April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
Analysis of Corneal Wavefront Aberrations for Classification of Keratoconus, Pellucid Marginal Degeneration and Normal Eyes
Author Affiliations & Notes
  • Daniela-Luisa Ott
    Department of Ophthalmology, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
  • Jens Buehren
    Department of Ophthalmology, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
  • Roland F. Schwarz
    Cambridge Research Institute, Cambridge, United Kingdom
  • Oliver K. Klaproth
    Department of Ophthalmology, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
  • Thomas Kohnen
    Department of Ophthalmology, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
    Cullen Eye Institute, Baylor College of Medicine, Houston, Texas
  • Footnotes
    Commercial Relationships  Daniela-Luisa Ott, None; Jens Buehren, None; Roland F. Schwarz, None; Oliver K. Klaproth, None; Thomas Kohnen, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 4186. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Daniela-Luisa Ott, Jens Buehren, Roland F. Schwarz, Oliver K. Klaproth, Thomas Kohnen; Analysis of Corneal Wavefront Aberrations for Classification of Keratoconus, Pellucid Marginal Degeneration and Normal Eyes. Invest. Ophthalmol. Vis. Sci. 2011;52(14):4186.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose: : To evaluate the ability of wavefront aberrations of the anterior and posterior corneal surface in order to classify eyes with keratoconus (KC), pellucid marginal degeneration (PMD) and normal eyes.

Methods: : This retrospective study included 55 eyes of 32 patients with KC (group 1), 60 eyes of 43 patients with PMD (group 2) and 64 eyes of 32 subjects with normal eyes (group 3). From axial-keratometric data of the anterior corneal surface and elevation data (Orbscan IIz, Bausch & Lomb) of the posterior corneal surface a Zernike decomposition (2nd - 7th order, 6 mm pupil diameter) was performed. Explorative analysis and supervised support vector machine (SVM) classification assessed anterior and posterior corneal wavefront aberrations in their ability to divide patient eyes into groups. Cross-validation was used to estimate the classification error on unseen data. The most significant Zernike coefficients (ZC) for classification between the three groups were ascertained by SVM feature selection and sparse principal component analysis. Discriminative ability of individual ZC was assessed by receiver operating characteristic curve (ROC) analysis.

Results: : Hierarchical clustering of anterior and posterior corneal wavefront data showed a clear grouping of patients into the three major disease groups (KC, PMD, normal) as a result of the first two hierarchical splits. The first split separated healthy from diseased eyes, the second one KC from PMD eyes. The most influential ZC to distinguish between KC, PMD and normal eyes were C22, C3-1, C2-2 and C3-3. Anterior primary vertical coma C3-1 had the highest ability to discriminate between both PMD and normal eyes (standardized area under the ROC curve [AzROC] 0.991) as well as KC and normal eyes (AzROC 0.986). Anterior primary astigmatism C22 was the most powerful ZC to discriminate between KC and PMD (AzROC 0.891). Discriminative ability of anterior wavefront aberrations was higher (average AzROC 0.91) than of posterior (average AzROC 0.78). SVM classification of all 33 anterior ZC achieved a correct classification rate of 87% for unseen data.

Conclusions: : Our data suggest that ZC from the anterior and posterior corneal surface classify between KC, PMD and normal eyes with high accuracy.

Keywords: keratoconus • cornea: clinical science • aberrations 
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×