Journal of Glaucoma:
Corneal Biomechanical Properties Affect Goldmann Applanation Tonometry in Primary Open-angle Glaucoma
Costin, Bryan R. MD*; Fleming, Gloria P. MD*; Weber, Paul A. MD*; Mahmoud, Ashraf M. BS*,†; Roberts, Cynthia J. PhD*,†
*Department of Ophthalmology, William H. Havener Eye Institute, The Ohio State University Medical Center
†Department of Biomedical Engineering, The Ohio State University, Columbus, OH
Disclosure: The authors declare no conflict of interest.
Reprints: Gloria P. Fleming, MD, The William H. Havener Eye Institute, The Ohio State University Wexner Medical Center, 915 Olentangy River Road, Columbus, OH 43212 (e-mail: firstname.lastname@example.org).
Received December 17, 2011
Accepted July 3, 2012
Purpose: To study differences in corneal biomechanical properties between primary open-angle glaucoma (POAG) and central corneal thickness (CCT)-matched control subjects and their effect on intraocular pressure (IOP) measurement.
Methods: Thirteen eyes of 13 POAG subjects and 15 eyes of 15 normal subjects underwent corneal topography; IOP using Goldmann applanation tonometry (GAT), dynamic contour tonometry (DCT), and corneal compensated IOP (IOPcc) using the Reichert ocular response analyzer (ORA); corneal hysteresis; and CCT. Results from POAG and control eyes were then compared using t tests.
Results: Ages in the POAG group were slightly greater than that in the control group. CCT was closely matched between groups. Significant differences were found between GAT versus DCT and GAT versus IOPcc within both groups: Mean GAT IOP was not significantly different between POAG and controls, whereas mean DCT IOP did show a significant difference between groups as did mean IOPcc. The delta differences, GATΔDCT and GATΔIOPcc, were of greater magnitude in POAG subjects when compared with controls. Corneal hysteresis was significantly lower in POAG subjects.
Conclusions: The delta differences between GAT and newer measures of IOP are greater in magnitude in patients with POAG than in the normal controls, independent of CCT. This is likely due to differences in the corneal biomechanical properties with POAG corneas being softer than healthy corneas, which causes greater underestimation of IOP by GAT in POAG than controls. Underestimation of IOP could affect treatment decisions and outcomes in POAG.
Recent studies have reported a significant difference between intraocular pressure (IOP) measurement obtained with Goldmann applanation tonometry (GAT), the standard of care since 1957, and intracameral pressure measurements, the gold standard of IOP estimation.1–3 This discrepancy may not have surprised Goldmann and Schmidt who reported that IOP readings using their applanation device could be affected by “ocular rigidity,” thickness and curvature of the cornea, as well as the tear film.4,5 Indeed, IOP measurements with GAT are influenced by several factors including the biomechanical properties of the cornea, central corneal thickness (CCT), corneal curvature (K), astigmatism, and axial length (AL).6 The term “corneal biomechanical properties” encompasses the elastic and viscoelastic characterization of the cornea, including elastic modulus or stiffness and corneal hysteresis (CH). It has also been shown in vivo that GAT is most accurate for CCT between 520 and 550 μm in biomechanically homogenous populations.7,8 However, it has been reported that “normal” CCT values can vary widely between 427 and 670 μm.9,10 Yet, CCT has come to the clinical forefront as the major variable taken into consideration when putting GAT IOP into an accuracy context.
In response, many formulas have been proposed to “correct for” CCT and provide a more accurate GAT reading, but these have been unsatisfactory.11–15 It is felt that a mixture of CCT, corneal biomechanical properties, and other variables explains the difference between GAT and true intracameral IOP measurements, rather than a single variable alone, like CCT, accounting for the difference. It is difficult to determine which variables exert the most effect on GAT IOP measurements, but it is possible that biomechanical properties of the cornea may actually have the greatest effect.14,16,17 It is also distinctly possible that, although currently thought of as the central parameter, CCT is only the “tip of the iceberg” in the GAT accuracy question with corneal biomechanical properties being the major determinant.
Part of the reason that CCT has become the variable of interest for GAT accuracy is that central thickness is a long established and fundamental concept in ophthalmology and pachymetry is a technically simple measurement that requires little interpretation. This is in stark contrast to the much newer concept of corneal biomechanical properties, including not only the viscoelastic response represented by CH, but also the elastic properties of the cornea, such as stiffness. Until recently, our inability to measure corneal biomechanical properties, let alone interpret exactly what these measurements mean for the cornea being studied, led to confusion in making judgments about the accuracy of GAT values. Also, corneal biomechanics has a much more detailed set of terminology not found with CCT that makes it a more challenging area to explore. However, as previously stated, it has been proposed that biomechanical properties, specifically the elastic modulus, may in fact be the most important factor in explaining the inaccuracy of GAT when compared with intracameral values.16
Just as CCT and K values vary from patient to patient, it is likely that individual patients, and perhaps diseases, differ with respect to corneal biomechanical properties. Given all of these varying parameters, it seems that the “one-size-fits-all” model of GAT may not apply to the human cornea given all of its polymorphic variations. In response, several devices have been developed in recent years in an attempt to obtain IOP estimates that are less influenced by biomechanical properties and CCT.3,18–22 The Pascal dynamic contour tonometer (DCT) and the ocular response analyzer (ORA) are 2 such devices, and several studies have shown that the DCT may in fact be closer to intracameral IOP measurements both in vivo and in cadaver eyes.1,2,11 The purpose of the current study was to investigate differences in corneal biomechanical properties between CCT-matched primary open-angle glaucoma (POAG) and control subjects and determine their effect on the measurement of IOP.
This study was a prospective, nonrandomized comparison approved by The Ohio State University IRB and conducted in accordance with The Declaration of Helsinki. After discussing the risks and benefits of participation, informed consent was obtained from all participants. To be eligible, subjects had to be older than 21 years of age, could not be pregnant, could not have corneal or retinal diseases, had no secondary causes of glaucoma, had no previous episodes of angle closure, and could not have had any previous corneal or intraocular surgeries including LASER procedures such as laser peripheral iridotomy, argon or selective LASER trabeculoplasty. Glaucoma subjects had been diagnosed with POAG by a fellowship-trained glaucoma specialist based on glaucomatous optic nerve head appearance, IOP>21 mm Hg by GAT, glaucomatous visual field defects, and open angles on gonioscopy. Control subjects were recruited through faculty and staff and their family and friends who met criteria for inclusion.
All subjects underwent the following tests on the same day and during the same visit. All measurements were taken by the same tonometry-experienced clinician (B.R.C.) and in duplicate with the exception of the visual field, which was performed once per enrolled eye. All data were recorded on collection sheets immediately after collection in order to maintain fidelity. The Humphrey visual field (Humphrey Field Analyzer II; Carl Zeiss Meditec, Dublin, CA) was performed first. The test for POAG subjects was a full threshold 24-2 field, whereas for control patients it was a SITA-Fast 24-2 field. Thereafter, corneal topography, simulated keratometry, and anterior chamber dimensions were obtained using the Galilei Dual Scheimpflug Analyzer (Zeimer Ophthalmic Systems AG, Port, Switzerland), and acceptability of the measurements was determined on the basis of the manufacturer’s guidelines.
Finally, 1 drop of fluorescein sodium and benoxinate hydrochloride ophthalmic solution (Fluress, Akorn, Buffalo Grove, IL) was instilled in each eye and IOP was measured twice with GAT (Goldmann Applanation Tonometer AT 900 BQ; Haag-Streit, Köniz, Switzerland), followed by determination of 2 Pascal DCT measurements (Zeimer Ophthalmic Systems AG). Adequacy for GAT measurements was based on mire quality in terms of thickness and shape. DCT measurements were included if the quality reading was 3 or better. The second GAT measurements were taken immediately after the tonometer tip was cleaned of fluorescein, and the second DCT measurements were taken immediately after the first. DCT measurements were taken 1 to 2 minutes after GAT allowing time only for the Pascal to be attached to the slit lamp.
CCT was then measured first using a standard ultrasonic pachymeter (Pachette, DGH Technology Inc., Sherman’s Dale, PA). The pachymeter probe was placed on the center of the cornea over an undilated pupil, and the mean of 6 readings within a range of ±5 μm was calculated for each eye. Blood pressure and heart rate were assessed using an automated cuff (Omron HEM-780 IntelliSense Blood Pressure Monitor; Omron Healthcare, Kyoto, Japan). Finally, CH and IOPcc were measured using the ORA (Reichert Technologies, Depew, NY). ORA measurements were accepted if the appearance of peaks 1 and 2 were as per the manufacturer’s specifications. Approximately 5 minutes elapsed between GAT and DCT measurements and the ORA measurements.
Results from POAG and control eyes were then compared using t tests. P<0.05 was considered statistically significant.
Initially there were 15 POAG subjects and 23 control subjects. Chart review showed a history of SLT in one of the POAG patients, and the ORA signal was not recorded in another so these subjects were subsequently removed from the study, resulting in 13 eyes of 13 subjects in the POAG group. Eight subjects from the control group were removed from the study in an attempt to better control for age between the 2 groups, for a total enrollment of 15 control subjects. Ages in the POAG group were slightly greater than those in the control group (mean 63.6±12.1 y, mean 56.5±5.7 y, P=0.051). With respect to race, 64.3% of the POAG group reported themselves as white and 35.7% as black, whereas the control group identified themselves as 86.7% white and 13.3% as black. In the POAG group, 71.4% were female and 28.6% male, whereas the control group comprised 66.7% female and 33.3% were male. There was no significant difference in CCT between both groups (546.7±35 μm, 546.1±35.5 μm, P=0.96). In addition, there was no significant difference between simulated keratometry between the 2 groups (44.46 D, 44.24 D, respectively; P=0.71).
CH was significantly different in POAG subjects when compared with controls (9.02±1.51, 10.26±1.3, respectively; P=0.028; Table 1). A statistically significant difference was found between GAT versus DCT and GAT versus IOPcc in both groups: Mean GAT IOP was not significantly different between POAG and controls (14.5±3.6 mm Hg, 12.9±2.4 mm Hg, respectively; P=0.19), whereas mean DCT IOP did show a significant difference between the 2 groups (18.08±2.4 mm Hg, 14.9±2.0 mm Hg, respectively; P=0.0008), as did mean IOPcc (17.9±2.5 mm Hg, 13.8±2.6 mm Hg, respectively; , P=0.0002; Table 2). The mean delta difference of GATΔDCT (3.62 mm Hg in POAG, 2.01 mm Hg in controls, P=0.026) and GATΔIOPcc (3.45 mm Hg in POAG, 0.83 mm Hg in controls, P=0.0063) was of a significantly greater magnitude in POAG subjects when compared with controls (Table 3). A total of 11 out of 13 (84.6%) patients in the POAG group were actively on topical prostaglandin analogues (Table 4).
Glaucoma is the leading cause of irreversible blindness in the world and the incidence of this devastating disease is expected to increase drastically in the near future as the life expectancy of the world population increases.23 The problem is compounded by the fact that despite much research, the pathophysiology of this condition remains a mystery. Despite the challenges, IOP remains the only modifiable risk factor in the treatment of glaucoma. The Ocular Hypertension Treatment Study and The Early Manifest Glaucoma Trial showed that even a reduction in IOP as small as 1 mm Hg can reduce the risk of disease progression.24,25 Therefore, determination of an accurate IOP is crucial in the management paradigm of these patients. However, IOP measurements using GAT, the current standard of care, have been shown to underestimate true IOP as measured by intracameral studies both in cadaveric specimens and in vivo.1–3 The effects of corneal biomechanical properties, CCT, and other parameters are thought to explain the discrepancy.
CCT has been the variable most explored, but has failed to account for all of the differences despite numerous correction formulas11–15 and CCT fails to account for the IOP magnitude differences by measurement devices found between groups in the current study, where CCT was closely matched. Recent theories support corneal biomechanical properties as the major determinant of IOP inaccuracy by GAT and a possible key to pathophysiology.14,16,17 Biomechanics may be the major determinant, although it has been shown that corneal elastic properties determine the relationship between CCT and IOP measurement error, with stiffer eyes having a stronger relationship compared with softer eyes.16 With all of these facts in mind, it is clear that we must take great interest not only in how much GAT underestimates IOP, but also why it underestimates IOP.
This study examined differences in corneal biomechanical properties and various IOP measurement devices in subjects with POAG and in controls by keeping CCT constant between groups in an effort to isolate the variable of corneal properties. We found that with CCT-matched groups, mean DCT and IOPcc were significantly higher than GAT in both the glaucoma and the controls. This finding is well established, as it has been shown in many studies that DCT and IOPcc measure higher IOP compared with GAT on average and in specific populations.14,17,26–28 Kniestedt et al1 showed that mean DCT was 0.58±0.70 mm Hg higher than mean intracameral pressure, while GAT measured 4.01±1.76 mm Hg lower, on average. These studies, however, were performed ex vivo on cadaveric eyes without tear film or corneal epithelium.
In vivo studies also compared GAT and DCT measurements in both glaucoma and in normal patients and report that mean DCT values are higher than mean GAT values by anywhere from 0.7 to 4.4 mm Hg with a range, however, that included some subjects with GAT higher than DCT.29 In addition, we found no statistically significant difference in DCTΔIOPcc between the 2 groups and the literature also supports this finding with a high concordance between DCT and IOPcc readings.13,21,30 Repeated consistency between DCT and IOPcc could reflect the fact that both tonometers were designed to provide IOP values that are less influenced by corneal biomechanical properties and CCT yet do so by entirely different methodologies. DCT is a direct, nonapplanating transcorneal measurement while IOPcc is empirically determined by population studies and generated by a noncontact tonometer.
The most interesting finding in our study was a statistical significance in the magnitude of difference, or delta difference (Δ), between GAT, DCT, and IOPcc between the POAG and control groups, represented as GATΔDCT and GATΔIOPcc. In contrast, comparisons between the 3 tonometric readings within each group are represented as GAT versus DCT, GAT versus IOPcc, and DCT versus IOPcc (Table 5). This “Δ magnitude difference” has been designated ΔIOP by Ceruti et al and Wang et al, dIOP by Detorakis et al, DIOP by Sullivan-Mee et al, and GATΔDCT and GATΔIOPcc in our study for clarity.17,31–33 Four studies have compared GAT in POAG to both of the newer, less biomechanically sensitive tonometers, DCT and ORA, using CCT-matched control, similar to our study. Unfortunately, 2 of these 4 comparative studies, placed the glaucoma subjects and the controls into the same group for data analysis, which assumes that these 2 populations are biomechanically similar.13,21 These studies provide valuable information on the difference in measurement values for the individual devices themselves, but little can be said about differences between glaucoma subjects and controls, such as Δ magnitude differences, when they are grouped together for analysis.
Wells et al34 investigated relationships between CH and optic disc depth using GAT, DCT, and ORA in glaucoma patients and controls, but the IOP measurements between these devices were not reported. However, Wang and colleagues specifically examined the IOP magnitude difference between devices: GAT, DCT, and ORA were measured in POAG and control patients, along with glaucoma suspects and ocular hypertensives, in an effort to determine which factors influence “ΔIOP,” defined as the difference between GAT and DCT. Comparison of ΔIOP between groups allowed examination of IOP magnitude differences. The study showed mean ΔIOP to be larger in the POAG group than in controls, which is consistent with our results.17 However, it was not reported whether there were differences in CCT between the POAG group and the controls to which they were compared.
There are multiple studies comparing GAT versus DCT, and others that compare GAT versus IOPcc in POAG subjects and controls. Of the GAT versus DCT studies, only 2 reported CCT-matched POAG and control groups.31,35 Both of these studies are well constructed with data collection occurring in a masked fashion and in a random order on much larger sample sizes. Both studies found no significant difference in the GAT versus DCT gap between the groups. However, neither of these studies reported patients’ topical antiocular hypertensive drop regimen, which could explain the inconsistency with the results of the work presented. Detorakis et al32 studied the effect of prostaglandin analogues on IOP measurement with GAT and DCT. They reported that the difference between GAT and DCT was greater in the glaucoma group treated with latanoprost when compared with glaucoma patients treated with other pressure drops, as well as controls. From these data, they concluded that prostaglandin analogues may affect corneal biomechanical properties. Of the remaining GAT versus DCT studies, several place POAG subjects and controls into the same pool for analysis, whereas others fail to match CCT between groups.9,14,27,29,36
Of the GAT versus IOPcc studies comparing POAG subjects with controls, one study did not conduct CCT-matching with groups, whereas another did not report CCT.37,38 There were 2 remaining studies, which did conduct CCT matching of groups, and found a trend in IOP magnitude difference similar to our study.28,33 Sullivan-Mee and colleagues showed a 3.04+1.73 mm Hg difference in GAT-IOPcc magnitude in POAG subjects and only 1.44+1.71 mm Hg difference in CCT-matched controls. Interestingly, the Sullivan-Mee study also reported that 73% of their POAG group were on topical prostaglandin analogues and this is one of few studies which looked at the drops with which their POAG subjects were treated. However, this study was conducted through a Veterans Affairs Medical Center and the study population is almost entirely male (personal communication). The other studies which reported no significant difference in the magnitude of the GATΔDCT difference or the GATΔIOPcc difference did not report the number of subjects on these medications.17,31,35,37,38 It is possible that differences in medications, specifically prostaglandin analogues, are responsible for the different findings of these studies in our study.
The larger delta difference between GATΔDCT and GATΔIOPcc in POAG is consistent with the conclusion that POAG corneas are softer than corneas in control groups or POAG corneas that are not treated with prostaglandins.32 An overestimation by GAT can be explained by corneas that are stiffer, thicker, or more curved. The current CCT-matched study with no difference in K’s between groups, leads to the conclusion that the POAG corneas, and perhaps POAG eyes, are softer than healthy eyes. Interestingly, it has also been reported that there is a significant relationship between CCT and IOP in normal controls, but not in treated glaucoma subjects that is consistent with theoretical predictions that the relationship between CCT and IOP measurement error is weaker in softer corneas.14,16 It should be noted that the terms “stiffness” and “softness” refer to modulus of elasticity, or purely elastic properties of the cornea, whereas CH is a viscoelastic parameter. Two eyes with the same CH can be of different elastic moduli—with one stiffer than the other.
Our study showed that the 2 groups differed with respect to CH. The glaucoma group had, on average, a lower CH than the control group, which is consistent with the literature. CH has been found to be lower in POAG than in CCT-matched controls and in non–CCT-matched groups and has been associated with visual field progression in glaucoma.28,37,39,40 As stated, CH is a viscoelastic parameter, however, and cannot be directly related to elastic properties alone because it is influenced by both elasticity and viscosity.41 Yet, CH is lower in keratoconus than in normal corneas and upregulation of membrane metaloproteinases (MMPs) has been reported with histologic analysis of keratoconic corneas.42 An interesting glaucoma correlation to this finding in keratoconus is the genetic triggering of MMPs by topical prostaglandin analogues that has been shown to occur in human sclera.43,44 It is conceivable that prostaglandin analogues are also associated with upregulation of MMPs in the cornea as well and may have similar effects on corneal biomechanics without causing ectasia. More research is needed on this subject.
A sobering concept, however, is the thought that IOP could be underestimated by GAT in a large number of glaucoma patients on prostaglandin analogues. However, it is also possible that the difference between GATΔDCT, as well as GATΔIOPcc, is greater in POAG subjects versus controls because glaucomatous eyes are simply biomechanically different than healthy eyes. Vandewalle and colleagues highlight other alarming possibilities that we may face should these newer devices replace GAT: “If DCT and ORA were to be used today as the gold standard, we would have many more patients labeled as ocular hypertensive and possibly overtreated with all the socio-economic drawbacks as a consequence.” However, these potential costs may be outweighed by the benefits of preventing blindness in glaucoma patients. An optimistic possibility would be that a large population study on “normal” IOP range using newer devices may show a trend or trends which would clarify normal or higher risk IOP’s or other factors that may actually allow better diagnosis and treatment of glaucoma. Regardless of the consequences, this issue demands further study.
The major limitation of this study is its small size. Further study with a larger sample size is required to explore our findings and the findings of others in greater detail, including the effect of prostaglandin analogues. This study was not masked and data collection did not occur in a randomized fashion, but rather in the same order each time. There was a small, but borderline significant difference in age between the 2 groups. Age has been shown to affect corneal biomechanical properties with corneal stiffness in general increasing with age.45 However, due to the small difference in age between our POAG and control groups we feel age does not explain the IOP difference between groups. In fact, Elsheikh et al45 placed 50 to 64 years old in the same group for comparison with other age groups, which encompasses the means in our study. Also, axial length, which Wang and colleagues showed was associated with increased GATΔDCT, was not evaluated.
There was heterogeneity with respect to sex and race between the POAG and control groups in this study. This raises the question as to whether differences in race and/or sex could be the explanation for the IOP differences between the 2 groups. A literature search investigating sex, race, and corneal biomechanical properties suggests that these demographics would likely not explain biomechanical difference seen in the current study. Kamiya et al46 studied CH in 86 eyes and found no significant difference between male and female subjects. Although Narayanaswamy et al47 reported greater CH in women than men, the current study has a greater percentage of women in the POAG group, with a lower mean CH. Therefore, sex is not likely to influence the differences reported. With respect to race, Leite et al48 did find a statistically significant difference in CH when comparing black subjects to white. However, this study concluded that this difference was largely explained by the racial differences in CCT with corneas of black subjects being in general thinner than those of white subjects. Again, since there was no statistically significant difference between CCT in the current study groups, the IOP difference is not likely explained by race.
A major strength of this study was that our POAG and control groups were matched for CCT. Another strength was the exclusion criteria that did not permit participation of patients who had had argon or selective LASER trabeculoplasty, as the possible effects of these LASER procedures on the biomechanical properties of the cornea has not been fully investigated. It should be noted that, of the papers reviewed, none excluded patients from participation based on LASER surgery. Observation of this criterion was the major factor limiting our sample size as it precluded participation in a great number of subjects, but we felt it important for data quality. Also, we report drop treatment regimens for our glaucoma subjects, which some studies failed to report. Other strengths include measurements by a single observer, eliminating intraobserver bias, and measurements were all collected on the same day and in duplicate.
Corneal biomechanics is a much newer concept than CCT and, in contrast to pachymetry, only recently have devices entered the clinical arena to allow quantification of these properties. These devices like the DCT and the ORA likely provide more accurate estimates of the true IOP and therefore the pressure being experienced by the optic nerve. Our study not only showed that GAT underestimated IOP compared with measurements by DCT and IOPcc, but most interestingly that it underestimated IOP to a greater degree in glaucoma subjects: those to whom an accurate IOP is most critical. We feel the explanation for a greater magnitude difference (GATΔDCT, GATΔIOPcc) seen in the POAG group, with CCT kept constant, is due to the fact that POAG corneas are biomechanically different than healthy controls in this study. Specifically, they are softer, or have a lower modulus of elasticity. Perhaps these biomechanical differences extend to include the entire corneoscleral tract including the peripapillary ridge and lamina cribrosa in this disease state. Perhaps the difference in corneal properties is limited to the cornea and due to the effects of topical therapies. Perhaps both possibilities are in fact true about glaucomatous eyes. Regardless, the most striking and disquieting possibility is that GAT is preferentially underestimating IOP in our POAG patients.
1. Kniestedt C, Nee M, Stamper R.Dynamic contour tonometry: a comparative study on human cadaver eyes.Arch Ophthalmol.2004;122:1287–1293.
2. Kniestedt C, Nee M, Stamper R.Accuracy of dynamic contour tonometry compared with applanation tonometry in human cadaver eyes of different hydration states.Graefe’s Arch Clin Exp Ophthalmol.2005;243:359–366.
3. Feltgen N, Leifert D, Funk J.Correlation between central corneal thickness, applanation tonometry, and direct intracameral IOP readings.Br J Ophthalmol.2001;85:85–87.
4. Goldmann H, Schmidt T.Applanation tonometry.Ophthalmologica.1957;134:221–242.
5. Goldmann H, Schmidt T.Further contribution to applanation tonometry.Ophthalmologica.1961;141:441–456.
6. Whitacre R, Stein R.Sources of error with use of Goldmann-type tonometers.Surv Ophthalmol.1993;38:1–30.
7. Ehlers N, Bramsen T, Sperling S.Applanation tonometry and central corneal thickness.Acta Ophthalmol (Copenh).1975;53:34–43.
8. Kohlhass M, Boehm A, Eberhard S, et al..Effect of central corneal thickness, corneal curvature, and axial length on applanation tonometry.Arch Ophthalmol.2006;124:471–476.
9. Ku J, Danesh-Myer H, Craig J, et al..Comparison of intraocular pressure by Pascal dynamic contour tonometry and Goldmann applanation tonometry.Eye.2006;20:191–198.
10. Kotecha A.What biomechanical properties of the cornea are relevant for the clinician?Surv Ophthalmol.2007;52:S109–S114.
11. Boehm A, Weber A, Pillunat LE, et al..Dynamic contour tonometry in comparison to intracameral IOP measurements.Invest Ophthalmol Vis Sci.2004;45:3118–3121.
12. Chihara E.Assessment of true intraocular pressure: the gap between theory and practical data.Surv Ophthalmol.2008;53:203–218.
13. Renier C, Zeyen T, Fieuws S, et al..Comparison of ocular response analyzer, dynamic contour tonometer, and Goldmann applanation tonometer.Int Ophthalmol.2010;6:651–659.
14. Realini T, Weinreb R, Hobbs G.Correlation of intraocular pressure measured with Goldmann and dynamic contour tonometry in normal and glaucoma eyes.J Glaucoma.2009;18:119–123.
15. Vandewalle E, Vandenbroeck S, Stalmans I, et al..Comparison of iCare, dynamic contour tonometer, and ocular response analyzer with Goldmann applanation tonometer in patients with glaucoma.Eur J Ophthalmol.2009;19:783–789.
16. Liu J, Roberts C.Influence of corneal biomechanical properties on intraocular pressure measurement: quantitative analysis.J Cataract Refract Surg.2005;31:146–155.
17. Wang J, Cayer MM, Descovich D, et al..Assessment of factors affecting the difference in intraocular pressure measurements between dynamic contour tonometry and Goldmann applanation tonometry.J Glaucoma.2011;20:482–487.
18. Kannigiesser H, Kniestedt C, Robert Y.Dynamic contour tonometry: presentation of a new tonometer.J Glaucoma.2005;14:344–350.
19. Luce D.Determining in vivo biomechanical properties of the cornea with an ocular response analyzer.J Cataract Refract Surg.2005;31:156–162.
20. Elsheikh A, Alhasso D, Kotecha A, et al..Assessment of the ocular response analyzer as a tool for intraocular pressure measurement.J Biomech Eng.2009;131:081010.
21. Kotecha A, White E, Schlottmann P, et al..Intraocular pressure measurement precision with the Goldmann applanation, dynamic contour, and ocular response analyzer tonometers.Ophthalmology.2010;117:730–737.
22. Streho M, Dariel R, Giraud JM, et al..Evaluation of the Ocular Response Analyzer in ocular hypertension, glaucoma, and normal populations. Prospective study on 329 eyes.J Fr Ophthalmol.2008;31:953–960.
23. Quigley H, Broman A.The number of people with glaucoma worldwide in 2010 and 2020.Br J Ophthalmol.2006;90:262–267.
24. Gordon M, Beiser J, Brandt J, et al..The Ocular Hypertension Treatment Study: baseline factors that predict the onset of primary open-angle glaucoma.Arch Ophthalmol.2002;120:714–720.
25. Leske M, Heijl A, Hussein M, et al..Factors of glaucoma progression and the effect of treatment: the early manifest glaucoma trial.Arch Ophthalmol.2003;121:48–56.
26. Grieshaber M, Schoetzau A, Zawinka C, et al..Effect of central corneal thickness on dynamic contour tonometry and Goldmann applanation tonometry in primary open angle glaucoma.Arch Ophthalmol.2007;125:740–744.
27. Punajbi O, Kniestedt C, Bostrom A, et al..Intraocular pressure and ocular pulse amplitude comparisons in different types of glaucoma using dynamic contour tonometry.Curr Eye Res.2006;31:851–862.
28. Touboul D, Roberts C, Kérautret M, et al..Correlations between corneal hysteresis, intraocular pressure, and corneal central pachymetry.J Cataract Refract Surg.2008;34:616–622.
29. Heras-Mulero H, Moreno-Montanes J, Sadaba Echarri L, et al..Comparison of dynamic contour tonometry (Pascal) with pneumotonometry and Goldmann tonometry.Arch Soc Esp Oftalmol.2007;82:337–342.
30. Sullivan-Mee M, Gerhardt G, Halverson K, et al..Repeatability and reproducibility for intraocular pressure measurement by dynamic contour, ocular response analyzer, and Goldmann applanation tonometry.J Glaucoma.2009;18:666–673.
31. Ceruti P, Morbio R, Marraffa M, et al..Comparison of Goldmann applanation tonometry and dynamic contour tonometry in healthy and glaucomatous eyes.Eye.2009;23:262–269.
32. Detorakis E, Arvanitaki V, Pallikaris I, et al..Applanation tonometry versus dynamic contour tonometry in eyes treated with latanoprost.J Glaucoma.2010;19:194–198.
33. Sullivan-Mee M, Billingsley S, Patel A, et al..Ocular response analyzer in subjects with and without glaucoma.Optom Vis Sci.2008;85:463–470.
34. Wells A, Garway-Heath D, Poostchi A, et al..Corneal hysteresis but not corneal thickness correlates with optic nerve surface compliance in glaucoma patients.Invest Ophthalmol Vis Sci.2008;19:3262–3268.
35. Fogagnolo P, Figus M, Frezzotti P, et al..Test-retest variability of intraocular pressure and ocular pulse amplitude for dynamic contour tonometry: a multicentre study.Br J Ophthalmol.2010;94:419–423.
36. Kamppeter B, Jonas J.Dynamic contour tonometry for intraocular pressure measurement.Am J Ophthalmol.2005;140:318–320.
37. Mangourisas G, Morphis G, Mourtzoukos S, et al..Association between corneal hysteresis and central corneal thickness in glaucomatous and non-glaucomatous eyes.Acta Ophthalmol.2009;87:901–905.
38. Moreno-Montanes J, Maldonado M, Garcia N, et al..Reproducibility and clinical relevance of the ocular response analyzer in nonoperated eyes: corneal biomechanical and tonometric implications.Invest Ophthalmol Vis Sci.2008;49:968–974.
39. Abitbol O, Bouden J, Doan S, et al..Corneal hysteresis measured with the ocular response analyzer in normal and glaucomatous eyes.Acta Ophthalmol.2009;88:116–119.
40. Congdon N, Broman A, Bandeen-Roche K, et al..Central corneal thickness and corneal hysteresis associated with glaucoma damage.Am J Ophthalmol.2006;141:868–875.
41. Glass D, Roberts C, Litsky A, et al..A viscoelastic biomechanical model of the cornea describing the effect of viscosity and elasticity on hysteresis.Invest Ophthalmol Vis Sci.2008;49:3919–3926.
42. Zhou L, Sawaguchi S, Twining S, et al..Expression of degradative enzymes and protease inhibitors in corneas with keratoconus.Invest ophthalmol Vis Sci.1998;39:1117–1124.
43. Lindsey J, Crowston J, Tran A, et al..Direct matrix metalloproteinase enhancement of transscleral permeability.Invest Ophthalmol Vis Sci.2007;48:752–755.
44. Kim J, Lindsey J, Wang N, et al..Increased human scleral permeability with prostaglandin exposure.Invest Ophthalmol Vis Sci.2001;42:1514–1521.
45. Elsheikh A, et al..Assessment of corneal biomechanical properties and their variation with age.Curr Eye Res.2007;32:11–19.
46. Kamiya K, Hagishima M, Fujimura F, et al..Factors affecting corneal hysteresis in normal eyes.Graefes Arch Clin Exp Ophthalmol.2008;246:1491–1494.
47. Narayanaswamy A, Chung RS, Wu RY, et al..Determinants of corneal biomechanical properties in an adult Chinese population.Ophthalmology.2011;118:1253–1259.
48. Leite MT, Alencar LM, Gore C, et al..Comparison of corneal biomechanical properties between healthy blacks and whites using the Ocular Response Analyzer.Am J Ophthalmol.2010;150:163–168.
corneal biomechanics; primary open-angle glaucoma; intraocular pressure; Goldmann applanation tonometry; dynamic contour tonometry; ocular response analyzer
© 2014 by Lippincott Williams & Wilkins.
Highlight selected keywords in the article text.