Abstract
Purpose :
To image the tear film lipid layer and quantify the decrease rate of the tear film thickness non-invasively using ultrahigh-resolution optical coherence tomography (UHR-OCT).
Methods :
10 healthy subjects were included in this study that used a custom-built UHR-OCT system based on a Ti:Sapphire laser yielding a theoretical axial resolution of 1.2 µm in tissue. For each OCT measurement, five volumes of the central cornea, each comprising 256x256x4096 voxels and covering an imaging range of 5.5 x 5.5 x 1.4 mm3, were acquired directly after blinking. Measurements of the five volumes lasted 5.5 seconds and were repeated every ten minutes for one hour, leading to a total of 140 OCT datasets for all subjects. Simultaneous measurements of the tear film lipid layer quantity index (LQI) and total tear film thickness (TFT) were obtained after data processing, using a custom software written in Matlab. We recently demonstrated that TFT can be obtained from the OCT data using efficient delay estimation of each tear film interface and that LQI can be obtained from air-tear interface OCT reflectance data. Tear film lipid layer thickness (TFLL) values were obtained using a commercial system (Lipiview, TearScience Inc., Morrisville, NC, USA).
Results :
Fig. 1 shows a representative TFT measurement in one healthy subject. Fig.1 (a) shows en face TFT maps over time and Fig. 1(b) depicts the corresponding mean TFT value in each map. A continuous TFT decrease can clearly be observed. As seen in Fig.1 , over the measurement time the mean TFT decrease rate amounts to 0.145 µm/s . In Fig. 2, representative 2D maps of the tear film lipid layer are shown. LQI of the 140 OCT dataset was 8.2 ± 2.4. TFLL values were 67 ± 13 nm.
Conclusions :
A OCT-based approach for simultaneous measurement of TFT and LQI was reported. This method can be used to study the role of the lipid layer in the tear film evaporation/decrease rate and could be used to study dry eye and to test efficacy of dry eye treatments.
This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.