July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Accuracy of integrated corneal biomechanical and tomographic data for detecting subclinical keratectasia
Author Affiliations & Notes
  • Prema Padmanabhan
    Department of Cornea and Refractive Surgery, Medical Research Foundation, Chennai, TamilNadu, India
  • Pratik kataria
    Department of Cornea and Refractive Surgery, Medical Research Foundation, Chennai, TamilNadu, India
  • vasanthi Padmanaban
    Department of Cornea and Refractive Surgery, Medical Research Foundation, Chennai, TamilNadu, India
  • Sangly P Srinivas
    Optometry, Indiana University, Bloomington, Indiana, United States
  • Renato Ambrosio
    Instituto de Olhos Renato Ambrosio, Rio de Janeiro, Brazil
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 1417. doi:
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      Prema Padmanabhan, Pratik kataria, vasanthi Padmanaban, Sangly P Srinivas, Renato Ambrosio; Accuracy of integrated corneal biomechanical and tomographic data for detecting subclinical keratectasia. Invest. Ophthalmol. Vis. Sci. 2018;59(9):1417.

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

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Abstract

Purpose : Detection of early and subclinical keratectasia remains a clinical challenge. This study tested the predictive accuracy of the Belin/Ambrosio Deviation Index (BAD-D), the Stiffness parameter (SPA1), the Corvis Biomechanical Index (CBI) & the Tomography / Biomechanical Index (TBI) for distinguishing subclinical and mild keratoconic eyes from normal eyes.

Methods : Method : All 300 eyes in this cross-sectional study underwent comprehensive examination including corneal topography (TMS-IV), Scheimpflug tomography (Pentacam HR) and dynamic Scheimpflug analysis (Corvis ST). Eyes with normal topography from patients with clinical ectasia in the fellow eye (VAE-NT-very asymmetric ectasia with normal topography) and eyes with mild clinical keratoconus (mean central keratometry <48D) constituted the study group. One eye randomly selected from patients who remained stable for 2 years following Lasik served as normal controls.
The outcome measures were BAD-D, SPA1, CBI & TBI. Comparitive analysis was performed using the t-test or the Wilcoxon rank-sum test considering the distribution by Shapiro-Wilk test. Receiver operating characteristic (ROC) curve analysis was performed to determine the predictive accuracy of each parameter.

Results : VAE-NT (100 eyes), mild keratoconus (100 eyes) and controls (100 eyes) were studied. The area under ROC (AUROC) for distinguishing VAE-NT from controls were 0.81 (BAD-D), 0.76 (SPA1) 0.78 (CBI) & 0.90 (TBI). The TBI, with a cut off value of 0.16 showed the highest accuracy (85%) of making this distinction with a sensitivity of 84% & specificity of 86%. The AUROC for distinguishing mild keratoconus from controls were 1.00 (BAD-D), 0.91 (SPA1), 0.97 (CBI) & 1.00 (TBI). The TBI, with a cut off value of 0.63, showed the highest accuracy (99.5%) of making this distinction with a sensitivity of 99% & specificity of 100%.

Conclusions : The TBI was the most accurate parameter to distinguish subclinical and mild keratoconus from normal eyes. This data is consistent with the hypothesis that the TBI epitomizes biomechanical susceptibility, making it a useful screening tool for refractive surgery. Some cases with VAE-NT may represent truly unilateral keratoconus. Longitudinal evaluation of this subset of patients is needed to establish such a possibility.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

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