Description:
Summary
The current technology provides for an OCT-based artificial intelligence (AI) algorithm to improve classification and diagnosis between common corneal shape abnormalities including forme fruste (pre-clinical) keratoconus (FFK), contact lens related warpage, dry eye disease, and Fuch’s endothelial dystrophy.
Technology Overview
Keratoconus is a contraindication for LASIK eye surgery as it can lead to serious complications after surgery; however early preclinical keratoconus can be challenging to distinguish from other corneal abnormalities, like corneal warpage. Because many LASIK candidates are contact lens wearers, the distinction between contact lens-related warpage and FFK is a common diagnostic question faced by clinicians seeking to avoid post-LASIK complications.
The current technology provides an OCT-based AI approach to corneal shape abnormality classification that could be incorporated into existing OCT based software systems to aid in diagnostic decision making. The current AI based algorithm uses multiple OCT-based measurements including corneal shape maps, corneal thickness and reflectance. This set of parameters has not previously been used for AI-based corneal shape abnormality detection, and has the potential for both enhanced diagnostic capability and reduced computational demand. This method demonstrated greater than 90% accuracy in distinguishing between normal corneal shape, keratoconus and Fuch’s endothelial dystrophy in preliminary testing.
Publication
Pavlatos E, Huang D, Li Y. Detection of corneal ectasia using OCT maps of pachymetry and posterior surface mean curvature. Investigative Ophthalmology & Visual Science June 2022, Vol.63, 2109 – F0098. Link
Licensing Opportunity
This technology is available for licensing.