The Detection of Keratoconus using a Three-Dimensional Corneal Model Derived from Anterior Segment Optical Coherence Tomography

Abstract

Abstract Purpose: To differentiate between keratoconus and healthy corneas via three-dimensional (3D) measurements of surface area and volume. Measurements are derived from anterior segment optical coherence tomography (AS-OCT) images. Methods: Keratoconus patients were identified along with healthy controls patients between the ages of 20 and 79 years old. The selected patients underwent a nine-line raster scan AS-OCT. ImageJ was used to determine the central 6mm of each image and each corneal image was then divided into six 1mm segments. Free-D software was then used to render the nine different images into a 3D model to calculate corneal surface area and volume. Results: 33 eyes with keratoconus, along with 33 eyes healthy controls were enrolled. There were statistically significant (p < 0.05) differences between the healthy and keratoconus groups in the metric of anterior corneal surface area (13.927 vs 13.991 mm2, p = 0.046), posterior corneal surface area (14.045 vs 14.173 mm2, p < 0.001), and volume (8.430 vs 7.773 mm3, p < 0.001) within the central 6 mm. Conclusion: 3D corneal models derived from AS-OCT can be used to measure anterior corneal surface area, posterior corneal surface area, and corneal volume. All three parameters are statistically different between corneas with keratoconus and healthy corneas. Further study and application of these parameters may yield new methodologies for the detection of keratoconus.