Radiation Therapy Optimization Modulating Dose via Objective Function
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Solution Overview
Problem
Current radiation therapy treatment planning algorithms often get stuck in local minima, limiting the ability to achieve optimal dose modulation and beam shaping due to time constraints and complex computational requirements, especially when re-optimizing plans for changing patient conditions.
Innovation Solution
Modifying the objective function by adding an extra component that increases dose modulation, such as favoring a range of monitor units or multileaf collimator openings, to guide the optimization algorithm towards better solutions with higher modulation, using techniques like simulated annealing or gradient back projection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If standard optimization algorithms are used for treatment planning, then computational speed is maintained, but dose modulation quality deteriorates due to getting stuck in local minima
Solution Approach 1:
The patent applies simulated annealing, a dynamic optimization algorithm that allows the system to escape local minima by temporarily accepting worse solutions during the optimization process. This dynamic approach transforms the static optimization process into one that can explore the solution space more effectively, improving both dose modulation quality and convergence reliability.
Solution Approach 2:
The patent modifies the objective function by adding an extra component that increases dose modulation. This parameter change in the optimization landscape guides the algorithm toward better solutions while maintaining computational feasibility, directly addressing the contradiction between solution quality and algorithm reliability.
2Manufacturing precision
If more computational time is allocated for optimization, then dose modulation improves, but treatment planning time increases beyond clinical constraints
Solution Approach 1:
The patent incorporates an extra component into the objective function that pre-guides the optimization toward higher dose modulation solutions. This preliminary structuring of the optimization problem reduces the computational iterations needed to achieve clinical-quality plans, balancing solution quality with time constraints.
3Manufacturing precision
If the objective function is modified to increase dose modulation, then beam shaping quality improves, but computational complexity increases
Solution Approach 1:
The modified objective function provides feedback to the optimization algorithm by incorporating an extra component that continuously guides the search toward higher dose modulation solutions. This feedback mechanism improves beam shaping quality while maintaining computational tractability through directed optimization rather than brute-force search.
Data Source
AI summary
Methods for developing and using treatment plans with improved modulation for radiation therapy are disclosed. The methods involve adding an extra component to the patient-related objective function in order to make the optimization algorithm used to develop the treatment plan arrive at a solution with increased modulation. The extra component may take many forms. For example, the user may specify that the treatment plan favor solutions using a range of monitor units. The present invention is particularly useful in conjunction with radiotherapy systems having multileaf collimators for beam shaping, and in connection with advanced radiotherapy techniques, such as IMRT and arc therapy.