Purpose. To compare the corneal biomechanical properties of keratoconic patients and age-matched controls using corneal visualization Scheimpflug technology (Corvis ST).Methods. Sixty keratoconic eyes from 47 keratoconus patients and 60 normal eyes from 60 controls were enrolled in this prospective study. Tomography and biomechanical parameters of all eyes were obtained with the Pentacam and Corvis ST, respectively. Intraocular pressure was measured using a Goldmann applanation tonometer.Results.The tomography and biomechanical parameters of the keratoconic corneas were significantly different from those of the normal corneas except for the anterior chamber angle, first applanation length, the highest concavity time, and peak distance. The deformation amplitude was the best predictive parameter (area under the curve: 0.882), with a sensitivity of 81.7%, although there was a significant overlap between keratoconic and normal corneas that ranged from 1.0 to 1.4 mm. In both the keratoconus and control groups, the deformation amplitude was negatively correlated with intraocular pressure, central corneal thickness, and corneal volume at 3 and 5 mm.Conclusions. Corvis ST offers an alternative method for measuring corneal biomechanical properties. The possibility of classifying keratoconus based on deformation amplitude deserves clinical attention.

Corneal biomechanical properties are important for the diagnosis of corneal diseases, individualized design and prognosis of corneal surgery. Clinical available devices such as Ocular Response Analyzer (ORA) and Corneal Visualization Scheimpflug Technology (Corvis ST) can provide corneal biomechanics related parameters, while corneal elastic modulus cannot be extracted directly from them at present. The aim of this study is to suggest a method to determine corneal elastic modulus based on the results of Corvis ST test according to Reissner’s theory on the relation between stress and small displacement in shallow spherical shell. Five rabbits (10 eyes) and 10 healthy humans (20 eyes) were measured with Corvis ST to obtain the normal range of corneal elastic modulus. Results showed Corneal elastic modulus of rabbit was 0.16 MPa to 0.35 MPa, human corneal elastic modulus was 0.16–0.30 MPa. Rabbit corneas were also measured at different intraocular pressures (IOP), and results showed corneal elastic modulus, first applanation time (A1T) and stiffness parameter (SP-A1) were positively correlated with IOP. Deformation amplitude (DA), the second applanations time (A2T), and peak distance (PD) were negatively correlated with IOP. Finite element method was used to simulate the Corvis measurements according to the calculated elastic modulus and the simulated corneal apical displacements were agreement with experimental results in general. The method to determine corneal elastic modulus based on Corvis test according to the relationship between force and displacements of shallow spherical shell is convenient and effective.

Severe dry eye disease causes ocular surface damage, which is highly associated with mitochondrial dysfunction. Mitochondrial transcription factor A (TFAM) is essential for packaging mitochondrial DNA (mtDNA) and is crucial for maintaining mitochondrial function. Herein, we aimed to explore the effect of a decreased TFAM expression on ocular surface damage. Female C57BL/6 mice were induced ocular surface injury by topical administrating benzalkonium chloride (BAC). Immortalized human corneal epithelial cells (HCECs) were stimulated by tert-butyl hydroperoxide (t-BHP) to create oxidative stress damage. HCECs with TFAM knockdown were established. RNA sequencing was employed to analyze the whole-genome expression. Mitochondrial changes were measured by transmission electron microscopy, Seahorse metabolic flux analysis, mitochondrial membrane potential, and mtDNA copy number. TFAM expression and inflammatory cytokines were determined using RT-qPCR, immunohistochemistry, immunofluorescence, and immunoblotting. In both the corneas of BAC-treated mice and t-BHP-induced HCECs, we observed impaired TFAM expression, accompanied by mitochondrial structure and function defects. TFAM downregulation in HCECs suppressed mitochondrial respiratory capacity, reduced mtDNA content, induced mtDNA leakage into the cytoplasm, and led to inflammation. RNA sequencing revealed the absent in melanoma 2 (AIM2) inflammasome was activated in the corneas of BAC-treated mice. The AIM2 inflammasome activation was confirmed in TFAM knockdown HCECs. TFAM knockdown in t-BHP-stimulated HCECs aggravated mitochondrial dysfunction and the AIM2 inflammasome activation, thereby further triggering the secretion of inflammatory factors such as interleukin (IL) -1β and IL-18. TFAM reduction impaired mitochondrial function, activated AIM2 inflammasome and promoted ocular surface inflammation, revealing an underlying molecular mechanism for ocular surface disorders.

Purpose: To explore the feasibility of corneal morphological and biomechanical parameters for keratoconus and forme fruste keratoconus diagnosis. Methods: This case–control study included a total of 517 eyes from 408 keratoconus patients (KC group), 83 eyes from 83 forme fruste keratoconus patients (FFKC group), and 158 eyes from 158 patients with normal corneas (NL group). All subjects underwent routine ophthalmologic examinations. Pentacam and Corneal Visualization Scheimpflug Technology (Corvis ST) were used to obtain corneal morphological and biomechanical parameters. Differences between groups were compared using receiver operating characteristic (ROC) curve analysis. Results: ROC analysis showed that all corneal morphological parameters and most biomechanical parameters distinguished KC from NL, with an area under the curve (AUC) greater than 0.80, of which Belin–Ambrósio enhanced ectasia total deviation index (BAD-D) and tomographic and biomechanical index (TBI) were most efficient. The AUC for distinguishing KC from NL of the BAD-D was 0.989 and the TBI was 0.993, which were not statistically significant (DeLong et al., P= .232). The BAD-D cut-off point of 1.595 provided 95.9% sensitivity for distinguishing KC from NL with 100% specificity. The TBI cut-off point of 0.515 provided 96.7% sensitivity for distinguishing KC from NL with 100% specificity. The ability of other parameters to distinguish KC from NL was lower than that of BAD and TBI. Except for central astigmatism from the anterior corneal surface (AstigF), the AUC that distinguished FFKC from NL was 0.862. The AstigF cut-off point of 4.65 provided 73.5% sensitivity for distinguishing FFKC from NL with 99.3% specificity. Other parameters distinguished FFKC from NL with low efficiency. Among them, the AUC for distinguishing FFKC from NL of the TBI was 0.722, whose cut-off point of 0.273 provided 55.4% sensitivity for distinguishing KC from NL with 79.7% specificity. Conclusion: BAD-D and TBI have the highest efficiency, sensitivity, and specificity for distinguishing KC from NL. Except for AstigF, other corneal morphological and biomechanical parameters have a relatively low ability to distinguish FFKC from NL.

Meibomian gland dysfunction (MGD) is one of the most common diseases observed in clinics and is the leading cause of evaporative dry eye. Today, diagnostics of MGD is not fully automatic yet and is based on a qualitative assessment made by an ophthalmologist. Therefore, an automatic analysis method was developed to assess MGD quantiatively. The analysis made use of 228 images of 57 patients recorded by OCULUS Keratograph® 5 M with a resolution of 1024 × 1360 pixels concern 30 eyes of healthy individuals (14 women and 16 men) and 27 eyes of sick patients (10 women and 17 men). The diagnosis of dry eye was made according to the consensus of DED in China (2013). The presented method of analysis is a new, developed method enabling an automatic, reproducible and quantitative assessment of Meibomian glands. The analysis relates to employing the methods of analysis and image processing. The analysis was conducted in the Matlab environment Version 7.11.0.584, R2010b, Java VM Version: Java 1.6.0_17-b04 with Sun Microsystems Inc. with toolboxes: Statistical, Signal Processing and Image Processing. The presented, new method of analysis of Meibomian glands is fully automatic, does not require operator’s intervention, allows obtaining reproducible results and enables a quantitative assessment of Meibomian glands. Compared to the other known methods, particularly with the method described in literature it allows obtaining better sensitivity (98%) and specificity (100%) results by 2%.