Laser Treatment Pattern Optimization for Eye Therapy
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Solution Overview
Problem
Conventional laser-based eye treatments face challenges in accurately positioning laser treatment beams for sub-visible lesions and patterned treatments, as physicians rely on visible lesions for positioning and must pre-determine patterns, limiting the ability to treat sub-visible or patterned areas effectively.
Innovation Solution
A system that determines a recommended pattern of laser treatment beam spots based on user-provided parameters, using a reference database of laser treatment parameters and associated lesion sizes, allowing for interpolation to calculate the expected lesion size and spacing, enabling precise application of multiple lesions over a desired area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physicians use visible lesions for positioning subsequent laser applications, then positioning accuracy is improved, but treatment of sub-visible lesions and patterned treatments is limited
Solution Approach 1:
The system performs preliminary calculation of expected lesion sizes based on laser parameters before treatment. A reference database stores pre-measured lesion sizes for various laser settings, allowing the system to predict lesion dimensions and determine optimal spot patterns in advance, enabling both sub-visible and patterned treatments without relying on visible lesions for positioning
Solution Approach 2:
The patent introduces an intermediary computational system that acts as a mediator between laser parameters and lesion outcomes. This system uses a reference database and interpolation algorithms to translate laser settings into expected lesion sizes, providing a predictive model that guides spot pattern determination without requiring direct visual feedback from previous lesions
2Productivity
If physicians pre-determine pattern of laser spots, then treatment efficiency is improved, but ability to treat sub-visible areas is limited
Solution Approach 1:
The system performs preliminary calculation of expected lesion sizes based on laser parameters before treatment. A reference database stores pre-measured lesion sizes for various laser settings, allowing the system to predict lesion dimensions and determine optimal spot patterns in advance, enabling both sub-visible and patterned treatments without relying on visible lesions for positioning
Solution Approach 2:
The system establishes a feedback loop where the predicted lesion size from the reference database informs the determination of subsequent spot patterns. This predictive feedback mechanism allows the system to optimize treatment patterns for sub-visible lesions while maintaining treatment efficiency, as the expected outcomes guide the treatment plan without requiring visual confirmation of each previous lesion
3Area of stationary object
If multiple laser applications are applied to cover desired area, then treatment coverage is improved, but treatment precision is reduced due to manual positioning
Solution Approach 1:
The system performs preliminary calculation of expected lesion sizes based on laser parameters before treatment. A reference database stores pre-measured lesion sizes for various laser settings, allowing the system to predict lesion dimensions and determine optimal spot patterns in advance, enabling both sub-visible and patterned treatments without relying on visible lesions for positioning
Solution Approach 2:
The patent replaces the manual mechanical positioning method with a computational system. Instead of physicians manually calculating and positioning each laser spot based on visual feedback, the system uses automated calculations based on a reference database to determine optimal spot patterns, thereby improving precision while maintaining coverage
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
Enables accurate and efficient application of both visible and sub-visible lesions, as well as patterned treatments, by determining the optimal number and spacing of laser spots, improving treatment precision and coverage without relying on pre-existing lesion positioning.
Implementation Method 1
laser-based interventional treatments of the eye... application of laser energy in the form of a laser treatment beam... to create visible or sub-visible lesions
Data Source
AI summary
Systems and processes for the optimization of laser treatment of an eye are disclosed. The process can include receiving a set of parameters of a laser treatment (e.g., an aerial beam size, contact lens, pulse duration, and the desired clinical grade), determining an estimated size of a lesion to be generated by the laser treatment beam, receiving a lesion pattern density (e.g., full grid, mild grid, or other), and determining a recommended pattern of laser treatment beam spots. The recommended pattern of laser treatment beam spots may include a recommended number of laser treatment spots and a spacing between the spots.


