Keratoconus diagnosis with optical coherence tomography–based pachymetric scoring system.

PURPOSE: To develop an optical coherence tomography (OCT) pachymetry map–based keratoconus risk scoring system.

SETTINGS: Doheny Eye Institute, University of Southern California, Los Angeles, California, and Brass Eye Center, New York, New York, USA; Department of Ophthalmology, Affiliated Eye Hospital of Wenzhou Medical College, Wenzhou, China.

DESIGN

Cross-sectional study.

METHODS

Fourier-domain OCT was used to acquire corneal pachymetry maps in normal and keratoconus subjects. Pachymetric variables were minimum, minimum−median, superior–inferior (S–I), superonasal–inferotemporal (SN–IT), and the vertical location of the thinnest cornea (Ymin). A logistic regression formula and a scoring system were developed based on these variables. Keratoconus diagnostic accuracy was measured by the area under the receiver operating characteristic (ROC) curve.

RESULTS

One hundred thirty-three eyes of 67 normal subjects and 82 eyes from 52 keratoconus subjects were recruited. The keratoconus logistic regression formula = 0.543 × minimum + 0.541 × (S–I) − 0.886 × (SN–IT) + 0.886 × (minimum–median) + 0.0198 × Ymin. The formula gave better diagnostic power with the area under the ROC than the best single variable (formula = 0.975, minimum = 0.942; P<.01). The diagnostic power with the area under the ROC of the keratoconus risk score (0.949) was similar to that of the formula (P=.08).

CONCLUSION

The OCT corneal pachymetry map–based logistic regression formula and the keratoconus risk scoring system provided high accuracy in keratoconus detection. These methods may be useful in keratoconus screening.