Radiotherapy Plan Optimization for Photon–Proton Resource Allocation
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Solution Overview
Problem
Existing radiotherapy treatments face challenges in efficiently utilizing limited resources, such as proton delivery systems, to achieve the best possible treatment outcomes for individual patients and groups, particularly when combining photon and proton therapies.
Innovation Solution
A method for optimizing treatment plans that allocates resources between patients using an optimization problem considering resource requirements and plan quality, allowing for the efficient use of multiple radiation sets, including photon and proton therapies, by incorporating constraints and objective functions that balance resource utilization and treatment quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If ion therapy is used to improve treatment precision and quality, then treatment quality is improved, but resource cost and scarcity increase
Solution Approach 1:
The patent applies local quality by assigning different radiation modalities to different patients based on their specific treatment needs and characteristics. Each patient receives a customized treatment plan that locally optimizes the use of ion therapy for those who benefit most, rather than applying ion therapy uniformly to all patients. This resolves the contradiction by concentrating precision resources where they provide maximum value.
Solution Approach 2:
The optimization system changes parameters including the number of ion therapy fractions, photon therapy fractions, and beam angles to find the optimal balance between treatment quality and resource utilization. By dynamically adjusting these parameters based on patient-specific factors and resource availability, the system maximizes treatment effectiveness while managing scarce ion therapy resources.
2Reliability
If ion therapy fractions are increased to maximize treatment benefit for individual patients, then treatment effectiveness is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent employs dynamic optimization that adjusts treatment plans based on real-time resource availability and patient response. The system dynamically determines the optimal number of ion therapy fractions for each patient by considering both individual treatment needs and overall resource constraints, allowing flexibility to maximize both effectiveness and efficiency simultaneously.
Solution Approach 2:
The optimization system incorporates feedback mechanisms that evaluate treatment outcomes and resource utilization to continuously improve allocation decisions. By analyzing which patients benefit most from ion therapy and adjusting future allocations based on this feedback, the system achieves both high treatment effectiveness and efficient resource utilization.
3Manufacturing precision
If multiple radiation sets are combined for single patient treatment to improve plan quality, then treatment quality is improved, but resource allocation complexity increases
Solution Approach 1:
The patent segments the treatment planning process into distinct optimization stages: first determining optimal resource allocation across multiple patients, then generating specific treatment plans for each patient based on allocated resources. This segmentation reduces complexity by breaking down the multifaceted problem of combining multiple radiation sets across a patient population into manageable, sequential steps.
Solution Approach 2:
The system adds a new dimension to treatment planning by optimizing across the population level rather than just individual patient level. By considering resource allocation across multiple patients simultaneously and then deriving individual plans from this higher-dimensional optimization, the system manages complexity while achieving superior plan quality through combined radiation sets.
Data Source
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AI summary
A method of optimizing the use of resources in treatment planning involving more than one radiation set delivered to one or more patients, the radiation sets requiring different resources, respectively, wherein the optimization is performed using an optimization problem comprising an optimization function related to the first and second sets of resources. The method may be used for optimizing one plan for one patient, or a number of plans for different patients, in such a way that the available resources are used in the best possible way.