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使用泪膜表面评估的非侵入性技术预测干眼症。

Predicting dry eye using noninvasive techniques of tear film surface assessment.

机构信息

School of Optometry, Queensland University of Technology, Brisbane, Australia.

出版信息

Invest Ophthalmol Vis Sci. 2011 Feb 9;52(2):751-6. doi: 10.1167/iovs.10-5173.

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 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.

RESULTS

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.

CONCLUSIONS

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.

摘要

目的

使用三种非侵入性的泪膜质量评估技术来测量健康和干眼受试者的泪膜表面质量,并确定这些非侵入性技术预测干眼的能力。

方法

34 名受试者参与了这项研究,并根据标准临床评估将其分为干眼或正常。三种非侵入性技术用于测量泪膜表面质量:动态区域高速角膜地形图(HSV)、波前感应(DWS)和横向剪切干涉仪(LSI)。在自然(NBC)和抑制(SBC)眨眼条件下进行测量。

结果

为了研究每种方法区分干眼受试者和正常受试者的能力,计算了接收器工作曲线(ROC),然后提取曲线下面积(AUC)。LSI 技术的最佳结果(SBC 中的 AUC=0.80 和 NBC 中的 AUC=0.73),其次是 HSV(SBC 中的 AUC=0.72 和 NBC 中的 AUC=0.71)。DWS 的最佳结果是 SBC 中垂直彗差变化的 AUC 为 0.64,而在 NBC 中,结果较差。

结论

泪膜表面评估的非侵入性技术可用于预测干眼,并且这种检测可以在 NBC 和 SBC 中进行。在这项研究中,LSI 显示出最佳的检测性能,紧随其后的是动态区域 HSV。DWS 技术的效果较差,特别是在 NBC 中。

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