Supporting Dry Eye Diagnosis with a New Method for Noninvasive Tear Film Quality Assessment.

Abstract

Noninvasive high-speed videokeratoscopy equipped with specific software has shown potential for assessing the homeostasis of tear film, providing clinicians with a fast and consistent tool for supporting dry eye diagnosis and management. The purpose of this study was to evaluate the efficacy of a recently proposed method for characterizing tear film dynamics using noninvasive high-speed videokeratoscopy in assessing the loss of homeostasis of tear film. Thirty subjects from a retrospective study, of which 11 were classified as dry eye and 19 as healthy, were included. High-speed videokeratoscopy measurements were performed using E300 videokeratoscope (Medmont Pty., Ltd., Melbourne, Australia). Raw data were analyzed using a recently proposed method to estimate the dynamics of the tear film based on a fractal dimension approach. This method provides three time-varying indicators related to the regularity of the reflected rings: tear film surface quality indicator, breaks feature indicator, and distortions feature indicator. From each indicator, five parameters were extracted and analyzed, including noninvasive breakup time, mean value of the indicator in the stability phase, mean value of the indicator in the whole interblink interval, mean value of the indicator in the leveling phase, and the general trend of the time series. Receiver operating characteristic curves were used to determine the sensitivity and specificity of each parameter in dry eye detection. The best discrimination performance between dry eye and healthy subjects was achieved with the breaks feature indicator noninvasive breakup time parameter, with an area under the curve of 0.85. For a cutoff value of 10 seconds, the sensitivity was 100% and the specificity was 84%. The analyzed method improves the assessment of tear film homeostasis in comparison with previous high-speed videokeratoscopy methods showing higher potential in assisting dry eye diagnosis.