June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
A Decision Tree Using OCT Corneal and Epithelial Thickness Map Parameters and Patterns for Keratoconus Detection
Author Affiliations & Notes
  • Yan Li
    Ophthalmology, Oregon Health and Science University, Portland, Oregon, United States
  • Yuli Yang
    Ophthalmology, Oregon Health and Science University, Portland, Oregon, United States
    Third Military Medical University, Southwest Eye Hospital, Chongqing, Chongqing, China
  • Elias Pavlatos
    Ophthalmology, Oregon Health and Science University, Portland, Oregon, United States
  • David Huang
    Ophthalmology, Oregon Health and Science University, Portland, Oregon, United States
  • Footnotes
    Commercial Relationships   Yan Li, Optovue, Inc (F), Optovue, Inc. (P); Yuli Yang, None; Elias Pavlatos, None; David Huang, Optovue, Inc. (F), Optovue, Inc. (I), Optovue, Inc. (P), Optovue, Inc. (R)
  • Footnotes
    Support  Supported by the National Institutes of Health, Bethesda, MD (grant no.: R01EY028755, R01EY029023, T32EY023211, P30EY010572); a research grant and equipment support from Optovue, Inc., Fremont, CA; unrestricted grants to Casey Eye Institute from Research to Prevent Blindness, Inc., New York, NY.
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 4743. doi:
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    • Get Citation

      Yan Li, Yuli Yang, Elias Pavlatos, David Huang; A Decision Tree Using OCT Corneal and Epithelial Thickness Map Parameters and Patterns for Keratoconus Detection. Invest. Ophthalmol. Vis. Sci. 2020;61(7):4743.

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

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Abstract

Purpose : To detect keratoconus using optical coherence tomography (OCT) pachymetry and epithelial thickness map parameters and patterns.

Methods : A 70-KHz Fourier-domain OCT system was used to acquire corneal and epithelial thickness maps. OCT maps of normal, manifest keratoconic, subclinical keratoconic, and forme fruste keratoconus (FFK) eyes were studied. A two-step decision tree was designed to screen for keratoconus. First, an eye suspicious for keratoconus was recognized if any of the quantitative pachymetric (minimum, minimum-maximum, superonasal-inferotemporal) and epithelial (standard deviation) map parameters exceeded cutoff values. Second, the suspicious eye was either confirmed or ruled out for keratoconus by visually identifying the existence of coincident thinning pattern on its pachymetry and epithelial thickness maps and concentric thinning pattern on its epithelial thickness map. Sensitivity and specificity were calculated to evaluate the performance of the decision tree for keratoconus detection.

Results : The study included 54 eyes of 29 normal participants, 90 manifest keratoconic eyes of 65 patients, 12 subclinical keratoconic eyes of 11 patients and 19 FFK eyes of 19 patients. The decision tree demonstrated excellent diagnostic accuracy in keratoconus screening. It provided 100% specificity for normal, excellent sensitivity in manifest keratoconus (97.8%) and subclinical keratoconus (100.0%), and good sensitivity in FFK (73.7%).

Conclusions : The two-step decision tree provided a useful tool to detect keratoconus including cases at early disease stage (subclinical keratoconus and FFK). OCT pachymetry and epithelial thickness map parameters and patterns can be used in conjunction with topography to improve keratoconus screening.

This is a 2020 ARVO Annual Meeting abstract.

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