Predicting Dry Eye Using Noninvasive Techniques of Tear Film Surface Assessment

Abstract

To measure tear film surface quality in healthy and dry eye subjects using three noninvasive techniques of tear film quality assessment and to establish the ability of these noninvasive techniques to predict dry eye. Thirty-four subjects participated in the study and were classified as dry eye or normal, based on standard clinical assessments. Three noninvasive techniques were applied for measurement of tear film surface quality: dynamic-area high-speed videokeratoscopy (HSV), wavefront sensing (DWS), and lateral shearing interferometry (LSI). The measurements were performed in both natural (NBC) and suppressed (SBC) blinking conditions. To investigate the capability of each method to discriminate dry eye subjects from normal subjects, the receiver operating curve (ROC) was calculated and then the area under the curve (AUC) was extracted. The best result was obtained for the LSI technique (AUC = 0.80 in SBC and AUC = 0.73 in NBC), which was followed by HSV (AUC = 0.72 in SBC and AUC = 0.71 in NBC). The best result for DWS was an AUC of 0.64 obtained for changes in vertical coma in SBC, whereas for NBC, the results were poorer. Noninvasive techniques of tear film surface assessment can be used for predicting dry eye, and such an assay can be achieved in NBC as well as SBC. In this study, LSI showed the best detection performance, closely followed by the dynamic-area HSV. The DWS technique was less powerful, particularly in NBC.