Combined tomography and epithelial thickness mapping for diagnosis of keratoconus.

Abstract

Scanning Scheimpflug provides information regarding corneal thickness and 2-surface topography while arc-scanned high-frequency ultrasound allows depiction of the epithelial and stromal thickness distributions. Both techniques are useful in detection of keratoconus. Our aim was to develop and test a keratoconus classifier combining information from both methods. We scanned 111 normal and 30 clinical keratoconus subjects with Artemis-1 and Pentacam data. After selecting one random eye per subject, we performed stepwise linear discriminant analysis on a dataset combining parameters generated by each method to obtain classification models based on each technique alone and in combination. Discriminant analysis resulted in a 4-variable model (R2 = 0.740) based on Artemis data alone and a 4-variable model (R2 = 0.734) using Pentacam data alone. The combined model (R2 = 0.828) consisted of 3 Artemis- and 4 Pentacam-derived variables. The combined model R value was significantly higher than either model alone (p = 0.031, one-tailed). In cross-validation, Artemis had 100% sensitivity and 99.2% specificity, Pentacam had 97.3% sensitivity and 98.0% specificity, and the combined model had 97.3% sensitivity and 100% specificity. Pentacam, Artemis, and combined models were all effective in distinguishing normal from clinical keratoconus subjects. From the standpoint of variance explained by the model (R2 values), the combined model was most effective. Application of the model to early and subclinical keratoconus will ultimately be required to assess the effectiveness of the combined approach.