Purpose:
To assess the wettability of soft contact lenses in-vivo by a new thin film interferometry measures.
Methods:
Doane’s interferometer connected to a digital camera captured images of the pre- contact lens tear film of 4 soft CLs representing the range of current soft CL materials. These were: Oasys (Acuvue, Johnson&Johnson); Soflens 38 (Bausch&Lomb), Night & Day (CibaVision) and ProClear (Cooper Vision). 5 healthy subjects (3 CLs wearers and 2 non CLs wearers aged 29±3.5 years, 3M 2F) were recruited.Subjects attended for 4 separate visit days and wore 1 of 4 lenses, chosen randomly. After 15 minutes adaptation subjects were seated at the interferometer, asked to blink once, and keep their eye open as long as possible. The camera captured images of the pre-lens liquid until the front surface became completely dry (no fringes). The procedure was repeated over 5 drying cycles and the resultant images were analysed by a MATLAB programme. Four new parameters were assessed: time to first break-up, onset latency (OL), duration of drying after first break-up (DD), maximum speed of drying (MS) and time to reach maximum speed (PL).
Results:
The new measures offered a range of values in assessment of wettability across the CL types (Table 1). A one way ANOVA showed a significant difference between CLs for DD (p=0.008), a value close to significant was also found for MS (p=0.06). The other measures did not show significant differences between the lens types for the size of sample in this pilot study, at least in part, because of the variation in wetting as a result of individual tear chemistry. The sample sizes required to give sufficient power in measuring wetting with each of the measures were calculated, these are: n=177 (OL), 5 (DD), 8 (MS), 11 (PL).
Conclusions:
This pilot study suggests that the technique of assessing CL wettability by interferometry, developed in-vitro can be applied in-vivo. Wetting measured by DD, MS and PL appear to be the most feasible for future experiments.
Keywords: contact lens • imaging/image analysis: non-clinical