Correlation of Anterior and Posterior Corneal Shape in Keratoconus

Montalbán, Raúl; Alió, Jorge L.; Javaloy, Jaime; Piñero, David P.

doi:10.1097/ico.0b013e3182904950

Cited by 30 publications

(40 citation statements)

References 22 publications

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“…error: 0.038, 95% confidence interval: 0.849-0.988), with a cut-off value of 0.099 mm, and an associated sensitivity and specificity of 90.01% and 88.41%, respectively; sagittal plane area at minimum thickness point (area under the ROC curve: 0.853, p < 0.0001, std. error: 0.039, 95% confidence interval: 0.780-0.932), with a cut-off value of 4.266 mm 2 , and an associated sensitivity and specificity of 62.02% and 91.07%, respectively; posterior minimum thickness point deviation (area under the ROC curve: 0.694, p < 0.0001, std. error: 0.059, 95% confidence interval: 0.577-0.812), with a cut-off value of 0.0855 mm, and an associated sensitivity and specificity of 63.1% and 91.11%, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…This study included 55 healthy eyes that did not present any ocular pathology [2], constituting 30 females (54.5%) and 25 males (45.5%), and 52 eyes diagnosed with keratoconus (KC) in grade I [35] formed by 27 females (51.9%) and 25 males (48.1%). Table 1 shows the morphological, refractive, and visual outcomes in the two groups of eyes analysed during the study.…”

Section: Resultsmentioning

confidence: 99%

“…However, three opposing characteristics can be seen due to the lack of symmetry: surfaces do not present symmetry of revolution, so they have deformations, misalignments, and decentralizations. For this reason, the analysis of the corneal geometry by studying the changes in its morphogeometric properties is fundamental to the assessment of vision quality and to improve the diagnosis of corneal pathologies [2].…”

Section: Introductionmentioning

confidence: 99%

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A Study for Parametric Morphogeometric Operators to Assist the Detection of Keratoconus

et al. 2017

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Abstract:The aim of this study is to describe a new keratoconus detection method based on the analysis of certain parametric morphogeometric operators extracted from a custom patient-specific three-dimensional (3D) model of the human cornea. A corneal geometric reconstruction is firstly performed using zonal functions and retrospective Scheimpflug tomography data from 107 eyes of 107 patients. The posterior corneal surface is later analysed using an optimised computational geometry technique and the morphology of healthy and keratoconic corneas is characterized by means of geometric variables. The performance of these variables as predictors of a new geometric marker is assessed through a receiver operating characteristic (ROC) curve analysis and their correlations are analysed through Pearson or Spearman coefficients. The posterior apex deviation variable shows the best keratoconus diagnosis capability. However, the strongest correlations in both healthy and pathological corneas are provided by the metrics directly related to the thickness as the sagittal plane area at the apex and the sagittal plane area at the minimum thickness point. A comparison of the screening of keratoconus provided by the Sirius topographer and the detection of corneal ectasia using the posterior apex deviation parameter is also performed, demonstrating the accuracy of this characterization as an effective marker of the diagnosis and ectatic disease progression.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Study for Parametric Morphogeometric Operators to Assist the Detection of Keratoconus

et al. 2017

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“…In most cases imaging was done using a Sirius topographer (CSO, http://www.csoitalia.it/en/asp/home.asp?prod=1&dbpID=17) although a subset of patients were imaged using the Orbscan II (Orbtek) . The Sirius is a new topography device that has been validated in KC screening …”

Section: Methodsmentioning

confidence: 99%

“…37 The Sirius is a new topography device that has been validated in KC screening. 38 At least three photos of each eye were usually taken, although only the best was saved. The corneal map of each participant was examined and a common KC pattern was characterized by asymmetric bow-tie with a skewed radial axis 3 and KC screening indices.…”

Section: Methodsmentioning

confidence: 99%

Risk factors for keratoconus in Israel: a case–control study

Gordon‐Shaag

Millodot

Kaiserman³

et al. 2015

Ophthalmic Physiologic Optic

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Efficacy of Morpho-Geometrical Analysis of the Corneal Surfaces in Keratoconus Disease According to Moderate Visual Limitation

Cavas

Fernández-Pacheco

Barrio

et al. 2020

Lecture Notes in Mechanical Engineering

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The cornea is a complex hemispheric structure, made of collagen fibres that provide it a homogenous and stable geometry. During keratoconus disease, a loss of tenacity takes place in the collagen fibres that form the corneal structure, producing an alteration of its geometry, this is, a change of its curvature, and therefore, a loss of visual quality of patients. The geometric characterization of the hemispheric structure by means of biometric parameters is a very solid technique of diagnosis, based in a virtual 3D model, which has already been validated for several degrees of severity of keratoconus pathology. In this prospective comparative study, 93 corneas (50 healthy subjects and 43 patients with keratoconus with moderate visual limitation) were geometrically modelled. The results obtained in this work suggest that the best predictive biometric parameters are anterior corneal surface area and posterior apex deviation, and that the strongest correlation is produced between sagittal plane apex area in minimum thickness point and sagittal plane apex area. The studied biometric parameters have shown significant differences between groups. Therefore, the analysis of the biometric parameters that register the geometric decompensation that locally appear in a corneal region, as a response to the asymmetry produced during the development of keratoconus disease with a moderate visual impairment, is a new approach that may lead to a better understanding of the disease with this degree of optical limitation.

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Correlation of Anterior and Posterior Corneal Shape in Keratoconus

Abstract: Central posterior corneal curvature and shape factor in the keratoconus eye can be consistently predicted from the anterior corneal curvature and shape factor, respectively, in combination with other anatomical and ocular parameters.

Cited by 30 publications

References 22 publications

A Study for Parametric Morphogeometric Operators to Assist the Detection of Keratoconus

A Study for Parametric Morphogeometric Operators to Assist the Detection of Keratoconus

Risk factors for keratoconus in Israel: a case–control study

Efficacy of Morpho-Geometrical Analysis of the Corneal Surfaces in Keratoconus Disease According to Moderate Visual Limitation

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