Semi-Meridian Corneal Astigmatism Vector Planning
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Solution Overview
Problem
Current methods for determining corneal astigmatism are inconsistent and fail to accurately represent the entire cornea, leading to erratic results in simulating keratometry and irregularity quantification, especially in refractive surgery planning.
Innovation Solution
A method using computer-assisted videokeratography and vector summation to determine semi-meridian parameters for the cornea, weighting zones based on proximity and area, combining topographic and refractive parameters to reduce and regularize astigmatism through laser ablation profiles applied to each semi-meridian.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods for determining corneal astigmatism are used, then the process is simple, but the results are inconsistent and inaccurate
Solution Approach 1:
The cornea is divided into two separate semi-meridians (superior and inferior), each analyzed independently with separate vector parameters. This segmentation allows for more precise local measurement of astigmatism in each half of the cornea, resolving the inconsistency in current methods that treat the cornea as a single unit.
Solution Approach 2:
Different weighting coefficients are applied to different concentric zones (3mm, 5mm, 7mm) based on their proximity to the central axis and area. This local quality approach ensures that zones closer to the visual axis have appropriate influence on the final astigmatism calculation, improving measurement accuracy while maintaining a systematic methodology.
2Reliability
If simulated keratometry is used for astigmatism determination, then the method is straightforward, but it produces erratic results in representing the entire cornea
Solution Approach 1:
The invention transitions from traditional two-dimensional simulated keratometry to a three-dimensional vector analysis that incorporates magnitude, axis, and semi-meridian separation. By adding the dimension of semi-meridian-specific vector parameters, the method reliably represents the entire cornea without producing erratic results.
Solution Approach 2:
The methodology changes from single-parameter simulated keratometry to multi-parameter vector analysis including magnitude, axis, and weighting coefficients for different zones. This parameter transformation ensures reliable and consistent representation of corneal astigmatism across the entire cornea.
3Manufacturing precision
If traditional astigmatism treatment planning is used, then the procedure is simple, but it fails to reduce and regularize ocular aberrations effectively
Solution Approach 1:
The treatment planning divides the cornea into superior and inferior semi-meridians with separate vector parameters, allowing independent analysis and correction planning for each half. This segmentation enables precise customization of laser ablation profiles to address specific astigmatism patterns in each semi-meridian, improving correction precision.
Solution Approach 2:
Different laser ablation profiles are applied to different semi-meridians based on their specific vector parameters and astigmatism characteristics. This local quality approach ensures that each region of the cornea receives customized treatment, effectively reducing and regularizing ocular aberrations while maintaining a systematic treatment framework.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides a more accurate and consistent quantification of corneal astigmatism, enabling effective reduction and regularization of ocular aberrations, thereby improving visual performance by minimizing residual astigmatism and ensuring better corrected visual acuity.
Implementation Method 1
applying different laser ablation profiles to each of the two semi-meridians of the cornea
Data Source
AI summary
Techniques are disclosed in which a topographic parameter is determined in each semi-meridian of the eye by considering the topography in each of three concentric zones from the central axis at 3 mm, 5 mm, and 7 mm and assigning weighting factors for each zone, By selectively treating the weighted values in the three zones, parameters of magnitude and meridian can be obtained for each semi-meridian. From these parameters, a single topographic value for the entire eye (CorT) can be found as well as a value representing topographic disparity (TD) between the two semi-meridians. The topography values for the semi-meridians are used in a vector planning system to obtain treatment parameters in a single step operation.