Study of Morpho-Geometric Variables to Improve the Diagnosis in Keratoconus with Mild Visual Limitation

The validation of new methods for the diagnosis of incipient cases of Keratoconus (KC) with mild visual limitation is of great interest in the field of ophthalmology. During the asymmetric progression of the disease, the current diagnostic indexes do not record the geometric decompensation of the corneal curvature nor the variation of the spatial profile that occurs in singular points of the cornea. The purpose of this work is to determine the structural characterization of the asymmetry of the disease by using morpho-geometric parameters in KC eyes with mild visual limitation including using an analysis of a patient-specific virtual model with the aid of computer-aided design (CAD) tools. This comparative study included 80 eyes of patients classified as mild KC according to the degree of visual limitation and a control group of 122 eyes of normal patients. The metric with the highest area under the receiver operating characteristic (ROC) curve was the posterior apex deviation. The most prominent correlation was found between the anterior and posterior deviations of the thinnest point for the mild keratoconic cases. This new custom computational approach provides the clinician with a three-dimensional view of the corneal architecture when the visual loss starts to impair.

[1]  N. Maeda,et al.  Changes in anterior and posterior corneal curvatures in keratoconus. , 2000, Ophthalmology.

[3]  Aditi Dubey,et al.  Management of advanced corneal ectasias , 2015, British Journal of Ophthalmology.

[4]  P. Peña-garcía,et al.  Keratoconus Management Guidelines , 2015 .

[5]  J. Alió,et al.  Keratoconus Detection Based on a New Corneal Volumetric Analysis , 2017, Scientific Reports.

[6]  M. Borgstrom,et al.  Assessing progression of keratoconus: novel tomographic determinants , 2016, Eye and Vision.

[7]  Francesco Versaci,et al.  Use of a support vector machine for keratoconus and subclinical keratoconus detection by topographic and tomographic data. , 2012, Ophthalmology.

[8]  J. Alió,et al.  Placido-Based Indices of Corneal Irregularity , 2011, Optometry and vision science : official publication of the American Academy of Optometry.

[9]  Ferdinando Auricchio,et al.  A framework for designing patient‐specific bioprosthetic heart valves using immersogeometric fluid–structure interaction analysis , 2018, International journal for numerical methods in biomedical engineering.

[10]  E. Pellizzer,et al.  Effect of different types of prosthetic platforms on stress-distribution in dental implant-supported prostheses. , 2017, Materials science & engineering. C, Materials for biological applications.

[11]  D. R. Iskander,et al.  Optimal modeling of corneal surfaces with Zernike polynomials , 2001, IEEE Transactions on Biomedical Engineering.

[12]  David Elad,et al.  Biomechanical analysis of the keratoconic cornea. , 2009, Journal of the mechanical behavior of biomedical materials.

[13]  C. O'donnell,et al.  Reduction in Corneal Volume with Severity of Keratoconus , 2011, Current eye research.

[14]  Henryk T. Kasprzak,et al.  Non-rotational aspherical models of the human optical system , 2013 .

[15]  A. Pandolfi,et al.  A model for the human cornea: constitutive formulation and numerical analysis , 2006, Biomechanics and modeling in mechanobiology.

[16]  Neslihan Bayraktar Bilen,et al.  Correlation between visual function and refractive, topographic, pachymetric and aberrometric data in eyes with keratoconus. , 2016, International journal of ophthalmology.

[17]  K. Shimizu,et al.  Assessment of Anterior, Posterior, and Total Central Corneal Astigmatism in Eyes With Keratoconus. , 2015, American journal of ophthalmology.

[18]  Sundaram Natarajan,et al.  Keratoconus , 2013, Indian journal of ophthalmology.

[19]  Ehsan Samei,et al.  Can a 3D task transfer function accurately represent the signal transfer properties of low-contrast lesions in non-linear CT systems? , 2018, Medical Imaging.

[20]  J. Alió,et al.  Geometrical Custom Modeling of Human Cornea In Vivo and Its Use for the Diagnosis of Corneal Ectasia , 2014, PloS one.

[21]  Bernardo T. Lopes,et al.  Correlation of Topometric and Tomographic Indices with Visual Acuity in Patients with Keratoconus , 2012 .

[22]  Michael D Karon,et al.  Advantages and disadvantages of the Zernike expansion for representing wave aberration of the normal and aberrated eye. , 2004, Journal of refractive surgery.

[23]  William J Dupps,et al.  Biomechanics of corneal ectasia and biomechanical treatments. , 2014, Journal of cataract and refractive surgery.

[24]  L. Gallo,et al.  Displacement of teeth without and with bonded fixed orthodontic retainers: 3D analysis using triangular target frames and optoelectronic motion tracking device. , 2018, Journal of the mechanical behavior of biomedical materials.

[25]  Y. Rabinowitz,et al.  Keratoconus: Classification scheme based on videokeratography and clinical signs , 2009, Journal of cataract and refractive surgery.

[26]  Terry Kim,et al.  Anatomy and physiology of the cornea , 2011, Journal of cataract and refractive surgery.

[27]  J. Alió,et al.  A new approach to keratoconus detection based on corneal morphogeometric analysis , 2017, PloS one.

[28]  Rodivaldo H. Cunha,et al.  Keratoconus prediction using a finite element model of the cornea with local biomechanical properties. , 2009, Arquivos brasileiros de oftalmologia.

[29]  J. Alió,et al.  Keratoconus‐integrated characterization considering anterior corneal aberrations, internal astigmatism, and corneal biomechanics , 2011, Journal of cataract and refractive surgery.

[30]  B. Calvo,et al.  Computational Simulation of Scleral Buckling Surgery for Rhegmatogenous Retinal Detachment: On the Effect of the Band Size on the Myopization , 2016, Journal of ophthalmology.

[31]  Renato Ambrósio,et al.  Simplified Nomenclature for Describing Keratoconus , 2012 .

[32]  A. Sinha Roy,et al.  Patient-specific computational modeling of keratoconus progression and differential responses to collagen cross-linking. , 2011, Investigative ophthalmology & visual science.

[33]  A. Jiménez-Corona,et al.  Repeatability, reproducibility, and agreement between three different Scheimpflug systems in measuring corneal and anterior segment biometry. , 2014, Journal of refractive surgery.

[34]  D. Piñero,et al.  Characterization of corneal structure in keratoconus. , 2012, Journal of cataract and refractive surgery.

[35]  J. Alió,et al.  Correlation of Anterior and Posterior Corneal Shape in Keratoconus , 2013, Cornea.

[36]  Kevin Anderson,et al.  Application of structural analysis to the mechanical behaviour of the cornea , 2004, Journal of The Royal Society Interface.

[37]  J. Alió,et al.  Corneal volume, pachymetry, and correlation of anterior and posterior corneal shape in subclinical and different stages of clinical keratoconus , 2010, Journal of cataract and refractive surgery.

[38]  Wen-jia Xie Recent advances in laser in situ keratomileusis‐associated dry eye , 2016, Clinical & experimental optometry.