, Funkenbusch P D, <italic>et al</italic>. Sensitivity of corneal biomechanical and optical behavior to material parameters using design of experiments method. Comput Meth Biomech Biomed Eng, 2018, 21(3): 287-296.
11. Wang X J, Li X N, Chen W Y, <italic>et al</italic>. Effects of ablation depth and repair time on the corneal elastic modulus after laser in situ keratomileusis. BioMed Eng OnLine, 2017, 16(1): 20.
12. Ariza-Gracia M Á, Zurita J F, Piñero D P, <italic>et al</italic>. Coupled biomechanical response of the cornea assessed by non-contact tonometry. A simulation study. PLoS One, 2015, 10(3): e0121486.
13. Ariza-Gracia M Á, Zurita J, Pi Ero D P, <italic>et al</italic>. Automatized patient-specific methodology for numerical determination of biomechanical corneal response. Ann Biomed Eng, 2016, 44(5): 1753-1772.
14. Wang L K, Tian L, Zheng Y P. Determining <italic>in vivo</italic>, elasticity and viscosity with dynamic Scheimpflug imaging analysis in keratoconic and healthy eyes. J Biophoton, 2016, 9(5): 454-463.
15. Zhang H X, Ahmad K M, Zhang D, <italic>et al</italic>. Corneal biomechanical properties after FS-LASIK with residual bed thickness less than 50% of the original corneal thickness. J Ophthalmol, 2018, 2018: 1-10.
16. Grytz R, Günther M. A computational remodeling approach to predict the physiological architecture of the collagen fibril network in corneo-scleral shells. Biomech Model Mechanobiol, 2010, 9(2): 225-235.
17. 赵科超. 基于 ORA 及 Corvis ST 检测研究手术及病变对角膜生物力学特性的影响. 太原: 太原理工大学, 2019.

Journal of Biomedical Engineering

Finite element analysis of determining corneal biomechanical properties in vivo based on Corvis ST

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