Purpose: To improve the effectivity of patient-specific finite element analysis (FEA) to predict refractive power change (RPC) in rigid Ortho-K contact lens fitting. Novel eyelid boundary detection is introduced to the FEA model to better model the effects of the lid on lens performance, and stress and strain outcomes are investigated to identify the most effective FEA components to use in modelling. Methods: The current study utilises fully anonymised records of 249 eyes, 132 right eyes, and 117 left eyes from subjects aged 14.1 ± 4.0 years on average (range 9 to 38 years), which were selected for secondary analysis processing. A set of custom-built MATLAB codes was built to automate the process from reading Medmont E300 height and distance files to processing and displaying FEA stress and strain outcomes. Measurements from before and after contact lens wear were handled to obtain the corneal surface change in shape and power. Tangential refractive power maps were constructed from which changes in refractive power pre- and post-Ortho-K wear were determined as the refractive power change (RPC). A total of 249 patient-specific FEA with innovative eyelid boundary detection and 3D construction analyses were automatically built and run for every anterior eye and lens combination while the lens was located in its clinically detected position. Maps of four stress components: contact pressure, Mises stress, pressure, and maximum principal stress were created in addition to maximum principal logarithmic strain maps. Stress and strain components were compared to the clinical RPC maps using the two-dimensional (2D) normalised cross-correlation and structural similarity (SSIM) index measure. Results: On the one hand, the maximum principal logarithmic strain recorded the highest moderate 2D cross-correlation area of 8.6 ± 10.3%, and contact pressure recorded the lowest area of 6.6 ± 9%. Mises stress recorded the second highest moderate 2D cross-correlation area with 8.3 ± 10.4%. On the other hand, when the SSIM index was used to compare the areas that were most similar to the clinical RPC, maximum principal stress was the most similar, with an average strong similarity percentage area of 26.5 ± 3.3%, and contact pressure was the least strong similarity area of 10.3 ± 7.3%. Regarding the moderate similarity areas, all components were recorded at around 34.4% similarity area except the contact pressure, which was down to 32.7 ± 5.8%. Conclusions: FEA is an increasingly effective tool in being able to predict the refractive outcome of Ortho-K treatment. Its accuracy depends on identifying which clinical and modelling metrics contribute to the most accurate prediction of RPC with minimal ocular complications. In terms of clinical metrics, age, Intra-ocular pressure (IOP), central corneal thickness (CCT), surface topography, lens decentration and the 3D eyelid effect are all important for effective modelling. In terms of FEA components, maximum principal stress was found to be the best FEA barometer that can be used to predict the performance of Ortho-K lenses. In contrast, contact pressure provided the worst stress performance. In terms of strain, the maximum principal logarithmic strain was an effective strain barometer.

Background: The aim is to investigate induced higher-order aberrations (HOA)s and astigmatism as a result of non-toric ortho-k lens decentration and utilise artificial intelligence (AI) to predict its magnitude and direction. Methods: Medmont E300 Video topographer was used to scan 249 corneas before and after ortho-k wear. Custom-built MATLAB codes extracted topography data and determined lens decentration from the boundary and midpoint of the central flattened treatment zone (TZ). An evaluation was carried out by conducting Zernike polynomial fittings via a computer-coded digital signal processing procedure. Finally, an AI-based machine learning neural network algorithm was developed to predict the direction and magnitude of TZ decentration. Results: Analysis of the first 21 Zernike polynomial coefficients indicate that the four low-order and four higher-order aberration terms were changed significantly by ortho-k wear. While baseline astigmatism was not correlated with lens decentration (R = 0.09), post-ortho-k astigmatism was moderately correlated with decentration (R = 0.38) and the difference in astigmatism (R = 0.3). Decentration was classified into three groups: ≤0.50 mm, reduced astigmatism by −0.9 ± 1 D; 0.5~1 mm, increased astigmatism by 0.8 ± 0.1 D; >1 mm, increased astigmatism by 2.7 ± 1.6 D and over 50% of lenses were decentred >0.5 mm. For lenses decentred >1 mm, 29.8% of right and 42.7% of left lenses decentred temporal-inferiorly and 13.7% of right and 9.4% of left lenses decentred temporal-superiorly. AI-based prediction successfully identified the decentration direction with accuracies of 70.2% for right and 71.8% for left lenses and predicted the magnitude of decentration with root-mean-square (RMS) of 0.31 mm and 0.25 mm for right and left eyes, respectively. Conclusions: Ortho-k lens decentration is common when fitting non-toric ortho-k lenses, resulting in induced HOAs and astigmatism, with the magnitude being related to the amount of decentration. AI-based algorithms can effectively predict decentration, potentially allowing for better control over ortho-k fitting and, thus, preferred clinical outcomes.

Orthokeratology lenses are commonly used for myopia control, especially in children. Tear lipids and proteins are immediately adsorbed when the lens is put on the cornea, and protein deposition may cause discomfort or infection. Therefore, we established an in vitro protein deposition analysis by mimicking the current cleaning methods for orthokeratology lens wearers for both short-term and long-term period. The results showed that the amounts of tear proteins accumulated daily and achieved a balance after 14 days when the lens was rubbed to clean or not. Protein deposition also affected the optical characteristics of the lens regardless of cleaning methods. Our results provided an in vitro analysis for protein deposition on the lens, and they may provide a potential effective method for developing care solutions or methods that can more effectively remove tear components from orthokeratology lenses.

Soft contact lenses are usually characterised at room temperature, yet they function on the eye at body temperature, where their mechanics and optical performance can change. This study investigated whether soft silicone hydrogel lenses become more compliant in a physiological environment. Two silicone hydrogel materials (Definitive 74 and Unisil) were tested at 24 °C and 35 °C using uniaxial tensile and compression methods, with Ogden hyperelastic models fitted and finite element analysis performed on a realistic eye model. Both materials became more compliant at 35 °C, with Definitive 74 showing a larger modulus decrease (0.40 to 0.32 MPa) than Unisil (0.73 to 0.70 MPa). Finite element simulations indicated that these temperature-driven changes in compliance significantly affected refractive power, especially when the lens base curve exceeded the corneal radius by more than 5%. These findings demonstrate that soft silicone hydrogel lenses are indeed more compliant in a warm, hydrated environment, highlighting the need for physiologically relevant testing to inform design, fitting strategies, comfort, and vision outcomes.

Objectives: To evaluate the impact of a new orthokeratology (OrthoK) lens on corneal epithelial thickness and higher-order aberrations (HOAs). Methods: This three-arm, prospective, crossover study randomly assigned participants to the control group, T1 group (1.5× control-group lens-design reverse curve [RC] height), and T2 group (2× control-group lens-design RC height). Participants underwent basic ophthalmological examinations, corneal topography, and corneal epithelial thickness and HOA measurements at each visit. Corneal zones were analyzed based on topographic changes induced by lens wear, corresponding to the central treatment zone and the reverse zone. Results: The spherical equivalent was significantly lower in T1 and T2 than in the control group on days 7 and 28 of lens wear (P<0.001). The corneal curvature was noticeably flatter in T1 and T2 than in the control group. No significant differences were observed among groups in the epithelial thickness of the central treatment zone after OrthoK lens wear. However, epithelial thickness in the reverse zone was significantly greater (P<0.05) in T1 and T2 compared with the control group after 28 days of lens wear. A significant difference in HOA was observed among the three groups after OrthoK lens wear for 1 and 7 days (P<0.01). T2 demonstrated higher levels of HOA than the other groups. Conclusions: This new design of OrthoK can alter the corneal epithelium thickness and stabilize central corneal flattening, thereby achieving a better correction for myopia. However, this design also induces HOAs and is associated with a mild but significant compromise in uncorrected visual acuity compared with conventional designs. Therefore, clinicians should weigh the potential benefits of myopia control against the associated effects on visual quality when selecting OrthoK lens designs.