Direct Parameter Adjustment for Radiation Therapy Planning
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Solution Overview
Problem
The existing radiation therapy treatment planning systems require iterative and time-consuming modifications to achieve a desired dose distribution, as users can only indirectly influence the dose distribution by adjusting weights of objective functions, leading to unsatisfactory results.
Innovation Solution
A system that allows direct calculation of parameter changes for radiation components based on their contribution to the dose distribution, enabling faster and easier adaptation of treatment plans by modifying parameter values within specified thresholds, thereby reducing computational complexity and maintaining local changes to minimize dose constraint violations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If iterative optimization procedures with weight adjustments are used to modify treatment plans, then treatment plans can be adapted to achieve desired dose distributions, but the process becomes time-consuming and computationally complex
Solution Approach 1:
The system directly changes the parameters quantifying the amount of radiation provided by individual radiation components based on calculated contributions to dose at specific volume elements, rather than iteratively adjusting objective function weights. This direct parameter modification approach eliminates multiple optimization cycles and significantly reduces planning time while maintaining the ability to adapt dose distributions.
Solution Approach 2:
Instead of indirectly influencing dose distribution through weight adjustments in objective functions, the system directly calculates and applies parameter changes for radiation components based on their contribution to dose. This inverted approach goes from direct cause (parameter change) to effect (dose modification) rather than the conventional indirect path.
2Manufacturing precision
If iterative optimization with weight modifications is applied, then dose distribution can be adjusted, but computational complexity increases
Solution Approach 1:
The system directly modifies parameters of radiation components based on calculated dose contributions, using a straightforward calculation approach rather than complex iterative optimization. This maintains dose distribution precision while significantly simplifying the computational procedure.
Solution Approach 2:
The system extracts and directly modifies only the specific parameters of radiation components that contribute to dose at targeted volume elements, rather than performing full-system iterative optimization. This selective parameter extraction and modification reduces computational complexity while maintaining precision.
3Reliability
If global optimization is performed to satisfy all dose constraints, then overall dose distribution is optimized, but local adjustments become difficult and time-consuming
Solution Approach 1:
The system calculates and applies parameter changes for individual radiation components based on their specific contribution to dose at targeted volume elements. This localized approach allows easy adjustment of specific regions while maintaining overall dose constraint compliance, making local adjustments straightforward and efficient.
Solution Approach 2:
The system segments the dose adjustment problem into individual radiation components and their contributions to specific volume elements. By handling each component separately based on its local contribution, the system enables easy local adjustments while maintaining global constraint satisfaction.
4Manufacturing precision
If multiple optimization cycles are performed, then treatment plan can be refined, but productivity decreases due to repeated calculations
Solution Approach 1:
The system achieves treatment plan refinement through direct parameter modification of radiation components based on dose contribution calculations, eliminating the need for multiple optimization cycles. This single-step approach maintains high treatment plan quality while significantly improving planning speed and productivity.
Data Source
AI summary
The invention relates to a system for planning a radiation therapy treatment. The system obtains a first treatment plan generated in accordance with values of parameters quantifying an amount of radiation provided by radiation components, obtains an instruction to change a radiation dose delivered to at least one volume element, and directly calculates, for each of the radiation components, a change of the amount of radiation provided by the radiation component based on the instruction and based on the contribution of the radiation component to the radiation dose delivered to the at least one volume element. In order to observe upper and/or lower thresholds of the parameter values, the updated parameter values are calculated by iteratively adding the determined changes to the parameter values until a parameter value reaches the threshold or until the desired dose change is realized.