Dynamic OFV Goal Adjustment in Radiation Treatment Optimization
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Solution Overview
Problem
Existing auto-planning approaches for radiation treatment planning fail to adequately capture patient-to-patient variability and may struggle with difficult or impossible objective goals, leading to suboptimal dose distribution and sparing of critical organs at risk.
Innovation Solution
The method involves performing multiple optimization loops with adjustable objective function value (OFV) goals, allowing for dynamic adjustment of OFV goals based on the compliance of the dose distribution with the current OFV goals, and updating these goals between optimization loops to improve the balance and robustness of the radiation treatment plan.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional auto-planning approaches are used with fixed objective function value goals, then the planning process is automated, but the system fails to capture patient-to-patient variability and struggles with difficult or impossible objective goals
Solution Approach 1:
The patent implements dynamic adjustment of OFV goals across multiple optimization loops. The system transitions from static, fixed OFV goals to dynamic goals that are updated based on compliance metrics from each optimization loop, enabling the system to adapt to patient-specific variability while maintaining automation.
Solution Approach 2:
The patent introduces feedback mechanisms where compliance metrics from each optimization loop are used to update OFV goals for subsequent loops. This feedback loop allows the system to learn from previous optimization results and adjust goals accordingly, improving adaptability to difficult or impossible objectives while maintaining automated operation.
2Adaptability or versatility
If multiple optimization loops with dynamic OFV goal adjustment are implemented, then adaptability to patient-specific variability improves, but the computational complexity and time increase
Solution Approach 1:
The patent implements a multi-loop optimization process where the system performs multiple optimization loops with dynamic OFV goal adjustment. This partial action approach allows the system to achieve better adaptability through iterative improvement, balancing the increased computational time against the significant gains in treatment plan quality and patient-specific adaptability.
Data Source
AI summary
In radiation treatment planning, a plurality of optimization loops are performed. In each optimization loop computes a dose distribution (60) in a patient represented by a planning image (42) with regions of interest (ROIs) defined in the planning image. Weights (64) for objective functions (50) are determined from objective function value (OFV) goals (52) for the objective functions. An optimized dose distribution is produced by adjusting the plan parameters to optimize the computed dose distribution respective to composite objective function (62). At least one optimization loop may include updating (70) at least one OFV goal to be used in at least the next performed optimization loop. At least one optimization loop may include updating an objective function quantifying compliance with a target dose for a target ROI based on a comparison of a metric of coverage of the target ROI and a desired coverage of the target ROI.