Application of optimization model with piecewise penalty to intensity-modulated radiation therapy
Application of optimization model with piecewise penalty to intensity-modulated radiation therapy
复制标题
分段惩罚优化模型在调强放射治疗中的应用
DOI：
10.1016/j.future.2017.10.003
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发表时间：
2018-04
影响因子：
7.5
通讯作者：
Shu Huazhong
中科院分区：
文献类型：
--
作者：
Guo Caiping;Zhang Pengcheng;Zhang Liyuan;Gui Zhiguo;Shu Huazhong
目的：基于最大剂量和基于广义等效均匀剂量（gEUD）的二次分值对高于规定剂量的剂量进行惩罚，在可行解空间中均存在半偏差和梯度消失的缺点。为了解决这些缺陷，本研究提出了最大剂量标准和gEUD标准的新分值。方法：在新的分值中，对低于规定剂量的剂量给予线性惩罚函数，对高于规定剂量的剂量给予二次惩罚函数。为了测试它们的效率，分别将它们纳入物理模型和物理生物混合模型，并在TG119幻影和两种类型的临床病例上进行测试。将改进后的方法与原方法和基于剂量-体积的优化方法进行了比较。此外，将改进的基于geud的方法与另一种基于geud的二次优化方法进行了比较。采用基于梯度的优化算法求解这些大规模优化问题。结果：对于相似或更好的PTV覆盖，基于我们提出的二次模型的优化能够提高OARs节约。在实践中，通过对每个优化结构使用多个DV约束，基于DV的优化可能会得到相似的方案，但需要进行更多的试错来调整优化模型的参数。虽然最佳处方剂量尚不清楚，但在相同的处方剂量下，我们提出的优化方法可以获得更好的方案。结论：本文提出的优化方法具有拓展求解空间、提高放疗计划质量的潜力。
Purpose: Both maximum-dose-based and generalized equivalent uniform dose (gEUD)-based quadratic sub-scores, which penalize doses higher than the prescribed dose, exhibit the shortcomings of semi-deviation and a vanishing gradient in the feasible solution space. To address these drawbacks, this study proposes new sub-scores for the maximum dose criterion and the gEUD criterion.Methods: In new sub-scores, a dosage lower than the prescribed dose is assigned a linear penalty function, and one higher than the prescribed dose is assigned an extra quadratic penalty function. To test their efficiency, they were incorporated into a physical model and a hybrid physical–biological model, respectively, and were tested on a phantom TG119 and two types of clinic cases. The improved methods were compared with their original methods and the dose-volume (DV)-based optimization method. Additionally, the improved gEUD-based method was compared with another gEUD-based quadratic optimization method. The gradient-based optimization algorithm was applied to solve these large-scale optimization problems.Results: For similar or better PTV coverage, optimization based on our proposed quadratic models is capable of improving the OARs sparing. In practice, by using multiple DV constraints for each optimized structures, the DV based optimization may be able to arrive at similar plan, whereas greater trial-and-error is performed to adjust parameters of optimization model. Although the optimal prescribed dose remains unclear, at the same prescribed dose, our proposed optimization method can obtain better plan.Conclusion: Our proposed optimization method has the potential to expand the solution space and improve the quality of radiotherapy plan.
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影响因子：
2.7
作者：
LIU, DC;NOCEDAL, J
通讯作者：
NOCEDAL, J
影响因子：
3.8
作者：
Deasy, JO;Blanco, AI;Clark, VH
通讯作者：
Clark, VH
影响因子：
3.8
作者：
Wu, QW;Mohan, R
通讯作者：
Mohan, R
影响因子：
3.8
作者：
Holdsworth, Clay;Kim, Minsun;Phillips, Mark H.
通讯作者：
Phillips, Mark H.
DOI：
10.1007/978-3-662-03107-0_11
发表时间：
1995
期刊：
--
影响因子：
--
作者：
Anders Brahme
通讯作者：
Anders Brahme