Department of Medical Physics in Radiation Oncology, German Cancer Research Center-DKFZ, Im NeuenheimerFeld 280, D-69120 Heidelberg, Germany. Heidelberg Institute for Radiation Oncology-HIRO, Im Neuenheimer Feld 280, D-69120, Germany.
Phys Med Biol. 2017 Nov 10;62(23):8959-8982. doi: 10.1088/1361-6560/aa915d.
Particle therapy is especially prone to uncertainties. This issue is usually addressed with uncertainty quantification and minimization techniques based on scenario sampling. For proton therapy, however, it was recently shown that it is also possible to use closed-form computations based on analytical probabilistic modeling (APM) for this purpose. APM yields unique features compared to sampling-based approaches, motivating further research in this context. This paper demonstrates the application of APM for intensity-modulated carbon ion therapy to quantify the influence of setup and range uncertainties on the RBE-weighted dose. In particular, we derive analytical forms for the nonlinear computations of the expectation value and variance of the RBE-weighted dose by propagating linearly correlated Gaussian input uncertainties through a pencil beam dose calculation algorithm. Both exact and approximation formulas are presented for the expectation value and variance of the RBE-weighted dose and are subsequently studied in-depth for a one-dimensional carbon ion spread-out Bragg peak. With V and B being the number of voxels and pencil beams, respectively, the proposed approximations induce only a marginal loss of accuracy while lowering the computational complexity from order [Formula: see text] to [Formula: see text] for the expectation value and from [Formula: see text] to [Formula: see text] for the variance of the RBE-weighted dose. Moreover, we evaluated the approximated calculation of the expectation value and standard deviation of the RBE-weighted dose in combination with a probabilistic effect-based optimization on three patient cases considering carbon ions as radiation modality against sampled references. The resulting global γ-pass rates (2 mm,2%) are [Formula: see text]99.15% for the expectation value and [Formula: see text]94.95% for the standard deviation of the RBE-weighted dose, respectively. We applied the derived analytical model to carbon ion treatment planning, although the concept is in general applicable to other ion species considering a variable RBE.
粒子治疗特别容易出现不确定性。这个问题通常通过基于情景抽样的不确定性量化和最小化技术来解决。然而,对于质子治疗,最近有人表明,也可以使用基于分析概率建模(APM)的闭式计算来达到这个目的。APM 与基于采样的方法相比具有独特的特点,这激发了在这方面进行进一步的研究。本文展示了 APM 在强度调制碳离子治疗中的应用,以量化在设置和范围不确定性对 RBE 加权剂量的影响。特别是,我们通过将线性相关的高斯输入不确定性通过铅笔束剂量计算算法传播,推导出了 RBE 加权剂量的期望值和方差的非线性计算的解析形式。我们为 RBE 加权剂量的期望值和方差提出了精确和近似的公式,并随后对一维碳离子扩展布拉格峰进行了深入研究。其中 V 和 B 分别是体素和铅笔束的数量,所提出的近似方法仅导致略微的精度损失,同时将计算复杂度从期望值的 [Formula: see text] 降低到 [Formula: see text],方差的 [Formula: see text] 降低到 [Formula: see text]。此外,我们评估了在考虑碳离子作为辐射模式的三个患者病例中,结合基于概率的效应优化,对 RBE 加权剂量的期望值和标准偏差的近似计算,并与采样参考进行了比较。结果的全局γ通过率(2 mm,2%)分别为 RBE 加权剂量的期望值为 [Formula: see text]99.15%和标准偏差为 [Formula: see text]94.95%。我们将推导的分析模型应用于碳离子治疗计划,尽管该概念通常适用于考虑可变 RBE 的其他离子种类。