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Raanan Gefen, Fani Segev, Noa Geffen, Anat Galor, Yoel Cohen, Yoel Arieli, Shlomi Epshtin, Alon Harris; A new hyperspectral imaging method to evaluate dry eye disease – 3D-WLT study results. Invest. Ophthalmol. Vis. Sci. 2019;60(9):6780.
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© ARVO (1962-2015); The Authors (2016-present)
<span lang="EN-US" style="color:rgb(119, 119, 119); font-family:arial,sans-serif; font-size:9pt; line-height:115%; margin:0px">Dry eye syndrome (DES) is a multi-factorial condition that is difficult to diagnose, in part due the inconsistent results of objective testing methodologies. The study purpose was to evaluate a new hyperspectral imaging method, the Tear Film Imager (TFI), to measure key parameters of tear film composition that are abnormal in the dry eye state. </span>
DES severity was graded using conventional DES testing methods, including: Schirmer test, tear breakup time (TBUT), tear meniscus height, corneal fluorescein staining and a patient questionnaire. Subsequently, each patient underwent 40 seconds TFI test followed by a retest after 45 minutes (average). The TFI measures the aqueous layer thickness (ALT) at a nanometer level and calculates average ALT as well as the ALT rate. In addition, the TFI measures the lipid layer thickness (LLT) at a sub-nanometer level and establishes average LLT and lipid breakup time (LBUT)
49 patients with a mean age of 58.8 years and a female majority (69%). Reproducibility of the Muco-Aqueous Tear Layer Thickness (MALT) was excellent (r=0.88). MALT measurements significantly correlated with the Schirmer score. TFI Lipid Break Up Time (LBUT) significantly correlated Tear Break Up Time (TBUT) (r=0.73). MALTand LBUT were significantly thinner and shorter, respectively, in the DE group compared to controls. TheTFI diagnosed DE disease with 87% sensitivity and 88% specificity.
The TFI is the first machine capable of reproducibly measuring muco-aqueous layer thickness in human subjects which correlates with Schirmer score. In parallel, it assesses other important aspects of tear film function which correlate with clinician assessed DE metrics.
This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.
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