Analytical probabilistic modeling of RBE-weighted dose for ion therapy
Analytical probabilistic modeling of RBE-weighted dose for ion therapy
复制标题
离子治疗 RBE 加权剂量的分析概率模型
DOI：
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发表时间：
2017
影响因子：
3.5
通讯作者：
M. Bangert
中科院分区：
文献类型：
--
作者：
H. Wieser;Philipp Hennig;N. Wahl;M. Bangert
粒子疗法尤其容易出现不确定性。这个问题通常是解决不确定性量化和最小化技术的基础上情景抽样。然而，对于质子治疗，最近表明，也可以使用基于分析概率建模（APM）的封闭形式计算。APM产生独特的功能相比，基于采样的方法，激励在这方面的进一步研究。本文演示了APM的应用程序调强碳离子治疗，以量化的设置和范围的不确定性的RBE加权剂量的影响。特别是，我们通过传播线性相关的高斯输入不确定性，通过笔形射束剂量计算算法的期望值和方差的RBE加权剂量的非线性计算的解析形式。精确和近似公式的RBE加权剂量的期望值和方差，随后深入研究了一维碳离子扩展布拉格峰。V和B分别是体素和笔形射束的数量，所提出的近似仅引起精度的边际损失，同时将期望值的计算复杂度从O（V×B2）降低到O（V×B），将RBE加权剂量的方差的计算复杂度从O（V×B4）降低到O（V×B2）。此外，我们评估了RBE加权剂量的期望值和标准差的近似计算，并结合基于概率效应的优化，对三个患者病例进行了评估，将碳离子作为辐射模态，对照采样参考。由此产生的全局γ-通过率（2 mm，2%）为$？>> 99.15%的期望值和$？>> 94.95%的RBE加权剂量的标准差。我们应用衍生的分析模型碳离子治疗计划，虽然这个概念是在一般情况下适用于其他离子物种考虑变量RBE。
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 O(V×B2) to O(V×B) for the expectation value and from O(V×B4) to O(V×B2) 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 $ ?>>99.15% for the expectation value and $ ?>>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.
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DOI：
10.1186/s13014-016-0705-8
发表时间：
2016-10-07
期刊：
Radiation oncology (London, England)
影响因子：
--
作者：
Steitz J;Naumann P;Ulrich S;Haefner MF;Sterzing F;Oelfke U;Bangert M
通讯作者：
Bangert M
影响因子：
3.4
作者：
M. Zaider;H. Rossi
通讯作者：
M. Zaider;H. Rossi
影响因子：
3.8
作者：
SIDDON, RL
通讯作者：
SIDDON, RL
影响因子：
3.8
作者：
Liu, Wei;Zhang, Xiaodong;Mohan, Radhe
通讯作者：
Mohan, Radhe
影响因子：
3.8
作者：
Unkelbach, Jan;Bortfeld, Thomas;Soukup, Martin
通讯作者：
Soukup, Martin