Evaluating the quality and stability of the tear film is a key clinical task in the diagnosis and management of dry eye. However, many of the available clinical methods for tear film evaluation can be invasive or semi-invasive, rely on subjective judgments, can be time consuming, and unreliable.1 These shortcomings in traditional clinical tests suggest a need for the development of new methods that are noninvasive, simple to perform, and provide objective quantitative measures of tear film quality and kinetics.2 Noninvasive methods for assessing the tear film are defined here as methods in which no substance is instilled into the eye, there is no forced blinking or forcible holding of the eyelids, and there is no contact between the measuring instrument and the eye or eyelids. Such noninvasive methods include techniques based on observing changes in the specular reflection of a grid pattern projected on the cornea,3, 4, 5, 6, 7, 8 observing changes in measured wavefront aberrations,9, 10, 11, 12 and those based on observing changes in lateral shearing interferometric patterns.13, 14, 15
Taking a series of measurements or recording a video in each of these noninvasive techniques enables evaluation of the temporal changes of the tear film surface, and can allow derivation of a time-series-based tear film surface quality (TFSQ) indicator. Then, such an indicator can be used to assess several clinically relevant parameters such as tear film build-up time, a parameter closely related to the spread of the lipid layer,16, 17 the average tear film surface quality in the interblink interval, tear film velocity (the rate of tear flow over time), and may also be used to predict tear film break-up time.
In high-speed videokeratoscopy, changes in corneal topography estimates5, 18 or changes in the quality of videokeratoscopic images7, 19 can be used to infer changes in tear film surface quality. In wavefront sensing, changes in higher-order aberrations (particularly in vertical coma) can be thought as originating from changes in the tear film surface.10, 11, 12 Finally, the assessment of the tear film surface quality in lateral shearing interferometry is essentially based on the first-order frequency estimates of the interference fringes.14 There are several obvious advantages and disadvantages of each of the three considered noninvasive techniques. Among them, the modified lateral shearing interferometry technique appears to be the most sensitive way of recording tear film surface irregularities.14 At the same time, the technique is hindered by the natural microfluctuations of the eye, resulting in significant measurement noise.13 The technique is usually limited to an analysis area of approximately square, unless large optical elements with high numerical apertures are used. Wavefront sensing provides a very sensitive and accurate assessment of the eye’s optics. However, temporal changes in ocular wavefront aberrations can be related to cardiopulmonary signals.20, 21 Wavefront-sensing-based evaluation of tear film surface quality is also limited to the exit pupil area. Finally, high-speed videokeratoscopy with Placido disks may have less spatial resolution than the previous two methods, but it provides maximum surface coverage, encompassing the entire visible corneal surface for analysis.19
Our aim in this study was to perform a comparative study of the three considered techniques by conducting measurements of tear film surface kinetics on a cohort of healthy subjects with no evidence of any tear film abnormalities. Two parameters were of particular interest, the tear film build-up time and the average tear film surface quality in the stable phase of the interblink interval.
Materials and Methods
Right eyes from 18 Caucasian subjects, nine females and nine males, aged from were measured in this study. The mean age of all subjects was . None of the subjects were using ocular or systemic medications and none were contact lens wearers. No subject reported any history of significant ocular pathology, injury, or surgery. The study was approved by the university research ethics committee, and all subjects gave informed consent before participation and were treated in accordance with the Declaration of Helsinki.
All subjects were clinically assessed as having a tear film quality within normal limits with no evidence of ocular pathology. The clinical assessment included clinical history, slit lamp examination, phenol red thread test of tear volume, and fluorescein tear film break-up time (FTBUT). The slit lamp assessment included examination of the lid margins and meibomian glands, the bulbar and tarsal conjunctiva, and staining of the ocular surface with fluorescein and lissamine green dye. The central lower tear meniscus height was measured with a slit lamp graticule. All subjects recorded a phenol red thread wetted length of greater than . Three measurements of FTBUT were conducted and the average was taken. Fluorescein staining of the cornea and lissamine green staining of the bulbar conjunctiva were graded according to the National Eye Institute (NEI) grading scale.22 All subjects exhibited corneal and conjunctival staining scores of less than 3. The group average statistics of the clinical measurements, including the mean, standard deviation, median, and the median average distance (MAD), are shown in Table 1 .
Group average statistics of the objective clinical measurements.
|Phenol thread wet length (mm)||23.3||6.5||24.0||5.3|
|Corneal (fluorescein) stain score(0 to 15)||1.03||0.67||1.0||0.54|
|Conjunctival (lissamine green)stain score (0 to 18)||0.47||0.55||0.25||0.47|
|Tear meniscus height (mm)||0.26||0.06||0.27||0.05|
For each of the subjects, all measurements were taken in the afternoon within a two-hour time frame between 3 and 5 pm. To ensure that the room environmental conditions did not significantly affect tear film quality, all three instruments were located in the same room (see Fig. 1 ). Temperature and humidity of the room were controlled and recorded at the beginning of each measurement session. The average temperature in the measurement room was and the average humidity was .
Due to the need to save large amounts of digital data, the order of use of the instruments was standardized to optimize time management and reduce subject fatigue. Two measurements were taken with each instrument in the following order: high-speed videokeratoscopy (HSV), followed by dynamic wavefront sensing (DWS), and finally lateral shearing interferometry (LSI). During the measurements, subjects were asked to focus on the instrument’s fixation target and blink as naturally as possible without deliberately keeping their eyes open during a measurement period. A break of about was allowed for the subject before a further measurement was taken. Data were excluded from analysis if there was obvious reflex tearing and significant eye movements during measurements (i.e., subject not focusing on the target). These decisions were made by an experimenter who was masked to the clinical tear analysis results. Five subjects out of the initially enrolled 23 subjects were excluded from further analysis.
For completeness, a short summary of the technical aspects of each of the three procedures is given. However, greater detail of each of the procedures can be found in the work of Alons-Caneiro, Iskander, and Collins for HSV,19 in the works of Iskander and Zhu for the DWS technique,20, 21 and in the works of Szczesna and Szczesna and Iskander for LSI.14, 23
The HSV and LSI techniques captured images at a constant rate of , while the DWS provided sampling frequencies that fluctuated around . For each of the methods, blinks were automatically detected in the image sequences, and each sequence was divided into a series of interblink intervals.
During recordings, the eye undergoes natural micromovements,24 which represent an interference that needs to be detected, because it can cause motion-related blur of the images. This effect is particularly evident in the HSV and LSI measurements. Hence, algorithms were developed to detect the images affected by the blur motion. Such blurred images were subsequently excluded from the analysis in both methods.
The image processing technique from HSV recording operates on the set of images within the interblink interval and involves the following steps.19 First, estimation of the region of interest is performed. Once the region with the fundamental information is extracted, the next step is to detect the unaltered ring pattern within this area. The technique separates the parts of the image that present a well-structured Placido disk pattern from the interference. After this, the interference is further clustered into two types, depending on the cause. Once the interference from eyelashes has been removed, the remaining interference is assumed to be related to the poor quality tear film.
Finally, tear film surface quality is estimated in the area of analysis (AOA), formed by the area related to the unaltered videokeratoscopy pattern signal and tear disturbance interference. The tear film surface quality indicator is estimated by using the method of image coherence analysis, in which the value of this indicator for each image is the average of the coherence measurement across the area of analysis.19 Examples of tear film surface quality kinetics estimated within the area of analysis , and within the pupil area, , are shown in Fig. 2 . The pupil area was used for comparison with the DWS and the LSI techniques that are limited to measuring this region of the ocular surface.
Dynamic wavefront sensing
The Complete Ophthalmic Analysis System (COAS™, WaveFront Sciences, Incorporated) was used for dynamic wavefront sensing. Measurements were performed in a multifile mode. Sampling instabilities are taken into account in the analysis by registering the exact time stamp of each single measurement. Since natural blinking occurred during data acquisition, a procedure for detecting the blinks in the original Hartmann-Shack images was used.
The remaining Hartman-Shack images were used to estimate the wavefront aberrations that were decomposed into Zernike terms, up to and including the eighth radial order, resulting in 45 time-varying coefficients. For this, the instrument’s own modal Zernike polynomial fitting algorithm was used. Finally, time series of total, higher-order, comatic terms, and the Zernike polynomial rms fit error were used as possible indicators of tear film surface quality.10, 11, 12, 18, 25
Wavefront aberrations are also affected by the variations in pupil size, and since the time-varying Zernike polynomial coefficients are calculated for a given pupil size, it is necessary to rescale such coefficient values to a common pupil size.26 Wavefront aberrations were rescaled to the smallest common pupil diameter in each of the recordings. Examples of wavefront dynamics are shown in Fig. 3 , where the time series of total aberrations (TAs), higher-order aberrations (HOA), total comatic terms ( , and , and the Zernike polynomial rms fit error are given. The total comatic terms include the third, fifth, and seventh order comatic terms.
Wavefront dynamics are affected by signals of the cardiopulmonary system, such as pulse and respiration.20, 21 In particular, this effect is prominent in the lower-order aberrations of defocus and astigmatism.27 However, changes in comatic terms (both horizontal and vertical) have been shown to be associated with tear film kinetics.18
Lateral shearing interferometer
In the LSI apparatus,14, 28 the wavefront generated from the HeNe laser illuminates the tear film on the cornea and reflects from its surface. The reflected wavefront is split in the LSI optical wedge into two wavefronts that interfere with each other to create an interferogram. For an evenly spread precorneal tear film, the fringes are regular and horizontal. In the case of an uneven tear film surface, the interference fringes reveal irregularities, and their background is inhomogeneous.29 The central part of the cornea is exposed to the laser light, thus the tear film in the pupil area (approximately square region) is measured.
Assessing tear film surface quality from interferometric images is based on estimates of the first harmonic of the interference fringes.14 The technique combines the traditional spectral estimation techniques with morphological image processing techniques,23 in which a smoothed 2-D periodogram [fast Fourier transform (FFT)-based spectral estimator] is treated like an image, from which local maxima are extracted and classified according to a set of criteria. Finally, a spatial-average localized-weighted estimate of the first harmonic is used as a measure, called M2, of tear film surface quality. An example of the tear film surface quality recorded with the LSI is shown in Fig. 4 . The data show the kinetics of the tear film surface after every blink recorded during the sequence. Immediately after each blink, the tear film stabilizes and reveals irregularities. The values of the TFSQ descriptor are high (worse quality) at the beginning, but decrease (better quality) with the tear film build-up time. It has previously been shown that the interferometric method is able to clearly observe the phenomenon of the tear film build-up immediately after each blink.29
Each of the three considered techniques for noninvasive measurement of tear film surface quality are based on different physical principles, have a different illumination source, and involve a different subject-instrument interface (i.e., headrest, proximity to instrument’s elements, fixation target). Hence, in the initial part of the study, it was important to determine whether the blinking patterns naturally exhibited by subjects changed from one instrument to another.
The group mean interblink interval across the instruments was , , and for HSV, DWS, and the LSI, respectively. Statistical testing by means of the repeated measures ANOVA revealed that across the individual subjects, there were statistically significant differences in the interblink interval. However, the type of instrument that was used did not cause statistically significant differences . Also, no statistically significant differences were identified when comparing the first measurement to the second measurement, indicating that the subjects’ blinking patterns were similar in the two consecutive measurements with each of the instruments. The lower sampling rate in DWS as compared to that of HSV and LSI had little effect on the estimated variability of blink patterns.
Tear Film Parameter Estimation
The time series of a tear film surface quality indicator within an individual interblink interval is used to estimate two parameters: the tear film build-up time , and the average tear film surface quality , in the stable phase of the interblink interval. This phase is defined as a period from the end of the tear film build-up phase to the end of the interblink interval. Statistical modeling of tear film surface quality has been considered earlier in the context of interferometric data,30 where a set of four parametric functions has been considered: a bilinear, a trilinear, Hoerl’s, and an optimal polynomial function.
The bilinear function seems to be appropriate for the analysis of tear film surface quality in interblink intervals for subjects with normal tears, as they usually exhibit up to two phases of the tear film kinetics (i.e., the tear film build-up phase and the relatively stable interblink phase). In this work, we have extended the bilinear function model so that the second linear function describing the stable interblink phase is constrained by the estimator of the first linear function describing the tear film build-up phase. This is performed using an iterative nonlinear constrained least-squares approach. An example of such bilinear fitting is shown in Fig. 5 .
Since the two distinct phases of tear film behavior cannot always be observed in all measured interblink intervals, it was necessary to test in each sequence whether a bilinear fit is warranted. This has been achieved by performing a log likelihood ratio test of the Pearson’s correlation coefficients for a linear and bilinear fit, as suggested by Owsley, Knoblauch, and Katholi.31 In summary, the estimated Pearson’s correlation coefficients and are first transformed using Fisher transformation and are multiplied by a factor , with being the number of sample points, to become standard normal and . Then the log likelihood ratio , where denotes the standard Gaussian probability density function, and is distributed with of freedom. The -value for which the linear fit was rejected in this test was set to .
Tear Film Build-Up Time
The group statistics of the tear film build-up time measures , acquired from the three considered instruments, are shown in Table 2 . Since the data did not always follow a Gaussian distribution, we also considered the median and the median absolute deviation (MAD).
Group statistics of the tear film build-up time across the instruments.
For the HSV, the group average was when calculated across the whole visible corneal surface (AOA) and was in the pupil area, while the group median values were , respectively. Five descriptors of were used in the case of the DWS method. They were based on total aberrations (TA), higher-order aberrations (HOA), total vertical coma , total horizontal coma , and the Zernike polynomial rms fit error. An increased variability of tear film surface parameter estimates is apparent in the results from the DWS. The group average ranged from for vertical coma to for horizontal coma. Median-based statistics did not reduce the variability, but rather shifted it toward shorter values (i.e., ranged from ). The group average of the measure acquired from LSI was . It is worth noting that the estimated median values for HSV in the pupil area and for vertical coma in DWS are remarkably close to the estimates of median from LSI.
To ascertain whether the two distinct phases of tear film behavior—the build-up phase and the stability phase—were observed in all measured interblink intervals, a count was kept on how many times the hypothesis of a single linear fit (rather than the bilinear fit) to the interblink data was rejected. The number of rejected linear fits to the data was on average 20, 42, and 98% of the total number of interblink intervals for the HSV, DWS, and the LSI, respectively (see the percentage count in Table 2). This indicates that the phase of tear film build-up was almost always observed with the LSI technique, but not using the HSV and DWS methods. No cases were encountered in which the hypothesis of the linear fit to the data was retained for all interblink intervals in the measurement.
Tear Film Surface Quality
The statistics of the average tear film surface quality in the stable phase of the interblink interval , acquired from HSV using the entire visible corneal area (AOA) and the pupil area, are shown in Table 3 . The estimated averages and standard deviations are very close to median and MAD values, indicating only small numbers of outliers. We note that the tear film quality within the pupil is, as expected, slightly better than across the whole area of analysis.
Group statistics of TFSQAv acquired from HSV.
|TFSQAv from HSV|
The statistics of the tear film parameters acquired from DWS are shown in Table 4 . Large variations were observed between the mean/standard deviation and median/MAD statistics only for based on total aberrations.
Group statistics of TFSQAv acquired from DWS.
|TFSQAv from DWS|
|TA (μm)||HOA (μm)||ComaV (μm)||ComaH (μm)||RMSfit (nm)|
The statistics of the tear film parameters acquired from LSI are shown in Table 5 . As in the case of the HSV technique, there was not much difference between the mean/standard deviation and median/MAD statistics.
Group statistics of TFSQAv acquired from LSI.
|TFSQAv from LSI|
The mean and median values for the estimator of are similar, indicating that the data are not skewed and are free of outliers. This is not the case for the estimator of , where median values were consistently lower than the mean values. One possible explanation is the observed nature of the build-up phase that occasionally exhibits longer periods of tear film formation, and hence does not follow a Gaussian distribution.
To ascertain the precision of the instrument in measuring , the coefficient of variation CV was also calculated. First, the coefficient of variation was calculated using the original TFSQ data in the stable phase of the interblink interval. This was followed by calculating the coefficient of variation for detrended data, in which the linear trend in TFSQ was removed. The group statistics of the coefficient of variation for the are given in Table 6 .
Group statistics of the coefficient of variation (CV) across the instruments.
The coefficient of variation for in HSV was found to be very low (below 1%). The precision of the DWS in quantifying tear film surface quality was found to be more variable. The coefficient of variation for ranged from about 1.5% for the total aberrations to about 15% for the horizontal coma, when the linear trend in the TFSQ was removed. This result was expected, as the total aberrations, which are dominated by the spherical and cylindrical components, are usually more stable than the higher-order aberrations. The coefficient of variation for for the LSI method was also found to be low at 3%.
Correlation between Instruments
Correlation between TBLD measured with the three instruments. The asterisk indicates statistically significant values (p<0.01) .
|Pearson’s correlation coefficient|
Correlation between TFSQAv measured with the three instruments. The asterisk indicates statistically significant values (p<0.01) .
|Pearson’s correlation coefficient|
Moderate but significant correlation was found between measured with LSI and DWS based on the vertical coma ( , ), and between LSI and DWS ( , ) based on the high-order aberrations. Also, moderate but significant correlation was found between measured with LSI and HSV ( , ) and between LSI and DWS ( , ) based on the rms fit error. No significant correlation was found between HSV and DWS for both and .
Statistical significance testing by means of the repeated measures ANOVA for each of the instruments revealed that across the subjects, there are statistically significant differences in and , suggesting that the tear film build-up process as well as the tear film quality level are different between subjects. However, for each of the methods, no statistically significant differences were found in for an individual subject, across the interblink intervals (within a measurement period), or between the two sequential measurement periods. Considering the computed for pairwise comparison across instruments, no statistically significant differences were observed between the HSV and LSI , while DWS showed statistically significant differences when compared to the other two instruments. Hence, as expected from the descriptive statistics, HSV and LSI provide close agreement for measurements of , while DWS differs from the HSV and LSI results.
We have compared three instruments for noninvasive assessment of tear film surface quality (TFSQ), in terms of their precision and agreement for measurements describing the characteristics of the kinetics of the tear film in normal subjects. We aimed to ascertain whether each of the three techniques—the dynamic-area HSV, dynamic wavefront sensing (DWS), and lateral shearing interferometry (LSI)—were capable of consistently and reliably evaluating the quality of tear film surface in natural blinking conditions. It was also of interest whether the estimates of tear film surface quality parameters, such as the tear film build-up time and the average tear film surface quality in the stable phase of the interblink interval, were comparable between the instruments.
Since each of the three considered techniques are based on different physical principles, and since the TFSQ descriptors could not be normalized, it was not possible to directly compare the results of average TFSQ from one instrument with the other. The size and location of the area of analysis in each of the instruments were different, so the pupil areas that were used in each of the instruments were only approximately equal. Also worth noting are the spatial sampling differences between the instruments. The DWS technique samples the pupil area at about intervals. The rings in HSV are spaced between 150 and , while its angular resolution is determined by the charge-couple device (CCD) pixel size. Finally, the LSI technique has a resolution of ( interval). Nevertheless, Pearson’s correlation analysis revealed that the LSI technique was providing that moderately but statistically significantly correlated with the measurement obtained with HSV and DWS, while this was not the case when the HSV technique was compared to DWS. A reason for this could be some difference in the area of the analysis used in both techniques, as the pupil size in HSV measurement is normally smaller than that measured in DWS. The three instruments were found to differ in their precision for deriving the average TFSQ, with the HSV instrument found to be the most precise (i.e., lowest CV), and measures derived from the DWS were typically found to have the lowest precision (i.e., highest CV).
The tear film build-up time is potentially a useful descriptor of tear film dynamics,5, 16 and it can be compared directly between the instruments. This parameter essentially represents the time required following a blink for the tear film quality to stabilize. For all considered instruments, the estimated tear film build-up time was less than and showed a remarkably close median value of around . This suggests that the tear film reaches stable levels relatively rapidly following a blink in normal subjects. This rapid stabilization of the tear film following a blink is advantageous for the visual system, as it ensures a stable optical surface of the anterior eye throughout the majority of the interblink interval. Our findings are in contrast to some previous results recorded with videokeratoscopy5, 6 and wavefront sensing,12 where values of tear film build-up time from were recorded. Differences in the analysis techniques employed, the sampling frequency of the instruments, and the measurement protocols utilized are the likely reasons for the differences noted with these previous studies. In particular, those studies used a protocol in which subjects were asked to blink to try to keep their eyes open, rather than blinking naturally. Our findings do agree closely with those of Szczesna and Kasprzak29 utilizing LSI on a different group of subjects, and with Owens and Philips,32 who estimated the velocity of the particles in the tear film and the time to tear stabilization of . Our results are also consistent with previous estimates of the tear film lipid layer spread of Goto and Tseng33 and Yokoi 16 (less than ), who used another interferometric technique (DR-1 camera), and of Zhu, Collins, and Iskander,18 who measured postblink changes in corneal topography and estimated tear film build-up time to be less than . The improvement of tear film surface quality during the build-up phase, as its name could suggest, may not necessarily be associated with the thickening of tear film, but most likely with the increase of tear film smoothness.34, 35 Hence, the tear film smoothing phase can seem to be a more appropriate name for this phase of tear film dynamic.
We found that the DWS system exhibited lower precision in terms of the average tear film surface quality, and had less agreement in terms of tear film build-up time. In contrast to HSV and LSI, the DWS provides dynamic information regarding changes in the optical quality of the whole eye (as opposed to the dynamics of the anterior surface of the eye alone, as provided by HSV and LSI), and as such can be influenced by concomitant changes in other ocular structures not related to the tear film. Changes in aberrations due to nontear-film-related ocular components (e.g., lens fluctuations or retinal movement) is the likely reason for the lower precision and differences found in tear film build-up time with DWS. There was no significant difference found between measurements obtained using total wavefront aberrations and higher-order aberrations, suggesting that the influence of the cardiopulmonary signals on the lower-order aberrations are of little significance in the measurement of tear film surface quality. The Zernike polynomial rms fit error that has been advocated as a descriptor for tear film surface quality7, 25 showed better performance than the other considered measures based on wavefront aberrations, and was the only DWS parameter to show a moderate correlation with the LSI technique.
In conclusion, the technique of dynamic-area HSV was the most precise method for measuring the average TFSQ by virtue of its lower coefficient variation. It was closely followed by LSI, which also showed low variability within the interblink interval. The LSI technique also appears to be the most sensitive technique for measuring the changes in the tear film surface associated with the tear film build-up phase. We found that the tear film build-up (smoothing) phase is consistently present in natural blinking, but it requires very sensitive methods for its detection. Although in general, the DWS system exhibited lower precision in terms of the average tear film surface quality, and less agreement in terms of tear film build-up time, moderate but significant correlation has been found between estimates of using and HOA descriptors and estimates using LSI. This indicates that DWS also has potential for describing tear film kinetics. Therefore, whilse HSV and LSI techniques demonstrated superior precision to the DWS technique, all three techniques appear to exhibit some merit for describing aspects of the quality and dynamics of tear film. The fact that the techniques are based on different physical principles and have slightly different measurement/analysis areas on the ocular surface suggests that the three techniques can provide information regarding slightly different aspects of the tear film. This study has established the relative precision and reliability of these noninvasive techniques for tear film assessment in normal subjects: however, further information regarding the techniques will be provided by future research investigating the abilities of the methods to detect dry eye, and differentiate dry eye from normal tear film quality.
Part of this study was funded by the 2008 Endeavour Research Fellowship, ERF08_PDR_884, to Dorota H. Szczesna. We thank Beata Sander for assistance with the clinical examination of subjects participating in the study.