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2025
Journal Article
Title
Decision support for combining photon and proton plans
Abstract
Purpose/Objective:
Proton therapy can often achieve a better dose distribution than photon therapy. However, proton therapy centers are scarce, patients often must travel longer distances, and treatment is more expensive than photon therapy. For some patients, a plan quality similar to proton treatment can be achieved with few proton fractions. We want to help planners to answer questions such as: Would this patient benefit from proton therapy? How much can we achieve with x fractions of proton therapy? What would we lose with fewer proton fractions and gain with more?
Material/Methods:
We assume a Pareto front approximation of the photon planning problem and some proton plans highlighting different trade-offs have been computed.
Established methods for navigating a Pareto front [1], are used in photon radiotherapy treatment planning [2][3]. Multi-criteria optimization methods can also be employed in proton therapy planning [4][5]. While the calculation of plans combining proton and photon treatment has been studied [6], and decision support methods for multiple Pareto fronts exist [7][8], no decision support system for interactive mixing of treatment modalities has been proposed.
Results:
We present a decision support method for navigating a Pareto front obtained by mixing a photon front and proton plans. The proportion of proton fractions can be changed within the decision-making process, allowing the influence of the proton fraction proportion on the solution to be observed. Figure 1 shows the objective values of the photon and proton plans together with the mixed plans for different numbers of proton fractions (upper left). In the upper right, the decision maker can navigate the Pareto front using sliders. The user can select the proportion of proton fractions (lower right). The lower left shows the DVH curves of the selected mixed plan as well as the pure photon and proton plan.
Conclusion:
While there are not enough proton treatment facilities to provide proton therapy to every patient who would benefit, there is a need for combined plans to allow certain patients to benefit partially from the improved dose distribution of proton plans.
We present a first decision support tool that allows the decision maker to directly navigate the Pareto front of the mixed plans and compare the DVH curves for the respective navigated photon and proton plans as well as the mixed plan. The decision maker can interactively change the number of proton fractions and observe the resulting change in the objective values and DVH curves.
Proton therapy can often achieve a better dose distribution than photon therapy. However, proton therapy centers are scarce, patients often must travel longer distances, and treatment is more expensive than photon therapy. For some patients, a plan quality similar to proton treatment can be achieved with few proton fractions. We want to help planners to answer questions such as: Would this patient benefit from proton therapy? How much can we achieve with x fractions of proton therapy? What would we lose with fewer proton fractions and gain with more?
Material/Methods:
We assume a Pareto front approximation of the photon planning problem and some proton plans highlighting different trade-offs have been computed.
Established methods for navigating a Pareto front [1], are used in photon radiotherapy treatment planning [2][3]. Multi-criteria optimization methods can also be employed in proton therapy planning [4][5]. While the calculation of plans combining proton and photon treatment has been studied [6], and decision support methods for multiple Pareto fronts exist [7][8], no decision support system for interactive mixing of treatment modalities has been proposed.
Results:
We present a decision support method for navigating a Pareto front obtained by mixing a photon front and proton plans. The proportion of proton fractions can be changed within the decision-making process, allowing the influence of the proton fraction proportion on the solution to be observed. Figure 1 shows the objective values of the photon and proton plans together with the mixed plans for different numbers of proton fractions (upper left). In the upper right, the decision maker can navigate the Pareto front using sliders. The user can select the proportion of proton fractions (lower right). The lower left shows the DVH curves of the selected mixed plan as well as the pure photon and proton plan.
Conclusion:
While there are not enough proton treatment facilities to provide proton therapy to every patient who would benefit, there is a need for combined plans to allow certain patients to benefit partially from the improved dose distribution of proton plans.
We present a first decision support tool that allows the decision maker to directly navigate the Pareto front of the mixed plans and compare the DVH curves for the respective navigated photon and proton plans as well as the mixed plan. The decision maker can interactively change the number of proton fractions and observe the resulting change in the objective values and DVH curves.
Author(s)