Abstract

This work extends and validates the scenario-based generalization of margins presented in Fredriksson and Bokrantz (2016 Phys. Med. Biol. 61 2067–82). Scenario-based margins are, in their original form, a method for robust planning under setup uncertainty where the sum of a plan evaluation criterion over a set of scenarios is optimized. The voxelwise penalties in the summands are weighted by a distribution of coefficients defined such that the method is mathematically equivalent to the use of conventional geometric margins if the scenario doses are calculated using the static dose cloud approximation. The purpose of this work is to extend scenario-based margins to general types of geometric uncertainty and to validate their use on clinical cases. Specifically, we outline how to incorporate density heterogeneity in the calculation of coefficients and demonstrate the extended method’s ability to safeguard against setup errors, organ motion, and range shifts (and combinations thereof). For a water phantom with a high-density slab partly covering the target, the extended form of scenario-based margins method led to improved target coverage robustness compared to the original method. At most minor differences in robustness were, however, observed between the extended and original method for a prostate and two lung patients, all treated with intensity-modulated proton therapy, yielding evidence that the calculation of weighting coefficients is generally insensitive to tissue heterogeneities. The scenario-based margins were, furthermore, verified to provide a comparable level of robustness to expected value and worst case optimization while circumventing some known shortcomings of these methods.

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