Patient-Specific Cornea Finite Element Model with Depth-Dependent Fiber Distribution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for modeling the cornea for simulating tissue cuts during refractive surgery lack precision due to insufficient consideration of the depth-dependent mechanical properties and collagen fiber distribution, leading to inaccurate predictions of post-operative corneal form.
Innovation Solution
A computerized device and method that generate a patient-specific finite element model of the cornea, distributing main fibers parallel to the surface and inclined cross-linked fibers with a non-uniform depth distribution function, along with permeability values dependent on depth, to simulate tissue cuts accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a general axis-symmetrical model is used for corneal modeling, then the modeling process is simplified, but the prediction accuracy of post-operative corneal form deteriorates
Solution Approach 1:
The patent applies local quality by differentiating fiber orientation and mechanical properties across different corneal layers. The model distinguishes between anterior stroma with randomly oriented collagen fibers and posterior stroma with regularly oriented fibers, assigning different constitutive laws to each layer. This localized differentiation improves prediction accuracy while maintaining manageable complexity through systematic layer-specific parameter assignment.
Solution Approach 2:
The patent employs composite material principles by modeling the cornea as a multi-layered structure with distinct material properties. Each layer (anterior stroma, posterior stroma, Descemet's membrane, endothelium) is assigned specific mechanical characteristics and fiber distributions, creating a composite model that captures the heterogeneous nature of corneal tissue. This approach balances complexity by using standardized composite material theories for each layer while achieving high overall prediction accuracy.
2Device complexity
If depth-independent material properties are used, then the modeling process is simpler, but the simulation accuracy of tissue cuts deteriorates
Solution Approach 1:
The patent implements depth-dependent material properties by assigning different constitutive laws to different corneal layers. The anterior stroma uses a fiber-reinforced hyperelastic model to capture random fiber orientation, while the posterior stroma uses a different model for regular fiber patterns. This local differentiation of material properties throughout the depth of the cornea significantly improves cut simulation accuracy while maintaining systematic modeling approaches.
Solution Approach 2:
The patent transitions from two-dimensional surface modeling to three-dimensional depth-resolved modeling by incorporating the depth dimension into material property assignment. The model assigns varying fiber orientations, densities, and mechanical properties at different depths within the cornea, capturing the through-thickness heterogeneity that is critical for accurate cut simulation while managing complexity through structured 3D parameterization.
3Device complexity
If a uniform distribution of collagen fibers is assumed, then the modeling process is simplified, but the mechanical property prediction deteriorates
Solution Approach 1:
The patent applies local quality by assigning different fiber distribution patterns to different corneal layers. The anterior stroma is modeled with randomly oriented collagen fibers using a fiber distribution function, while the posterior stroma is modeled with regularly oriented fibers following a different statistical distribution. This layer-specific fiber characterization significantly improves mechanical property predictions while maintaining manageable complexity through systematic parameter assignment.
Solution Approach 2:
The patent employs parameter changes by varying fiber orientation angles, fiber density, and fiber distribution parameters across different corneal layers. The model uses depth-dependent parameter functions to capture the transition from random to regular fiber patterns, improving mechanical property accuracy while managing complexity through parameterized descriptions rather than explicit geometric modeling of individual fibers.
Data Source
AI summary
A patient-specific finite element model of the cornea is generated for the purposes of modeling a cornea for simulating tissue cuts in the cornea. A first group of tissue fibers, with main fibers that extend parallel to the surface of the cornea, is distributed in the finite element model in accordance with a first distribution function. Moreover, a second group of tissue fibers, with inclined cross-linked fibers that do not extend parallel to the surface of the cornea, is distributed in the finite element model in accordance with a second distribution function. Here, the second distribution function distributes the cross-linked fibers with a non-uniform weighting function over the depth of the cornea, from the outer surface of the cornea to the inner surface of the cornea.