Bowman's topography for improved detection of early ectasia

Rachana Chandapura, Marcella Q. Salomao, Renato Ambrosio, Rishi Swarup, Rohit Shetty, Abhijit Sinha Roy*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

17 Citations (Web of Science)

Abstract

The aim of this study was to evaluate whether OCT topography of the Bowman's layer and artificial intelligence (AI) can result in better diagnosis of forme fruste (FFKC) and clinical keratoconus (KC). Normal (n = 221), FFKC (n = 72) and KC (n = 116) corneas were included. Some of the FFKC and KC patients had the fellow eye (VAE-NT) with normal topography (n = 30). The Scheimpflug and OCT scans of the cornea were analyzed. The curvature and surface aberrations (ray tracing) of the anterior corneal surface [air-epithelium (A-E) interface in OCT] and epithelium-Bowman's layer (E-B) interface (in OCT only) were calculated. Four random forest models were constructed: (1) Scheimpflug only; (2) OCT A-E only; (3) OCT E-B only; (4) OCT A-E and E-B combined. For normal eyes, both Scheimpflug and OCT (A-E and E-B combined) performed equally in identifying these eyes (P = .23). However, OCT A-E and E-B showed that most VAE-NT eyes were topographically similar to normal eyes and did not warrant a separate classification based on topography alone. For identifying FFKC eyes, OCT A-E and E-B combined performed significantly better than Scheimpflug (P = .006). For KC eyes, both Scheimpflug and OCT performed equally (P = 1.0). Thus, OCT Topography of Bowman's layer significantly improved the detection of FFKC eyes.

Original languageEnglish
Article number201900126
Number of pages11
JournalJournal of Biophotonics
Volume12
Issue number10
DOIs
Publication statusPublished - Oct 2019

Keywords

  • aberrations
  • Bowman's layer
  • ectasia
  • keratoconus
  • OCT
  • topography
  • SUBCLINICAL KERATOCONUS
  • MACHINE
  • SURFACE
  • LAYER
  • EYES

Cite this