International Journal of Keratoconus and Ectatic Corneal Diseases

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VOLUME 2 , ISSUE 3 ( September-December, 2013 ) > List of Articles

RESEARCH ARTICLE

Accuracy of Topometric Indices for Distinguishing between Keratoconic and Normal Corneas

Bernardo Lopes, Isaac C Ramos, Bruno F Valbon, Marcella Q Salomao, Frederico P Guerra, Livia F Jordao, Ana Laura C Canedo, Rosane Correa

Citation Information : Lopes B, Ramos IC, Valbon BF, Salomao MQ, Guerra FP, Jordao LF, Canedo AL, Correa R. Accuracy of Topometric Indices for Distinguishing between Keratoconic and Normal Corneas. Int J Kerat Ect Cor Dis 2013; 2 (3):108-112.

DOI: 10.5005/jp-journals-10025-1062

Published Online: 00-12-2013

Copyright Statement:  Copyright © 2013; Jaypee Brothers Medical Publishers (P) Ltd.


Abstract

Purpose

To evaluate the sensitivity and specificity of the Pentacam topometric indices derived from the corneal surface curvature to distinguish between normal and keratoconic corneas.

Methods

The study consisted of 226 normal corneas from 113 patients and 88 keratoconic eyes from 44 patients. Eyes were defined as keratoconus based on comprehensive ocular examination, including Placido-disk-based corneal topography (Atlas Corneal Topography System; Humphrey, San Leandro, California) and rotating Scheimpflug corneal tomography (Pentacam HR; Oculus, Wetzlar, Germany). Corneal Topometric indices ISV, IVA, KI, CKI, IHA and IHD, along with the TKC (Topometric Keratoconus Classification) score were calculated from the Pentacam HR exam. Statistical analysis were accomplished using BioEstat 5.0 (Instituto Mamiraua, Amazonas, Brazil) and MedCalc 12.0 (MedCalc Software, Mariakerke, Belgium) using unpaired nonparametric Mann Whitney test (Wilcoxon ranked-sum). ROC curves were calculated for each topometric parameter to determine the best cut off values from the significantly different parameters. A logistic regression analysis was performed to provide a combined parameter for optimizing accuracy.

Results

Statistical significant differences were found between keratoconic and normal corneas for all topometric indices (Mann Whitney, p < 0.05). There were four false negative cases among the keratoconic cases on the TKC classification (4.54%) and 16 false positive cases among normal (7.08%), so that the sensitivity and specificity of the TKC were 95.54 and 92.92% respectively. The areas under the ROC curves (AUC) for the individual topometric indices varied from 0.843 (CKI) and 0.992 (ISV). The sensitivity and specificity of the most accurate ISV were 97.7 and 96.5% respectively. The calculated parameter from logistic regression had AUC of 0.996, with sensitivity of 97.7% and specificity of 98.7%.

Conclusion

Pentacam topometric indices were useful for distinguishing between normal and keratoconic corneas. The TKC classification should be expected to have false positives and negatives and should not be considered alone. TKC had more false positives and false negatives than some individual topometric parameters. A novel combined parameter based on logistic regression analysis may improve accuracy for the diagnosis of keratoconus. Further studies are necessary to evaluate if adding other curvature derived indices is beneficial for the regression analysis, as well as for testing the sensitivity of such parameters for the diagnosis of milder forms of ectasia and for testing correlations with severity of the disease.

How to cite this article

Salomao MQ, Guerra FP, Ramos IC, Jordao LF, Canedo ALC, Valbon BF, Luz A, Correa R, Lopes B, Ambrósio Jr R. Accuracy of Topometric Indices for Distinguishing between Keratoconic and Normal Corneas. J Kerat Ect Cor Dis 2013;2(3):108-112.


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  1. Keratoconus and related noninflammatory corneal thinning disorders. Surv Ophthalmol 1984;28(4):293-322.
  2. Keratoconus. Surv Ophthalmol 1998;42(4): 297-319.
  3. Risk factors and prognosis for corneal ectasia after LASIK. Ophthalmology 2003;11:267-275.
  4. The forme fruste of keratoconus. Wien Klin Wochenschr 1961;73:842-843.
  5. Computer-assisted corneal topography. High resolution graphic presentation and analysis of keratoscopy. Invest Ophthalmol Vis Sci 1984;25(12):1426-1435.
  6. Corneal topography of keratoconus. Cornea 1991;10(1):2-8.
  7. Keratoconus detection using corneal topography. J Refract Surg 2009;25(Suppl):S958-962.
  8. Automated keratoconus screening with corneal topography analysis. Inves Ophthalmol Vis Sci 1994;35(6):2749-2757.
  9. Computer-assisted corneal topography in keratoconus. Refract Corneal Surg 1989;5(6): 400-408.
  10. Corneal topographic and pachymetric screening of keratoreractive candidates. J Refract Surg 2003;19(1):24-29.
  11. Corneal topography in LASIK. Semin Ophthalmol 1998;13(2):64-70.
  12. Complications of laser in situ keratomileusis: Etiology, prevention and treatment. J Refract Surg 2001;17(3):350-379.
  13. Risk assessment for ectasia after corneal refractive surgery. Ophthalmology 2008;115(1):37-50.
  14. Evaluation of a risk factor scoring system for corneal ectasia after LASIK in eyes with normal topography. J Refract Surg 2010;26(4):241-250.
  15. Collaborative longitudinal evaluation of keratoconus (CLEK) study: methods and findings to date. Cont Lens Anterior Eye 2007;30(4):223-232.
  16. Corneal thickness progression form the thinnest point to the limbus: Study based on a normal and a keratoconus population to create reference values. Arquivos Brasileiros de Oftalmologia. Arquivos Brasileiros de Oftalmologia 2006;69(4):579-583.
  17. Cornea thickness spatial profile and corneal volume distribution: Tomographic indices to detect keratoconus. J Cataract Refract Surg 2006;32(11):1851-1859.
  18. Novel pachymetric parameters based on corneal tomography for diagnosing keratoconus. J Refract Surg 2011;27(10):753-758.
  19. An introduction to understanding elevation-based topography: how elevation data are displayed — a review. Clin Experiment Ophthalmol 2009;37(1):14-29.
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