Department of Radiation Oncology, University Hospital Zürich, Zürich, Switzerland.
Department of Medical Physics in Radiation Oncology, German Cancer Research Center, Heidelberg, Germany.
Int J Radiat Oncol Biol Phys. 2020 Nov 1;108(3):792-801. doi: 10.1016/j.ijrobp.2020.04.029. Epub 2020 Apr 30.
Proton treatment slots are a limited resource. Combined proton-photon treatments, in which most fractions are delivered with photons and only a few with protons, may represent a practical solution to optimize the allocation of proton resources over the patient population. We demonstrate how a limited number of proton fractions can be optimally used in multimodality treatments and address the issue of the robustness of combined treatments against proton range uncertainties.
Combined proton-photon treatments are planned by simultaneously optimizing intensity modulated radiation therapy and proton therapy plans while accounting for the fractionation effect through the biologically effective dose model. The method was investigated for different tumor sites (a spinal metastasis, a sacral chordoma, and an atypical meningioma) in which organs at risk (OARs) were located within or near the tumor. Stochastic optimization was applied to mitigate range uncertainties.
In optimal combinations, proton and photon fractions deliver similar doses to OARs overlaying the target volume to protect these dose-limiting normal tissues through fractionation. Meanwhile, parts of the tumor are hypofractionated with protons. Thus, the total dose delivered with photons is reduced compared with simple combinations in which each modality delivers the prescribed dose per fraction to the target volume. The benefit of optimal combinations persists when range errors are accounted for via stochastic optimization.
Limited proton resources are optimally used in combined treatments if parts of the tumor are hypofractionated with protons and near-uniform fractionation is maintained in serial OARs. Proton range uncertainties can be efficiently accounted for through stochastic optimization and are not an obstacle for clinical application.
质子治疗插槽是一种有限的资源。联合质子-光子治疗,其中大多数分次采用光子,只有少数采用质子,可以代表一种优化质子资源在患者群体中分配的实用解决方案。我们展示了如何在多模态治疗中最佳地利用有限数量的质子分次,并解决了联合治疗对质子射程不确定性的稳健性问题。
通过同时优化调强放疗和质子治疗计划,并通过生物有效剂量模型考虑分次效应,来规划联合质子-光子治疗。该方法针对不同的肿瘤部位(脊柱转移瘤、骶骨脊索瘤和非典型脑膜瘤)进行了研究,其中危及器官(OARs)位于肿瘤内或附近。随机优化用于减轻射程不确定性。
在最佳组合中,质子和光子分次给予靶区重叠的 OARs 相似的剂量,通过分次保护这些剂量限制的正常组织。同时,部分肿瘤采用质子进行低分次治疗。因此,与每种模式按规定的分次给予靶区的单纯组合相比,光子治疗的总剂量降低。即使考虑到通过随机优化来计算射程误差,最佳组合的益处仍然存在。
如果部分肿瘤采用质子进行低分次治疗,并在连续的 OARs 中保持近似均匀的分次治疗,那么质子资源可以在联合治疗中得到最佳利用。通过随机优化可以有效地考虑质子射程不确定性,并且不会成为临床应用的障碍。