The scenario-based generalization of radiation therapy margins

TL;DR

This paper introduces a scenario-based optimization method for radiation therapy planning that improves robustness and accuracy over traditional geometric margins, especially when dose calculations are more precise.

Contribution

It develops a novel robust planning formulation that overcomes limitations of previous methods by accurately modeling uncertainties and providing sharp dose fall-off.

Findings

Method performs well on phantom cases with proton beam irradiation.

Provides better protection against practical uncertainties.

Avoids target underdosage in easy scenarios.

Abstract

We give a scenario-based treatment plan optimization formulation that is equivalent to planning with geometric margins if the scenario doses are calculated using the static dose cloud approximation. If the scenario doses are instead calculated more accurately, then our formulation provides a novel robust planning method that overcomes many of the difficulties associated with previous scenario-based robust planning methods. In particular, our method protects only against uncertainties that can occur in practice, it gives a sharp dose fall-off outside high dose regions, and it avoids underdosage of the target in ``easy'' scenarios. The method shares the benefits of the previous scenario-based robust planning methods over geometric margins for applications where the static dose cloud approximation is inaccurate, such as irradiation with few fields and irradiation with ion beams. These properties are demonstrated on a suite of phantom cases planned for treatment with scanned proton beams subject to systematic setup uncertainty.