A novel reduced-order prioritized optimization method for radiation therapy treatment planning.
A novel reduced-order prioritized optimization method for radiation therapy treatment planning.
复制标题
DOI：
10.1109/tbme.2013.2293779
复制
发表时间：
2014-04
期刊：
影响因子：
--
通讯作者：
Apte A
中科院分区：
文献类型：
--
作者：
Kalantzis G;Apte A
在这项研究中，一种新的降阶优先算法提出了放射治疗治疗计划的优化。所提出的方法包括三个阶段。在第一阶段，通过求解一系列无约束优化问题对强度空间进行采样。第一阶段的目标函数表示为目标和危险器官的部分目标的标量化加权和。拉丁超立方抽样被用来定义的权重为每次运行的无约束优化。在第二阶段中，主成分分析应用于在第一阶段中确定的解决方案，以确定强度空间中的主要本征模式，显着减少了自变量的数量。在第三阶段中，治疗计划目标/目的的优先级，并在降阶空间中解决问题。在每个目标被优化之后，该目标函数被转换为低优先级目标的约束。在目前的配方中，滑动因子是用来放松规划目标体积（PTV）覆盖的硬约束。所提出的方法的适用性证明了一个前列腺和一个肺调强放射治疗治疗计划。在完成顺序优先优化后，直肠和膀胱的平均剂量分别降低了21.3%和22.4%。此外，我们研究了滑动因子“s”对PTV覆盖率的影响，发现肿瘤剂量的降解最小（~4%）。最后，在不影响结果质量的情况下，降维后的加速因子高达49.9。
In this study, a novel reduced order prioritized algorithm is presented for optimization in radiation therapy treatment planning. The proposed method consists of three stages. In the first stage, the intensity space was sampled by solving a series of unconstrained optimization problems. The objective function of the first stage is expressed as a scalarized weighted sum of partial objectives for the target and organ at risk. Latin hypercube sampling was utilized to define the weights for each run of the unconstrained optimizations. In the second stage, principal component analysis is applied to the solutions determined in the first stage to identify the major eigen modes in the intensities space, significantly reducing the number of independent variables. In the third stage, treatment planning goals/objectives are prioritized, and the problem is solved in the reduced order space. After each objective is optimized, that objective function is converted into a constraint for the lower-priority objectives. In the current formulation, a slip factor is used to relax the hard constraints for planning target volume (PTV) coverage. The applicability of the proposed method is demonstrated for one prostate and one lung intensity-modulated radiation therapy treatment plan. Upon completion of the sequential prioritized optimization, the mean dose at the rectum and bladder was reduced by 21.3% and 22.4%, respectively. Additionally, we investigated the effect of the slip factor ‘s’ on PTV coverage and we found minimal degradation of the tumor dose (~4%). Finally, the speed up factors upon the dimensionality reduction were as high as 49.9 without compromising the quality of the results.