Determination of Corneal Elasticity Coefficient Using the ORA Database

Sé, Avetisov; Ia, Novikov; Ia, Bubnova; Antonov, A.A.; Siplivy, V. I.

doi:10.3928/1081597x-20091030-01

Cited by 26 publications

(16 citation statements)

References 4 publications

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“…Avetisov et al developed an elasticity coefficient from the ORA applanation curve that describes velocity change occurring at the end of applanation. 28 Touboul et al proposed a variable (CH-CRF) expressing the difference between CH and CRF that was greater in KC and post-LASIK corneas while rare in normal and glaucoma study groups. 20 Schweitzer et al investigated some aspects of the infrared signal (peak amplitude 1, peak amplitude 2, width of peak 1 at half the maximum value, and width of peak 2 at half the maximum value) and air pressure curve (P1, P2, Pmax and time at these points) and found that all but the width of peak 2 at half the maximum value were significantly lower in KC when compared to CCT-matched healthy corneas; however, significant overlap existed for the variables.…”

Section: Discussionmentioning

confidence: 99%

Discriminant Value of Custom Ocular Response Analyzer Waveform Derivatives in Keratoconus

et al. 2014

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Purpose To evaluate the performance of corneal hysteresis (CH), corneal resistance factor (CRF), and 16 investigator-derived Ocular Response Analyzer (ORA) variables in distinguishing keratoconus (KC) from the non-diseased state. Design Retrospective case series. Participants Fifty-four eyes of 27 unaffected patients and 49 eyes of 25 KC patients from the Instituto de Olhos, Rio de Janeiro, Brazil. Methods Sixteen candidate variables were derived from exported ORA signals to characterize putative indicators of biomechanical behavior. Area under the receiver operating characteristic curve (AUROC) and the Z-statistic were used to compare diagnostic performance. Main Outcome Measures Discriminant value of standard and derived ORA variables as measured by AUROC. Results Fifteen of 16 candidate variables performed significantly better than chance (AUROC > 0.5) at discriminating KC. Diagnostic performance was greatest for a custom variable related to the depth of deformation (ConcavityMin (0.985±0.002, mean AUROC±standard error) and a new measure incorporating the pressure-deformation relationship of the entire response cycle (Hysteresis Loop Area (HLA) 0.967 ± 0.002). Z statistics assessing the discriminative value of each of the top 5 variables demonstrated superiority to CH (AUROC 0.862 ± 0.002). ConcavityMin had the best overall predictive accuracy (cutoff value 50.37, 94.9% sensitivity, 91.7% specificity and 93.2% test accuracy), and the top 4 variables demonstrated the most consistent relationships to KC severity. Conclusions Investigator-derived ORA variables related to the depth of deformation and the pressure-deformation relationship demonstrated very high test accuracy for detecting presence of keratoconus. Beyond their diagnostic value, the candidate variables described in this report provide mechanistic insight into the nature of the ORA signal and the characteristic changes in corneal dynamics associated with keratoconus.

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Section: Discussionmentioning

confidence: 99%

Discriminant Value of Custom Ocular Response Analyzer Waveform Derivatives in Keratoconus

et al. 2014

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“…There are several studies in the literature analyzing aspects of the Ocular Response Analyzer corneal deformation signal waveform other than CH and CRF. 12,13 The clinical significance of these various waveform parameters is currently unknown. The purpose of our study was to identify which of the new parameters could differentiate post-femtosecond LASIK corneas from those with manifest keratoconus after controlling for potential confounding factors such as CCT and age.…”

Section: Discussionmentioning

confidence: 99%

Corneal deformation signal waveform analysis in keratoconic versus post-femtosecond laser in situ keratomileusis eyes after statistical correction for potentially confounding factors

Zarei‐Ghanavati

Ramírez-Miranda

et al. 2012

Journal of Cataract and Refractive Surgery

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“…Although a low CH (<8 mm Hg) might be a predictive index of a preectatic conditions [3, 33], the overlap in the distribution of both CH and CRF values within the normal population does not support a role for CH and CRF measurement as single predictors to detect early ectasia or to predict its onset before surgery [91]. Instead, waveform analysis of ORA signals [33, 82, 92] has shown that the morphology of the signal may provide additional information. For instance, in a case of iatrogenic ectasia after LASIK, Kerautret et al [33] found a lower Peak 1 height in the ectatic eye than in the fellow nonectatic eye, despite the similar CH and CRF values in the 2 eyes.…”

Section: Factors Affecting Corneal Biomechanical Propertiesmentioning

confidence: 99%

Corneal Biomechanical Properties in Different Ocular Conditions and New Measurement Techniques

et al. 2014

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Several refractive and therapeutic treatments as well as several ocular or systemic diseases might induce changes in the mechanical resistance of the cornea. Furthermore, intraocular pressure measurement, one of the most used clinical tools, is also highly dependent on this characteristic. Corneal biomechanical properties can be measured now in the clinical setting with different instruments. In the present work, we review the potential role of the biomechanical properties of the cornea in different fields of ophthalmology and visual science in light of the definitions of the fundamental properties of matter and the results obtained from the different instruments available. The body of literature published so far provides an insight into how the corneal mechanical properties change in different sight-threatening ocular conditions and after different surgical procedures. The future in this field is very promising with several new technologies being applied to the analysis of the corneal biomechanical properties.

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Determination of Corneal Elasticity Coefficient Using the ORA Database

Abstract: The elasticity coefficient calculated using the ORA applanation curve can be used in the evaluation of corneal biomechanical properties.

Cited by 26 publications

References 4 publications

Discriminant Value of Custom Ocular Response Analyzer Waveform Derivatives in Keratoconus

Discriminant Value of Custom Ocular Response Analyzer Waveform Derivatives in Keratoconus

Corneal deformation signal waveform analysis in keratoconic versus post-femtosecond laser in situ keratomileusis eyes after statistical correction for potentially confounding factors

Corneal Biomechanical Properties in Different Ocular Conditions and New Measurement Techniques

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