Department of Physics, University of Trento, Povo, Italy; Trento Institute for Fundamental Physics and Applications (TIFPA), National Institute for Nuclear Physics, (INFN), Povo, Italy.
Protontherapy Department, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy.
Phys Med. 2018 Jun;50:7-12. doi: 10.1016/j.ejmp.2018.05.018. Epub 2018 May 26.
Proton therapy for the treatment of breast cancer is acquiring increasing interest, due to the potential reduction of radiation-induced side effects such as cardiac and pulmonary toxicity. While several in silico studies demonstrated the gain in plan quality offered by pencil beam scanning (PBS) compared to passive scattering techniques, the related dosimetric uncertainties have been poorly investigated so far.
Five breast cancer patients were planned with Raystation 6 analytical pencil beam (APB) and Monte Carlo (MC) dose calculation algorithms. Plans were optimized with APB and then MC was used to recalculate dose distribution. Movable snout and beam splitting techniques (i.e. using two sub-fields for the same beam entrance, one with and the other without the use of a range shifter) were considered. PTV dose statistics were recorded. The same planning configurations were adopted for the experimental benchmark. Dose distributions were measured with a 2D array of ionization chambers and compared to APB and MC calculated ones by means of a γ analysis (agreement criteria 3%, 3 mm).
Our results indicate that, when using proton PBS for breast cancer treatment, the Raystation 6 APB algorithm does not allow obtaining sufficient accuracy, especially with large air gaps. On the contrary, the MC algorithm resulted into much higher accuracy in all beam configurations tested and has to be recommended.
Centers where a MC algorithm is not yet available should consider a careful use of APB, possibly combined with a movable snout system or in any case with strategies aimed at minimizing air gaps.
由于质子治疗乳腺癌具有降低放射性心脏毒性和肺毒性等潜在优势，其应用受到越来越多的关注。尽管一些计算机研究表明与被动散射技术相比，笔形束扫描（PBS）在计划质量上具有优势，但迄今为止，相关剂量学不确定性尚未得到充分研究。
采用 Raystation 6 解析笔形束（APB）和蒙特卡罗（MC）剂量计算算法对 5 例乳腺癌患者进行计划设计。首先采用 APB 对计划进行优化，然后使用 MC 重新计算剂量分布。考虑了可移动准直器和束分裂技术（即对于同一束入口使用两个子野，一个子野使用射程移动器，另一个子野不使用射程移动器）。记录了 PTV 剂量统计数据。采用相同的计划配置进行实验基准测试。采用二维电离室阵列测量剂量分布，并通过γ分析（一致性标准 3%，3mm）将其与 APB 和 MC 计算的剂量分布进行比较。
我们的结果表明，在使用质子 PBS 治疗乳腺癌时，Raystation 6 APB 算法无法获得足够的准确性，尤其是在存在较大气隙的情况下。相反，在所有测试的光束配置中，MC 算法的准确性要高得多，因此推荐使用 MC 算法。
对于尚未配备 MC 算法的中心，应谨慎使用 APB，可结合使用可移动准直器系统，或者采用旨在尽量减少气隙的策略。
