Automated keratoconus detection using the EyeSys videokeratoscope.

PURPOSE: To evaluate the effectiveness of indices derived from the EyeSys System 2000 in detecting keratoconic corneas.

SETTING

Department of Ophthalmology, Hôpital Saint Antoine, Paris VI University, Paris, France.

METHODS

Topographies of 208 corneas were evaluated. The corneas were from 8 groups of patients classified by the following diagnoses: normal, regular astigmatism, cataract, radial keratotomy, photorefractive keratectomy, myopic keratomileusis, penetrating keratoplasty (PKP), and keratoconus. Nine statistical indices derived from EyeSys data, 2 Holladay Diagnosis Summary indices (coefficient of uniformity and coefficient of asphericity [Asph]), and our refractive power symmetry index were studied. A training set of 104 corneas was used to determine the most efficient threshold value of each index based on sensitivity and specificity curves. Decision trees combining 2 indices were generated. Sensitivity and specificity were calculated in a validation set composed of the remaining 104 corneas.

RESULTS

Based on the results of the training set, the optimum indices were SDSD (standard deviation of the standard deviations of the radii of curvature of each ring) and Asph. In the validation set, the decision tree using these indices featured 88.5% sensitivity and 94.9% specificity; the 4 false-positive cases were in corneas in the PKP group of patients.

CONCLUSIONS

Clinically apparent keratoconus can be detected among normal corneas and irregular corneal shape patterns using the EyeSys System 2000 data and a decision tree combining 2 indices.