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Predicting dry eye using non-invasive techniques of tear film surface assessment

Szczesna, Dorota, Alonso-Caneiro, David, Iskander, D. Robert, Read, Scott A., & Collins, Michael J. (2011) Predicting dry eye using non-invasive techniques of tear film surface assessment. Investigative Ophthalmology and Visual Science, 52(2), pp. 751-756.

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Abstract

PURPOSE. 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. METHODS. Thirty four subjects participated in the study, and were classified as dry eye or normal, based on standard clinical assessments. Three non-invasive 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 blinking conditions (NBC) and in suppressed blinking conditions (SBC). RESULTS. In order 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 AUC=0.64 obtained for changes in vertical coma in suppressed blinking conditions, while for normal blinking conditions the results were poorer. CONCLUSIONS. Non-invasive techniques of tear film surface assessment can be used for predicting dry eye and this can be achieved in natural blinking as well as suppressed blinking conditions. In this study, LSI showed the best detection performance, closely followed by the dynamic-area HSV. The wavefront sensing technique was less powerful, particularly in natural blinking conditions.

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12 citations in Scopus
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9 citations in Web of Science®

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ID Code: 38348
Item Type: Journal Article
DOI: 10.1167/iovs.10-5173
ISSN: 0146-0404
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Optometry & Vision Science
Copyright Owner: Copyright 2010 by The Association for Reaserch in Vision and Ophthalmology, Inc.
Deposited On: 05 Nov 2010 15:58
Last Modified: 23 Jan 2013 22:11

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