RaySearch Laboratories, Stockholm, Sweden.
Division of Medical Physics, Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA.
Med Phys. 2018 Nov;45(11):e1011-e1023. doi: 10.1002/mp.12943.
Treatment planning for protons and heavier ions is adapting technologies originally developed for photon dose optimization, but also has to meet its particular challenges. Since the quality of the applied dose is more sensitive to geometric uncertainties, treatment plan robust optimization has a much more prominent role in particle therapy. This has led to specific planning tools, approaches, and research into new formulations of the robust optimization problems. Tools for solution space navigation and automatic planning are also being adapted to particle therapy. These challenges become even greater when detailed models of relative biological effectiveness (RBE) are included into dose optimization, as is required for heavier ions.
质子和重离子的治疗计划正在采用最初为光子剂量优化开发的技术,但也必须应对其特殊挑战。由于所应用剂量的质量对几何不确定性更敏感,因此在粒子治疗中,治疗计划稳健优化具有更为突出的作用。这导致了特定的计划工具、方法和对稳健优化问题的新公式的研究。用于解决方案空间导航和自动规划的工具也正在被应用于粒子治疗。当需要对重离子进行相对生物效应(RBE)的详细模型进行剂量优化时,这些挑战变得更加巨大。