Department of Biophysics, GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany.
Int J Radiat Oncol Biol Phys. 2013 Feb 1;85(2):528-35. doi: 10.1016/j.ijrobp.2012.04.011. Epub 2012 May 30.
To provide methods for quantification of uncertainties in 4-dimensional (4D) treatment during treatment planning.
Uncertainty information was generated by multiple 4D treatment simulations with varying parameters. Sampled data were analyzed using uncertainty visualization methods that have been added to common treatment plan evaluation methods (eg, dose-volume histogram and dose distribution analysis). To illustrate the potential of the introduced methods, uncertainty analysis was completed for a single lung cancer case using 3 motion mitigation techniques: gating, slice-by-slice rescanning, and breath-controlled rescanning.
By repeating 4D dose calculations with varying parameters, we were able to show local uncertainties in dose distributions and to evaluate the stability of treatment setups. The new methods were found suitable for uncertainty evaluation in 4D treatment planning of moving tumors. Calculation time of the uncertainty base data was time consuming but contrivable overnight.
Uncertainty analysis and visualization for 4D treatment planning provide an important tool in the decision process for an optimal treatment approach.
提供在治疗计划期间对 4 维(4D)治疗中的不确定性进行量化的方法。
通过具有不同参数的多个 4D 治疗模拟生成不确定性信息。使用已添加到常见治疗计划评估方法(例如,剂量-体积直方图和剂量分布分析)中的不确定性可视化方法来分析采样数据。为了说明所提出方法的潜力,使用 3 种运动缓解技术(门控、逐片重扫和呼吸控制重扫)对单个肺癌病例进行了不确定性分析。
通过对具有不同参数的 4D 剂量计算进行重复,可以显示剂量分布中的局部不确定性,并评估治疗设置的稳定性。新方法适用于移动肿瘤的 4D 治疗计划中的不确定性评估。不确定性基准数据的计算时间非常耗时,但可以在一夜之间完成。
4D 治疗计划的不确定性分析和可视化为最佳治疗方法的决策过程提供了重要工具。