May 2008
Volume 49, Issue 13
ARVO Annual Meeting Abstract  |   May 2008
Evaluation of Standard and Derived Ocular Response Analyzer (ORA) Biomechanical Measures in Keratoconus
Author Affiliations & Notes
  • K. M. Hallahan
    Cleveland Clinic Lerner College of Medicine, Cleveland, Ohio
  • A. Sinha-Roy
    Cole Eye Institute, Cleveland, Ohio
  • R. Ambrosio, Jr.
    Instituto de Olhos, Rio de Janeiro, Brazil
    Fluminense Federal University, Rio de Janeiro, Brazil
  • M. Salomao
    Instituto de Olhos, Rio de Janeiro, Brazil
  • W. J. Dupps, Jr.
    Cole Eye Institute, Cleveland, Ohio
    Biomedical Engineering, Cleveland Clinic Lerner Research Institute, Cleveland, Ohio
  • Footnotes
    Commercial Relationships  K.M. Hallahan, None; A. Sinha-Roy, None; R. Ambrosio, Reichert, C; M. Salomao, None; W.J. Dupps, None.
  • Footnotes
    Support  Research to Prevent Blindness, NIH Grant KL2RR024990
Investigative Ophthalmology & Visual Science May 2008, Vol.49, 4350. doi:
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    • Get Citation

      K. M. Hallahan, A. Sinha-Roy, R. Ambrosio, Jr., M. Salomao, W. J. Dupps, Jr.; Evaluation of Standard and Derived Ocular Response Analyzer (ORA) Biomechanical Measures in Keratoconus. Invest. Ophthalmol. Vis. Sci. 2008;49(13):4350.

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

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Purpose: : To develop alternative measures of biomechanical behavior from the Ocular Response Analyzer (Reichert, Inc) and compare their performance in discriminating keratoconic and normal eyes.

Methods: : Thirteen candidate variables were derived from ORA waveforms exported using ORA software (v.1.01) and analyzed with an in-house Matlab program. ORA measurements were analyzed retrospectively in 54 normal and 54 keratoconic eyes with disease state determined by one investigator (RA) on the basis of clinical signs and videokeratography. We compared derived variables and the current ORA measures, Corneal Hysteresis (CH) and Corneal Resistance Factor (CRF), using the area under the ROC (receiver operating characteristic) curve (AUC). ROC analysis was performed with JROCFIT software (v. 1.0.2) and AUC compared using MedCalc software (v.

Results: : CH and CRF were significantly lower in known keratoconus eyes (p<0.0002) with AUROC values of 0.863 and 0.92, respectively. Nine derived variables showed statistically significant differences between the keratoconus and normal groups (p<0.0002). Of these, the 3 top performers and their respective AUC values were PeakOnsetTime (POT), the time between applied pressure and the first applanation detector peak (0.859), MeanTroughNormalized (MTN), the mean value of the applanation signal between peaks normalized by the applied pressure (0.878), and Hysteresis Loop Area (HLA), the area under the pressure-applanation curve (0.928).

Conclusions: : CH, CRF, and several new variables derived from the ORA response waveform performed well in a formal analysis of statistical value for discriminating known cases of keratoconus from the unaffected state. HLA, which was designed to represent the classical definition of hysteresis, had the highest AUC value with diagnostic accuracy significantly better than POT and MTN (p<0.03) and not significantly different from CH or CRF (p>0.07). CRF outperformed CH (p=0.01)as a diagnostic test for keratoconus. The value of these variables in discriminating different grades of keratoconus severity is currently being investigated.

Keywords: keratoconus • cornea: clinical science 

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