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.

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.