Radiation Therapy Planning Reference Dose Functions
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Solution Overview
Problem
Radiation therapy treatment planning using multi-criteria optimization (MCO) faces challenges in generating clinically relevant and acceptable treatment plans that allow efficient navigation between dose distributions, as existing methods often require incompatible objective functions and lack consideration for realistic dose distributions.
Innovation Solution
A method is introduced that generates radiation therapy treatment plans by defining reference dose functions to minimize deviations from a clinically acceptable input dose distribution, using a confidence interval to create multiple reference dose distributions, which are then used in a multi-criteria optimization problem to produce a set of Pareto optimal plans, ensuring clinically relevant and navigable treatment options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple incompatible objective functions are used in MCO to explore different treatment options, then the ability to navigate between different dose distributions is improved, but the complexity of the optimization problem increases and clinical acceptability decreases
Solution Approach 1:
The patent applies preliminary action by pre-defining a set of compatible objective functions and their associated weighting factors before the optimization process begins. These pre-defined functions are based on clinical priorities and are established in advance to guide the MCO process, avoiding the need to manage multiple incompatible objective functions during navigation.
Solution Approach 2:
The patent utilizes parameter changes by adjusting the weighting factors of pre-defined objective functions rather than changing the objective functions themselves. This allows navigation between different dose distributions by modifying numerical parameters (weighting factors) while maintaining compatibility among all objective functions, thus reducing optimization complexity.
2Ease of operation
If the navigation range is limited around the initial dose distribution to simplify the process, then the ease of operation is improved, but the ability to find optimal treatment plans outside the limited range is reduced
Solution Approach 1:
The patent applies dynamics by making the navigation range adaptive rather than fixed. The system dynamically adjusts the exploration range based on the weighting factors and clinical priorities, allowing operators to navigate beyond the initial dose distribution when clinically appropriate while maintaining ease of operation through automated range adjustment.
3Manufacturing precision
If reference dose functions are used to minimize deviation from input dose distribution, then the manufacturing precision of treatment plans is improved, but the flexibility to explore alternative treatments is reduced
Solution Approach 1:
The patent resolves this contradiction by using parameter changes - specifically, by adjusting the weighting factors of reference dose functions rather than using them with fixed high weights. This allows the optimization to maintain quality (by respecting reference distributions when appropriate) while preserving flexibility (by allowing deviation when clinically justified through parameter adjustment).
Data Source
AI summary
Better Pareto dose distributions for multi-criteria optimization of treatment plans can be obtained by obtaining at least one reference dose function designed to result in an acceptable reference dose distribution, defining a multi-criteria optimization problem including the at least one reference dose function as at least one optimization function, performing at least two optimization procedures based on the multi-criteria optimization problem to generate a set of at least two possible treatment plans, obtaining a treatment plan to be used for treating the patient, based on the set of possible treatment plans, by selecting one plan or by combining plans.