Corneal endothelial morphology and central corneal thickness in type 2 diabetes mellitus patients

Potential applications of artificial intelligence in image analysis in cornea diseases: a review

Artificial intelligence (AI) is an emerging field which could make an intelligent healthcare model a reality and has been garnering traction in the field of medicine, with promising results. There have been recent developments in machine learning and/or deep learning algorithms for applications in ophthalmology-primarily for diabetic retinopathy, and age-related macular degeneration. However, AI research in the field of cornea diseases is relatively new. Algorithms have been described to assist clinicians in diagnosis or detection of cornea conditions such as keratoconus, infectious keratitis and dry eye disease. AI may also be used for segmentation and analysis of cornea imaging or tomography as an adjunctive tool. Despite the potential advantages that these new technologies offer, there are challenges that need to be addressed before they can be integrated into clinical practice. In this review, we aim to summarize current literature and provide an update regarding recent advances in AI technologies pertaining to corneal diseases, and its potential future application, in particular pertaining to image analysis.

Risk Factors for Corneal Endothelial Decompensation after Penetrating Keratoplasty: A Population-Based Cohort Study

(1) Background: Endothelial decompensation is a common complication after penetrating keratopathy (PK), while the risk factors for endothelial decompensation after PK have not been fully elucidated. Consequently, we aim to investigate the possible risk factors for endothelial decompensation after PK. (2) Methods: This retrospective study was conducted using the National Health Insurance Research Database (NHIRD) of Taiwan. The main outcome was the development of endothelial decompensation after PK surgery. The effects of potential risk factors were compared between the patients with endothelial decompensation and the patients without endothelial decompensation via Cox proportional hazard regression, which produced the adjusted hazard ratio (aHR) and a 95% confidence interval (CI). (3) Results: Overall, 54 patients developed endothelial decompensation after PK surgery, with a ratio of 16.12 percent. The pre-existing type 2 diabetes mellitus (T2DM) (aHR: 1.924, 95% CI: 1.257-2.533, p = 0.0095) and history of cataract surgery (aHR: 1.687, 95% CI: 1.328-2.440, p = 0.0026) were correlated with the development of endothelial decompensation. In the subgroup analysis, the correlation between a history of cataract surgery and post-PK endothelial decompensation was more prominent in patients older than 60 years compared to their younger counterparts (p = 0.0038). (4) Conclusions: Pre-existing T2DM and a history of cataract surgery are associated with a higher incidence of post-PK endothelial decompensation.

Effects of fluorescein on corneal endothelial morphology after fundus fluorescein angiography in patients with diabetic macular edema

PURPOSE

To evaluate the effects of fluorescein dye on corneal endothelial morphology (CEM) after fundus fluorescein angiography (FFA) in patients with diabetic macular edema (DME).

METHODS

In this retrospective study, patients were divided into two groups, nonproliferative diabetic retinopathy (Group-1, NPDR) and proliferative diabetic retinopathy (Group-2, PDR). CEM properties including endothelial cell density (ECD), coefficient of variation of cell area (CV), average cell area (AVG), percentage of hexagonal cells (HEX), and central corneal thickness (CCT) were measured before FFA and at week 1 and month 1 after FFA were collected from patients' charts.

RESULTS

The study consisted of 48 patient's 48 eyes in Group-1 and 50 patient's 50 eyes in Group-2. In both groups, the mean ECD, CV, AVG, HEX, and CCT measurements at week 1 and month 1 after FFA did not differ statistically from the mean measurements before FFA (p > 0.05). The mean ECD measurements in Group-1 were higher than that in Group-2 and showed statistically significant differences among the groups (p < 0.01 for all). In the Pearson correlation analysis in Group-1, there was no statistically significant relationship between best-corrected visual acuity (BCVA) and (intraocular pressure) IOP values and ECD, AVG, CV, HEX, and CCT measurements (except central macular thickness [CMT] and HEX) before FFA, at week 1 and month 1 after FFA (p > 0.05). In Group-2 there was no statistically significant relationship between BCVA, IOP, and CMT measurements and ECD, AVG, CV, HEX, and CCT measurements before FFA, at week 1 and month 1 after FFA (p > 0.05).

CONCLUSIONS

There is no significant change in CEM after FFA in patients with NPDR and PDR with DME.

Immune Fingerprint in Diabetes: Ocular Surface and Retinal Inflammation

Diabetes is a prevalent global health issue associated with significant morbidity and mortality. Diabetic retinopathy (DR) is a well-known inflammatory, neurovascular complication of diabetes and a leading cause of preventable blindness in developed countries among working-age adults. However, the ocular surface components of diabetic eyes are also at risk of damage due to uncontrolled diabetes, which is often overlooked. Inflammatory changes in the corneas of diabetic patients indicate that inflammation plays a significant role in diabetic complications, much like in DR. The eye's immune privilege restricts immune and inflammatory responses, and the cornea and retina have a complex network of innate immune cells that maintain immune homeostasis. Nevertheless, low-grade inflammation in diabetes contributes to immune dysregulation. This article aims to provide an overview and discussion of how diabetes affects the ocular immune system's main components, immune-competent cells, and inflammatory mediators. By understanding these effects, potential interventions and treatments may be developed to improve the ocular health of diabetic patients.

Meta-analysis of corneal endothelial changes after phacoemulsification in diabetic and non-diabetic patients

BACKGROUND

Currently, there is still controversy about the differential changes in corneal endothelium function and morphology after phacoemulsification between Diabetes Mellitus (DM) and non-Diabetes Mellitus (non-DM) patients. In this study, we aimed to evaluate the influence of phacoemulsification on the corneal endothelium in DM and non-DM patients.

METHODS

Databases of PubMed, Embase, Web of Science, and the Cochrane Library were searched for studies published between January 1, 2011 and December 25, 2021. The weighted mean difference and 95% confidence interval were used to estimate the outcomes of statistical analyses performed.

RESULTS

Thirteen studies involving 1744 eyes were included in this meta-analysis. No significant difference was observed in the central corneal thickness (CCT), endothelial cell density (ECD), coefficients of variation (CV), or hexagonal cell percentage (HCP) between the DM and non-DM groups (CCT: P = 0.91; ECD: P = 0.07; CV: P = 0.06; HCP: P = 0.09) preoperatively. The CCT was significantly thicker in the DM group at 1 month (P = 0.003) and 3 months (P = 0.0009) postoperatively, and there was no significant difference at 6 months postoperatively (P = 0.26) than non-DM group. The CV was significantly higher and HCP was significantly lower in the DM group at 1 month (CV:P < 0.0001, HCP: P = 0.002), with no significant difference at 3 months (CV: P = 0.09, HCP: P = 0.36) and 6 months (CV: P = 0.32, HCP: P = 0.36) postoperatively than non-DM group. DM patients had lower ECD than non-DM patients at all postoperative time points (1 month, 3 months: P < 0.00001, 6 months: P < 0.0001).

CONCLUSIONS

The influence of phacoemulsification on corneal endothelial damage is greater in diabetic patients. Moreover, the recovery of corneal endothelial function and morphology is delayed in these patients. Clinicians should be more attentive to the corneal health of DM patients when considering phacoemulsification.

The network structure of the corneal endothelium

A generic network model is applied to study the structure of the mammalian corneal endothelium. The model has been shown to reproduce the network properties of a wide range of systems, from low-dimensional inorganic glasses to colloidal nanoparticles deposited on a surface. Available extensive experimental microscopy results are analyzed and combined to highlight the behavior of two key metrics, the fraction of hexagonal rings (p₆) and the coefficient of variation of the area. Their behavior is analyzed as a function of patient age, the onset of diabetes, and contact lens wearing status. Wearing contact lenses for ∼10 years is shown to change the endothelium structure by the equivalent of ∼30 years contact lens-free. Model network configurations are obtained using a Monte Carlo bond-switching algorithm, with the resulting topologies controlled by two potential model parameters (the bond and angular force constants) and the Monte Carlo temperature. The effect of systematically varying these parameters is investigated. In addition, the effect of constraining the ring size distribution is investigated. The networks generated with relatively weak bond force constants are shown to correlate best with the experimental information. The importance of extracting the full ring size distribution (rather than simply the fraction of hexagons) is discussed.

Corneal endothelial cell morphology and optical coherence tomography findings in children with type 1 diabetes mellitus

Purpose

To evaluate central macular thickness, retinal nerve fibre layer thickness, corneal endothelial cell density and central corneal thickness in children with Type 1 Diabetes Mellitus (DM).

Methods

Thirty children with Type 1 DM and 30 age-matched children as controls were examined. Central macular thickness (CMT) and four quadrants of retinal nerve fibre layer thickness (RNFLT) were measured by optical coherence tomography (OCT), while endothelial cell density (ECD), coefficient of variation in cell size (CV), hexagonality (HEX) and central corneal thickness (CCT) were measured by noncontact specular microscopy.

Results

The mean ECD was 2810.77  ±  273.47 cells/mm2 and the mean hexagonality ratio was 49.77  ±  13.2 both were significantly lower (p < 0.001, p  =  0.037 respectively) in the diabetic group compared to the control group. The mean CV was 37.6  ±  7.27, it was significantly higher (p  =  0.024) in the diabetic group than the control group. The mean corneal thickness was greater in the DM group than the controls, but the difference was not significant (p  =  0.176). There were no significant differences in CMT or RNFLT between the two groups. There was a negative correlation between the HbA1c levels and the thickness of the superior quadrants of RNFL (r  =  -0.406, p  =  0.026). The duration of diabetes had no significant correlations with the corneal and retinal parameters.

Conclusion

The diabetic children had changes in corneal endothelial morphology and there was a negative correlation between HbA1c levels and superior quadrant of RNFLT.