DMPO IMRT Plan Adjustment via Dual Objective Function
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Solution Overview
Problem
Radiation therapy plans often suffer from local deficiencies, such as 'hot spots' and 'cold spots,' where cancerous regions receive either excessive or inadequate doses, despite globally meeting dose objectives, making it challenging to modify existing plans without significant changes to the dose distribution.
Innovation Solution
A method that adjusts radiation treatment plans by using a dual objective function system, where one function focuses on global optimization and the other on local corrections, allowing for user-controlled weighting to address specific dose requirements, thereby enabling local improvements without compromising overall plan characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a treatment plan is computed using numerical optimization based on an objective function, then global dose objectives are met, but local dose deficiencies (hot spots and cold spots) remain in the cancerous region
Solution Approach 1:
The patent divides the treatment plan modification into two distinct segments: (1) a first optimization phase that ensures global dose objectives are met, and (2) a second refinement phase that addresses local dose deficiencies. This segmentation allows each phase to focus on specific goals without compromising the other, resolving the contradiction between global compliance and local precision.
Solution Approach 2:
The patent performs preliminary optimization to establish a treatment plan that satisfies global dose objectives before addressing local deficiencies. By pre-establishing the global framework, subsequent local adjustments can be made without disrupting overall dose distribution compliance, thus resolving the contradiction between global and local dose requirements.
2Manufacturing precision
If manual modifications are made to the beam arrangement or objective function parameters to remove local deficiencies, then local dose accuracy improves, but the dose distribution undergoes significant unintended changes requiring manual backtracking
Solution Approach 1:
The patent implements an automated feedback mechanism where the system identifies local dose deficiencies, computes appropriate modifications to beam arrangement or objective function parameters, applies these modifications, and evaluates the resulting dose distribution. This closed-loop feedback process eliminates the need for manual trial-and-error backtracking, improving both local dose accuracy and operational ease.
Solution Approach 2:
The system performs self-correction by automatically detecting local dose deficiencies and generating appropriate plan modifications without requiring manual intervention. The automated optimization process adjusts beam parameters to resolve local issues while maintaining global objectives, thereby improving local dose precision without increasing operational complexity.
3Productivity
If the magnitude and type of change in dose distribution are beyond direct user influence, then automated optimization is efficient, but multiple manual backtracking steps are required to achieve desired local corrections
Solution Approach 1:
The patent introduces dynamic control mechanisms that allow users to adjust optimization parameters and constraints during the computation process. This enables users to directly influence the magnitude and type of changes in dose distribution while maintaining computational efficiency, as the system dynamically adapts to user preferences rather than requiring manual backtracking after fixed automated optimization.
Data Source
AI summary
A method and related system to adjust an existing treatment plan. A second optimization is run based on a dual objective function system that includes a first objective function used for the optimization in respect of the existing plan and a second, extended objective function that includes the said first objective function as a functional component.