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Impact of Gaussian uncertainty assumptions on probabilistic optimization in particle therapy
Physics in Medicine & Biology ( IF 3.3 ) Pub Date : 2020-07-14 , DOI: 10.1088/1361-6560/ab8d77
H P Wieser 1, 2 , C P Karger 1, 3 , N Wahl 1, 3 , M Bangert 1, 3
Affiliation  

Range and setup uncertainties in charged particle therapy may induce a discrepancy between the planned and the delivered dose. Countermeasures based on probabilistic (stochastic) optimization usually assume a Gaussian probability density to model the underlying range and setup error. While this standard assumption is generally taken for granted, this study explicitly investigates the dosimetric consequences if the actual range and setup errors obey a different probability density function (PDF) over the course of treatment to the one used during the probabilistic treatment plan optimization. Discrete random sampling was performed for conventionally and probabilistically optimized proton and carbon ion treatment plans utilizing various PDFs that modeled the setup and range error. This method allowed us to assess the treatment plan robustness against different PDFs of conventional and probabilistic plans, which both explicitly assume Gaussian uncertainties. The induced uncertainty...

中文翻译:

高斯不确定性假设对粒子治疗中概率优化的影响

带电粒子治疗中的范围和设置不确定性可能会导致计划剂量和已交付剂量之间出现差异。基于概率(随机)优化的对策通常采用高斯概率密度来对基础范围和设置误差进行建模。尽管通常认为该标准假设是理所当然的,但如果实际范围和设置误差在治疗过程中服从与概率治疗计划优化期间使用的概率密度函数(PDF)不同的概率密度函数(PDF),则本研究明确研究剂量学后果。使用各种模拟设置和范围误差的PDF对常规和概率优化的质子和碳离子处理计划进行离散随机采样。这种方法使我们能够针对常规和概率性计划的不同PDF评估治疗计划的鲁棒性,而这两个PDF都明确地假设了高斯不确定性。引起的不确定性...
更新日期:2020-07-15
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