Radiation Therapy Plan Optimization via Clinical Goal Interpolation
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Solution Overview
Problem
Current multi-criteria optimization methods for radiation therapy treatment plans require significant manual fine-tuning and operator skill to achieve clinical goals, as the indirect correlation between quality measures and clinical goals complicates precise navigation.
Innovation Solution
A method that involves defining an interpolation optimization problem based on clinical goals, using a set of input dose distributions to calculate interpolation weights for an optimized dose distribution, and automatically generating an updated treatment plan, reducing the need for manual adjustments and operator expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If multi-criteria optimization with manual slider adjustment is used, then treatment plan optimization is achievable, but significant manual fine-tuning and operator skill are required
Solution Approach 1:
The system performs automatic optimization by selecting treatment plans and adjusting parameters autonomously based on clinical goals, eliminating the need for manual slider adjustment by operators
Solution Approach 2:
The manual mechanical slider adjustment system is replaced with an automated computer-based selection and optimization system that uses algorithms to determine optimal treatment plans
2Manufacturing precision
If indirect quality measures are used for optimization, then mathematical optimization is enabled, but precise navigation to clinical goals becomes difficult
Solution Approach 1:
The system uses clinical goals as direct feedback criteria to evaluate and select treatment plans, creating a closed-loop optimization process that directly measures success against clinically relevant outcomes
Solution Approach 2:
The optimization approach changes from using indirect mathematical quality measures to directly optimizing based on clinical goal parameters, transforming the measurement and control parameters of the system
3Productivity
If multiple input treatment plans are precalculated, then real-time navigation is enabled, but time-consuming manual fine-tuning is required
Solution Approach 1:
Multiple treatment plans are precalculated with different objective function weightings, and the system automatically selects and combines these preprepared plans based on clinical goals, eliminating the need for manual fine-tuning during the planning process
Solution Approach 2:
The system autonomously performs the entire optimization process from plan selection to final parameter determination, requiring no manual intervention and significantly reducing planning time
Data Source
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AI summary
A method of obtaining an interpolated treatment plan is based on interpolating between associated dose distributions through optimization with respect to an optimization problem comprising optimization functions based on deviations from clinical goals. The method may suitably be used to improve navigated plans resulting from multi-criteria optimization.