Screening of sensitive in vivo characteristics for early keratoconus diagnosis: a multicenter study.

Purpose: To analyze and compare sensitive in vivo characteristics for screening early keratoconus. Methods: This multicenter, case-control study included 712 eyes, after matching for age and biomechanically corrected intraocular pressure, from three clinics in different cities. The keratoconus (n = 288), early keratoconus (n = 91), and normal cornea (n = 333) groups included eyes diagnosed with bilateral keratoconus, fellow eyes with relatively normal topography with unilateral keratoconus, and normal eyes before refractive surgery, respectively. After adjusting for central corneal thickness, differences in vivo characteristics were analyzed among the three groups. The in vivo characteristics were measured by Pentacam and Corvis ST. Fifty-four indices were evaluated to screen for a sensitive index for the detection of early keratoconus. Results: Significant differences were observed in 26 of the 36 corneal biomechanical indeces between the early keratoconus and normal corneas. The area under the receiver operating characteristic curve of tomographic and biomechanical index, Belin/Ambrósio deviation, and Da in differentiating keratoconus from normal cornea was 1.000. Among the top five indeces of the area under the receiver operating characteristic curve for detecting early keratoconus, the corneal biomechanical-related index accounted for 80% (4/5), including A1 dArc length, highest concavity radius, A2 time, and tomographic and biomechanical index, of which the area under the receiver operating characteristic curve of A1 dArc length was 0.901. Conclusion: A1 dArc length and several corneal biomechanical indices are highly sensitive for the detection of early keratoconus, even in the absence of topographic abnormalities. Ophthalmologists should focus on the clinical application of corneal biomechanics and combine corneal tomography for the timely and accurate detection of early keratoconus.

Relationship between postoperative residual refractive error and preoperative corneal stiffness in small-incision lenticule extraction.

PURPOSE: To explore the relationship between postoperative residual refractive error and preoperative corneal stiffness after small-incision lenticule extraction (SMILE). SETTING: Hospital clinic. DESIGN: Retrospective cohort study. METHODS: Corneal stiffness was evaluated using the stress-strain index (SSI). Associations between postoperative spherical equivalent (SE) and corneal stiffness were determined using longitudinal regression analysis after adjustment for sex, age, preoperative SE, and other variables. The cohort was divided into halves to compare risk ratios for residual refraction in corneas with different SSI values. Low SSI values were defined as having less-stiff corneas and others as having stiffer corneas. RESULTS: 287 patients (287 eyes) were included. Greater undercorrection was found in less-stiff corneas across all follow-up timepoints (less-stiff corneas: 1 day: -0.36 ± 0.45 diopters [D], 1 month: -0.22 ± 0.36 D, and 3 months: -0.13 ± 0.15 D; stiffer corneas: -0.22 ± 0.37 D, -0.14 ± 0.35 D, and -0.05 ± 0.11 D, respectively). Postoperative refraction exhibited a mean 0.05 D undercorrection for every 0.1-unit decrease in the SSI after adjustment for variables. The SSI accounted for nearly 10% of the variance in refractive outcomes. Less-stiff corneas increased the risk ratio of postoperative absolute SE >0 D and ≥0.25 D by 2.242 (95% CI, 1.334-3.768) and 3.023 (95% CI, 1.466-6.233), respectively, compared with stiffer corneas. CONCLUSIONS: Postoperative residual refractive error was associated with preoperative corneal stiffness. Patients with less-stiff corneas had a 2- to 3-fold increased risk of residual refractive error after SMILE. Preoperative analysis of corneal stiffness can help modify nomogram algorithms of surgery and improve the predictability of refractive outcomes.

Biomechanical properties analysis of forme fruste keratoconus and subclinical keratoconus.

PURPOSE: To analyze the biomechanical properties of the eye in patients with unilateral keratoconus with normal (forme fruste keratoconus [FFKC]) or abnormal topography (subclinical keratoconus [SKC]). METHODS: This study included 153 eyes of 153 participants, including 95 eyes of patients with unilateral keratoconus, and 58 eyes of 58 healthy controls. Contralateral eyes with unilateral keratoconus were divided into two groups according to clinical manifestations and global consensus: FFKC (n = 30) and SKC (n = 65). The biomechanical characteristics were analyzed using non-parametric tests; further analysis thereof was performed after adjusting for confounding factors (i.e., intraocular pressure, age, and corneal thickness). Receiver operating characteristic curve (ROC) was used to analyze the ability of the biomechanical parameters to distinguish FFKC from SKC. RESULTS: Statistically significant differences between the FFKC and SKC groups were found in 9 of the 18 corneal biomechanical parameters analyzed using non-parametric tests. After adjusting for confounding factors, the multivariate analysis still revealed significant statistical differences in A1-time (P = 0.017), integrated radius (IR) (P = 0.024), and tomographic and biomechanical index (TBI, P < 0.001) between the FFKC and SKC groups. Stiffness parameter at first applanation (SP-A1) (Area under ROC [AUROC] = 0.765) demonstrated the strongest distinguishing ability, except for TBI (AUROC = 0.858) and Corvis Biomechanical Index (AUROC = 0.849), however, there was no statistically significant difference in SP-A1 (P = 0.366) between FFKC and SKC. CONCLUSIONS: Biomechanical parameters A1-time and IR have a high diversity between FFKC and SKC, besides TBI, and may reflect more subtle changes in corneal biomechanical properties (BPs) preceding SP-A1. The BPs of SKC are weaker than FFKC, which might be a basic and clue for the classification and diagnosis of the severity of early keratoconus in terms of biomechanics.

Small Incision Lenticule Extraction (SMILE) Versus Laser Assisted Stromal In Situ Keratomileusis (LASIK) for Astigmatism Corrections: A Systematic Review and Meta-analysis.

PURPOSE: To compare small incision lenticule extraction (SMILE) and laser assisted stromal in situ keratomileusis (LASIK) for astigmatism correction. DESIGN: Systematic review and meta-analysis METHODS: We reviewed published studies comparing outcomes after LASIK and SMILE for astigmatism correction by querying PubMed, EMBASE, Cochrane, and Web of Science, with a cut-off date of September 3, 2022. We also compared the changes in visual acuity, refraction, and high-order aberrations between the surgeries. Astigmatism correction outcomes in the low-to-moderate group (less than or equal to -2.00 D) and high group (greater than -2.00 D) were evaluated using vector analysis. The Cochrane risk of bias tool in RevMan software was used for randomized studies (RCT), and Risk Of Bias In Nonrandomized Studies - of Interventions (ROBINS-I) was used for the nonrandomized studies (NRSs). RESULTS: There were 17 studies (5 randomized studies and 12 cohort studies), including 1,985 eyes. A statistically significant difference was found in the correction index (mean difference [MD] = -0.02, 95% confidence interval [CI] = -0.04 to -0.01, P =0.01), although there was no significant difference in the index of success (MD = 0.01, 95% CI = -0.03 to 0.05, P =0.51), different vector (MD = 0.07, 95% CI = 0.00 to 0.13, P =0.04), and angle of error (MD = 0.56, 95% CI = -0.34 to 1.45, P =0.22) between SMILE and LASIK. However, for low-to-moderate astigmatism correction, SMILE exhibited a smaller correction index (MD = -0.08, 95% CI= -0.13 to -0.02, P =0.008) and a larger difference vector (MD = 0.18, 95% CI = 0.09 to 0.27, P <0.0001) than LASIK. There was no significant difference between the different procedures in visual acuity and refraction (spherical equivalent: MD = -0.04, 95% CI = -0.08 to 0.01, P =0.15) or high-order aberration (MD = -0.01, 95% CI = -0.07 to 0.04, P =0.67), except spherical aberration (MD = -0.12, 95% CI = -0.23 to -0.01, P =0.04). The risk of bias was moderate in most studies because of poor reporting of several bias domains for RCTs, and because of confounding and selective outcome reporting for NRSs. CONCLUSIONS: When used to treat severe astigmatism, both SMILE and LASIK provide effective and predictable results and generally have equivalent outcomes. However, evidence reveals a tendency toward undercorrection in the SMILE groups for astigmatism correction. In addition, LASIK has a greater probability of causing postoperative spherical aberration.

Artificial Intelligence-Based Diagnostic Model for Detecting Keratoconus Using Videos of Corneal Force Deformation.

Purpose: To develop a novel method based on biomechanical parameters calculated from raw corneal dynamic deformation videos to quickly and accurately diagnose keratoconus using machine learning. Methods: The keratoconus group was included according to Rabinowitz's criteria, and the normal group included corneal refractive surgery candidates. Independent biomechanical parameters were calculated from dynamic corneal deformation videos. A novel neural network model was trained to diagnose keratoconus. Tenfold cross-validation was performed, and the sample set was divided into a training set for training, a validation set for parameter validation, and a testing set for performance evaluation. External validation was performed to evaluate the model's generalizability. Results: A novel intelligent diagnostic model for keratoconus based on a five-layer feedforward network was constructed by calculating four biomechanical characteristics, including time of the first applanation, deformation amplitude at the highest concavity, central corneal thickness, and radius at the highest concavity. The model was able to diagnose keratoconus with 99.6% accuracy, 99.3% sensitivity, 100% specificity, and 100% precision in the sample set (n = 276), and it achieved an accuracy of 98.7%, sensitivity of 97.4%, specificity of 100%, and precision of 100% in the external validation set (n = 78). Conclusions: In the absence of corneal topographic examination, rapid and accurate diagnosis of keratoconus is possible with the aid of machine learning. Our study provides a new potential approach and sheds light on the diagnosis of keratoconus from a purely corneal biomechanical perspective. Translational Relevance: Our findings could help improve the diagnosis of keratoconus based on corneal biomechanical properties.

Predictive factors of posterior corneal shift after small incision lenticule extraction: a 5-year follow-up study.

PURPOSE: The aim of this study was to determine risk factors affecting changes in posterior corneal elevation (PCE) and predict the 5-year stability after small incision lenticule extraction (SMILE). METHODS: This retrospective, longitudinal study enrolled 161 patients post-SMILE. The PCE values were measured at the apex, thinnest, maximal and 24 other prespecified preoperative points and at 6 months, 1 year and 5 years postoperatively. RESULTS: Posterior corneas exhibited time-dependent, region-dependent and angle-dependent changes. For every dioptre increase in the absolute preoperative spherical equivalent (SE), 10-µm decrease in the central corneal thickness (CCT), 10-µm increase in the maximum lenticule thickness (MLT), 10-µm decrease in the residual bed thickness (RBT), 10% increase in the percentage ablation depth (PAD, MLT divided by CCT) and 10% decrease in the percentage stromal bed thickness (PSBT, RBT divided by CCT), PCE exhibited average forward displacements of 0.2-0.4, 0.2-0.7, 0.1-0.2, 0.1-0.3, 0.6-1.0 and 0.5-1.1 µm, respectively (p < 0.05). PSBT was the variable with the highest accuracy in predicting 5-year stability of posterior corneas (area under curve = 0.75). The cut-off values of SE, CCT, MLT, RBT, PAD and PSBT for increased PCE were -8.00 to -8.31 D, 481.0-498.5 µm, 139.5-144.5 µm, 255.5-263.5 µm, 26.9-28.3% and 48.9-52.6%, respectively. CONCLUSION: Eyes with thinner corneas, higher myopia requiring greater MLT and lower RBT exhibited greater predispositions towards posterior protrusion. The thresholds for preventing forward posterior corneal displacement were 26.9-28.3% for PAD and 48.9-52.6% for PSBT. Prediction of posterior corneal stability is useful for assessing surgical risks post-SMILE.

Three-year clinical outcomes and posterior corneal elevation change after small-incision lenticule extraction in suspicious corneas.

PURPOSE: To determine the long-term clinical outcomes and change in posterior corneal elevation after small-incision lenticule extraction (SMILE) in eyes with suspicious tomographic features. SETTING: Hospital clinic. DESIGN: Retrospective, case-controlled, observational. METHODS: This study included 43 patients with suspicious corneas (group A), defined by corneal morphology and a final D score from a Scheimpflug camera (Pentacam), and 43 patients with normal corneal topography (group B). Refraction, visual acuity, and posterior corneal elevation over a 6-mm central diameter, including posterior central elevation (PCE), posterior elevation at the thinnest point (PTE), and posterior maximal elevation (PME), were measured preoperatively and at 6 months, 12 months, and 36 months postoperatively. RESULTS: The preoperative spherical equivalent was -5.51 ± 1.33 D in group A (n = 43) and -5.41 ± 1.19 D in group B (n = 43). Postoperative uncorrected distance visual acuity was 20/20 or better in 39 (91%) of 43 eyes in group A and 41 (95%) of 43 eyes in group B ( P = .160); all eyes in both groups remained stable or had gained corrected distance visual acuity. The mean change in PCE, PTE, and PME at 3 years was -1.22 ± 2.65 µm, -1.21 ± 2.70 µm, and -1.00 ± 5.09 µmin group A and -1.76 ± 3.25 µm, -1.60 ± 3.33 µm, and -1.56 ± 5.01 µm in group B, respectively, indicating a tendency for backward displacement of the posterior surface, whereas the between-group difference was not statistically significant ( P = .154, P = .547, and P = .319, respectively). CONCLUSIONS: Refraction, visual outcomes, and posterior corneal shift seem comparable between corneas with normal and suspicious tomographic features three years after SMILE. More long-term studies are warranted to corroborate the findings of this study.

Quantitative Evaluation of Aerosol Generation from Non-contact Tonometry and its Correlation with Tear Film Characteristics.

INTRODUCTION: Ophthalmologists are inevitably exposed to tears and ocular discharge during ophthalmologic examinations and are at high risk for SARS-CoV-2 infection. To understand the role of aerosols in disease transmission, we adopted a prospective cross-sectional study design and investigated the count and size distribution of aerosols generated by a non-contact tonometer and its correlation with individual tear film characteristics. METHODS: This study constituted two parts. The study population included outpatients who underwent an intraocular pressure examination in an intraocular pressure examination room (Part I) and 20 participants who underwent an intraocular pressure examination in a laboratory (Part II). The following main outcomes were measured: aerosol counts at 0, 50, 100, 150, and 200 cm from the non-contact tonometer (Part I); aerosol counts after each participant underwent non-contact tonometry, and lipid layer thickness score and tear film break-up time (Part II). RESULTS: The aerosol count decreased with increasing distance from the tonometer. The aerosol count at 0 cm had the highest value compared to that at other distances. For aerosols of diameters 0.25-0.5 µm and 0.5-1.0 µm, the count decreased at 50 cm and remained stable at further distances. For aerosols of diameters 1.0-2.5 µm and ≥ 2.5 µm, the count dropped progressively at all five distances. The aerosol count from each tonometer correlated positively with the lipid layer thickness score (r = 0.490, P = 0.028), whereas the aerosol count correlated negatively with the tear film break-up time (r = - 0.675, P = 0.001). CONCLUSIONS: Aerosols tended to coagulate during diffusion. A 50-cm distance from the tonometer could confer safety from aerosols with < 1.0-µm diameter. Aerosols generated during non-contact tonometry could contain a lipid layer component. Moreover, tear film stability could affect aerosol generation. Protective eyewear is recommended for reducing infection risk from aerosols. Individual tear film characteristics should be considered during non-contact tonometry.