July 2019
Volume 60, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2019
A Coincident-Thinning Index for Identification of Keratoconus Based on OCT Pachymetry and Epithelial Thickness Maps
Author Affiliations & Notes
  • Elias Pavlatos
    Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States
  • Yan Li
    Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States
  • David Huang
    Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States
  • Footnotes
    Commercial Relationships   Elias Pavlatos, None; Yan Li, Optovue, Inc. (F), Optovue, Inc. (P); David Huang, Optovue, Inc. (F), Optovue, Inc. (I), Optovue, Inc. (P), Optovue, Inc. (R)
  • Footnotes
    Support  NIH grants 1R01EY029023, R01EY028755, P30 EY010572 and an unrestricted departmental grant from Research to Prevent Blindness (New York, NY)
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 4234. doi:https://doi.org/
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    • Get Citation

      Elias Pavlatos, Yan Li, David Huang; A Coincident-Thinning Index for Identification of Keratoconus Based on OCT Pachymetry and Epithelial Thickness Maps. Invest. Ophthalmol. Vis. Sci. 2019;60(9):4234. doi: https://doi.org/.

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

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Abstract

Purpose : To develop a Coincident-Thinning (CT) Index to differentiate between keratoconic and healthy corneas using OCT measurements of pachymetry and epithelial thickness.

Methods : 33 eyes from 22 keratoconus patients and 19 eyes from 10 healthy subjects were included in the study. Keratoconus was diagnosed based on topography and slit lamp findings. A Fourier-domain OCT system (RTVue XR, Optovue, Fremont, CA) was used to obtain 6mm-wide pachymetry and epithelial thickness maps. Pattern deviation (PD) maps were generated to show thickness differences relative to a previously measured group of normal eyes (Fig. 1) (Li et al, JCRS, 2016). The locations of minimum pachymetry and epithelial thickness were identified within a region that included the central 3mm of the cornea as well as the inferior, inferotemporal, and inferonasal octants within a diameter of 5 mm. A localized region of each map, centered at the location of minimum thickness, was cross-correlated with a Gaussian waveform (amplitude = minimum thickness value, FWHM = 3.1 mm). The normalized correlation coefficients from both maps and the product of the two Gaussian waveforms were used to calculate the CT index for each eye. The area under the ROC curve (AUC), sensitivity, and specificity were calculated.

Results : The corneal and epithelial thinning patterns were more strongly correlated to the Gaussian waveform in the keratoconus group compared to the healthy group (correlation coefficients = 0.91 ± 0.07 vs. 0.71 ± 0.16 for pachymetry, 0.77± 0.11 vs. 0.46 ± 0.12 for epithelial thickness). The CT Index ranged from 0.3 to 2.6 for the healthy eyes (mean ± SD = 1.1 ± 0.7) and from 6.5 to 17.2 for the keratoconic eyes (mean ± SD = 10.9 ± 3.0). The AUC was equal to 1.0 (95% CI = 0.93-1.0) indicating 100% sensitivity and specificity at a cutoff CT Index value of 2.6 (Fig. 2).

Conclusions : Coincident thinning observed in OCT pachymetry and epithelial thickness maps can be quantified using the CT Index. Calculation of the CT Index represents an effective method for identifying keratoconus and may provide a more sensitive measure for keratoconus detection.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

 

Fig 1. Representative maps for a keratoconic cornea with a CT Index = 10.3.

Fig 1. Representative maps for a keratoconic cornea with a CT Index = 10.3.

 

Fig 2. CT Index values for all keratoconic (n = 33) and healthy (n = 19) corneas. The dashed line indicates the sensitivity and specificity cutoff value. G = Gaussian waveform, c = correlation coefficient.

Fig 2. CT Index values for all keratoconic (n = 33) and healthy (n = 19) corneas. The dashed line indicates the sensitivity and specificity cutoff value. G = Gaussian waveform, c = correlation coefficient.

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