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 x minimum + 0.541 x (S-I) - 0.886 x (SN-IT) + 0.886 x (minimum-median) + 0.0198 x 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. (C) 2013 ASCRS and ESCRS