Application of influence diagrams to prostate intensity-modulated radiation therapy plan selection
Application of influence diagrams to prostate intensity-modulated radiation therapy plan selection
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DOI：
10.1088/0031-9155/49/9/004
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发表时间：
2004-05-07
影响因子：
3.5
通讯作者：
Doctor, JN
中科院分区：
文献类型：
--
作者：
Meyer, J;Phillips, MH;Doctor, JN
其目的是将临床相关因素，如患者特异性和剂量测定信息以及临床试验数据纳入前列腺调强放射治疗（IMRT）计划选择的决策过程。该方法是将决策理论的概念的影响图的多目标优化逆规划问题的解决方案。通过改变计划靶区（PTV）和危及器官（OAR）的重要性因素，结合模拟退火来探索大部分解空间，从而获得一组候选调强放射治疗计划。分析了PTV和OAR的帕累托集，以展示加权因子的选择如何影响解决方案空间的哪一部分。设计了一个基于18节点贝叶斯网络的影响图模型，用于方案选择的决策过程。该模型具有来自临床研究的临床实验室结果、肿瘤分级、分期信息、患者特异性信息、剂量测定信息、并发症和生存统计的节点。一个实用程序节点用于决策过程。影响图根据可用信息成功地对计划进行了排序。通过敏感性分析判断了该图和结果的合理性。总之，影响图很好地模拟了IMRT计划选择的决策过程。它们提供了一种很好的方法，可以将数据和信念的概率性质合并到一个模型中。它们还以临床试验结果的形式提供了一种将循证医学引入决策过程的手段。
The purpose is to incorporate clinically relevant factors such as patient-specific and dosimetric information as well as data from clinical trials in the decision-making process for the selection of prostate intensity-modulated radiation therapy (IMRT) plans. The approach is to incorporate the decision theoretic concept of an influence diagram into the solution of the multiobjective optimization inverse planning problem. A set of candidate IMRT plans was obtained by varying the importance factors for the planning target volume (PTV) and the organ-at-risk (OAR) in combination with simulated annealing to explore a large part of the solution space. The Pareto set for the PTV and OAR was analysed to demonstrate how the selection of the weighting factors influenced which part of the solution space was explored. An influence diagram based on a Bayesian network with 18 nodes was designed to model the decision process for plan selection. The model possessed nodes for clinical laboratory results, tumour grading, staging information, patient-specific information, dosimetric information, complications and survival statistics from clinical studies. A utility node was utilized for the decision-making process. The influence diagram successfully ranked the plans based on the available information. Sensitivity analyses were used to judge the reasonableness of the diagram and the results. In conclusion, influence diagrams lend themselves well to modelling the decision processes for IMRT plan selection. They provide an excellent means to incorporate the probabilistic nature of data and beliefs into one model. They also provide a means for introducing evidence-based medicine, in the form of results of clinical trials, into the decision-making process.