Session Item

The increased relative biological effectiveness (RBE) at the end of the proton range might increase the risk of radiation-induced toxicities. This, however, is not accounted for in clinical practice when using the constant RBE of 1.1. This study aims to quantify the impact of variable RBE models with uncertainties in the plan evaluation and to apply indirect RBE optimisation for mitigating the potential clinical consequences.

Proton plans with various fractionation doses for breast, brain, H&N and prostate cases (optimised with RBE=1.1) were evaluated using several LET_d- and α/β-dependent RBE models. Resulting distributions of the RBE-weighted dose (D_RBE) and LET_d were analysed together with NTCPs. Furthermore, robustness evaluations accounting for uncertainties in setup, density, RBE model parameters, LET_d and α/β were performed. Subsequently, two indirect RBE optimization methods were applied: (1) Re-optimising the physical dose based on variable RBE predictions from the LET_d distribution (LET_d-based re-optimisation). (2) Reducing the D_RBE in OARs while maintaining the physical target dose by penalising protons stopping in OARs (proton track-end optimisation). Reducing the number of track-ends is an appropriate surrogate for LET_d and RBE reduction, as both increase rapidly at the end of range. 

For CTVs with α/β≈5-15 Gy, the D_RBE using variable RBE models was predicted to be similar to RBE=1.1 (average RBE of 1.05–1.15 for brain/H&N), whereas it was predicted to be higher for targets with α/β≈1-5 Gy (average RBE of 1.1–1.3 for breast/prostate). For most OARs, the predicted D_RBE was often substantially higher, resulting in higher NTCPs. Inclusion of RBE uncertainties generally broadened the error bands for the nominal DVHs, with the largest contribution from the α/β uncertainty. The LET_d-based re-optimisation allowed for satisfying target coverage for several variable RBE models and treatment sites. For prostate and breast cases, robust plans fulfilling clinical target and OAR goals were generated. Proton track-end optimisation allowed for substantial reductions in D_RBE, LET_d, and NTCP for several OARs compared to only dose-based optimisation, without compromising target coverage or the integral dose. For brain lesions, LET_d reduction of 50% or more could be achieved, resulting in fulfilment of clinical OAR goals assuming variable RBE models where dose optimised plans failed.

Robustness evaluation including RBE uncertainties allows for comprehensive analyses where potential adverse effects could be evaluated and mitigated on quantitative individual bases. LET_d-based re-optimisation could be used as a pragmatic solution for prostate and breast cases to fulfil clinical goals assuming variable RBE models, whereas proton track-end optimisation might be a generalised indirect RBE optimisation tool that could produce biologically advantageous plans compared to dose-optimised plans, without compromising physical criteria in current treatment protocols.