Head and neck cancers present challenges in radiation treatment planning due to the large number of critical structures near the target(s) and highly heterogeneous tissue composition. While Monte Carlo (MC) dose calculations currently offer the most accurate approximation of dose deposition in tissue, the switch to MC presents challenges in preserving the parameters of care. The differences in dose‐to‐tissue were widely discussed in the literature, but mostly in the context of recalculating the existing plans rather than reoptimizing with the MC dose engine. Also, the target dose homogeneity received less attention. We adhere to strict dose homogeneity objectives in clinical practice. In this study, we started with 21 clinical volumetric‐modulated arc therapy (VMAT) plans previously developed in Pinnacle treatment planning system. Those plans were recalculated “as is” with RayStation (RS) MC algorithm and then reoptimized in RS with both collapsed cone (CC) and MC algorithms. MC statistical uncertainty (0.3%) was selected carefully to balance the dose computation time (1–2 min) with the planning target volume (PTV) dose‐volume histogram (DVH) shape approaching that of a “noise‐free” calculation. When the hot spot in head and neck MC‐based treatment planning is defined as dose to 0.03 cc, it is exceedingly difficult to limit it to 105% of the prescription dose, as we were used to with the CC algorithm. The average hot spot after optimization and calculation with RS MC was statistically significantly higher compared to Pinnacle and RS CC algorithms by 1.2 and 1.0 %, respectively. The 95% confidence interval (CI) observed in this study suggests that in most cases a hot spot of ≤107% is achievable. Compared to the 95% CI for the previous clinical plans recalculated with RS MC “as is” (upper limit 108%), in real terms this result is at least as good or better than the historic plans.

RayStation treatment planning system employs pencil beam (PB) and Monte Carlo (MC) algorithms for proton dose calculations. The purpose of this study is to evaluate the radiobiological and dosimetric impact of RayStation PB and MC algorithms on the intensity-modulated proton therapy (IMPT) breast plans. Methods: The current study included ten breast cancer patients, and each patient was treated with 1-2 proton beams to the whole breast/chestwall (CW) and regional lymph nodes in 28 fractions for a total dose of 50.4 Gy relative biological effectiveness (RBE). A total clinical target volume (CTV_Total) was generated by combining individual CTVs: AxI, AxII, AxIII, CW, IMN, and SCVN. All beams in the study were treated with a range shifter (7.5 cm water equivalent thickness). For each patient, three sets of plans were generated: (a) PB optimization followed by PB dose calculation (PB-PB), (b) PB optimization followed by MC dose calculation (PB-MC), and (c) MC optimization followed by MC dose calculation (MC-MC). For a given patient, each plan was robustly optimized on the CTVs with same parameters and objectives. Treatment plans were evaluated using dosimetric and radiobiological indices (equivalent uniform dose (EUD), tumor control probability (TCP), and normal tissue complication probability (NTCP)). Results: The results are averaged over ten breast cancer patients. In comparison to PB-PB plans, PB-MC plans showed a reduction in CTV target dose by 5.3% for D 99% and 4.1% for D 95% , as well as a reduction in TCP by 1.5-2.1%. Similarly, PB overestimated the EUD of target volumes by 1.8─3.2 Gy(RBE). In contrast, MC-MC plans achieved similar dosimetric and radiobiological (EUD and TCP) results as the ones in PB-PB plans. A selection of one dose calculation algorithm over another did not produce any noticeable differences in the NTCP of the heart, lung, and skin. Conclusion: If MC is more accurate than PB as reported in the literature, dosimetric and radiobiological results from the current study suggest that PB overestimates the target dose, EUD, and TCP for IMPT breast cancer treatment. The overestimation of dosimetric and radiobiological results of the target volume by PB needs to be further interpreted in terms of clinical outcome.

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