Haixia Zhang1,2, Ashkan Eliasy1, Bernardo Lopes1, Ahmed Abass3,4, Riccardo Vinciguerra5,6, Paolo Vinciguerra7,8, Renato Ambrósio9,10, Cynthia J Roberts11, Ahmed Elsheikh1,12,13. 1. School of Engineering, University of Liverpool, Liverpool, United Kingdom. 2. School of Biomedical Engineering, Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China. 3. Department of Mechanical, Materials and Aerospace Engineering, School of Engineering, University of Liverpool, Liverpool, United Kingdom. 4. Department of Production Engineering and Mechanical Design, Faculty of Engineering, Port Said University, Port Fouad, Egypt. 5. Department of Ophthalmology, Humanitas San Pio X Hospital, Milan, Italy. 6. The School of Engineering, University of Liverpool, Liverpool, United Kingdom. 7. Humanitas Clinical and Research Center, IRCCS, Rozzano, Italy. 8. Department of Biomedical Sciences, Humanitas University, Milan, Italy. 9. Department of Ophthalmology, Federal University of São Paulo (UNIFESP), São Paulo, Brazil. 10. Department of Ophthalmology, Federal University of the State of Rio de Janeiro (UNIRIO), Rio de Janeiro, Brazil. 11. Department of Ophthalmology and Visual Sciences and Biomedical Engineering, The Ohio State University, Columbus, OH, United States. 12. Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China. 13. NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust, UCL Institute of Ophthalmology, London, United Kingdom.
Abstract
PURPOSE: To introduce a new method to map the mechanical stiffness of healthy and keratoconic corneas. METHODS: Numerical modeling based on the finite element method was used to carry out inverse analysis of simulated healthy and keratoconic corneas to determine the regional variation of mechanical stiffness across the corneal surface based on established trends in collagen fibril distribution. The Stress-Strain Index (SSI), developed and validated in an earlier study and presented as a parameter that can estimate the overall stress-strain behavior of corneal tissue, was adopted in this research as a measure of corneal stiffness. The regional variation of SSI across the corneal surface was estimated using inverse analysis while referring to the common features of collagen fibrils' distribution obtained from earlier x-ray scattering studies. Additionally, for keratoconic corneas, a method relating keratoconic cone features and cornea's refractive power to the reduction in collagen fibril density inside the cone was implemented in the development of SSI maps. In addition to the simulated cases, the study also included two keratoconus cases, for which SSI maps were developed. RESULTS: SSI values varied slightly across corneal surface in the simulated healthy eyes. In contrast, both simulated and clinical keratoconic corneas demonstrated substantial reductions in SSI values inside the cone. These SSI reductions depended on the extent of the disease and increased with more considerable simulated losses in fibril density in the cone area. SSI values and their regional variation showed little change with changes in IOP, corneal thickness, and curvature. CONCLUSION: SSI maps provide an estimation of the regional variation of biomechanical stiffness across the corneal surface. The maps could be particularly useful in keratoconic corneas, demonstrating the dependence of corneal biomechanical behavior on the tissue's microstructure and offering a tool to fundamentally understand the mechanics of keratoconus progression in individual patients.
PURPOSE: To introduce a new method to map the mechanical stiffness of healthy and keratoconic corneas. METHODS: Numerical modeling based on the finite element method was used to carry out inverse analysis of simulated healthy and keratoconic corneas to determine the regional variation of mechanical stiffness across the corneal surface based on established trends in collagen fibril distribution. The Stress-Strain Index (SSI), developed and validated in an earlier study and presented as a parameter that can estimate the overall stress-strain behavior of corneal tissue, was adopted in this research as a measure of corneal stiffness. The regional variation of SSI across the corneal surface was estimated using inverse analysis while referring to the common features of collagen fibrils' distribution obtained from earlier x-ray scattering studies. Additionally, for keratoconic corneas, a method relating keratoconic cone features and cornea's refractive power to the reduction in collagen fibril density inside the cone was implemented in the development of SSI maps. In addition to the simulated cases, the study also included two keratoconus cases, for which SSI maps were developed. RESULTS: SSI values varied slightly across corneal surface in the simulated healthy eyes. In contrast, both simulated and clinical keratoconic corneas demonstrated substantial reductions in SSI values inside the cone. These SSI reductions depended on the extent of the disease and increased with more considerable simulated losses in fibril density in the cone area. SSI values and their regional variation showed little change with changes in IOP, corneal thickness, and curvature. CONCLUSION: SSI maps provide an estimation of the regional variation of biomechanical stiffness across the corneal surface. The maps could be particularly useful in keratoconic corneas, demonstrating the dependence of corneal biomechanical behavior on the tissue's microstructure and offering a tool to fundamentally understand the mechanics of keratoconus progression in individual patients.
Authors: Leon C Ho; Ian A Sigal; Ning-Jiun Jan; Alexander Squires; Zion Tse; Ed X Wu; Seong-Gi Kim; Joel S Schuman; Kevin C Chan Journal: Invest Ophthalmol Vis Sci Date: 2014-08-07 Impact factor: 4.799
Authors: Alejandro Rodriguez-Garcia; Raul Alfaro-Rangel; Andres Bustamante-Arias; Julio C Hernandez-Camarena Journal: J Ophthalmic Vis Res Date: 2020-08-06
Authors: Dong Zhou; Ashkan Eliasy; Ahmed Abass; Petar Markov; Charles Whitford; Craig Boote; Alexander Movchan; Natalia Movchan; Ahmed Elsheikh Journal: PLoS One Date: 2019-04-01 Impact factor: 3.240
Authors: Bernardo T Lopes; Prema Padmanabhan; Ashkan Eliasy; Haixia Zhang; Ahmed Abass; Ahmed Elsheikh Journal: Front Bioeng Biotechnol Date: 2022-06-08