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Keratoconus detection using OCT corneal and epithelial thickness map parameters and patterns.

Yuli Yang1, Elias Pavlatos, Winston Chamberlain

  • 1From The Center for Ophthalmic Optics and Lasers, Casey Eye Institute, and Department of Ophthalmology, Oregon Health and Science University, Portland, Oregon (Yang, Pavlatos, Chamberlain, Huang, Li); Southwest Hospital/Southwest Eye Hospital, Third Military Medical University, Chongqing, China (Yang).

Journal of Cataract and Refractive Surgery
|November 12, 2020
PubMed
Summary
This summary is machine-generated.

A new two-step decision tree using optical coherence tomography (OCT) effectively detects keratoconus, including early stages like subclinical keratoconus and forme fruste keratoconus (FFK). This method enhances screening by analyzing corneal and epithelial thickness maps.

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Corneal Disease Diagnostics

Background:

  • Keratoconus is a progressive corneal ectasia affecting vision.
  • Early detection of keratoconus is crucial for timely intervention and management.
  • Current diagnostic methods may have limitations in identifying early or forme fruste cases.

Purpose of the Study:

  • To develop and validate a diagnostic tool for keratoconus detection.
  • To utilize optical coherence tomography (OCT) corneal and epithelial thickness maps for improved accuracy.
  • To identify keratoconus, including subclinical and forme fruste keratoconus (FFK) stages.

Main Methods:

  • A spectral-domain OCT was employed to generate corneal and epithelial thickness maps.
  • A two-step decision tree algorithm was designed for classification.
  • Classification criteria included quantitative map parameters and visual pattern analysis of thinning.

Main Results:

  • The decision tree achieved 100% specificity in classifying normal eyes.
  • High sensitivities were observed for manifest keratoconus (97.8%), subclinical keratoconus (100.0%), and FFK (73.7%).
  • The study included a diverse cohort of normal, manifest keratoconic, subclinical keratoconic, and FFK eyes.

Conclusions:

  • The developed two-step decision tree is a valuable tool for keratoconus detection.
  • The method demonstrates efficacy in identifying early-stage keratoconus (subclinical and FFK).
  • OCT-derived map parameters and patterns, combined with topography, can enhance keratoconus screening.