Corneal biomechanical properties in normal, forme fruste keratoconus, and manifest keratoconus after statistical correction for potentially confounding factors

Corneal biomechanics in early diagnosis of keratoconus using artificial intelligence

Keratoconus is a blinding eye disease that affects activities of daily living; therefore, early diagnosis is crucial. Great efforts have been made toward an early diagnosis of keratoconus. Recent studies have shown that corneal biomechanics is associated with the occurrence and progression of keratoconus. Hence, detecting changes in corneal biomechanics may provide a novel strategy for early diagnosis. However, an early keratoconus diagnosis remains challenging due to the subtle and localized nature of its lesions. Artificial intelligence has been used to help address this problem. Herein, we reviewed the literature regarding three aspects of keratoconus (keratoconus, early keratoconus, and keratoconus grading) based on corneal biomechanical properties using artificial intelligence. Furthermore, we summarized the current research progress, limitations, and possible prospects.

Keratoconus: A Biomechanical Perspective

PURPOSE

The relevance of corneal biomechanics and the importance of including it in the clinical assessment of corneal ectasias are being increasingly recognized. The connection between corneal ultrastructure, biomechanical properties, and optical function is exemplified by a condition like keratoconus. Biomechanical instability is seen as the underlying basis for the secondary morphological changes in the cornea. Asymmetric biomechanical weakening is believed to drive progressive corneal steepening and thinning. Biomechanical strengthening is the principle of collagen crosslinking that has been shown to effectively arrest progression of the keratoconus. Corneal biomechanics has therefore ignited the interest of researchers and clinicians alike and has given us new insights into the cause and course of the disease. This article is an overview of the extensive work published, predominantly in the last two decades, on the biomechanical aspect of keratoconus.

METHODS

Published articles on corneal biomechanics in the specific context of keratoconus were reviewed, based on an electronic search using PubMed, Elsevier, and Science Direct. The search terms used included "Corneal Biomechanics," "Mechanical properties of the cornea," "Corneal ultrastructure," "Corneal Collagen," and "Keratoconus". Articles pertaining to refractive surgery, keratoplasty, collagen crosslinking, or intrastromal rings were excluded.

RESULTS

The electronic search revealed more than 500 articles, from which 80 were chosen for this article.

CONCLUSIONS

The structural and organizational pattern of the corneal stroma determines its mechanical properties and are responsible for the maintenance of the normal shape and function of the cornea. Changes in the ultrastructure are responsible for the biomechanical instability that leads to corneal ectasia. As non-invasive methods for evaluating corneal biomechanics in vivo evolve, our ability to diagnose subclinical keratoconus will improve, allowing identification of patients at risk to develop ectasia and to allow early treatment to arrest progression of the disease.

Analysis of Various Modalities for Intraocular Pressure Measurement in Relation to Keratoconus Severity in 246 Eyes of the Homburg Keratoconus Center

PURPOSE

Intraocular pressure (IOP) measurement may be difficult in keratoconus (KC) due to corneal protrusion and irregular astigmatism. This study aimed to assess which IOP measurement modality is least affected by KC severity.

METHODS

Data from 246 corneas of 246 patients with KC were retrospectively analyzed. KC stages were determined using the Topographic KC (TKC) and ABCD KC classifications derived from Pentacam (Oculus, Germany). IOP was measured using Goldmann applanation tonometry (GAT), Ocular Response Analyzer (ORA, Reichert Instruments, USA), and Corvis ST (CST, Oculus, Germany). Cronbach alpha (CA), analysis of variance with Bonferroni correction, Dunnett T3, and Pearson correlation were performed.

RESULTS

Using CA, the reliability of measurements using various modalities increased to 0.764 to 0.943 when excluding IOP Goldmann overall and in each KC stage (TKC and ABCD). Analysis of variance revealed significant differences between TKC and ABCD stages for almost all IOP modalities. The Bonferroni post hoc test showed significant differences between the measured IOP in earlier and advanced KC stages, except for the biomechanically CST-corrected IOP (bIOP). Pearson correlation analysis showed a significant correlation between IOP and thinnest corneal thickness (TCT) for all IOP modalities except bIOP.

CONCLUSIONS

CST-based bIOP seems to be best suited for IOP measurement in KC because it did not correlate with TCT in contrast to IOP measurements by ORA or GAT. The measurement results from GAT in patients with KC should be interpreted with care and always in view of corneal thickness. As a thumb rule, we suggest to add at least 2 mm Hg to the measured GAT value.

Biomechanical properties of the cornea in Floppy eyelid syndrome

Background: Floppy eyelid syndrome (FES) is a frequently underdiagnosed disorder of unknown pathogenesis. FES has been associated with ocular conditions such as keratoconus. At present, despite the frequent combination of FES and keratoconus, there are almost no data on the biomechanical properties of the cornea in these patients. Aims: to determine the corneas biomechanical properties in patients with floppy eyelid syndrome. Methods: The study included 40 patients (54 eyes) with hyper-extensible eyelid syndrome. The average age was 53.96.7 years. The central corneal thickness averaged 55125 m. All the patients underwent a standard ophthalmological examination, including pneumotonometry. The intraocular pressure (IOP) and biomechanical properties of the cornea were measured using dynamic bidirectional applanation. Results: The study of the corneas biomechanical properties in patients with floppy eyelid syndrome showed a decrease in the corneal hysteresis (CH) indices to 9.960.61 mm Hg on the average, in the corneal resistance factor (CRF) to 9.540.64 mm Hg. Moreover, their value varied depending on the severity of the syndrome. The mean value of the corneal compensated IOP (IOPcc) in the entire sample was 15.51.0 mm Hg, Goldman IOP (IOPg) 15.12.0 mm Hg, pneumotonometric IOP 11.612.9 mm Hg. Regardless of the severity, the pneumotonometric IOP indices did not have statistically significant differences, while as this syndrome progressed, the IOPcc and IOPg indices showed a steady decrease in the mean values. Conclusions: It was found that, in floppy eyelid syndrome, the biomechanical parameters of the cornea were reduced. At the same time, the value of these indicators varied significantly with the severity. The largest and the smallest decrease were observed in the corneal hysteresis index and the corneal-compensated IOP, respectively.

Effects of water drinking on corneal biomechanics: The association with intraocular pressure changes

Purpose:

We aimed to assess the impact of drinking water (500 and 1000 mL) on corneal biomechanics and determine the level of association between changes in intraocular pressure and variations in the different biomechanical properties of the cornea.

Methods:

A total of 39 healthy young adults ingested either 1000 mL (n = 21) or 500 mL (n = 18) of tap water in 5 min. The CorVis ST system was used to assess corneal biomechanics at baseline and at 15, 30, and 45 min after water ingestion.

Results:

Water drinking induced statistically significant changes in the deformation amplitude (P < 0.001, η² = 0.166), highest concavity time (P = 0.012, η² = 0.093), peak distance (P < 0.001, η² = 0.171), time and velocity of the first applanation (P < 0.001, η² = 0.288 and P = 0.016, η² = 0.087, respectively), and time and velocity of the second applanation (P = 0.030, η² = 0.074 and P = 0.001, η² = 0.132, respectively), being independent of the amount of water ingested (P > 0.05 in all cases). There were significant associations between changes in intraocular pressure and some parameters of corneal biomechanics

Conclusion:

Small variations in whole-body hydration status alter different biomechanical properties of the cornea, with these changes being associated with intraocular pressure levels. These findings indicate that whole-body hydration status can be considered for the diagnosis and management of different ocular conditions.

Detektion des subklinischen Keratokonus

Das Frühstadium eines Keratokonus, ohne klassische und kennzeichnende klinische Befunde, stellt eine Kontraindikation für refraktive Chirurgie dar. Dieser Beitrag zeigt deshalb gemäß dem aktuellen Stand der Technik Möglichkeiten auf, Risikofaktoren für einen subklinischen Keratokonus zu erkennen.

[Detection of Subclinical Keratoconus]

The early stage of a keratoconus (KC), without classic and characteristic clinical findings, is a contraindication for refractive surgery. This article therefore shows, in accordance with the current state of the art, ways of identifying risk factors for subclinical keratoconus.After delimitation, this publication contains a current summary of epidemiology, etiology and pathophysiology of subclinical and clinical KC. Furthermore, an overview of different grading scales is given. A detailed description of several practical possibilities for detection of subclinical KC is the focus of this publication: typical abnormalities with subclinical KC in ocular aberrometry, corneal topography, Zernike analysis, Fourier analysis, indices of the corneal anterior surface; especially tomography of the anterior segment of the eye respecting addition of the corneal posterior surface and the pachymetry, and also innovative techniques counting in the rigidity or biomechanical properties, as well as traditional techniques giving hints for subclinical KC as retinoscopy, ophthalmoscopy and subjective refraction.In preparation for refractive surgical interventions and to avoid possible consequences of subclinical KC, a suitable analysis with different methods should always be carried out in addition to a specific anamnesis. An exclusive consideration of the available indices is not sufficient, as this does not reveal early stages. Ideally, the biomechanics of the cornea is included in the diagnosis. The combination of tomography and biomechanics with methods of artificial intelligence are trendsetting in detection of subclinical KC.

The effect of corneal crosslinking on the rigidity of the cornea estimated using a modified algorithm for the Schiøtz tonometer

Purpose:

The aim of this study was to test a method for estimating corneal rigidity before and after cross-linking (CXL) using a Schiøtz tonometer.

Methods:

The study was performed in the Kyiv City Clinical Ophthalmological Hospital “Eye Microsurgical Center”, Ukraine. This was a prospective, consecutive, randomized, masked, case-by-case, clinical study. Corneal rigidity, indicated by the gradient (G) between lg applied weight and corresponding lg scale reading during Schiøtz tonometry, were obtained by increasing (A-mode) then reducing (D-mode) weights by two operators [A] in keratoconus, post-CXL and control subjects for estimation of (i) interoperator and (ii) intersessional errors, (iii) intergroup differences; [B] before and after CXL. Central corneal thickness CCT was measured by scanning slit pachymetry. ANOVA, t tests, linear regression were the statistical tools used.

Results:

Average interoperator difference (ΔG) was –0.120 (SD = ±0.294, 95%CI = –0.175 to –0.066). A significant correlation between ΔG and the mean of each pair of G values was found (r = –0.196, n = 112, P = 0.038). Intersessional differences in mean G values were insignificant (P > 0.05). There was a significant correlation between G at first session (X₁) and difference between sessions (ΔG) [Operator 1, ΔG = 0.598x₁–0.461, r = 0.601, n = 27, P = 0.009]. Significant intergroup differences in G were found (Operator 1, one-way ANOVA, F = 4.489, P = 0.014). The difference (Δ) between the pre-(X₂) and post-CXL treatment G values was significantly associated with the pre-CXL treatment value (Operator 1, Δ = 1.970x₂-1.622, r = 0.642, n = 18, P = <.001). G values were correlated with CCT in keratoconus and post-CXL.

Conclusion:

Corneal rigidity (G) estimated using the Schiøtz tonometer can be useful for detecting changes after CXL. However, G values are linked to CCT, can vary from time-to-time and the procedure is operator dependent.

A Systematic Review of Subclinical Keratoconus and Forme Fruste Keratoconus

PURPOSE

To identify the definitions used for the terms sub-clinical keratoconus and forme fruste keratoconus in published articles.

METHODS

This was a prospective, systematic literature review of the electronic database in PubMed, the Cochrane Library, and LILACS Database of all studies using the keywords "subclinical keratoconus" and/or "forme fruste keratoconus" until August 18, 2017. Two independent reviewers analyzed the data. The inclusion criteria for articles were having analyzed subclinical keratoconus or forme fruste keratoconus eyes with a sample size greater than 10 eyes; containing the definition of subclinical keratoconus or forme fruste keratoconus; and the quality of published reports was assessed using standards quality index methods. The following aspects of the selected articles were then analyzed: inclusion criteria for definition and technology used.

RESULTS

A total of 198 and 95 studies, respectively, including the definition of subclinical keratoconus and forme fruste keratoconus were collected in an initial search, of which 165 and 73 studies, respectively, were excluded. Definitions for subclinical keratoconus and forme fruste keratoconus included the criteria of having keratoconus in the fellow eye in 72.72% (24 of 33) and 77.27% (17 of 22) of the articles, respectively. A total of 96.97% (32 of 33) and 90.90% (20 of 22) of the studies used more than one parameter to define subclinical keratoconus and forme fruste keratoconus, respectively. The most common extra parameters included normal slit-lamp examination and cornea on slit-lamp biomicroscopy and inferior-superior asymmetry and/or bowtie pattern with skewed radial axes.

CONCLUSIONS

This review demonstrates the lack of unified criteria to define subclinical keratoconus and forme fruste keratoconus. According to the literature review, the most common subclinical keratoconus definition used refers to an eye with topographic signs of keratoconus and/or suspicious topographic findings under normal slit-lamp examination and keratoconus in the fellow eye and the most common forme fruste keratoconus definition refers to an eye with normal topography, normal slit-lamp examination, and keratoconus in the fellow eye. [J Refract Surg. 2020;36(4):270-279.].

A Combined Biomechanical and Tomographic Model for Identifying Cases of Subclinical Keratoconus

PURPOSE

To develop a combined biomechanical and tomographic model for identifying eyes with subclinical keratoconus (SKC) that are categorized as normal or borderline in the Pentacam Belin/Ambrósio Enhanced Ectasia Display.

METHODS

This case-control study comprised 62 eyes with SKC and randomly selected eyes of 186 age-matched healthy controls. SKC was defined as the presence of the following: 1) normal topography, topometric indices, and slit lamp; 2) normal or borderline Belin/Ambrósio Enhanced Ectasia Display D index, back and front elevation difference; and 3) keratoconus in the fellow eye. Stepwise logistic regression analysis was performed to identify the best variable combination for detecting SKC cases from Ocular Response Analyzer and Pentacam parameters. Receiver operating characteristic curve analysis was used to determine the predictive accuracy [area under the curve (AUC)] of the model. Based on the predictors in the final logistic regression model, a linear equation was derived using the discriminant function analysis.

RESULTS

The final model (AUC: 0.948, sensitivity: 87.1%, and specificity: 91.4%) chose corneal hysteresis (CH) and D index from a total of 63 candidate variables. The final model had a higher AUC compared with D (0.933, P = 0.053) and CH (0.80, P < 0.001) alone. According to the discriminant function analysis, a higher CH was required with increasing D index to classify an eye as normal.

CONCLUSIONS

The proposed combined model provided varying cutoffs for CH and D as a function of the other. The probability plot as a function of CH and D index may be used for identifying eyes with SKC.

Biomechanical Properties in Different Types of Thin Corneas in Menoufia Population

Background

To evaluate and compare corneal hysteresis (CH) and corneal resistance factor (CRF) in normal thin (NT) healthy corneas with central corneal thickness (CCT) of 470–500 μm with matched thickness in keratoconus suspect (KCS) and keratoconus (KC) eyes.

Methods

A total of 103 eyes in three groups were included prospectively: NT, KCS, and KC groups based on clinical examination and Pentacam findings. Corneal hysteresis (CH) and corneal resistance factor (CRF) were measured using the ocular response analyzer (ORA). CCT, CH, and CRF were compared between the three groups and statistically analyzed by variance tests.

Results

The three groups consisted of 44 NT, 26 KCS, and 33 KC. The mean CH measured was 8.689 ± 1.775, 9.051 ± 1.1190, and 8.129 ± 0.8539 mmHg in NT, KCS, and KC eyes, respectively. The mean CRF was 8.441 ± 1.663, 8.337 ± 1.114, and 7.2422 ± 1.3110 mmHg in NT, KCS, and KC eyes, respectively. Within the range of central corneal thickness (470–500 μm), only mean CRF was statistically significantly different between the NT and KC (P < 0.05); there was no statistically significant difference between NT and KCS, nor was the mean CH between each group (P > 0.05).

Conclusions

CRF only can be helpful in differentiating KC from NT eyes; KCS could not be predicted with either corneal biomechanical metrics. There was no benefit from CH in differentiating between the three study groups.

Fine-mapping and cell-specific enrichment at corneal resistance factor loci prioritize candidate causal regulatory variants

Corneal resistance factor (CRF) is altered during corneal diseases progression. Genome-wide-association studies (GWAS) indicated potential CRF and disease genetics overlap. Here, we characterise 135 CRF loci following GWAS in 76029 UK Biobank participants. Enrichment of extra-cellular matrix gene-sets, genetic correlation with corneal thickness (70% (SE = 5%)), reported keratoconus risk variants at 13 loci, all support relevance to corneal stroma biology. Fine-mapping identifies a subset of 55 highly likely causal variants, 91% of which are non-coding. Genomic features enrichments, using all associated variants, also indicate prominent regulatory causal role. We newly established open chromatin landscapes in two widely-used human cornea immortalised cell lines using ATAC-seq. Variants associated with CRF were significantly enriched in regulatory regions from the corneal stroma-derived cell line and enrichment increases to over 5 fold for variants prioritised by fine-mapping-including at GAS7, SMAD3 and COL6A1 loci. Our analysis generates many hypotheses for future functional validation of aetiological mechanisms.

Corneal Biomechanical Properties in Childhood Obesity

PURPOSE

To investigate corneal biomechanical properties in patients with childhood obesity.

METHODS

The study included 47 patients with childhood obesity (study group) and 39 healthy patients (control group). Corneal hysteresis, corneal resistance factor, corneal compensated intraocular pressure (IOPcc), and Goldmann-correlated IOP (IOPg) were measured with the Ocular Response Analyzer (Reichert, Ophthalmic Instruments, Buffalo, NY) in each eye. Central corneal thickness (CCT), anterior chamber angle (ACA), anterior chamber volume (ACV), and anterior chamber depth (ACD) measurements were obtained by the Pentacam rotating Scheimpflug camera (Oculus Optikgeräte GmBh, Wetzlar, Germany).

RESULTS

The mean corneal hysteresis was 10.56 ± 1.52 mm Hg in the study group and 11.16 ± 1.92 mm Hg in the control group (P = .022). The mean IOP was 14.9 ± 2.0 mm Hg in the study group and 14.1 ± 1.3 mm Hg in the control group (P = .003). Corneal hysteresis showed a significant, positive correlation with corneal resistance factor (P < .001, r = 0.851), IOPg (P = .044, r = 0.213), CCT (P < .001, r = 0.477), and IOP (P = .005, r = 0.295). Corneal hysteresis showed a significant, negative correlation with IOPcc (P = .001, r = -0.355), ACA (P = .005, r = -0.294), ACV (P = .019, r = -0.246), and ACD (P = .046, r = -0.211).

CONCLUSIONS

Patients with childhood obesity have lower corneal hysteresis and higher IOPcc measurements when compared with healthy patients. Corneal tissue changes may occur in early life in childhood obesity, which could lead to ocular disease in the future. [J Pediatr Ophthalmol Strabismus. 2020;57(2):103-107.].

Corneal pulsation and biomechanics during induced ocular pulse. An ex-vivo pilot study

The purpose of this study was to ascertain the relationships between the amplitude of the corneal pulse (CP) signal and the parameters of corneal biomechanics during ex-vivo intraocular pressure (IOP) elevation experiments on porcine eyes with artificially induced ocular pulse cycles. Two experiments were carried out using porcine eyes. In the first one, a selected eye globe was subjected to three IOP levels (15, 30 and 45 mmHg), where changes in physical ocular pulse amplitude were controlled by infusion/withdrawal volumes (ΔV). In the second experiment, six eyes were subjected to IOP from 15 mmHg to 45 mmHg in steps of 5 mmHg with a constant ΔV, where corneal deformation parameters were measured using Corvis ST. In both experiments, at each IOP, the CP and IOP signals were acquired synchronically using a non-contact ultrasonic distance sensor and a pressure transmitter, respectively. Based on the amplitudes of the CP and IOP signals ocular pulse based corneal rigidity index (OPCRI) was calculated. Results indicate positive correlations between ΔV and the physical ocular pulse amplitude, and between ΔV and the corneal pulse amplitude (both p < 0.001). OPCRI was found to increase with elevated IOP. Furthermore, IOP statistically significantly differentiated changes in OPCRI, the amplitudes of CP and IOP signals and in most of the corneal deformation parameters (p < 0.05). The partial correlation analysis, with IOP as a control variable, revealed a significant correlation between the length of the flattened cornea during the first applanation (A1L) and the corneal pulse amplitude (p = 0.002), and between A1L and OPCRI (p = 0.003). In conclusion, this study proved that natural corneal pulsations, detected with a non-contact ultrasonic technique, reflect pressure-volume dynamics and can potentially be utilized to assess stiffness of the cornea. The proposed new rigidity index could be a simple approach to estimating corneal rigidity.

The Role of Ocular Response Analyzer in Differentiation of Forme Fruste Keratoconus From Corneal Astigmatism

PURPOSE

To determine the diagnostic accuracy of corneal biomechanical factors in differentiating patients with forme fruste keratoconus (FFKC) from astigmatic and normal cases.

METHODS

A total of 50 eyes with FFKC, 50 with astigmatism and 50 normal eyes, were included in this study. All patients had a detailed ophthalmologic examination including slit-lamp evaluation, Goldmann tonometry, indirect fundoscopy, topography by Scheimpflug imaging biomicroscopic anterior and posterior segment examination, and corneal biomechanical and intraocular pressure evaluation with ocular response analyzer (ORA).

RESULTS

All topographic findings were statistically significant among the three groups (P>0.05). Although there was no statistically significant difference in the corneal-compensated intraocular pressure (IOPcc) among the three groups, the Goldmann-correlated intraocular pressure (IOPg), corneal hysteresis (CH), and corneal resistance factor (CRF) were statistically significantly lower in the FFKC group, compared with the other groups (P<0.001). There were no statistically significant difference in the IOPg, CH, and CRF between astigmatism and control groups (P=0.99, 0.79, and 0.86, respectively). The area under the receiver operating characteristic (AUROC) curve was greater than 0.85 for IOPg (0.80), CH (0.85), and CRF (0.90) for discriminating between FFKC and controls; whereas the AUROC was greater than 0.85 for IOPg (0.80), CH (0.79), and CRF (0.85) for discriminating between FFKC and astigmatism groups.

CONCLUSION

Based on our study results, in differentiation of patients with FFKC from normal control cases or astigmatic patients, corneal biomechanical parameters play a role particularly in patients with suspicious results. We suggest using ORA in combination with corneal topography for better and more accurate diagnosis of FFKC.

Correlation Between Corneal Topographic, Densitometry, and Biomechanical Parameters in Keratoconus Eyes

Purpose

To investigate the correlation between corneal densitometry, corneal topographic parameters, and corneal biomechanical properties in keratoconus.

Methods

A total of 76 eyes of 76 keratoconus patients were enrolled in this cross-sectional study. Corneal densitometry and topography were measured using Pentacam HR. Corneal biomechanical properties were measured using CorVis ST.

Results

The corneal densitometry values of the anterior 0 to 2 and 2 to 6 mm layers significantly correlated with the maximum keratometry values (R = 0.373, P = 0.001 and R = 0.276, P = 0.016, respectively), thinnest corneal thickness values (R = -0.331, P = 0.003 and R = -0.234, P = 0.042, respectively), anterior corneal elevation (R = 0.392, P < 0.001 and R = 0.323, P = 0.004, respectively), and posterior corneal elevation (R = 0.450, P < 0.001 and R = 0.367, P = 0.001, respectively). The stiffness parameter-applanation time 1 (SP-A1) significantly correlated with the corneal densitometry values for the anterior 0 to 2 mm (R = -0.397, P < 0.001), anterior 2 to 6 mm (R = -0.331, P = 0.004), central 0 to 2 mm (R = -0.306, P = 0.007), central 2 to 6 mm (R = -0.228, P = 0.048), posterior 2 to 6 mm (R = -0.243, P = 0.035), total 0 to 2 mm (R = -0.291, P = 0.011), and total 2 to 6 mm (R = -0.295, P = 0.010) layers.

Conclusions

The corneal densitometry values correlated with the severity of keratoconus and the SP-A1 values.

Translational Relevance

Corneal densitometry values may serve as markers to predict the severity of keratoconus.

A Review of Structural and Biomechanical Changes in the Cornea in Aging, Disease, and Photochemical Crosslinking

The study of corneal biomechanics is motivated by the tight relationship between biomechanical properties and visual function within the ocular system. For instance, variation in collagen fibril alignment and non-enzymatic crosslinks rank high among structural factors which give rise to the cornea's particular shape and ability to properly focus light. Gradation in these and other factors engender biomechanical changes which can be quantified by a wide variety of techniques. This review summarizes what is known about both the changes in corneal structure and associated changes in corneal biomechanical properties in aging, keratoconic, and photochemically crosslinked corneas. In addition, methods for measuring corneal biomechanics are discussed and the topics are related to both clinical studies and biomechanical modeling simulations.

Four-year changes in corneal biomechanical properties in children

BACKGROUND

To determine four-year changes of corneal biomechanical parameters in Iranian children aged seven to eleven years and their correlation with optical components.

METHODS

In this four-year prospective cohort study, 468 children aged seven to eleven years who were initially evaluated in 2012 were re-evaluated in 2016-2017. Multi-stage stratified cluster sampling was applied. Cycloplegic refraction, biometry using LENSTAR/BioGraph, and corneal biomechanical assessment using Ocular Response Analyzer (ORA) were undertaken for each participant. The corneal biomechanical parameters assessed were corneal hysteresis (CH), corneal resistance factor (CRF), areas under the peaks 1 and 2 (p1 and p2 areas) and irregularity indices (A and B indices).

RESULTS

All biomechanical parameters except A index decreased in phase 2. The mean changes of CH and CRF were 0.68 ± 0.16 mmHg (for both parameters) during four years. The mean difference in CH and CRF was 0.23 ± 0.23 and 0.24 ± 0.23 mmHg in females and 1.03 ± 0.23 and 0.96 ± 0.23 mmHg in males, respectively. Different age groups showed varying amounts of decrease in all parameters except for A index. The age group 'ten years' experienced the smallest decrease in CH (0.02 ± 0.48 mmHg) and CRF (0.20 ± 0.47 mmHg) and the age group 'eleven years' showed the greatest decrease in CH (1.41 ± 0.35 mmHg) and CRF (0.99 ± 0.34 mmHg). According to linear regression analysis, CH and CRF had a significant direct relationship with corneal power and an inverse relationship with axial length (p < 0.001).

CONCLUSION

Age and sex are influencing factors on the ORA parameters. Older age is associated with reduced biomechanical parameters and reductions are more significant in males than females. Axial elongation and corneal flattening decrease CH and CRF.

Corneal biomechanical properties after laser-assisted in situ keratomileusis and photorefractive keratectomy

BACKGROUND

The purpose of this study was to evaluate the effects of laser-assisted in situ keratomileusis (LASIK) and photorefractive keratectomy (PRK) on corneal biomechanical properties.

METHODS

We used the ocular response analyzer to measure corneal hysteresis (CH) and corneal resistance factor (CRF) before and after refractive surgery.

RESULTS

In all, 230 eyes underwent LASIK and 115 eyes underwent PRK without mitomycin C (MMC). Both procedures decreased CH and CRF from baseline. When MMC was used after PRK in 20 eyes, it resulted in lower corneal biomechanical properties at 3 months when compared to the other procedures, but all three procedures had similar values at 12 months.

CONCLUSION

Significant but similar decreases in corneal biomechanical properties after LASIK, PRK without MMC, and PRK with MMC were noted.

Corneal Biomechanics in Ectatic Diseases: Refractive Surgery Implications

BACKGROUND

Ectasia development occurs due to a chronic corneal biomechanical decompensation or weakness, resulting in stromal thinning and corneal protrusion. This leads to corneal steepening, increase in astigmatism, and irregularity. In corneal refractive surgery, the detection of mild forms of ectasia pre-operatively is essential to avoid post-operative progressive ectasia, which also depends on the impact of the procedure on the cornea.

METHOD

The advent of 3D tomography is proven as a significant advancement to further characterize corneal shape beyond front surface topography, which is still relevant. While screening tests for ectasia had been limited to corneal shape (geometry) assessment, clinical biomechanical assessment has been possible since the introduction of the Ocular Response Analyzer (Reichert Ophthalmic Instruments, Buffalo, USA) in 2005 and the Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany) in 2010. Direct clinical biomechanical evaluation is recognized as paramount, especially in detection of mild ectatic cases and characterization of the susceptibility for ectasia progression for any cornea.

CONCLUSIONS

The purpose of this review is to describe the current state of clinical evaluation of corneal biomechanics, focusing on the most recent advances of commercially available instruments and also on future developments, such as Brillouin microscopy.

Corneal biomechanics - a review

PURPOSE

In recent years, the interest in corneal biomechanics has strongly increased. The material properties of the cornea determine its shape and therefore play an important role in corneal ectasia and related pathologies. This review addresses the molecular origin of biomechanical properties, models for their description, methods for their characterisation, techniques for their modification, and computational simulation approaches.

RECENT FINDINGS

Recent research has focused on developing non-contact techniques to measure the biomechanical properties in vivo, on determining structural and molecular abnormalities in pathological corneas, on developing and optimising techniques to reinforce the corneal tissue and on the computational simulation of surgical interventions.

SUMMARY

A better understanding of corneal biomechanics will help to improve current refractive surgeries, allow an earlier diagnosis of ectatic disorders and a better quantification of treatments aiming at reinforcing the corneal tissue.

Second-generation corneal deformation signal waveform analysis in normal, forme fruste keratoconic, and manifest keratoconic corneas after statistical correction for potentially confounding factors

PURPOSE

To evaluate the difference in corneal biomechanical waveform parameters between manifest keratoconus, forme fruste keratoconus, and healthy eyes with a second-generation biomechanical waveform analyzer (Ocular Response Analyzer 2).

SETTING

Jules Stein Eye Institute, University of California, Los Angeles, California, USA.

DESIGN

Retrospective chart review.

METHODS

The biomechanical waveform analyzer was used to obtain corneal hysteresis (CH), corneal resistance factor (CRF), and 37 biomechanical waveform parameters in manifest keratoconus eyes, forme fruste keratoconus eyes, and healthy eyes. Useful distinguishing parameters were found using t tests and a multivariable logistic regression model with stepwise variable selection. Potential confounders were controlled for.

RESULTS

The study included 68 manifest keratoconus eyes, 64 forme fruste keratoconus eyes, and 249 healthy eyes. There was a statistical difference in the mean CRF between the normal group (10.2 mm Hg ± 1.7 [SD]) and keratoconus group (6.3 ± 1.9 mm Hg) (P = .003), and between the normal group and the forme fruste keratoconus group (7.8 ± 1.4 mm Hg) (P < .0001). There was no statistical difference in the mean CH between the normal group and the keratoconus group or the forme fruste keratoconus group. The CRF, height of peak 1 (P1) (P = .001), downslope of P1 (dslope1) (P = .027), upslope of peak 2 (P2) (P = .004), and downslope of P2 (P = .006) distinguished the normal group from the keratoconus groups. The CRF, downslope of P2 derived from upper 50% of applanation peak (P = .035), dslope1 (P = .014), and upslope of P1 (P = .008) distinguished the normal group from the forme fruste keratoconus group.

CONCLUSION

Differences in multiple biomechanical waveform parameters can differentiate between healthy and diseased conditions and might improve early diagnosis of keratoconus and forme fruste keratoconus.

FINANCIAL DISCLOSURE

No author has a financial or proprietary interest in any material or method mentioned.

Consideration of corneal biomechanics in the diagnosis and management of keratoconus: is it important?

Keratoconus is a bilateral, non-inflammatory, degenerative corneal disease. The occurrence and development of keratoconus is associated with corneal thinning and conical protrusion, which causes irregular astigmatism. With the disruption of the collagen organization, the cornea loses its shape and function resulting in progressive visual degradation. Currently, corneal topography is the most important tool for the diagnosis of keratoconus, which may lead to false negatives among the patient population in the subclinical phase. However, it is now hypothesised that biomechanical destabilisation of the cornea may take place ahead of the topographic evidence of keratoconus, hence possibly assisting with disease diagnosis and management. This article provides a review of the definition, diagnosis, and management strategies for keratoconus based on corneal biomechanics.

Comparison of Corneal Biomechanical Characteristics After Surface Ablation Refractive Surgery and Novel Lamellar Refractive Surgery

PURPOSE

To investigate and compare corneal biomechanical changes in the form of corneal hysteresis (CH) and corneal resistance factor (CRF) after small-incision lenticule extraction (SMILE) and laser-assisted subepithelial keratectomy (LASEK).

METHODS

In this retrospective observational study, patients who underwent either SMILE (36 eyes, 21 patients) or LASEK (35 eyes, 19 patients) were included. Data were collected preoperatively and at 1 and 3 months postoperatively, which included corneal topography and Ocular Response Analyzer values of CH, CRF, and intraocular pressure (IOP). Differences between both surgical groups and the relationships between variables were evaluated.

RESULTS

CH, CRF, Goldmann IOP, and corneal compensated IOP after surgery were significantly lower than the preoperative values (P < 0.05) in both surgical groups. Lenticule thickness (LT) correlated with ΔCRF (Δ = postoperative - preoperative value) in the SMILE group (r = -0.513, P = 0.001), but the ablation depth (AD) and ΔCRF showed no correlation in the LASEK group (r = -0.297, P = 0.083). In the SMILE group, ΔCRF/LT (-0.036 ± 0.01) and ΔCH/LT (-0.021 ± 0.01) values were significantly lower than ΔCRF/AD (-0.048 ± 0.02) and ΔCH/AD (-0.026 ± 0.02) values in the LASEK group (P < 0.05).

CONCLUSIONS

Both SMILE and LASEK alter corneal biomechanical strength. However, the changes induced by SMILE are more predictable than those induced by LASEK. In terms of per unit tissue removed, SMILE seems to have less effect on corneal biomechanics than LASEK, which may be due to preservation of the stiffer anterior stroma.

Comparison of Diaton transpalpebral tonometer with applanation tonometry in keratoconus

AIM

To investigate the added value of using a Diaton transpalpebral tonometer (DT) to measure IOP in keratoconus. Most type of tonometers use corneal applanation or biomechanical resistance to measure intraocular pressure (IOP); however, these factors can be altered by keratoconus. Specifically, we examined whether DT can detect false-negative low Goldmann applanation tonometry (AT) measurements.

METHODS

Patients with keratoconus were recruited from our tertiary academic treatment center. Measurements included AT and DT (in random order) and Scheimpflug imaging. An age- and gender-matched group of control subjects with no history of corneal disease or glaucoma was also recruited.

RESULTS

In total, 130 eyes from 66 participants were assessed. In the keratoconus group, mean AT was 11.0 ± 2.6, mean DT 11.2±5.5 (P=0.729), and the two measures were correlated significantly (P=0.006, R=0.323). However, a Bland-Altman plot revealed a wide distribution and poor agreement between both measurements. Previous corneal crosslinking, corneal pachymetry, and Krumeich classification had no effect on measured IOP.

CONCLUSION

Measurements obtained using a Diaton tonometer are not affected by corneal biomechanics; however, its poor agreement with Goldmann AT values calls into question the added value of using a Diaton tonometer to measure IOP in keratoconus.

Relationship of Structural Characteristics to Biomechanical Profile in Normal, Keratoconic, and Crosslinked Eyes

PURPOSE

To evaluate the correlation of corneal biomechanical parameters with structural characteristics in normal, keratoconic, and collagen crosslinked eyes.

METHODS

A prospective observational study that included 50 normal, 100 keratoconic, and 25 crosslinked eyes. All eyes were imaged using a Scheimpflug camera and an ocular response analyzer. The main outcome measures analyzed were central corneal thickness (CCT), corneal volume (CV), maximal keratometry (Kmax), corneal hysteresis (CH), and corneal resistance factor (CRF).

RESULTS

Significant differences were noted among all 3 groups of eyes for CCT, CV, Kmax, CH, and CRF values (P < 0.05 by analysis of variance). CH and CRF correlated negatively (CH, r = -0.40; CRF, r = -0.44; both P < 0.0001) with the Pentacam topographic keratoconus classification. Both CH and CRF correlated positively with CCT and CV for the normal, keratoconic, and crosslinked eyes. In contrast, significant negative correlations were observed between CH, CRF, and Kmax in the keratoconic eyes (CH, r = -0.43; CRF, r = -0.53; both P < 0.0001), whereas no association was noted for the normal and crosslinked eyes.

CONCLUSIONS

CH and CRF are influenced by the corneal structure, with higher values noted in corneas with greater thickness and volume. Corneal biomechanical parameters progressively decrease as the severity of keratoconus increases. After collagen crosslinking, the relationship of the corneal curvature to the biomechanical profile is similar to normal eyes.

Ocular response analyzer parameters in healthy, keratoconus suspect and manifest keratoconus eyes

Background:

To evaluate and compare corneal biomechanical indices and their specificity among keratoconus (KC), keratoconus suspect (KCS), and normal eyes (NL) before and after controlling potential confounders.

Materials and Methods:

A total of 160 eyes in three groups were included prospectively: NL, KC, and KCS groups based on clinical examination and topography. Corneal hysteresis (CH) and corneal resistance factor (CRF) were measured by the ocular response analyzer. CH and CRF were compared between the three groups by analysis of variances test.

Results:

The three groups consisted of 80 NL, 48 KC, and 32 KCS eyes. The mean CH measured was 10.4 ± 1.25, 7.83 ± 1.28 and 10.17 ± 1.80 mm Hg in NL, KC and KCS eyes, respectively. The mean CRF was 10.23 ± 1.75, 6.5 ± 1.63 and 9.98 ± 2.00 mm Hg in NL, KC and KCS eyes, respectively. Mean CH and CRF were significantly different between the NL and KC (P < 0.05); however after controlling for central corneal thickness and sex; there was no significant difference between NL and KCS (P > 0.05).

Conclusion:

CH and CRF can be helpful in differentiating KC from NL eyes; however, they are not valuable for detecting KCS that is the main concern for refractive surgery. Future studies focusing on more accurate tests for identifying KCS, using a consistent grading scale for defining KC and KCS are still warranted.

Protective Effects of Soluble Collagen during Ultraviolet-A Crosslinking on Enzyme-Mediated Corneal Ectatic Models

Collagen crosslinking is a relatively new treatment for structural disorders of corneal ectasia, such as keratoconus. However, there is a lack of animal models of keratoconus, which has been an obstacle for carefully analyzing the mechanisms of crosslinking and evaluating new therapies. In this study, we treated rabbit eyes with collagenase and chondroitinase enzymes to generate ex vivo corneal ectatic models that simulate the structural disorder of keratoconus. The models were then used to evaluate the protective effect of soluble collagen in the UVA crosslinking system. After enzyme treatment, the eyes were exposed to riboflavin/UVA crosslinking with and without soluble type I collagen. Corneal morphology, collagen ultrastructure, and thermal stability were evaluated before and after crosslinking. Enzyme treatments resulted in corneal curvature changes, collagen ultrastructural damage, decreased swelling resistance and thermal stability, which are similar to what is observed in keratoconus eyes. UVA crosslinking restored swelling resistance and thermal stability, but ultrastructural damage were found in the crosslinked ectatic corneas. Adding soluble collagen during crosslinking provided ultrastructural protection and further enhanced the swelling resistance. Therefore, UVA crosslinking on the ectatic model mimicked typical clinical treatment for keratoconus, suggesting that this model replicates aspects of human keratoconus and could be used for investigating experimental therapies and treatments prior to translation.

Topographic and biomechanical evaluation of corneas in patients with ocular rosacea

PURPOSE

To compare the topographic and biomechanical properties of corneas in the eyes of patients with ocular rosacea (OR) with those of healthy individuals.

METHODS

Thirty-four healthy individuals (control group) and 34 patients with OR (study group) were evaluated in this study. Topographic measurements including keratometry values, irregularity, and surface asymmetry index in the right eye of each participant were obtained using a Scheimpflug camera with a Placido disc topographer (Sirius). Corneal hysteresis (CH), corneal resistance factor (CRF), corneal-compensated intraocular pressure (IOP), and Goldmann-related IOP were measured using the Reichert Ocular Response Analyzer. Central corneal thickness was also measured using ultrasonic pachymetry and the Sirius corneal topography system.

RESULTS

Topographic parameters were not significantly different between the groups (P > 0.05). Mean CH and CRF were significantly lower in patients with OR (P = 0.003 and 0.001, respectively). Central corneal thickness was significantly lower in patients with OR compared with healthy controls (P < 0.001). Mean Goldmann-related IOP and corneal-compensated IOP were not significantly different between the groups (P = 0.09 and 0.13, respectively).

CONCLUSIONS

This study demonstrated that although the eyes of patients with OR had corneal topographic findings similar to those of healthy controls, corneal biomechanical measurements (CH and CRF) were significantly lower in patients with OR. These results need to be considered when planning corneal refractive surgery in patients with OR.

Air-pulse corneal applanation signal curve parameters for characterization of astigmatic corneas

PURPOSE

The aim of this study was to test the 42 parameters of the ocular response analyzer for distinguishing between the biomechanical properties of emmetropic eyes with normal topography and eyes with moderate-to-high with-the-rule astigmatism (WTA) and against-the-rule astigmatism (ATA) that have symmetric bowtie topography.

METHODS

This retrospective case series study included 37 patients (37 studied eyes) with WTA astigmatism and 35 patients (35 studied eyes) with ATA astigmatism. The control group consisted of 70 patients with emmetropia (70 studied eyes) with normal topography. We first tested correlations of the parameters that describe the applanation curve during ocular response analyzer measurements with the maximum keratometry values and the corneal thickness in all 3 groups. We then evaluated the significant parameters among them in search of any group differences in the biomechanical properties of the cornea.

RESULTS

Fifteen parameters correlated with Kmax reading values or corneal thickness values. The correlation coefficients (r) were low. The best correlated parameters were p1area, p2area, h1, dive1, p2area1, h11, h2, and h21. The ATA group had the highest number of parameters (n = 6) with significant differences compared with the control group. Only p2area was predictive for ATA. In contrast, the WTA group had only 1 parameter (p2area1) that was found to be significantly different compared with the control group.

CONCLUSIONS

Some of the new waveform parameters can distinguish between patients with ATA and WTA and normal topography patterns and may delineate the differences in biomechanical properties between these groups that may predict the risk of corneal ectasia after laser in situ keratomileusis.

Corneal resistance factor and corneal hysteresis in a 6- to 18-year-old population

PURPOSE

To determine the distribution and normal range of the corneal resistance factor (CRF) and corneal hysteresis (CH) in the 6- to 18-year age range and their relationship with biometric components.

SETTING

Dezful, Iran.

DESIGN

Cross-sectional study.

METHODS

This study of Dezful school children used a multistage, stratified, cluster approach sampling. All students had examinations for biometry, noncycloplegic refraction, and corneal biomechanical properties; the examinations were performed in the same order in all cases.

RESULTS

Of the 864 selected students, 683 participated in the study. The mean CRF and CH was 11.74 mm Hg±1.77 (SD) (95% confidence interval [CI], 11.58-11.89) and 11.49±1.91 mm Hg (95% CI, 11.33-11.65), respectively. In a linear multiple regression model, the CRF significantly correlated with female sex (β coefficient=0.488, P=.013), central corneal thickness (CCT) (β coefficient=.034, P=.001), and keratometry (β-coefficient=0.157, P=.003) and CH significantly correlated with CCT (β coefficient=0.025, P<.001), axial length (β coefficient=-0.303, P=.011), and keratometry (β coefficient=0.11, P=.043). Each year increase in age was associated with a 42-unit decrease in the peak 1 area (P=.003).

CONCLUSIONS

The distribution of CRF and CH in an Iranian population was symmetrical and bell shaped. However, the CRF did not have a normal distribution. The mean CRF and CH were higher than those reported in almost all previous studies.

FINANCIAL DISCLOSURE

No author has a financial or proprietary interest in any material or method mentioned.

Impaired corneal biomechanical properties and the prevalence of keratoconus in mitral valve prolapse

Objective. To investigate the biomechanical characteristics of the cornea in patients with mitral valve prolapse (MVP) and the prevalence of keratoconus (KC) in MVP. Materials and Methods. Fifty-two patients with MVP, 39 patients with KC, and 45 control individuals were recruited in this study. All the participants underwent ophthalmologic examination, corneal analysis with the Sirius system (CSO), and the corneal biomechanical evaluation with Reichert ocular response analyzer (ORA). Results. KC was found in six eyes of four patients (5.7%) and suspect KC in eight eyes of five patients (7.7%) in the MVP group. KC was found in one eye of one patient (1.1%) in the control group (P = 0.035). A significant difference occurred in the mean CH and CRF between the MVP and control groups (P = 0.006 and P = 0.009, resp.). All corneal biomechanical and topographical parameters except IOPcc were significantly different between the KC-MVP groups (P < 0.05). Conclusions. KC prevalence is higher than control individuals in MVP patients and the biomechanical properties of the cornea are altered in patients with MVP. These findings should be considered when the MVP patients are evaluated before refractive surgery.

Corneal biomechanical properties in different ocular conditions and new measurement techniques

Several refractive and therapeutic treatments as well as several ocular or systemic diseases might induce changes in the mechanical resistance of the cornea. Furthermore, intraocular pressure measurement, one of the most used clinical tools, is also highly dependent on this characteristic. Corneal biomechanical properties can be measured now in the clinical setting with different instruments. In the present work, we review the potential role of the biomechanical properties of the cornea in different fields of ophthalmology and visual science in light of the definitions of the fundamental properties of matter and the results obtained from the different instruments available. The body of literature published so far provides an insight into how the corneal mechanical properties change in different sight-threatening ocular conditions and after different surgical procedures. The future in this field is very promising with several new technologies being applied to the analysis of the corneal biomechanical properties.

Relationship Between Corneal Hysteresis and Corneal Resistance Factor with Other Ocular Parameters

PURPOSE

To evaluate the relationship between corneal hysteresis (CH) and corneal resistance factor (CRF) with age, central corneal thickness (CCT), corneal curvature (KM), corneal volume (CV), and refractive error in naïve eyes.

METHODS

105 healthy subjects (58 male and 47 female) were included in this study. The ages ranged from 19 to 82 years (mean 43.1 ± 15.4 years) and refraction between -11 D and +6 D (mean -0.79 ± 2.95 D). CH and CRF obtained with the Ocular Response Analyzer (ORA) were correlated with age, refractive error, Goldmann Applanation Tonometry (GAT), and with CCT, KM, CV obtained with the Pentacam, and with Corneal-Compensated Intraocular Pressure (IOPcc) and Goldmann-correlated intraocular pressure measurement (IOPg) obtained with ORA. A multivariable mixed effect model was used to evaluate associations among these parameters.

RESULTS

CH ranged from 6.9 to 14.6 mmHg (mean 10.26 ± 1.49 mmHg); CRF ranged from 5.8 to 17 mmHg (mean 10.38 ± 1.64 mmHg). Multivariate analysis showed a statistically significant correlation between CH with CCT (p < 0.001), and KM (p < 0.001), and between CRF with CCT (p < 0.001) and GAT (p < 0.001).

CONCLUSIONS

Our findings support the hypothesis that CH and CRF are related to the corneal shape and thickness, and show a decrease of CH with age.

Corneal topographic and tomographic analysis of fellow eyes in unilateral keratoconus patients using Pentacam

PURPOSE

To evaluate topographic and tomographic changes in fellow eyes in unilateral keratoconus (KCN) patients by comparing them with normal eyes.

DESIGN

Retrospective comparative case series.

METHODS

Fourteen eyes of 14 patients with unilateral KCN and 34 eyes of 34 refractive surgery candidates were divided into 3 diagnostic groups using a Pentacam rotating Scheimpflug camera: advanced KCN eyes of unilateral KCN (KCN group, 14 eyes), normal fellow eyes of unilateral KCN (fellow eye group, 14 eyes), and refractive surgery candidates (normal group, 34 eyes). Topographic and tomographic parameters, which were obtained from Pentacam using sagittal curvature, elevation, and corneal thickness maps, were compared among the 3 groups. Receiver operating characteristic (ROC) curves were used to identify cutoff points in discriminating between fellow and normal eyes.

RESULTS

Keratometric asymmetry, topometric indices, and elevation differences (maximum - minimum) on both the anterior and posterior surfaces were statistically different (P < .05). On ROC curve analysis, keratometric asymmetry and topometric index were best at discriminating fellow eyes from normal, followed by elevation differences (maximum - minimum) on the posterior and anterior cornea surface.

CONCLUSIONS

Fellow eyes in unilateral KCN showed differences in several parameters that were not detectable with the Pentacam detection program, when compared with normal. However, each single parameter alone is not sufficient to detect early changes; thus, elevation indices as well as indices of anterior curvature should be considered together.

Keratoconus: current perspectives

Keratoconus is characterized by progressive corneal protrusion and thinning, leading to irregular astigmatism and impairment in visual function. The etiology and pathogenesis of the condition are not fully understood. However, significant strides have been made in early clinical detection of the disease, as well as towards providing optimal optical and surgical correction for improving the quality of vision in affected patients. The past two decades, in particular, have seen exciting new developments promising to alter the natural history of keratoconus in a favorable way for the first time. This comprehensive review focuses on analyzing the role of advanced imaging techniques in the diagnosis and treatment of keratoconus and evaluating the evidence supporting or refuting the efficacy of therapeutic advances for keratoconus, such as newer contact lens designs, collagen crosslinking, deep anterior lamellar keratoplasty, intracorneal ring segments, photorefractive keratectomy, and phakic intraocular lenses.

The biomechanical properties of the cornea and anterior segment parameters

BACKGROUND

To investigate the biomechanical properties of the cornea measured with the Ocular Response Analyzer (ORA) and their association with the anterior segment parameters representing the geometric dimensions including the corneal volume and anterior chamber volume.

METHODS

A retrospective review of 1020 patients who visited the BGN Eye Clinic was done. The mean radius of the corneal curvature, corneal astigmatism, corneal volume, anterior chamber depth, and anterior chamber volume were measured with an anterior segment tomographer. The central corneal thickness (CCT) was measured with an ultrasonic pachymeter. The corneal diameter was measured with an Orbscan as White to White. Cornea hysteresis (CH), corneal resistance factor (CRF), Goldmann correlated intraocular pressure (IOPg), and cornea-compensated IOP (IOPcc) were measured with an ORA. Multiple linear regression models were constructed with CH and CRF as the dependent variables and age, gender, and the anterior segment parameters as the covariates.

RESULTS

958 eyes from 958 patients (mean age 26.7 years; male 43.4%) were included in this study after excluding some eyes according to the exclusion criteria. The mean CH and CRF were 10.1 and 9.9 mmHg, respectively. The mean IOPg and IOPcc were 14.8 and 15.8 mmHg. The multivariate analysis showed that CH was negatively associated with the mean radius of the cornea curvature (regression coefficient = -0.481, p = 0.023) and positively associated with CCT (regression coefficient = 0.015, p < 0.001) and corneal volume (regression coefficient =0.059, p = 0.014). The association between CH and the corneal diameter, anterior chamber depth, and anterior chamber volume were not statistically significant. The evaluation of CRF showed that CRF was negatively associated with the mean radius of the cornea curvature (regression coefficient = -0.540, p = 0.013), and positively associated with CCT (β = 0.026, p < 0.001). The association between CRF and the corneal diameter, corneal volume, anterior chamber depth, and anterior chamber volume were not statistically significant.

CONCLUSION

The CH was shown to be positively associated with the corneal volume and the association between CH and the anterior chamber volume were not significant. The associations of CRF with the corneal volume or anterior chamber volume were not significant.

Laser in situ keratomileusis in 2012: a review

Laser in situ keratomileusis (LASIK) is a safe and effective treatment for refractive error. A combination of technological advances and increasing surgeon experience has served to further refine refractive outcomes and reduce complication rates. In this article, we review LASIK as it stands in late 2012: the procedure, indications, technology, complications and refractive outcomes.

Relative importance of factors affecting corneal hysteresis measurement

PURPOSE

To evaluate the relative influences of several demographic, ocular, and systemic parameters on corneal hysteresis (CH).

METHODS

This is a prospective, observational, cross-sectional study using subjects recruited from consecutive Albuquerque VAMC eye clinic patients. We classified eligible subjects as primary open-angle glaucoma (POAG), ocular hypertension, glaucoma suspect, or normal. We used the Ocular Response Analyzer, Pascal Dynamic Contour Tonometer, and Goldmann applanation tonometer to obtain intraocular pressure (IOP), CH, corneal resistance factor, and ocular pulse amplitude values. We also obtained corneal curvature, central corneal thickness (CCT), axial length, retinal nerve fiber layer thickness, clinical cup/disc ratio (CDR) estimates, and standard automated perimetry metrics (mean defect, pattern standard deviation). We gathered glycosylated hemoglobin (A1C) data through chart review. Multivariate regression analyses were used to determine independent relationships between CH and the other parameters.

RESULTS

Three hundred seventeen eyes in 317 subjects were studied (116 POAG, 87 ocular hypertension, 47 glaucoma suspect, and 67 normal). In univariate regression analysis, CH varied directly with CCT (β = 0.39, p < 0.001), corneal curvature (β = 0.16, p = 0.01), corneal resistance factor (β = 0.57, p < 0.001), A1C (β = 0.15, p = 0.01), mean defect (β = 0.29, p < 0.001), and retinal nerve fiber layer (β = 0.31, p < 0.001). Factors inversely related to CH were age (β = -0.22, p < 0.001), IOP (β = -0.29, p < 0.001), ocular pulse amplitude (β = -0.11, p = 0.04), CDR (β = -0.34, p < 0.001), and pattern standard deviation (β = -0.29, p < 0.001). CH was lower in POAG compared with the other diagnostic groups. In multivariate analysis, CH was independently associated with age, IOP, CCT, A1C, glaucoma diagnosis, and CDR. Of these factors, CCT and IOP demonstrated twice as much influence on CH compared with the other four factors.

CONCLUSIONS

Although this study identified six separate variables that independently influence CH values, the overall r value indicates that these variables together only explain 40% of CH variability. These results suggest that other significant sources of variability exist and deserve investigation.