Association between optic nerve head morphology in open-angle glaucoma and corneal biomechanical parameters measured with Corvis ST

Corneal Biomechanical Properties Demonstrate Anisotropy and Correlate With Axial Length in Myopic Eyes

Purpose

The purpose of this study was to investigate the ex vivo and in vivo biomechanical characteristic of cornea in myopic eyes.

Methods

Fifty-one corneal stromal lenticules were obtained from myopic eyes during the SMILE procedure and were tested by a biaxial tensile system within 24 hours postoperatively. The material properties of the lenticules were described using stress-strain curves and were compared among axial length (AL) <26 mm and AL ≥ 26 mm group. Pre-operative stress-strain index (SSI) parameters were used to evaluate the biomechanical properties of the cornea in vivo.

Results

Compared with AL < 26 mm, the tangent modulus significantly decreased in horizontal and vertical directions when AL ≥ 26 mm (P < 0.05); SSI also significantly decreased when AL ≥ 26 mm (P < 0.05). Anisotropic parameter is positively correlated with AL (r = 0.307, P < 0.05). Compared with AL < 26 mm, anisotropic parameter significantly increased when AL ≥ 26 mm (P < 0.05). SSI was negatively correlated with AL (r = -0.380, P < 0.05) in the AL < 26 mm group but not in the AL ≥ 26 mm group (P > 0.05). Compared with 26 mm ≤ AL < 27 mm group, the tangent modulus significantly decreased in the horizontal direction (P < 0.05) but not in the vertical direction when 27 mm ≤ AL < 28 mm (P > 0.05).

Conclusions

The biomechanical properties of cornea decreased with the increase of AL. Tangent modulus significantly decreased in the horizontal direction compared with vertical direction. AL should be taken into account during calculation of corneal biomechanical parameters in order to improve validity.

Efficacy of corneal shape index in the evaluation of ocular hypertension, primary open-angle glaucoma and exfoliative glaucoma

Purpose:

The aim of the present study is to calculate Concavity Shape Index (CSI) in patients with POAG and exfoliative glaucoma (XFG) and correlate CSI with the severity of glaucoma, comparing to control and ocular hypertension (OHT) patients.

Methods:

This was a cross‑sectional study with 146 eyes/146 subjects: 37 healthy eyes, 23 eyes with OHT and 86 glaucoma eyes (70 with POAG, 16 with XFG). The severity of glaucoma was scored with the Glaucoma Staging System 2 (GSS2). Corvis ST® was used to calculate CSI.

Results:

Central corneal thickness (CCT) was significantly thinner in POAG (526 ± 40.0 µm) and XFG (520 ± 38.2 µm) than control group (553 ± 28.8 µm). CSI had no significant differences between the groups. XFG had a higher mean of GSS 2 (2.42 ± 1.38) than POAG (1.87 ± 1.55) and OHT (1.87 ± 1.55). OHT had a significantly less deformable cornea than: control (higher A1 length, lower A1 velocity, higher A2 velocity), POAG (higher A1 length, lower A1 velocity, lower deflection amplitude at highest concavity), and XFG group (lower A1 velocity, lower deflection amplitude at highest concavity), which was independent of age and CCT. No significant correlation was found between GSS 2 and CSI.

Discussion:

OHT patients had stiffer corneas (less deformed by the air puff) when compared to control, POAG or XFG patients. A less deformable cornea could potentially be related to a more resistant LC/peripapillary sclera. As such, this would result in a lesser optic nerve susceptibility to IOP damage.

The Effect of Axial Length Elongation on Corneal Biomechanical Property

Background: To investigate the correlation between the corneal biomechanical parameter stress-strain index (SSI) and axial length (AL) in moderately elongated eye (MEE) and severely elongated eye (SEE).

Methods: This study included 117 eyes from 117 participants. Among them, 59 (50.4%) had MEE (AL<26 mm) and 58 (49.6%) had SEE (AL≥26 mm). AL was measured using Lenstar LS-900, and central corneal thickness (CCT) and anterior chamber volume (ACV) were measured using Pentacam. SSI was measured via corneal visualisation Scheimpflug technology (Corvis ST). Kolmogorov-Smirnov test, Student’s t-test, and Pearson and partial correlation analyses were used for statistical analyses.

Results: The mean (±SD) SSI was 1.08 ± 0.15 in the MEE group and 0.92 ± 0.13 in the SEE group (p < 0.01). SSI was positively correlated with age (MEE: r = 0.326, p < 0.05; SEE: r = 0.298, p < 0.05) in both groups; it was negatively correlated with AL (r = −0.476, p < 0.001) in the MEE group but not in the SEE group (p > 0.05). CCT was negatively correlated with AL (r = −0.289, p < 0.05) and ACV positively correlated with AL (r = 0.444, p < 0.001) in the MEE group. Neither CCT nor ACV was correlated with AL (p > 0.05) in the SEE group.

Conclusion: Corneal biomechanical parameter SSI, which represents the stiffness of corneal tissue, was lower in the SEE group than in the MEE group. When analyzed separately, SSI was negatively correlated with AL in the MEE group, but not in the SEE group, which may provide insight into different ocular growth patterns between lower myopia and higher myopia.

Association between visual field damage and corneal structural parameters

The main goal of this study is to identify the association between corneal shape, elevation, and thickness parameters and visual field damage using machine learning. A total of 676 eyes from 568 patients from the Jichi Medical University in Japan were included in this study. Corneal topography, pachymetry, and elevation images were obtained using anterior segment optical coherence tomography (OCT) and visual field tests were collected using standard automated perimetry with 24-2 Swedish Interactive Threshold Algorithm. The association between corneal structural parameters and visual field damage was investigated using machine learning and evaluated through tenfold cross-validation of the area under the receiver operating characteristic curves (AUC). The average mean deviation was − 8.0 dB and the average central corneal thickness (CCT) was 513.1 µm. Using ensemble machine learning bagged trees classifiers, we detected visual field abnormality from corneal parameters with an AUC of 0.83. Using a tree-based machine learning classifier, we detected four visual field severity levels from corneal parameters with an AUC of 0.74. Although CCT and corneal hysteresis have long been accepted as predictors of glaucoma development and future visual field loss, corneal shape and elevation parameters may also predict glaucoma-induced visual functional loss.