THE EFFECT OF TEAR FILM DEGRADATION ON CONTRAST SENSITIVITY FUNCTION

School of Health and Life Sciences
MSc Clinical Ophthalmology & Vision Research Project/Dissertation
TITLE: THE EFFECT OF TEAR FILM DEGRADATION ON CONTRAST SENSITIVITY FUNCTION

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Division of Vision Sciences Glasgow Caledonian University MSC COVR Project/Dissertation Submission Cover Sheet
Please use block capitals throughout

Project/Dissertation Title THE EFFECT OF TEAR FILM DEGRADATION ON CONTRAST SENSITIVITY FUNCTION
I hereby declare that the attached submission is all my own work, that it has not previously been submitted for assessment, and that I have not knowingly allowed it to be copied by another student. I understand that deceiving or attempting to deceive examiners by passing off the work of another writer as one’s own is plagiarism. I also understand that plagiarising another’s work or knowingly allowing another student to plagiarise from my work is against the University regulations and that doing so will result in loss of marks and possible disciplinary proceedings.

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Abstract
Purpose:
To observe the effect of tear film degradation during exposure to a low relative humidity (RH) environment on contrast sensitivity function (CSF).
Methods:
Twenty normal subjects aged from 24 to 43 years took part in this study. A Controlled environment chamber (CEC) was used to create normal (40% RH and 21°C temperature) and dry (5% RH and 21°C temperature) environmental conditions. The tear evaporation rate was measured using the Servomed EP3 Evaporimeter, in normal and dry conditions. A qCSF device, which is a computerised monitor-based test, was used to measure the CSF in both environmental conditions during three time intervals (0.5, 4 and 8 seconds) after a blink.
Results:
After exposing the tear film to low humidity environmental conditions, there was no significant difference in tear evaporation rate between the normal and dry environmental conditions (p > 0.05). The contrast sensitivity function tends to be stable after the tear film has been degraded by exposing it to a low relative humidity environment. There was no significant difference in CSF between the normal and dry environmental conditions within the three time intervals (p > 0.05).
Conclusion:
Contrast sensitivity function was not affected by tear film degradation in this study. Previous studies suggested that CSF was found to be reduced in severe dry eye patients and after the tear film breaks up as a result of tear film disturbance. However, in this study, the adverse effect of low humidity on the tear film seems to be insufficient to cause any disturbance in the tear film, as the longest time interval did not exceed the tear film break up time. Therefore, the CSF is not affected by the slight adverse environment and this theory is supported by the results from previous studies, which showed that CSF was not affected in mild or moderate dry eye patients.
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Table of Contents
Abstract ………………………………………………………………………………………………………………… iii   Acknowledgment …………………………………………………………………………………………………… xi   1   Introduction ……………………………………………………………………………………………………… 1   1.1   Tear film structure and thickness: …………………………………………………………………. 1   1.2   The tear film layers: …………………………………………………………………………………….. 2
1.2.1   The Lipid Layer ……………………………………………………………………………………. 2   1.2.1.1   Origin: …………………………………………………………………………………………… 2   1.2.1.2   Function: ……………………………………………………………………………………….. 2   1.2.2   The Aqueous Layer ………………………………………………………………………………. 3
1.2.2.1   Origin: …………………………………………………………………………………………… 3   1.2.2.2   Function: ……………………………………………………………………………………….. 3   1.2.3   The Mucous Layer ………………………………………………………………………………… 3   1.2.3.1   Origin: …………………………………………………………………………………………… 3
1.2.3.2   Function: ……………………………………………………………………………………….. 3   1.3   Dry Eye ……………………………………………………………………………………………………… 4   1.3.1   Types of Dry Eye: …………………………………………………………………………………. 4   1.3.2   Etiological Classification: ………………………………………………………………………. 5   1.3.2.1   Aqueous Deficient Dry Eye (ADDE): ……………………………………………….. 5
1.3.2.2   Evaporative Dry Eye (EDE): ……………………………………………………………. 6   1.3.3   Causative Mechanisms of Dry Eye: ………………………………………………………… 6   1.4   Treatment of Dry Eye: …………………………………………………………………………………. 6   1.4.1   Tear substitution …………………………………………………………………………………… 7
1.4.1.1   Artificial Tears: ………………………………………………………………………………. 7
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1.4.1.2   Ointments: …………………………………………………………………………………….. 7   1.4.2   Tear Preservation ………………………………………………………………………………….. 7
1.4.2.1   Contact Lenses: ………………………………………………………………………………. 7   1.4.2.2   Moisture Chamber Spectacles: …………………………………………………………. 7   1.4.3   Surgery ………………………………………………………………………………………………… 8   1.4.3.1   Punctual Occlusion: ………………………………………………………………………… 8
1.5   Contrast Sensitivity Function ……………………………………………………………………….. 9   1.5.1   Definition and Importance of Contrast Sensitivity: ……………………………………. 9   1.5.2   History of Contrast Sensitivity ……………………………………………………………… 10   1.6   The study aim: ………………………………………………………………………………………….. 13
2   Methodology …………………………………………………………………………………………………… 15   2.1   Participants: ……………………………………………………………………………………………… 15   2.2   Study design …………………………………………………………………………………………….. 16   2.3   Methods: ………………………………………………………………………………………………….. 18
2.3.1   Ocular Surface Disease Index questionnaire (OSDI) ……………………………….. 18   2.3.2   HIRCAL grid ……………………………………………………………………………………… 19   2.3.3   Servo Med EP Evaporimeter ………………………………………………………………… 21   2.3.4   Contrast sensitivity function (CSF) ……………………………………………………….. 25
2.3.5   Controlled environment chamber (CEC) ………………………………………………… 28   2.4   Data analysis …………………………………………………………………………………………….. 30   3   Results …………………………………………………………………………………………………………… 31   3.1   Tear evaporation rate …………………………………………………………………………………. 32
3.2   Contrast sensitivity function (CSF) ……………………………………………………………… 35   4   Discussion ………………………………………………………………………………………………………. 39   4.1   The effect of low humidity environment on tear evaporation rate: …………………… 39   4.2   The effect of tear film degradation on contrast sensitivity function ………………….. 42
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References …………………………………………………………………………………………………………… 50   Appendices ………………………………………………………………………………………………………….. 58
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List of Figures
Figure 1-1: Illustration of the tear film layers and their estimated thickness ………………….. 2   Figure 1-2: Major etiological causes of dry eye disease outlined by DEWS …………………… 5   Figure 1-3: Moisture chamber spectacles ………………………………………………………………….. 8   Figure 1-4: Contrast sensitivity chart ……………………………………………………………………… 11
Figure 1-5: The Vistech contrast sensitivity chart …………………………………………………….. 12   Figure 1-6: The Pelli-Robson contrast sensitivity chart ……………………………………………… 13   Figure 2-1: Study design. ……………………………………………………………………………………….. 17   Figure 2-2: HIRCAL grid ………………………………………………………………………………………. 20
Figure 2-3: The HIRCAL grid lines are normal and steady directly after the blink ………. 20   Figure 2-4: Simplified diagram for the temperature and humidity sensors ……………………. 21   Figure 2-5: Servomed EP3 Evaporimeter …………………………………………………………………. 22   Figure 2-6: Measurement of tear film evaporation. ……………………………………………………. 24
Figure 2-7: The three band pass-filtered Sloan letters ………………………………………………… 26   Figure 2-8: The eye tracker.. ………………………………………………………………………………….. 27   Figure 2-9: Controlled environment chamber (CEC) …………………………………………………. 28   Figure 2-10: The CEC control panel. ………………………………………………………………………. 29
Figure 3-1: Tear evaporation rate measured in normal (40% RH) and dry (5% RH) conditions. ……………………………………………………………………………………………………………. 32   Figure 3-2: Variation of tear evaporation rate difference (Normal – Dry). ……………………. 34   Figure 3-3: The Area Under the Log CSF (AULCSF) values in normal (A) and dry (B) conditions through the time intervals after blink. ………………………………………………………. 35
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List of Tables
Table 2-1: Dry eye classification ……………………………………………………………………………. 18   Table 3-1: The statistical summary for the age, NITBUT and OSDI score …………………… 31   Table 3-2: The descriptive statistics for tear evaporation rate ……………………………………… 33   Table 3-3:The statistical summary for contrast sensitivity function (AULCSF) values ….. 36
Table 3-4: The two-way ANOVA results for the influence of conditions and time interval on CSF ………………………………………………………………………………………………………………… 37   Table 3-5: The statistical summary for CSF (AULCSF) in different conditions and time intervals. ……………………………………………………………………………………………………………… 38
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List of Abbreviations

ACU …………………….…… Air Conditioning Unit
ADDE ………………………… Aqueous tear-Deficient Dry Eye
AULCSF ……………………… Area Under the Log Contrast Sensitivity Function
CEC ……………………..……. Controlled Environment Chamber
CSF ………………………..…. Contrast Sensitivity Function
DEWS ……………………..…. The Definition and Classification Subcommittee of the
International Dry Eye Workshop
EDE ………………………….. Evaporative Dry Eye
HACSS ……………………… The Holladay Automated Contrast Sensitivity System
IQR ……….………………….. Interquartile Rate
MGD ………………..……….. Meibomian Glands Dysfunction
NITBUT ………….………..… Non-Invasive Tear Break-Up Time
Non SS ……………..………… Non-Sjörgren’s Syndrome
OSDI …………….………..…. Ocular Surface Disease Index
PEK …………………..……… Punctual Epithelial Keratopathy
qCSF ……………………..….. Quick Contrast Sensitivity Function Test
RH …………………….……… Relative Humidity
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SKILL ……………………….. The Smith-Kettlewell Institute Low Luminance
SS ……………..….………..… Sjörgren’s Syndrome
TBUT …………………..……. Tear Break-Up Time
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Acknowledgment
First of all, thanks to my God “Allah” who helped and empowered me to accomplish this work.
I would like to express my deepest thanks and gratitude to my supervisor Prof. Anita Simmers for her guidance and encouragement throughout the research. This thesis would not have been possible without her valuable feedback and advice.
I am extremely grateful to Dr. E. Ian Pearce for his help and advice.
My sincere thanks and gratitude to my mother and my family for their prayers, support and encouragement.
I would like to express my heartfelt appreciation and gratitude to my wife for her loving help, backing and assistance throughout the Master’s period.
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1 Introduction
The tear film is a thin film which covers the outer ocular surface (Tomlinson, 2006). The tear film has many significant functions; the first is maintaining high quality vision because abnormal tear production or evaporation may change the tear film stability which can then negatively affect retinal image quality (Montes-Mico, 2007). Secondly, the tear film enhances ocular surface protection against environmental conditions such as extreme humidity and temperature (Pflugfelder et al., 2004). Thirdly, lubrication of the corneal surface to enhance comfort and protect the ocular surface during blinking (Ohashi et al., 2006). Fourthly, the tear film provides an immune-protection to the ocular surface against microbes and foreign bodies (Rolando & Zierhut, 2001). Fifthly, the tear film contributes to the removal of debris and cellular fragments from the eye (Johnson & Murphy, 2004). And finally, the tear film plays an important role in transporting nutritional substances and oxygen to the cornea. As the cornea relies on the tear film for the delivery of nutrients and oxygen and removal of carbon dioxide because it is an avascular structure (Tiffany, 2008).
1.1 Tear film structure and thickness:
The tear film consists of three layers these are the lipid layer, the aqueous layer and the mucous layer (Figure 1-1) (Tomlinson, 2006). Overall, the tear film thickness has been estimated to be 4 to 8 µm. The aqueous layer is estimated to be the thickest layer at 7 µm, the lipid layer is thinner with 0.1 µm and the thinnest layer is the mucous layer which has a thickness of 0.05 µm (Stahl et al., 2012). Later, studies using non-invasive interferometry estimated the tear film thickness to be around 40 µm (Prydal et al., 1992). However, the most recent measurements taken utilizing tomography and reflectance spectra techniques suggest values near to the original measurements in a range of 3 to 11 µm (King-Smith et al., 2004; Wang et al., 2003).
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Figure 1-1: Illustration of the tear film layers and their estimated thickness (Reproduced from Abusharha, 2014).
1.2 The tear film layers:
1.2.1 The Lipid Layer
1.2.1.1 Origin: The lipid layer is the outermost layer of the tear film. It is an oily and thin layer, and is around 100 nm in thickness (Stahl et al., 2012). It is excreted principally by the meibomian glands with a little assistance from the glands of Möll and Zeiss and partially by the lacrimal glands and epithelium cells (Craig, 2002).
1.2.1.2 Function: The lipid layer has many substantial protective functions, the main one of these being to decrease the evaporation rate from the ocular surface (Bron et al., 2004). Other functions of the lipid layer are to maintain a stable optical surface, to prevent tear film contamination by skin lipids which are different in structure, to lessen eye contamination caused by dust and organisms and to avoid the overflow of tears over the lids (Bron et al., 2004; Foulks, 2007).
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1.2.2 The Aqueous Layer
1.2.2.1 Origin: The aqueous layer is the thickest layer of the tear film. It is a watery layer located beneath the lipid layer and over the mucous layer. It consists of water, proteins, electrolytes, antimicrobial agents and some vitamins and hormones (Stahl et al., 2012). The aqueous layer is produced primarily by the main lacrimal gland and accessory lacrimal glands of Krause and Wolfring (Dartt, 2004).
1.2.2.2 Function: The aqueous layer has a number of significant functions. These include: to supply the cornea (which is avascular organ) with oxygen and essential nutrients, lubricating the ocular surface, protecting the ocular surface from microbes and cleaning the corneal epithelium from foreign bodies and debris (Stahl et al., 2012).
1.2.3 The Mucous Layer
1.2.3.1 Origin: The mucous layer consists of mucin, immunoglobulins, salts, urea, leukocytes, glucose and enzymes (Davidson & Kuonen, 2004). It is produced by the conjunctival goblet cells, the corneal and conjunctival epithelium and the lacrimal gland (Davidson & Kuonen, 2004; Paulsen et al., 2004).
1.2.3.2 Function: The mucous layer performs several functions in order to maintain the ocular surface in a healthy condition. The mucous layer provides a hydrophilic barrier to promote the stability of the aqueous layer (Pflugfelder et al., 2004). In addition, the mucous layer protects the ocular surface against debris and the shear force of blinking and enhances the optical clarity by maintaining a smooth and clear ocular surface (Dartt, 2004).
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1.3 Dry Eye
Dry eye is a common and complicated condition which may cause ocular discomfort and visual impairment (McGinnigle et al., 2012). The International Dry Eye Workshop (2007) defined dry eye disease as “A multifactorial disease of the tears and ocular surface that results in symptoms of discomfort, visual disturbance, and tear film instability with potential damage to the ocular surface. It is accompanied by increased osmolarity of the tear film and inflammation of the ocular surface” (Lemp, 2007). There are several causes of dry eye disease, which can be classified into physiological causes and external causes (McCann, 2009). Physiological causes of dry eye disease include reduced blink rate (Lemp, 2007), large palpebral aperture (Cho et al., 2000), Androgen deficiency (Sullivan, 2004) and increasing age (Uchino et al., 2006). On the other hand, the external factors involve environmental factors that can decrease humidity in the surrounding environment, such as air-conditioning and central heating, which may increase the evaporation of the tear film (Gonzalez-Garcia et al., 2007).
1.3.1 Types of Dry Eye: In 2007, the Definition and Classification Subcommittee of the International Dry Eye Workshop (DEWS) stated that dry eye could be classified based on three parameters: etiological, causative mechanisms and severity (Pinho Tavares et al., 2010). The etiological classification of dry eye disease consists of two classes: aqueous tear-deficient dry eye (ADDE) and evaporative dry eye (EDE) (Figure 1-2). The dry eye causative mechanisms are tear hyperosmolarity and tear film instability (Foulks, 2007). Dry eye disease is classified based on its severity into four grades: mild, moderate, severe frequent and severe constant (Lemp, 2007).
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Figure 1-2: Major etiological causes of dry eye disease outlined by DEWS. (Reproduced from Lemp, 2007).
1.3.2 Etiological Classification:
1.3.2.1 Aqueous Deficient Dry Eye (ADDE): The lacrimal glands produce aqueous tears, so any defect in these glands or decrease in the production of the aqueous tears causes ADDE. ADDE can be classified into Sjörgren’s (SS) and non-Sjörgren’s syndrome (Non SS) (Dogru & Tsubota, 2004). In the case of Sjörgren’s syndrome, the function of the lacrimal gland is impaired by autoantibodies which lead to dry eye disease (Zoukhri, 2006). Non- Sjörgren’s ADDE is caused by
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lacrimal gland dysfunction (Lemp, 2007). This dysfunction can be a result of many factors such as disease or damage to the lacrimal gland or blockage of the gland (Ogawa et al., 2003).
1.3.2.2 Evaporative Dry Eye (EDE): Evaporative dry eye is a result of excessive tear evaporation which is caused by interruption in the lipid barrier (Mathers, 2004). The causes of evaporative dry eye can be intrinsic and extrinsic. Intrinsic causes include meibomian glands dysfunction (MGD), eye lid disorders and reduced blink rate (Bron & Tiffany, 2004). The extrinsic causes involve ocular surface diseases, contact lens wear and allergic conjunctivitis (Abelson et al., 2003).
1.3.3 Causative Mechanisms of Dry Eye: The dry eye causative mechanisms are tear hyperosmolarity and tear film instability. Decreased aqueous secretion or increased tear evaporation can lead to tear hyperosmolarity which causes ocular surface inflammation and damage that can lead to tear film instability (Lemp, 2007). Tear film instability can increase the tear evaporation rate and lead, in turn, to hyperosmolarity (Pinho Tavares et al., 2010).
1.4 Treatment of Dry Eye:
The aim of treatment for dry eye disease is to improve the comfort and the quality of life of the patient and to normalize the state of the tear film and ocular surface (Pinho Tavares et al., 2010). Treatment varies depending on the type of dry eye disease and the severity of the case (Lemp, 2008). Several treatments can be used to treat dry eye disease, beginning with tear substitutes such as artificial tears and ointments which are used to compensate the tears and to improve lubrication at the ocular surface (Calonge, 2001). Another type of treatment is tear preservation, which plays an important role in decreasing evaporation of the tear film (McCulley et al., 2006) these treatments can come in the form of moisture chamber spectacles and contact lenses. Severe dry eye, which other methods of treatment may fail to treat satisfactory, may require surgery. Punctual occlusion is the most common surgery to be used for this purpose (Mansour et al., 2007).
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1.4.1 Tear substitution
1.4.1.1 Artificial Tears: Artificial tears are the most widely used treatment for dry eye disease particularly for mild cases (Asbell, 2006). They are designed to serve as an alternative to tears in cases of lacrimal or mucous deficiency. They are used to increase humidity and lubrication at the ocular surface and to improve the clarity of vision, as a secondary benefit, as a result of smoother corneal surface. Artificial tears are used to allay the patient’s symptoms but not inevitably to eliminate the symptoms (Calonge, 2001).
1.4.1.2 Ointments: Ointments are used to produce a longer lubrication time (Xiao et al., 2008). They often contain a mixture of mineral oil, lanolin and petroleum, which allow them to complete their task. However, they may cause blurring of vision and irritation of the eye because of their thickness (Vehige & Simmons, 2004).
1.4.2 Tear Preservation
1.4.2.1 Contact Lenses: One of the therapeutic aids in the treatment of dry eye disease is the use of contact lenses (Ramamoorthy & Nichols, 2008). The use of silicone hydrogel lenses and other types of lenses, which have high water content, and oxygen permeability (Dk values) may lead to an increase in the sense of comfort for the patient (Farris, 1994). This is a result of maintaining moisture on the ocular surface. However, contact lens wear can the occasional small risk, of corneal infection and neovascularization (Sindt & Longmuir, 2007).
1.4.2.2 Moisture Chamber Spectacles: Tight fitting goggles have also been used to decrease the evaporation rate from the tear film surface (Figure 1-3) (Tsubota et al., 1994). These goggles are worn to increase humidity around the ocular surface, which in turn will induce a reduction in the evaporation of the tear film (Tsubota, 1994).
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Figure 1-3: Moisture chamber spectacles (Reproduced from Waduthantri et al., 2014).
1.4.3 Surgery
1.4.3.1 Punctual Occlusion: Finally, surgery may become the only treatment option left to patients who suffer from severe dry eye who haven’t responded to other clinical treatments. There are multiple types of surgeries that can help to treat dry eye disease the most commonly used procedure is punctual occlusion (Pinho Tavares et al., 2010). This procedure reduces drainage, maintains natural tears and extends any lubricant effect (Baxter & Laibson, 2004). Punctual occlusion procedure is performed by inserting collagen plugs into the lacrimal canaliculi to close it. These plugs will usually dissolve after one or two weeks, and there are also long-lasting collagen plugs which will dissolve after several months and these tend to be used in the more severe cases (Hamano, 2005). In addition, silicon plugs have been commonly used as an alternative to the extended plugs. They are made in several sizes and the method of insertion differs in accordance with the plug’s type (Pinho Tavares et al., 2010). However, this procedure is not without its disadvantages and may reduce tear production clearance and ocular surface sensation which in turn may promote inflammation of the ocular surface (Calonge, 2001).
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1.5 Contrast Sensitivity Function
1.5.1 Definition and Importance of Contrast Sensitivity:
Contrast sensitivity, which indicates changes in luminance through an image, is a substantial property of the human visual system (Baker, 2013). Clinically, contrast sensitivity is significant because it predicts visual function better than other visual acuity measures. Visual acuity is one of the most efficient methods of measuring vision. It is a simple and fast technique to determine the eye’s ability to see, by finding the borderline between the images that can be distinguished and those that cannot. A visual acuity value represents the smallest letter or line on the eye chart that the patient can see (Rosenthal, 2006). However, visual acuity may be an inadequate way to illustrate a person’s ability to see low-contrast objects, even if they are large such as faces (Rubin, 2013).
Visual function consists of many other elements other than visual acuity, such as visual field, colour perception and contrast sensitivity function (CSF) (Rosenthal, 2006). Contrast sensitivity provides a more detailed picture of a person’s vision, and can be acquired by finding the faintest pattern that the patient can see (Baker, 2013). The CSF explains changes of grating sensitivity (1/threshold) to a range of spatial frequencies (sizes) (Lesmes et al., 2010). It gives information about how the visual system responds to the different contrast and spatial frequencies of the visual environment and tasks (Lee et al., 2014).
Contrast sensitivity deficits are present with visual neuro-pathologies, even when visual acuity or perimetry tests seem to be normal. This suggests that contrast sensitivity can be used as a screening tool as it may be more sensitive to early eye disease than visual acuity. The important value of a clinical contrast sensitivity test is that it gives a better understanding of the whole visual performance and therefore the effects any visual deficits may have on functional capability (Rubin, 2013).
Many dry eye patients report blurred or foggy vision and glare as symptoms, despite having normal, or corrected to normal, vision. These visual disturbances may affect quality of life and result in reductions in visual acuity and contrast sensitivity, which consequently can then cause difficulties with the performance of everyday tasks. These symptoms appear exacerbated in bright sunlight or in dark places with low contrast levels, such as
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night driving (Ridder et al., 2011). A study conducted by Miljanovic et al. (2007) on 589 subjects which approximately one third of them (190 subjects) had dry eye disease. The study results, which were based on surveys, revealed that people suffering from dry eye have a high rate of difficulty in reading. The questionnaire results showed that the subjects with dry eye disease mentioned limitations in their ability to read, drive, work at the computer, and watch TV, more than the subjects without the symptoms of dry eye.
Some of the characteristic features of dry eye disease, such as tear hyperosmolarity and increased evaporation of the tear film, can cause damage to the ocular surface. These physical irregularities of the ocular surface can cause visual impairment and may lead to punctual epithelial keratopathy (PEK). PEK may induce further irregularities in the corneal surface, which may also lead to constant perceptual changes, contributing to the reported reduction in visual acuity and contrast sensitivity (Ridder et al., 2011). It is also thought that these reductions in visual function may be caused by the reduction in tear breakup time (TBUT), which in turn causes an irregular tear film (Ridder et al., 2013).
1.5.2 History of Contrast Sensitivity In the middle of the 18th century, Pierre Bouguer created the first effective method to measure the human visual threshold of light contrast. His experiment was performed to see to what extent the shadow of a rod cast by a far candle on a white screen stayed visible (Bouguer, 1760; cited in Robson, 1993).
Subsequently, there were many efforts to produce a faster and more convenient way to measure contrast sensitivity. The first attempt was implemented by Ole Bull (1881, cited in Robson, 1993) who designed a chart, which was similar to the Snellen chart, but he used letters as visual stimuli, with different gradations of grey colour on a black background.
A few years later, Bjerrum (1884, cited in Robson, 1993) created a group of Snellen charts with various contrast ratios against a white background. Bjerrum’s charts might have been the first widely approved method to be used for measuring contrast sensitivity.
These charts continued to be used for more than thirty years, until George Young developed a new technique, which seemed to be quick and easy (Young, 1918; cited in Robson, 1993). He created a set of ink spots, which changed in contrast levels. The book starts with the low contrast spots and works towards the high contrast levels. The test uses
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the forced-choice method to force the individual to report the discovery of the spot and its location.
In 1948, Selwyn suggested a simple and more precise target for contrast sensitivity, which used sine wave gratings (Figure 1-4). In addition, Selwyn was the first person to study the effects of spatial frequency (i.e. size) on contrast sensitivity, known as the contrast sensitivity function (CSF) (Selwyn, 1948; cited in Robson, 1993).
Figure 1-4: Contrast sensitivity chart. It shows how the contrasts reduce over the vertical axis and the spatial frequencies increase (the width of the bars) over the horizontal axis (Reproduced from Ridder et al., 2011).
The modern contrast sensitivity measurements started in 1984 when Ginsburg produced the Vistech chart (Ginsburg, 1984). The Vistech chart aims to measure contrast sensitivity at five different spatial frequencies varying from 1.5 c/deg to 18 c/deg (Figure 1-5). It is still one of the most widely used methods for measuring contrast sensitivity because it is a rapid and easy method for the patient and the examiner, and it gives a number of spatial sensitivities which are wide enough to produce the shape of CSF.
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Figure 1-5: The Vistech contrast sensitivity chart (Reproduced from Mäntyjärvi et al., 1989).
Pelli, Robson and Wilkins (1988) designed a single letter chart to measure contrast sensitivity (Figure 1-6). They used a series of letters, which gradually reduce in contrast to make their chart. Currently, CSF is measured clinically by using preprinted letter/grating charts such as the Vistech chart, the Pelli-Robson chart and the CVS-1000 series chart (Hou et al., 2010). However, these charts have disadvantages regarding their limited number of contrast levels, which make the field and resolution of the grating stimuli extremely limited (Ginsburg, 2003).
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Figure 1-6: The Pelli-Robson contrast sensitivity chart (Reproduced from Abelson et al., 2006).
On the other hand, the CSF measurement in laboratory psychophysical tests showed high accuracy in results (Hou et al., 2010). The tests, which are equipped with a Bayesian adaptive strategy such as the qCSF method, can estimate the full CSF with acceptable accuracy in less than ten minutes, making it suitable for clinical use (Lesmes et al., 2010).
1.6 The study aim:
The aim of this study is to observe the effect of tear film degradation during exposure to a low humidity environment on the contrast sensitivity function (CSF). In order to monitor the tear film degradation during exposure to a dry environment, the tear evaporation rate will be measured in normal (40% relative humidity) and dry (5% relative humidity) environmental conditions. Thereafter, the effect of this degradation on CSF will be studied.
Many dry eye patients report blurry vision despite having normal or corrected vision (Ridder et al., 2011). Therefore, previous studies have been conducted to study the effect of dry eye disease on the contrast sensitivity function and the difference between dry eye patients and normal subjects in relation to the contrast sensitivity function (CSF) (Rolando et al., 1998; Huang et al., 2002; Puell et al., 2006; Teson et al., 2009; Ridder et al., 2013). However, this study is designed to observe the effect of tear film degradation during
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exposure to a low humidity environment, on the CSF of normal healthy subjects.
The advantages of this study are that it links the external effects on the ocular surface (low humidity environment) to perceptual (cortical) visual function (contrast sensitivity function). In addition, this study aims to find out that if ocular discomfort experienced by dry eye suffers reflected on reduced the visual functions.
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2 Methodology
2.1 Participants:
A total of 20 normal subjects (13 male, 7 female) are involved in the study. The participants’ age ranged from 24 to 43 years (mean ± SD: 29.8 ± 4.4 years). Participants were students from Glasgow Caledonian University with no consideration given to the ethnicity and gender of the participants when suitable subjects were selected. The subjects were included in this study if they fulfilled the inclusion criteria declared below:
1) Ocular surface disease index (OSDI) score < 12 (Schiffman et al., 2000).
2) Non-invasive tear break up time (NITBUT) > 10 seconds (Bron, 2001).
Exclusion criteria were defined as any subject under 18 years old, or with a history of dry eye syndrome, ocular disease, or ocular surgery. Contact lens wearers were asked to remove their lenses 24 hours prior to the test.
Ethical approval was obtained from the Glasgow Caledonian University Life Sciences Ethics Committee before embarking on any experiments or measurements (see Appendix 1: Ethical approval for research). All subjects had received a written information and consent sheet. The sheet included the study title and all the details which included the study aim and procedure. The participants were asked to sign the consent form after reading the whole sheet carefully (see Appendix 2: information and consent sheet). It was mentioned that taking part in the study was entirely voluntary and that the participants were free to withdraw from it at any time without affecting the standard of care they received. In addition, it was stated that any collected information would stay confidential and anonymous and that all the data would be held anonymously and stored in a secure location.
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2.2 Study design
To observe the effect of tear film degradation during exposure to a dry climate on contrast sensitivity function, contrast sensitivity function (CSF) and tear evaporation rate were tested in normal and dry environments for all the subjects. Two visits were required to perform this study, on two separate days, to allow plenty of time for the tear film to return to its natural state after the first visit. One visit was to measure the contrast sensitivity function and the tear evaporation rate in a normal environment. The other visit was to reassess the same measurements after exposing the eye to a very dry environment (Figure 2-1). The contrast sensitivity measurement takes a long time and requires a high level of attention so it was conducted first to avoid causing fatigue to the subjects. Visits were organised in an alternating procedure, where for example subject 1 was tested in a normal then dry environment, and subject 2 dry then normal etc.
In order to determine which subjects could enrol in this study, they were all asked to complete the Ocular Surface Disease Index (OSDI) questionnaire, and the tear film break up time was assessed using the HIRCAL grid on the first visit. The subjects who met the inclusion criteria mentioned above were asked to sign the consent form and were involved in the study.
In order to control the environment and create an adverse condition, the study was held inside a Controlled Environment Chamber (CEC) (Weiss-Gallenkamp Ltd, Loughborough, UK). The CEC was set at normal and dry conditions to investigate the effect of the change of relative humidity (RH) on contrast sensitivity function and tear evaporation rate. These conditions were set as below:
1/ Normal environment: surrounding temperature at 21°C and relative humidity at 40%.
2/ Dry environment: surrounding temperature at 21°C and relative humidity at 5%.
The normal temperature and relative humidity were selected at the values mentioned above because a number of environment and health organisations have recommended that the convenient surrounding temperature inside work buildings should be between 20°C and 23°C, while the lowest recommended relative humidity ranges from 35% to 45% (Nathanson, 1993; OSHA, 2003). On the other hand, a dry environment at 5% has been
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recorded in some working environments such as airplane cabins and high-technology devices factories (Wolkoff, 2008; Sato et al., 2003). All the subjects were asked to stay inside the CEC for 10 minutes for room adaptation before starting the tests in both environments. According to Purslow (2005), the required time for room adaptation to various environmental conditions should be at least 6 to 10 minutes before performing any ocular surface tests.
A
CSF Evaporation rate . Room adaptation ? ?

0 10

B
CSF Evaporation rate
Room adaptation ? ?

0 10
Figure 2-1: Study design. (A) The measurements were carried out in a normal environment (40% RH and 21°C). Contrast sensitivity function (CSF) and then tear evaporation rate were measured after 10 minutes of room adaptation. (B) The same measurements were performed in the same order but after adapting the subjects for 10 minutes in a dry environment (5% RH and 21°C).
Normal     Environment     40%  relative   humidity  (RH)   21°C   temperature
Dry     Environment     5%  relative   humidity  (RH)   21°C   temperature
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2.3 Methods:
2.3.1 Ocular Surface Disease Index questionnaire (OSDI)
The ocular surface disease index (OSDI) is a questionnaire which has been developed to evaluate ocular surface symptoms (Schiffman et al., 2000). It consists of twelve questions producing assessment of the three main symptom types. These include ocular symptoms (experiencing any sensitivity to light, eye grittiness, eye pain, blurred and poor vision), vision function difficulties (having problems with reading, driving at night, working with computers and watching TV) and symptoms related to environment (feeling uncomfortable in windy conditions, very dry areas and air conditioned places) (Schiffman et al., 2000). The OSDI scale ranges from 0 to 100 points. The maximum score of 100 points represents greater disability, while scores less than 12 points are considered normal (see Appendix 3: Ocular surface disease index OSDI) (Schiffman et al., 2000). The dry eye severity can be classified, based on the OSDI score, into 4 classifications (Table 2-1) (see Appendix 4: The evaluation sheet of OSDI) (Miller et al., 2010). The OSDI was used because it is a fast and easy questionnaire which provides information about the existence and recurrence of dry eye symptoms (Vitale et al., 2004; Miller et al., 2010). Furthermore, it has specific questions concerning symptoms which may present in special environment conditions such as windy and dry conditions (Miller et al., 2010).
Table 2-1: Dry eye classification based on Ocular Surface Disease Index OSDI score (Miller et al., 2010).
Overall OSDI score Diagnosis
0-12 points Normal
13-22 points Mild dry eye
23-32 points Moderate dry eye
33-100 points Severe dry eye
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2.3.2 HIRCAL grid
The HIRCAL grid was used to estimate non-invasive tear break-up time by observing the reflected precise grid image which is projected on the tear film and the anterior surface of the eye (Hirji et al., 1989). The major benefits of this method are that it avoids direct touching of the ocular surface and the use of fluorescein, which may change the tear volume and characteristics (Patel et al., 1985; Craig, 1995). Regular tear film appears smooth, then it becomes thin and begins to break down, and the reflected image tends to become blurry and distorted.
The HIRCAL grid is a modified Bausch and Lomb keratometer whose mire has been exchanged by a white on black grid (Figure 2-2). During the test, the subjects were advised to blink normally. The fine grid image which is reflected from the tear film was noted at the first signs of haziness or distortion of the grid lines (Figure 2-3). The tear break-up time is the recorded time (in seconds) between the blink and the appearance of the disturbance of the fine grid. It has been stated that a NITBUT value of 10 seconds produces a high percentage of sensitivity (82%) and specificity (86%) for the diagnosis of dry eye disease (Mengher et al., 1986). These measurements were taken three times and the average of three readings was calculated.
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Figure 2-2: HIRCAL grid (Reproduced from Abusharha, 2014).

A B
Figure 2-3: The HIRCAL grid lines are normal and steady directly after the blink (A). The HIRCAL grid lines appear to be distorted after a while because the tear film becomes thinner (B) (Reproduced from Craig, 1995).
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2.3.3 Servo Med EP Evaporimeter
The tear film evaporation rate was measured by a modified Servomed EP3 Evaporimeter (Servo Med, Varberg, Sweden) (Trees & Tomlinson, 1990). The tear evaporation rate can be predicted by counting the vapour pressure gradient between two sensors divided by a known distance (Trees & Tomlinson, 1990). One of the two sensors is for humidity and the other is for temperature (Figure 2-4). They are installed in a probe which is fixed on a slit lamp. The probe is connected with a modified swimming goggle which is far from the eye by a known distance (Figure 2-5). The goggle is used to segregate the ocular surface from the air stream and the surrounding environment and to avoid touching the ocular surface.
Figure 2-4: Simplified diagram for the temperature and humidity sensors (Reproduced from Abusharha, 2014).
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Figure 2-5: Servomed EP3 Evaporimeter
The subjects were instructed to sit comfortably on a chin rest whilst maintaining gentle pressure on the goggle over their right eye to avoid the presence of any gap between the goggle and skin. Each subject underwent the same measurements twice, once with an open eye which displayed the evaporation of the tear film and the skin inside the goggle, and then again with a closed eye which revealed the evaporation of the skin only. The subjects were instructed to blink normally and to focus on a fixed target while the measurements were taken for the open eye, and to close their eyes completely during the test for the closed eye.
In order to record the signals from the probe and calculate the evaporation rate, custom designed computer software (Workbench 5.0, Strawberry Tree Inc, Sunnyvale, Canada) was used (Figure 2-6). The software records six hundred readings for the evaporation in two minutes at a rate of five readings per second. However, to calculate the ultimate evaporation rate, only the last three hundred readings were used. This is to allow the evaporation values to be stable.
In addition, a digital picture of the open eye for each subject was taken to calculate the area of the eye using Image J 1.34 computer software (National Institute of Health, Rockville, USA). This is because the calculated evaporation rate for the open eye also involves the evaporation of the ambient skin inside the goggle. Therefore, only the evaporation rate for the eye area should be calculated. For this reason, an Excel spread
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sheet including the evaporation readings, eye area, humidity and temperature was used to calculate the final evaporation rate using the formula below: (Trees & Tomlinson, 1990).
*
Where:
A = the eye area (mm2)
G = the area within the goggle (mm2)
O = the evaporation rate for open eye (g/ m2/ h)
C = the evaporation rate for closed eye (g/ m2/ h)
: Correction factor for temperature and humidity
P = the partial pressure of water vapour
Pmax = Saturated water vapour pressure at certain temperature (Pa)
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Figure 2-6: Measurement of tear film evaporation. The figure displays the swimming goggle containing the sensors, the Servo Med EP Evaporimeter, and the Workbench 5.0 software which records the signals and calculates the evaporation (Reproduced from Abusharha, 2014).
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2.3.4 Contrast sensitivity function (CSF)
Full contrast sensitivity, which is widely used in psychophysics and physiology, is a comprehensive measurement of vision because it estimates the sensitivity of the visual system over a wide range of contrasts and spatial frequencies (Lesmes et al., 2010). The area under the curve of the CSF has been reliably shown to be a sensitive indicator for changes in neurologic and ophthalmologic vision (Lesmes et al., 2010). Nevertheless, standard measurement of CSF is time-consuming and has not generally been used in clinical eye research. Therefore, the use of computer-based display adaptive testing would produce a fast and reliable CSF measurement (Lesmes et al., 2010).
Recently, a new method called the quick CSF (qCSF) has been developed and used in the investigation of ophthalmic diseases, providing trusty results. It is hypothesised that the qCSF method could be more associated with any perceptual disturbance in dry eye than any other standard high contrast letter charts (Lesmes et al., 2010).
The qCSF device:
This is a computerised monitor-based test in which the stimuli are presented in three band pass-filtered Sloan letters in each of 25 trials (Figure 2-7). The letters appear at 0.5, 4 and 8 seconds after the beginning of the test. The stimuli were shown on a 19-inch coloured computer screen at a viewing distance of 60 cm. Spatial frequency (19 log-equidistant steps between 1.57 and 40.7 cycles per degree (cpd) of visual angle) and contrast (128 logequidistant levels between 0.2 and 100%) were selected by using a Bayesian adaptive algorithm which expands the anticipated information which is obtained based on the results of previous trials. The subjects were asked to respond to each letter. The responses were scored as correct, incorrect or letter not seen by the test monitor using the computer keyboard. All subjects had normal or corrected to normal vision.
A satisfactory estimation of the whole contrast sensitivity function is gained after the test completion because the qCSF estimates the contrast sensitivity threshold for a wide range of spatial frequencies. The median time for the test was twenty-five minutes, which included the time taken to enter subject details and to prepare the subject for the test. Throughout the preparation period in the first visit the subjects performed a preliminary trial, which consisted of five trials, to let the subjects accustom themselves to the stimuli.
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The qCSF device was equipped with an eye tracker to track any blink during the trial period (8 seconds) (Figure 2-8). The CSF software has been programmed to start the test directly after the subject blinks and to stop when the subject blinks during the trial or when the trial is completed. Therefore, the subject needed to accomplish 25 complete trials to finish the test. The subjects were asked to keep their eyes open during the test until the trial completed (8 seconds) and to respond by telling the test proctor which letters they could see. The test results provided summary statistics about contrast sensitivity function which included the area under the Log CSF (AULCSF) in the spatial frequency range from 1.5 to 18 cpd.
A B C
Figure 2-7: The H letter present in three band pass-filtered Sloan letters [(unfiltered H (A), low pass-filtered H (B) and high pass-filtered H (C)] (reproduced from Hall et al., 2014).
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Figure 2-8: The eye tracker. It is used to track any blink during the trial period which lasts 8 seconds. The subject’s initial blink starts the test.
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2.3.5 Controlled environment chamber (CEC)
A controlled environment chamber (CEC) was used in this study to generate various environmental conditions. This is an isolated room which was designed and built by Weiss-Gallenkmap, (Loughborough, UK). The CEC can be set at any temperature in the range of 5°C to 35°C and a relative humidity between 5% and 95% (Figure 2-9). The CEC is supplied with a control panel which allows the operator to control the temperature and humidity (Figure 2-10). The CEC is equipped with an air conditioning unit (ACU) to control the ambient temperature and with a vapour desiccant dehumidifier to produce the relative humidity inside the room.
Figure 2-9: Controlled environment chamber (CEC)
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Figure 2-10: The CEC control panel which allows the operator to control the humidity and temperature inside the room.
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2.4 Data analysis
All data were uploaded into a Microsoft Excel 2011 spreadsheet and the data were statistically analysed using the Minitab Express version 1.3 statistics software. The mean, median and standard deviation were calculated for the age, and the preliminary measurements (NITBUT and OSDI). For the tear evaporation rate, a box plot chart was drawn for the data to provide an overview of the difference between the tear evaporation rate in normal (40% RH) and dry (5% RH) conditions. To study the difference in tear evaporation rate between normal and dry conditions, a new variable (Difference = normal – dry) was computed. A test of normality was accomplished using the Anderson-Darling test. Data which was normally distributed was compared using the parametric Paired T-test to calculate the p-value. A p-value of less than 0.05 was considered statistically significant.
In order to study the effect of the different environmental conditions (normal and dry) on the contrast sensitivity function (CSF) at the varying time intervals after a blink, a two factor Analysis of Variance (ANOVA) was employed. The Two-Way ANOVA test is used to discover if there is an effect of two different independent variables on one dependent variable and if there is an interaction between them (Rasch et al., 2009). A normal probability plot was performed to ascertain whether the model fits the data and whether the test results are reliable.
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3 Results
The aim of this study was to observe the effect of tear film degradation during exposure to a dry climate on the contrast sensitivity function (CSF). Twenty normal subjects were recruited for this study (13 male, 7 female) the age average ± standard deviation was 29.8 ± 4.4 years. All the subjects who participated in the study fulfilled the inclusion criteria mentioned previously which include the NITBUT and OSDI score. The mean, median and standard deviation of the age, non-invasive tear break-up time (NITBUT) and ocular surface disease index (OSDI) score are listed in Table 3-1.
Table 3-1: The mean, median and standard deviation values for the age, NITBUT and OSDI score for the study sample (see Appendix 5: Statistical analysis of age, NITBUT and OSDI for more detailed statistics).
Variable N Mean StDev Median
Age (year) 20 29.75 4.44 29.50
NITBUT (sec) 20 12 1 11.50
OSDI (point) 20 2.95 2.16 2.50
The average NITBUT ± standard deviation was 12 ± 1 seconds for the study sample. Three subjects were excluded from the study because they failed to achieve the minimum limit which was stated as 10 seconds. The mean ± standard deviation for the OSDI score was 2.95 ± 2.16 points, which is much less than the exclusion limit which was > 12 points. In addition, two subjects were excluded from the study because they were wearing high powered prescription glasses which did not allow the eye tracker to follow their eyes during the contrast sensitivity test. The total number of subjects in this study (20 subjects) is the number after excluding these subjects.
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3.1 Tear evaporation rate
Tear evaporation rate for subjects at normal (40% relative humidity) and dry (5% relative humidity) environmental conditions are shown in figure 3-1. The box plot suggests that the median and the box part are slightly higher in dry conditions. However, there is no obvious difference between normal and dry conditions in the tear evaporation rate as the median and the box part are comparable.
Figure 3-1: A box plot illustrating tear evaporation rate measured in normal (40% RH) and dry (5% RH) conditions. There is no clear difference in tear evaporation rate between normal and dry conditions. The box part contains 50% of the study data which equals the interquartile rate (IQR). The horizontal line within the box part represents the median. The lines which are drawn from the box boundaries to the minimum and maximum values presented these fall within 1.5 × IQR of the specific quartile. Outliers represent the values which lie outside the limits of 1.5 × IQR from the respective quartile and are indicated by (*) symbol.
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The mean tear evaporation rate was 29.37 g/m2/h (0.08 µl/min) in normal conditions and 29.40 g/m2/h (0.08 µl/min) in dry conditions which means that they were almost equal i.e. there was no significant difference. To put this into context, according to Tomlinson et al. (2009), the evaporation cut off value between normal and dry eye patients is 79.20 g/m2/h (0.22 µl/min). Therefore, the tear evaporation rate in the current study falls within the range of normal values. (see Table 3-2 for the means and other descriptive statistics).
Table 3-2: The descriptive statistics for tear evaporation rate in normal and dry conditions (g/m2/h).
Variable N Mean
SE Mean
StDev Minimum Q1 Median Q3 Max.
Normal 20 29.36 5.19 23.24 -1.97 14.46 27.52 35.73 85.21
Dry 20 29.39 2.70 12.11 8.71 19.04 29.08 37.37 55.37
A new variable difference which was defined as: Difference = Normal – Dry was calculated. The dot plot in Figure 3-2 shows a reasonable variation as a wide range is observed and there are no signs of skewness as the number of points above and below zero are nearly similar. Data from the difference between normal and dry conditions were normally distributed and a parametric Paired T-test was implemented to find out the difference in the evaporation rate between normal and dry conditions (see Appendix 6: Statistical analysis for tear evaporation rate). The Paired T-test showed no significant difference between the evaporation rates in normal and dry conditions (p-value > 0.05).
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Figure 3-2: Variation of tear evaporation rate difference (Normal – Dry).
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3.2 Contrast sensitivity function (CSF)
A box plot of the Area Under the Log CSF (AULCSF) values in different conditions and time intervals is shown in Figure 3-3.
Figure 3-3: A box plot showing the Area Under the Log CSF (AULCSF) values in normal (A) and dry (B) conditions through the time intervals after blink. Time intervals 1,2 and 3 represent the CSF values after 0.5, 4 and 8 seconds from the beginning of the test respectively. There is no clear difference between A and B conditions within all time intervals.
In Figure 3-3, the letter A refers to normal environmental conditions while letter B refers to dry environmental conditions. In the time intervals, numbers 1, 2 and 3 represent the CSF values after 0.5, 4 and 8 seconds respectively from the initial blink, which starts the test. The medians and box parts suggest that there is no clear difference between the
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normal and dry (A and B) conditions within the three time intervals. Furthermore, the medians of A and B in time interval 1 seem to show a trend towards being slightly higher compared to the medians in time intervals 2 and 3. This means that the CSF would appear to be slightly better at the beginning of the test i.e. straight after a blink compared to 4 and 8 seconds after blinking (see Table 3-3 for the statistical summary of the AULCSF values).
Table 3-3:The statistical summary for contrast sensitivity function (AULCSF) values in normal (A) and dry (B) conditions at various time intervals 1, 2 and 3 which represent 0.5, 4 and 8 seconds after the beginning of the test respectively.
Time Interval Condition N Minimum Q1 Median Q3 Maximum
1
A 20 2.07 2.43 2.59 2.71 2.98
B 20 2.01 2.50 2.61 2.79 2.89
2
A 20 2.00 2.39 2.50 2.73 3.06
B 20 2.16 2.45 2.50 2.63 2.94
3
A 20 2.08 2.38 2.52 2.64 2.93
B 20 2.12 2.39 2.59 2.69 2.86
A two-way ANOVA test was carried out for CSF versus conditions and time intervals (Table 3-4). The p-values for the two variables (condition and time interval) were both >0.05 which suggest that the condition and time interval do not have any effect on the CSF. Moreover, the interaction between the two variables has a p-value > 0.05 which means that there is no interaction between conditions and time intervals.
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Table 3-4: The two-way ANOVA results for the influence of conditions and time interval on CSF. The Two-Way ANOVA test is used to discover if there is an effect of two different independent variables in one dependent variable and if there is an interaction between them (Rasch et al., 2009). The test shows that there is no effect of condition and time interval on the CSF and there is no interaction between them (p > 0.05).
Source DF Adj SS Adj MS F-Value P-Value
Condition 1 0.00884 0.0088408 0.17 0.6808
Time Interval 2 0.03643 0.0182158 0.35 0.7051
Condition * Time Interval 2 0.02758 0.0137908 0.27 0.7674
Error 114 5.92445 0.0519688
Total 119 5.99730
The means values for the CSF (AULCSF) in Table 3-5 show that the CSF was slightly higher in the dry (B) condition (2.55) compared to the normal (A) condition (2.53). In more detail, the CSF value was slightly higher in the dry conditions at all the time intervals, except time interval 2 (after 4 seconds). However, this difference is not significant as the p-value for the both variables (conditions and time intervals) and the interaction between them is > 0.05. In addition, a normal probability plot was performed to ascertain that the model fits the data and it was found that the data were normally distributed which means that the test results are reliable (see Appendix 7: The model summary and the normal probability plot).
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Table 3-5: The mean and standard error of mean values for CSF (AULCSF) in different conditions and time intervals. In general, the mean CSF value was slightly higher in the dry (B) condition compared to the normal (A) condition and the mean CSF value was higher in time interval 1 (after 0.5 seconds) compared to the other time intervals (after 4, 8 seconds). In more detail, the CSF value was slightly higher in the dry conditions at all the time intervals except in time interval 2 (after 4 seconds). However, the differences were not statistically significant which means that the conditions and time interval do not affect the CSF value (p > 0.05).
Term Fitted Mean SE Mean
Condition A 2.53150 0.02943
B 2.54867 0.02943
Time Interval
1 2.56450 0.03604
2 2.53075 0.03604
3 2.52500 0.03604
Condition * Time Interval
A 1 2.55900 0.05097
A 2 2.53900 0.05097
A 3 2.49650 0.05097
B 1 2.57000 0.05097
B 2 2.52250 0.05097
B 3 2.55350 0.05097
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4 Discussion
The aim of this study was to observe the effect of tear film degradation during exposure to a low humidity environment on the contrast sensitivity function (CSF). To monitor the tear film deterioration during exposure to a dry environment, the tear evaporation rate was measured in normal (40% RH) and dry (5% RH) environmental conditions. Thereafter, the effect of this deterioration on CSF was studied.
The advantages of this study are that it links the external effects on the ocular surface (low humidity environment) to perceptual (cortical) visual function (contrast sensitivity function). In addition, this study aims to find out that if ocular discomfort experienced by dry eye suffers reflected on reduced the visual functions.
4.1 The effect of low humidity environment on tear evaporation rate:
Earlier studies have suggested that environmental factors such as relative humidity (RH) and temperature could affect several tear film parameters (Borchman et al., 2009; Wolkoff, 2008). One of them is tear evaporation rate, which many previous studies indicated increases during exposure to a dry climate (McCulley et al., 2006; Uchiyama et al., 2007; Abusharha & Pearce, 2013). The elevation in tear evaporation rate is correlated with the thin and irregular lipid layer model (Craig & Tomlinson, 1997).
According to a study conducted by Abusharha and Pearce (2013), the lipid layer thickness was significantly decreased after exposure to a low relative humidity. Another study, which examined the tear evaporation rate in vitro, suggested that the difference between the tear evaporation rate in vitro and in vivo may be a result of the presence of the lipid layer in vivo, which is absent in vitro (Borchman et al., 2009). This provides evidence that one of the main functions of the lipid layer, is to prevent evaporation of tears (Bron, 2004).
According to Uchiyama and his colleagues (2007), there is an adverse impact of low humidity environments on tear evaporation rate. The study, which was conducted with 18 dry eye patients and 11 healthy subjects, showed that the tear evaporation rate was significantly increased in both groups after exposure to dry environmental conditions. The
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subjects were tested under two environmental conditions: 40% – 45% relative humidity RH then 20% – 25% RH. The results from this study illustrated that the tear evaporation rate was significantly increased in healthy and dry eye subjects by 99.72% (p = 0.001) after decreasing the relative humidity by 20%.
In addition, a study conducted by McCulley et al. (2006) showed an increase in tear evaporation rate, again after a decrease in the relative humidity. In McCulley study the tear evaporation rate was measured in 47 subjects (32 dry eye patients and 15 normal patients), in 25% to 35% relative humidity and then in 35% to 45% relative humidity. Their results revealed that the tear evaporation rate increased in both groups by 35.9% on average after exposure to a 10% decrease in relative humidity. In the normal group, there was a significant increase in tear evaporation rate after exposure to a 10% decrease in relative humidity (P= 0.001).
A more recent study conducted by Abusharha and Pearce (2013) showed that the tear evaporation rate and other tear film parameters, such as tear lipid layer thickness, ocular comfort, tear stability and production, were negatively affected after exposure to dry environmental conditions. The tear evaporation rate was studied in normal (40% RH) and dry (5% RH) environmental conditions over one hour. The study sample consisted of twelve healthy normal subjects and the ambient temperature was set at 21°C. The results showed that the tear evaporation rate increased sharply during exposure to the adverse environmental conditions (5% RH) after 20 minutes (p= 0.007) and 60 minutes (p= 0.004). However, there was no significant difference at baseline (0 minutes) nor after 40 minutes. All of these studies have suggested that the tear evaporation rate increases when the relative humidity decreases, and have proven that relative humidity affects the tear evaporation rate in the reverse way.
In our study, the results showed that there was no significant difference in the tear evaporation rate between normal (40% RH) and dry (5% RH) environmental conditions (p > 0.05) (Figure 3-1). The time for which the subjects were inside the Controlled Environment Chamber (CEC) before the evaporation rate was measured ranged from 30 to 40 minutes. This time included the period of time when the subject adapted to the room (10 minutes), plus the time taken for the contrast sensitivity test, which often lasts 20 to 30 minutes.
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These results can therefore be compared to Abusharha and Pearce’s (2013) study results after 40 minutes of exposure to a dry climate (5% RH). There was an increase in the tear evaporation rate after 40 minutes of exposure to a low humidity environment in both studies, although the increase was clearer in Abusharha and Pearce’s study, however this difference did not reach significance.
This difference in results might be because of the long period of time (30-40 minutes), which allows the body to increase tear production to amend the tear volume that is lost during the tear evaporation. This compensatory mechanism developed to protect the normal homeostatic state of the ocular surface (Abusharha & Pearce, 2013). However, Abusharha and Pearce’s study showed that there was significant decrease in tear production after one hour of exposure to a dry environmental condition (p= 0.02). This reduction in tear production, which was measured by Schirmer’s test, may be as a result of the dry environment which the test was performed inside it as it caused evaporation of the tears from the strip. On the other hand, the homeostatic response in dry eye patients tends to be weaker when responding to environmental changes, which may exacerbate the symptoms when exposed to negative changes in the environment (Bron et al., 2009).
In addition, Tomlinson et al. (2009) suggested that the reduction in tear evaporation rate in dry eyes could be related to an increase of the protecting action of the lipid layer. From their experience, they have noticed that dry eyes seem to be more viscous and sometimes have a thicker lipid layer than normal. In the same context, the results from the same study by Abusharha and Pearce (2013) showed that the lipid layer thickness continued to reduce significantly until 40 minutes of exposure to the dry environment condition, after which there was no significant difference.
The use of various techniques in measuring the tear evaporation rate makes the comparison between studies more difficult (Tomlinson et al., 2009). However, Tomlinson et al. (2009) made a summary of the tear evaporation rate, which took into account multiple studies of normal and dry eye patients. The values collected from 15 studies showed that the mean ± standard deviation for the normal group was 48.85 ± 23.47 g/m²/h (0.14 ± 0.07 µl/min), while the mean ± standard deviation for the dry eye group was 75.78 ± 50.25 g/m²/h (0.21 ± 0.13 µl/min).
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These results led to determining a cut-value to be used for the diagnosis of dry eye. The average cut-value of tear evaporation rate between normal and all dry eye type patients is 79.20 g/m²/h (0.22 µl/min). According to these values, the tear evaporation rate for the current study, which was 29.36 ± 23.24 g/m²/h (0.08 µl/min) in normal environmental conditions and 29.40 g/m²/h (0.08 µl/min) in dry conditions, falls within the range of normal values.
Generally, the relationship between low relative humidity environments and increased tear evaporation rate is well documented in many studies (Uchiyama et al., 2007; McCulley et al., 2006; Abusharha & Pearce, 2013). However, the results of the current study did not agree with the previous studies for the reasons mentioned above. Therefore, it would be preferable for future work to measure the tear evaporation rate at specific time after exposure to normal and dry environmental conditions (i.e. 60 minutes). This may reduce the conflicting results between the subjects, because the tear evaporation rate was measured in different times ranging from 25 to 50 minutes after exposure to the environmental conditions. This variability in time arose from the speed of performing the CSF test, which was difficult for some subjects and easier for others. This could allow enough time for the environmental conditions to affect the tear film properties while decreasing the contradictory results.
4.2 The effect of tear film degradation on contrast sensitivity function
The main aim of this study was to observe if tear film degradation (low humidity environments) had an effect on visual perception as measured by the contrast sensitivity function (CSF). Many studies have been conducted to study the difference between normal and dry eye subjects in relation to contrast sensitivity function (Rolando et al., 1998; Huang et al., 2002; Puell et al., 2006; Teson et al., 2009; Ridder et al., 2013). These studies provide contradictory reports. The reasons behind this may be because of various factors, such as: the severity of the dry eye disease in the subjects; the type of contrast sensitivity test; or the participants’ visual acuity, which makes it difficult to detect a reliable difference in CSF between normal and dry eye subjects (Ridder et al., 2011).
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The results of the present study showed that there was no significant difference in the CSF of the subjects after exposure to normal (40% RH) and dry (5% RH) environmental conditions during the time intervals (P > 0.05) (Figure 3-3). The CSF was measured in three time intervals (0.5, 4, 8 seconds) after blinking, during which time the subjects kept their eyes open. No significant difference in CSF between the normal and dry conditions was found when compared through all time intervals separately (P> 0.05). These results mean that degrading the tear film by exposing it to a low humidity environment (5% RH) did not have a significant effect on the CSF. These results can be compared to the results from previous studies, which show conflicting findings when comparing the CSF of normal and dry eye subjects (Rolando et al., 1998; Huang et al., 2002; Puell et al., 2006; Teson et al., 2009; Ridder et al., 2011; Ridder et al., 2013).
In the current study, the tear film was degraded by exposing it to a low humidity environment, thereby mimicking that of a of dry eye patient. However, as mentioned above, the severity of dry eye disease appears one of the confounding variables that has contributed to previous conflicting results. Severe dry eye patients are more likely to experience a reduction in contrast sensitivity (Huang et al, 2002), whilst mild and moderate dry eye patients tend to have normal CSF but suffer from temporal fluctuations in their vision. Thus, the type of contrast sensitivity test is important, as static tests may miss these fluctuations in visual performance (Ridder et al., 2011)
A study conducted by Rolando et al. (1998) used the Vistech chart, which displays the sinewave gratings at a series of contrast levels, to compare CSF in normal and dry eye subjects. The study reported that there was decrease in CSF in dry eye patients with and without punctual epithelial keratitis (PEK) when compared to the control subjects (Rolando et al., 1998). PEK is a disorder caused by a destruction of the corneal epithelium and can be a complication of dry eye disease (Ridder et al., 2011). This difference may be because of the difference in visual acuity levels between the two groups, which was better in the normal subjects. A reduction in visual acuity will reduce the CSF (Ridder et al., 2011).
Another study by Huang et al. (2002) was conducted on 40 dry eye patients with and without PEK and 20 normal subjects. The contrast sensitivity function was measured in both groups using the Contrast Plus, which is a chart-based system that produces sine wave
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gratings in five spatial frequencies, ranging from 1.5 to 18 cycles per degree (cpd). There was a significant reduction in the CSF in the dry eye with PEK group when compared to the control group. However, the difference between the dry eye without PEK group and the control group was not significant. The researchers attributed this to the irregularities on the corneal surface, which is a complication to the tear film abnormalities in dry eye patients. However, they argued that these abnormalities would be too delicate in the initial stages of dry eye, and are therefore not likely to affect the CSF measurements (Huang et al., 2002).
Puell et al. (2006) also stated that the CSF was significantly lower in dry eye patients when compared to normal subjects. In their study, 33 dry eye patients and 30 normal subjects were examined, to observe the difference in contrast sensitivity between both groups. The Contrast Glareterster 1000 was used to measure CSF. The instrument presents the stimuli in a changeable ring size and with a group of contrasts (Puell et al., 2006). However, the severity of dry eye in the dry eye patients group was not mentioned.
A study held by Teson et al. (2009) noted that the CSF was significantly worse, particularly at low spatial frequencies, in the dry eye group than in the control group. This is counter intuitive as any reduction in visibility i.e. clarity of vision would be associated with a loss in the high spatial frequency range. Their study was conducted on 22 dry eye patients and 22 normal age-matched subjects using the CSV-1000 test, which presents the stimuli in sine wave gratings of a fixed contrast, to measure the CSF. However, the study reported variable CSF measurements in the dry eye group (Teson et al., 2009). According to Ridder et al. (2011), this variability may arise if the subjects were not fully trained to perform the psychophysical test, which was used to measure CSF. As a result of this variability, the significant difference found in CSF between dry eye and control subjects in low spatial frequency range may occur by chance, as different studies did not find any effect at the low spatial frequencies (Ridder et al., 2011).
According to unpublished data from Ridder’s laboratories (cited in Ridder et al., 2011), CSF was found to be significantly lower (p= 0.002) in a group of 12 dry eye patients without PEK compared to 25 normal subjects, using a computerised CSF test which was equipped with an eye-tracker. The stimulus in the test, which was a sine-wave grating of 14 cpd, was produced for short time (16 msec) one second after a blink, which was monitored by the eye-tracker. However, the severity level of dry eye in the patients was not
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clear in the study. Ridder et al. (2011) argued that severe dry eye patients (i.e. with PEK) showed a reduction in CSF even with the static contrast sensitivity chart. In addition, they stated that in less severe dry eye (i.e. without PEK) the patients tended not to demonstrate a reduction in CSF when measured by static stimuli chart tests, as long as they could prolong the viewing time of the stimuli and blink frequently to make the image clearer. However, the patients may suffer from temporal variations in vision performance, which can be identified when the stimuli are presented in a brief time associated with a blink (Ridder et al., 2011).
A recent study held by Ridder et al. (2013) showed that there was no significant difference in CSF between dry eye patients and normal subjects (P > 0.05). The study sample consisted of 52 dry eye patients, who were divided into three groups depending on their sensitivity level (mild, moderate and severe), and 20 control healthy subjects. The CSF was measured by the Holladay Automated Contrast Sensitivity System (HACSS) using rotationally symmetric targets and randomly presented optotypes. The explanation behind these results is due to the dry eye patients trying to compensate the effects of tear film abnormalities by extending the viewing time to fixate well in the stimulus, and by increasing the blink rate to improve the distribution on the tear film surface (Ridder et al., 2013; Miljanovic et al., 2007).
As mentioned before, the conflicting results between all of these studies is very likely due to the variation of the contrast sensitivity tests which were used to measure CSF and the severity level of dry eye disease (Ridder et al., 2011). The studies suggested that severe dry eye patients tend to exhibit a reduction in CSF compared to the mild or moderate groups. Furthermore, they suggested that the use of computerised contrast sensitivity tests (which tests a range of spatial frequencies) is more likely to detect the decrease in CSF in dry eye patients than static contrast sensitivity charts, such as the Pelli-Robson letter CS chart, the Regan chart or the SKILL chart (usually either a fixed contrast or fixed spatial frequency).
Our present study employed a computerised monitor-based test (qCSF) to measure the CSF, the tear film degradation caused by adapting the subjects for 10 minutes to a dry environment doesn’t seem sufficient to reach (mimic) severe dry eye levels in which the reduction in CSF has previously been reported. Thus, the tear film degradation for the
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normal subjects who were recruited for this study should be stronger and last longer. In addition, the use of dry eye (with a range of severity) patient groups side by side with normal subjects may make future studies more successful.
It has also been suggested that blink suppression can cause a reduction in visual performance (Ridder & Tomlinson, 1993; Ridder & Tomlinson, 1995; Ridder & Tomlinson, 1997). The blink suppression is referred to as the neural suppression of vision which occurs during a blink (Volkmann et al., 1980). The blink suppression duration is reported to be between 40 to 200 msec (Volkmann et al., 1982; Manning et al., 1983). However, Ridder and Tomlinson (1993) reported that the longest duration of blink suppression is 100 msec in the low spatial frequency range (0.5 cpd) and it seems to reduce gradually as the spatial frequencies increase. In the same study, CSF was significantly different between 0 and 400 msec, particularly in the low spatial frequencies (p < 0.05). The study was conducted on four normal subjects, who wore soft contact lenses to prevent the drying of the cornea. The stimuli, which were sine-wave gratings lasting 16 msec, were produced using a CRT Image Synthesiser. They were presented in different contrasts at four spatial frequencies, ranging from 0.5 to 6 cpd at fixed time intervals (0, 25, 50, 100, 200 and 400 msec) (Ridder & Tomlinson, 1993). However, as mentioned above, Ridder and Tomlinson (1993) have proven that the duration of the blink suppression is 100 msec or less. During this period the visual performance, including the CSF, may be affected. However, in the present study, the CSF was measured within time intervals (0.5, 4 and 8 seconds after the initial blink). Thus, it seems that blink suppression cannot affect the CSF as the first measurement was taken 500 msec after the blink.
Other studies argued that ideal vision can be achieved after the blink suppression and before the tear break up time (Montes-Mico et al., 2005; Montes-Mico et al., 2010). However, Ridder and Tomlinson (2003) reported that, according to their previous work, they found that most subjects need 4 seconds after their TBUT to exhibit adequate tear film disturbance, which can lead to a decrease in CSF.
Nevertheless, the current study was conducted on normal healthy subjects, whose NITBUT measurements were showed to be high (mean ± standard deviation was 12 ± 1 seconds) (Table 3-1). However, these measurements were taken in normal environmental conditions. A recent study held by Abusharha and Pearce (2013), which compared the
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NITBUT in normal subjects in the same environmental conditions as the current study (40% and 5% RH), showed that there was a significant difference in NITBUT between the normal (40% RH) and dry (5% RH) environmental conditions (p < 0.05). The study results showed that the NITBUT decreased by 28% and 40% when the subjects adapted for 0 and 20 minutes inside the dry environment, when compared to the normal environmental conditions.
According to these results, the NITBUT in the current study can be assumed to decrease by 3.5 to 5 seconds from the results in the normal environmental conditions. Thus, the NITBUT for the current study in the dry environmental conditions can be assumed to occur at 7 to 8.5 seconds after blinking. When the 4 seconds that Ridder and Tomlinson suggested are added to the TBUT value, the time required to show the reduction in CSF for the current study will be 11 to 12.5 seconds after blinking. Therefore, the longest time interval in this study, which was 8 seconds, seems not to be sufficient to reveal the effect of low humidity on the CSF, as the CSF tends not to be affected in this time.
Dry eye patients usually suffer from blurred vision, although they have normal visual acuity (i.e. 6/6). This blurry vision might be due to the TBUT which induces an irregularity in the surface of the tear film (Liu et al., 2010). Many previous studies have shown that there was a reduction in the CSF after TBUT and this reduction appears to be larger at the high spatial frequencies (Tutt et al., 2000; Ridder & Tomlinsion 2003; Ridder et al., 2005; Liu et al., 2010).
Tutt et al. (2000) measured the CSF using the Pelli-Robson chart at a distance of 2m on 3 normal subjects. The subjects were asked to open their eyes and avoid blinking for as long as possible. The subjects then reported the time that each group of letters in different contrasts became difficult to read. The study results showed that the CSF reduced directly after the blink and continued to decrease until they reached levels between 20% to 40% reduction after 60 seconds.
A study by Ridder and Tomlinson (2003) on 5 normal subjects, measured CSF using sinewave gratings in a number of spatial frequencies, ranging from 0 to 14 cpd. The stimuli were presented in two time intervals after a blink, which was detected by an Eye Trac eye monitor. The time intervals were 2 seconds after the blink detection and 4 seconds after TBUT for each subject. The CSF was significantly decreased at 4 seconds after TBUT,
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particularly in the high spatial frequencies (P < 0.05). Another study conducted by Ridder et al. (2005) used the same methods and time intervals but on five subjects with mild and moderate dry eye. The high spatial frequency CSF was again significantly reduced at 4 seconds after TBUT (P < 0.05).
A more recent study held by Liu et al. (2010) measured the effect of TBUT on contrast sensitivity on 10 contact lens wearers. They used one 20/24 letter contrast sensitivity, which was presented on a computer screen. The subjects were asked to keep their eyes open for 18 seconds and report the time when the visible letters became unrecognisable. The CSF started to decrease after 7.5 seconds until it reached a 20% reduction after more than 10 seconds. All these studies suggested that the CSF decreases after TBUT and that the decrease tends to be greater at high spatial frequencies. The ideal test for CSF should be performed at different times after the blink and should include a time interval at 4 seconds after TBUT at least, to reveal the effect of tear film disturbance on CSF compared to the other time intervals.
In the current study, as mentioned above, the longest time interval was 8 seconds, which did not show a significant difference in CSF between normal and dry environmental conditions and when compared to the other time intervals. Thus, it would be better if the NITBUT was measured in both of the environmental conditions in this study and, according to the NITBUT value for each subject, the longest time interval should be 4 seconds after that value, to reveal the effect of tear film degradation by low humidity on the CSF, and to produce an ideal image of visual performance through a wider range of time.
In conclusion, the current study results showed that there was no significant difference in CSF between the normal and dry environmental conditions nor between the time intervals after blinking. It would seem that CSF was not affected by the change in relative humidity although this change can effect the tear film layer resembling the effects of mild or moderate dry eye. Previous studies also suggest that mild to moderate dry eye has little effect on CSF, as any reduction in CSF tends to be much more apparent in severe dry eye patients. Therefore, the tear film degradation in the current study, caused by exposing a healthy tear film to low humidity, seems not to be sufficient to reach the severity level
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which can reveal the reduction in CSF. Thus, it would be better if the tear film degradation was stronger and lasted for longer.
In addition, many studies suggest that the TBUT can cause a reduction in CSF, particularly at high spatial frequencies. Based on their previous work, some studies suggested a time interval of 4 seconds after TBUT to discover the effect of tear film disturbance on CSF. However, the longest time interval in the present study, which was 8 seconds after the blink, which would seem not to be sufficient to reveal that effect. Accordingly, it would be preferable if the TBUT was measured in normal and dry environmental conditions for each subject, and 4 seconds was added to that value to set the longest time interval in the experiment. The ideal method to measure CSF is psychophysically by using a computer-based system presenting stimuli in short duration and high spatial frequencies, at a wide range of time intervals after the blink. This test would have the highest possibility to reveal the effect of tear film disturbance on visual performance.
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Appendices
Appendix 1: Ethical approval for research …………………………………….. 59
Appendix 2: information and consent sheet ……………………………………. 62
Appendix 3: Ocular surface disease index OSDI ………………………………. 64
Appendix 4: The evaluation sheet of OSDI …………………………………….. 65
Appendix 5: Statistical analysis of age, NITBUT and OSDI …………………… 66
Appendix 6: Statistical analysis for tear evaporation rate ………………………. 67
Appendix 7: The model summary and the normal probability plot …………….. 69
59
Appendix 1: Ethical approval for research
60
61
62
Appendix 2: information and consent sheet
63
64
Appendix 3: Ocular surface disease index OSDI
65
Appendix 4: The evaluation sheet of OSDI
66
Appendix 5: Statistical analysis of age, NITBUT and OSDI
Descriptive Statistics: Age, NITBUT, OSDI
Variable N Mean SE Mean StDev Minimum Q1 Median Q3 Maximum
Age 20 29.75 0.99 4.44 24.00 27.00 29.50 32.00 43.00
NITBUT 20 12 0.23 1 10.00 11.00 11.50 12.00 14.00
OSDI 20 2.95 0.48 2.16 0.00 1.25 2.50 4.75 8.00
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Appendix 6: Statistical analysis for tear evaporation rate
Statistical summary:
Variable N Mean
SE Mean
StDev Minimum Q1 Median Q3 Maximum
Humidity 20 29.36 5.19 23.24 -1.97 14.46 27.52 35.73 85.21
Dry 20 29.39 2.70 12.11 8.71 19.04 29.08 37.37 55.37
Normality test of the variable Difference:
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Anderson-Darling Test
Null hypothesis H0: Data follow a normal distribution Alternative hypothesis H1: Data do not follow a normal distribution
AD-Value P-Value 0.30 0.5534
Paired T-test
Estimation for Paired Difference
N Mean StDev SE Mean 95% CI for µd
20 -0.028 18.107 4.049 (-8.502, 8.446)
µd: mean of (Sample 1 – Sample 2) Null hypothesis H0: µd = 0 Alternative hypothesis H1: µd ? 0
T-Value P-Value -0.01 0.9946
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Appendix 7: The model summary and the normal probability plot
Two-Way ANOVA: contrast sensitivity versus condition, time interval
Factor Information
Factor Levels Values H/D 2 A, B Sec 3 1, 2, 3

Model Summary
S R-sq R-sq(adj) R-sq(pred)
0.227967 1.21% 0.00% 0.00%
Fits  and  Diagnostics  for  Unusual  Observations   Obs Cont.Sentivit Fit Resid Std Resid 8 3.06 2.539 0.521 2.34 R
13 2.07 2.559 -0.489 -2.20 R 106 2.01 2.570 -0.560 -2.52 R 110 2 2.539 -0.539 -2.43 R
R Large residual
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The normal probability plot
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