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 Table of Contents  
ORIGINAL ARTICLE
Year : 2017  |  Volume : 30  |  Issue : 3  |  Page : 958-965

Corneal biomechanical changes in patients with thin cornea


1 Department of Ophthalmology, Faculty of Medicine, Menoufia University, Egypt
2 Ophthalmology Resident, Memorial Institute of Ophthalmology, Giza Governorate, Egypt

Date of Submission02-Jan-2017
Date of Acceptance21-Mar-2017
Date of Web Publication15-Nov-2017

Correspondence Address:
Mahmoud A Elsayed Hassan
Mit Ghamr, El Dakahlia, 35611
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mmj.mmj_12_17

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  Abstract 

Objectives
The aim of this study was to evaluate and compare corneal hysteresis (CH) and corneal resistance factor (CRF) in healthy eyes with a central corneal thickness of 470–500 μm with matched keratoconus (KC) and keratoconus suspect (KCS) cases.
Background
The ocular response analyzer is a device developed in recent years that reveals the biomechanical properties of the cornea. It reflects certain biomechanical properties of the cornea, such as CH and CRF.
Patients and methods
A total of 66 eyes in three groups were included prospectively based on clinical examination and topography: the normal (NL), KC, and KCS groups. CH and CRF were measured using the ocular response analyzer. CH and CRF were compared between the three groups using the analysis of variances test.
Results
The three groups consisted of 32 NL, 15 KC, and 19 KCS eyes. The mean CH measured was 8.55 ± 1.77, 9.03 ± 1.119, and 8.06 ± 0.85 mmHg in NL, KCS, and KC eyes, respectively. The mean CRF was 8.39 ± 1.47, 8.27 ± 1.09, and 7.24 ± 1.27 mmHg in NL, KCS, and KC eyes, respectively. On controlling the central corneal thickness (470–500 μm) and sex, only mean CRF was significantly different between the NL and KC groups (P < 0.05). There was no significant difference between NL and KCS eyes; there was no significant difference in the mean CH between each groups (P > 0.05).
Conclusion
Only CRF can be helpful in differentiating KC from NL eyes; however, it is not valuable for detecting KCS, which is the main concern for refractive surgery. CH is not beneficial in differentiating between the study groups. Future studies focusing on more accurate tests for identifying KCS using a consistent grading scale for defining KC and KCS are still warranted.

Keywords: corneal biomechanics, corneal hysteresis, corneal resistance factor, forme fruste keratoconus, keratoconus, ocular response analyzer


How to cite this article:
Marey HM, Zaky AG, Elsayed Hassan MA. Corneal biomechanical changes in patients with thin cornea. Menoufia Med J 2017;30:958-65

How to cite this URL:
Marey HM, Zaky AG, Elsayed Hassan MA. Corneal biomechanical changes in patients with thin cornea. Menoufia Med J [serial online] 2017 [cited 2020 Mar 30];30:958-65. Available from: http://www.mmj.eg.net/text.asp?2017/30/3/958/218250


  Introduction Top


Corneal refractive surgery performed using either lamellar (laser-assisted in-situ keratomileusis) or surface (photorefractive keratectomy and laser epithelial keratomileusis) techniques has shown safety, predictability, and stability when performed in patients with healthy thin corneas [1].

However, proper patient selection is challenging in such cases, as preoperative thin corneas and thinner residual stromal bed after excimer laser ablation are widely described as risk factors for the development of postoperative ectasia [2].

For decision making in these cases, preoperative evaluation is critically important to ensure successful immediate and long-term outcomes of refractive surgery. Corneal topography and tomography, the gold standard for screening refractive surgery candidates, have proven to be a valuable tool for ectasia diagnosis; however, it provides no direct information about corneal biomechanics, nor does it allow us to accurately predict a biomechanical response to treatment [3].

Central corneal thickness (CCT) is a biometric entity [4], and its biological variability in healthy eyes is believed to result from different amounts of collagen fibrils and interfibrillary substance in the corneal stroma [5]. It is a measure of tissue mass and perhaps an estimator of corneal rigidity. However, CCT varies among ethnic groups and also demonstrates strong heritability in families [6].

The development of a test for reliable assessment of corneal stiffness and its response to excimer laser ablation was an essential step in the evolution of refractive surgery. This was a significant engineering challenge until 2005, when the ocular response analyzer (ORA) became available [7].

The ORA has an infrared electro-optical system that monitors corneal deformations. It delivers a precisely metered collimated air pulse to the eye. The cornea suffers an inward movement, passing a first applanation state before assuming a concave shape. The air pressure progressively declines after this first applanation and the cornea passes through a second applanation state while returning to its normal convex curvature. The examination generates a waveform that contains two peaks, corresponding to the inward and outward applanation events.

Using this bidirectional applanation measurement, the ORA is able to present the four original parameters. Corneal hysteresis (CH) is the difference between these two pressure values, which represents the corneal viscoelastic damping. The mean of these two pressures is the Goldmann-correlated intraocular pressure (IOPg). The corneal-compensated intraocular pressure (IOPcc) is a pressure measurement that uses the CH to determine an IOP value that is less affected by corneal properties, such as CCT. Corneal resistance factor (CRF) is calculated using a proprietary algorithm and is an indicator of the overall corneal resistance [8].

Corneal biomechanical metrics were studied in different conditions. In a population of healthy individuals, corneal biomechanical metrics and CCT are strongly associated, while showing an inverse relationship with older age, and higher values in female patients [9]. When compared between keratoconus (KC) eyes and healthy controls, a statistical difference in CH and CRF was found between groups, but, when considered individually, the measures demonstrated low sensitivity, specificity, and test accuracy for KC and healthy cornea differentiation. Similar findings were found as regards CH and CRF in patients with mild KC and also in cases of KC with CCT greater than or equal to 520 μm [10]. In the present study, we investigated corneal biomechanical metrics in healthy eyes [normal (NL)] with CCT 470–500 μm and compared them with matched KC and keratoconus suspect (KCS) cases.


  Patients and Methods Top


A total of 66 eyes were enrolled in our study. Patients were selected from the ophthalmology outpatient clinics in the Ophthalmology Department of Menoufia University Hospitals and Memorial Institute of Ophthalmology in Giza. Patients were divided into three groups:

Group 1, which included 32 eyes with a CCT of 470–500 μm and a normal pattern on Pentacam (Optikgerate GmbH, Wetzlar, Germany).

Group 2, which included 15 eyes with a CCT of 470–500 μm and a suspicious pattern on Pentacam.

Group 3, which included 19 eyes with a CCT of 470–500 μm and a KC pattern on Pentacam.

Inclusion criteria

Inclusion criteria were as follows: age from 18 to 35 years, CCT between 470 and 500 μm. The inclusion criteria for the KCS group were as follows: no clinical signs of KC, CCT 470–500 μm, steep keratometric curvature greater than 47 D, minor topographic asymmetry defined as inferior–superior difference greater than or equal to 1.5 D and superior–inferior difference greater than or equal to 2.5 D.

The inclusion criteria for the KC group were as follows: any grade of KC with CCT within the range selected in the study (470–500 μm).

Exclusion criteria

Exclusion criteria were as follows: previous ocular surgery, corneal scars or opacities, chronic use of topical medications, systemic collagen diseases (e.g. Marfan and Ehler Danlos syndrome), and previous history of corneal ulcers.

Each participant was subjected to a comprehensive ophthalmologic examination, including a review of their medical history, best-corrected visual acuity, slit lamp biomicroscopy, and fundus examination. Pentacam topography (Oculus Pentacam; Optikgerate GmbH, Wetzlar, Germany) was performed and every patient was subjected to ORA (Ocular Response Analyzer; Reichert, New York, New York, USA) to measure corneal biomechanical parameters: CH, CRF, IOPg, and IOPcc.

Two consecutive ORA measurements were taken and the best waveform score from each patient was included in the analysis.

[Figure 1], [Figure 2], [Figure 3] represent the Pentacam images of study group 1 (NL), group 2 (KCS), and group 3 (KC), respectively, during our study.
Figure 1: Pentacam image of the left eye of patient number 22 from group 1 (normal).

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Figure 2: Pentacam image of the right eye of patient number 9 from group 2 (keratoconus suspect). CH, corneal hysteresis.

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Figure 3: Pentacam image of the left eye of patient number 14 from group 3 (keratoconus).

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The ORA is a noncontact tonometer with automated eye centration alignment. Participants were seated on a chair and instructed to place their foreheads on the headrest of the ORA device that was made to match their height by adjusting the height of a table.

To avoid startling the participants, they were first briefed about a noncontact probe that would move toward the eye and emit a sudden but gentle puff of air. Participants were told to focus on a blinking red light in the device.

Thereafter, the ORA was activated and the air puff was emitted onto the center of the cornea. The ORA readings were obtained consecutively and only good-quality readings were stored. If poor-quality waveforms were obtained, they were deleted and a new measurement was taken.

Only the readings with liability more than 6 were stored. The manufacturer defined good-quality readings as both force-in and force-out applanation signal peaks on the ORA waveform being fairly symmetrical in height. The ORA displayed a graphic representation of the corneal response after each measurement [Figure 4].
Figure 4: Ocular response analyzer signals.

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[Figure 5], [Figure 6], [Figure 7] represent the ORA signals provided from our three study groups.
Figure 5: Ocular response analyzer signal of the left eye of patient number 22 from group 1 (normal).

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Figure 6: Ocular response analyzer signal of the right eye of patient number 9 from group 2 (keratoconus suspect).

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Figure 7: Ocular response analyzer signal of the left eye of patient number 14 of the group 3 (keratoconus).

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The red curve is the 'dynamic map' of the cornea obtained during the rapid in/out deformation. That dynamic process generated two signal peaks that defined the two applanation states. The difference between these inward and outward motion applanation pressures (P1 and P2) was called CH.

The ORA software utilized the CH to generate two additional parameters: the IOPcc and the CRF. A IOPg was also provided by the machine.

Statistical analysis

Data were statistically described in terms of mean ± SD, median and range, or frequencies and percentages, when appropriate. Comparison of numerical variables between the study groups was made using the independent samples t-test. For comparing categorical data, the c2-test was performed. Fisher's exact test was used instead when the expected frequency was less than 5. Comparison of the continuous variables was made using one-way analysis of variance with Bonferroni correction for post-hoc analysis. The predictive ability of the ORA parameters was analyzed using receiver operating characteristics (ROC) curve. P values less than 0.05 were considered statistically significant. All statistical calculations were carried out using computer program statistical package for the social science (version 21; IBM Corp., New York, New York, USA) for Microsoft Windows. ROC curves were developed using MedCalc biomedical statistics software version 15.8 (MedCalc Software bvba, Ostend, Belgium).


  Results Top


A total of 66 eyes were enrolled in our study. Patients were selected from the ophthalmology outpatient clinics in Ophthalmology Department of Menoufia University Hospitals and Memorial Institute of Ophthalmology in Giza. The type of our study is a cross-sectional prospective comparative one. The study was carried out from December 2015 to November 2016.

The age of our study groups ranged from 17 to 35 years, with an average of 29.59 ± 3.02 years for group 1 (NL), 26.86 ± 5.42 years for group 2 (KCS), and 30.26 ± 3.85 years for group 3 (KC) [Table 1].
Table 1: The age of the study groups

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Our study included 40 eyes of male patients and 26 eyes of female patients. Group 1 (NL) included 20 male and 12 female patients, group 2 (KCS) included eight male and seven female patients, and group 3 (KC) included 12 male and seven female patients [Table 2].
Table 2: Sex distribution in both groups

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The study included 33 right eyes and 33 left eyes. Group 1 (NL) included 16 right eyes and 16 left eyes, group 2 (KCS) included eight right and seven left eyes, and group 3 (KC) included nine right and ten left eyes [Table 3].
Table 3: Eye side in three groups

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CCT ranged from 470 to 500 μm, with an average of 492.90 ± 8.07 μm years for group 1 (NL), 488.53 ± 9.47 μm for group 2 (KCS), and 486.10 ± 9.41 μm for group 3 (KC). The difference between the three groups was statistically nonsignificant (P = 0.057) [Table 4].
Table 4: Central corneal thickness in the three groups

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The CH of the study groups ranged from 5.7 to 14.10 mmHg with an average of 8.55 ± 1.77 mmHg for group 1 (NL); it ranged from 7.50 to 10.80 mmHg, with an average of 9.03 ± 1.119 mmHg for group 2 (KCS); and it ranged from 6.5 to 10.80 with an average of 8.06 ± 0.85 for the diabetic group (KC) [Table 5].
Table 5: Corneal hysteresis of the study group

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The CRF of the study groups ranged from 5.7 to 12.50 mmHg with an average of 8.39 ± 1.47 mmHg for group 1 (NL); it ranged from 6.90 to 10.10 mmHg, with an average 8.27 ± 1.09 mmHg for group 2 (KCS); and it ranged from 5 to 9.70 with an average of 7.24 ± 1.27 for the diabetic group (KC) [Table 6].
Table 6: Corneal resistance factor of the study groups

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  Discussion Top


The human cornea is a viscoelastic tissue that can be described by two principal properties: (i) a static resistance component (characterized by the CRF), for which deformation is proportional to applied force, and (ii) a dynamic resistance component (characterized by CH), for which the relationship between deformation and applied force depends on time, both CH and the CRF are measured with a dynamic bidirectional applanation process using the ORA [11].

The keratoconic cornea has a conical curvature with three characteristic features: thinning of the corneal stroma with folding artifacts; breaks in the Bowman's layer due to a weak collagen fiber network; and deposition of iron in the basal layers of the corneal epithelium. Additional structural changes may also be observed depending on the severity of the disease [12]. A decrease in the number of collagen lamellae concomitant with an increase in the ground substance (proteoglycans) is frequently observed in the stroma [13]. Loss of collagen fibrils in the stroma has been linked to proteolytic enzymes or decreased levels of proteinase inhibitors such as corneal α1 inhibitor and α2 macroglobulin [14].

Diagnosing mild-to-severe forms of KC is not difficult; however, diagnosing forme fruste keratoconus or KCS eyes remains challenging. Despite the improvements in detecting KCS eyes using topographic and tomographic tools, there is no specific accepted consensus for categorizing an eye as KCS [15] and new cases of corneal ectasia after refractive surgery are still reported [16],[17],[18],[19],[20]. Therefore, a test that could detect KCS eyes with high accuracy in doubtful cases is necessary.

Since Luce [8] developed ORA for measuring corneal biomechanics in vivo, various studies have evaluated the ORA parameters, CH and CRF accuracy, for detecting KC and KCS from NL eyes [21],[22],[23],[24],[25]. These studies have determined that CH and CRF are significantly lower in KC eyes than in NL eyes and reported CH and CRF as poor properties for discriminating mild KC from NL eyes [10],[24],[25]. Despite the various studies performed to evaluate the ORA accuracy for detecting KC and KCS from NL eyes, the diagnostic performance of the CH and CRF remains of limited value and the role of CCT as a confounding factor is not yet clearly defined [10],[21],[22],[23],[24],[25].

Our study assessed the diagnostic accuracy of ORA parameters for detecting clinical and subclinical forms of KC from NL eyes. Our results showed that only the mean CRF was significantly lower in KC eyes compared with NL ones, but no significant difference was seen in CCT, CH, and CRF parameters of KCS eyes compared with NL eyes.

Various studies have assessed CH and CRF between NL and KC eyes. Fontes et al. [10] found a significantly lower CH and CRF in KC in comparison with NL eyes. Our study found only the CRF to be significantly lower in KC than in NL eyes, with no significance to CH.

Our study results are similar to a study conducted by Galletti et al. [26], which proved that CRF was better than CH for detecting keratoconic corneas once the effect of CCT on ORA measurements was considered, even for topographically unaffected fellow eyes of patients with KC. The CCT-corrected CRF cutoff values and transformed indices may be of clinical use [26]. In other words, CH is probably decreased in eyes with KC but not to the point that it can be clinically useful in ORA-based subclinical KC detection.

Our results also showed that the mean CH, CRF, and CCT in KCS did not differ from NL eyes [22]. Using the principle Orbscan criterion to identify KCS, there was a difference of 1.5 D or greater between superior and inferior corneal curvature. There was no significant difference between groups [27]. Saad et al. [27] used a computer-based calculation from Nidek OPD scan videokeratographer; they found a significant difference between NL and KCS first, which failed to remain significant after controlling for CCT.

A possible explanation for this finding might be the confounding role of corneal thickness on corneal biomechanics, especially CH and CRF. CH and CRF are known to be highly correlated to corneal thickness [9],[28],[29]. As corneal thickness decreases significantly in keratoconic eyes [30] and usually is within NL limits in KCS and NL eyes, any changes in CH and CRF could be related to the changes in CCT. After controlling for the CCT in our study, only CRF differences between NL and KC remained significant. The CCT between NL and KCS eyes were not significantly different and therefore could not play a confounding role.

However, our results are not in agreement with a number of previous studies. Schweitzer et al. [23] used the NL fellow eye of a manifest keratoconic with a KISA index of less than 60% for defining KCS. They found a significant difference between NL and KCS eyes, which remained significant after controlling for CCT in the thinner groups. Johnson et al. [21] used the keratoconus severity score developed by the collaborative longitudinal evaluation of KC study group to define and grade the severity of KCS. They also found a significant difference between KCS and NL eyes after adjustment for CCT, age, and sex. The KCS grading of severity performed in this study has made the comparison of their result with other studies directly impossible. This discrepancy between the studies may be caused by the various definitions of KCS used in different studies as proposed by Johnson et al. [21]; therefore, the use of a unified grading scale for defining KCS in future studies is highly useful for comparing the results.

ROC curve analysis performed for KC and NL eyes showed that a cutoff point of 8.4 for CH provided 84.2% sensitivity and 46.8% specificity, and a cutoff point of 7.6 for CRF provided 78.95% sensitivity and 68.09% specificity. Because there was no significant difference between KCS and NL eyes in CH and CRF, the ROC curve analysis was only performed for the NL and the KC group and the KCS eyes were not included in our study. The ROC curve analysis performed in the study by Fontes et al. [10] showed a poor overall predictive value of CH (74.83%) and CRF (76.97%) with the cutoff points of 9.64 and 9.60 mmHg, respectively. In comparison with Fontes et al. [10], our study showed higher overall predictive values for CRF, similar to the findings of Galletti et al. [26].

The ORA parameters provided by ORA can be helpful in differentiating KC eyes from NL ones, but CH and CRF cannot detect KCS from NL eyes; therefore, ORA alone would not be a helpful diagnostic tool for detecting KCS eyes. However, as mentioned before, the clinical challenge is to have a test that could detect KCS with high accuracy from NL eyes. Our findings show that CRF, but not CH, is a reliable indicator even for subclinical cases with unremarkable topography, but only if corneal thickness is taken into account [26]. We have derived both optimized CRF cutoff values and transformed indices for this purpose and believe that ORA testing should be considered in the preoperative screening of laser-assisted in-situ keratomileusis candidates.


  Conclusion Top


In conclusion, the corneal biomechanics, in particular CRF, are significantly higher in the NL group compared with the KC group, as shown in results. The difference in CRF between groups 1 and 3 is statistically highly significant (P = 0.013), with no significant difference that could detect KCS eyes. Meanwhile, the difference in CH between the three groups is statistically highly nonsignificant (P = 0.147). We believe that CRF is the key factor in identifying biomechanical changes in keratoconic eyes with matched CCT normal thin cornea eyes. Future studies focusing on more accurate tests for finding KCS are still warranted.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]



 

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