Multiattribute decision theory for IMRT plan selection

目前的逆向规划方法包括简单的决策组件。一些 这些方法的不可取的特点包括不能处理不确定性， 用户偏好的原始形式（例如加权因子），以及需要进行大量， 麻烦的试错逆向计划尝试，以便向计划者呈现计划， 描述决策过程中固有的权衡。我们建议开发一种改进的 决策过程，耦合多目标进化算法与影响图在一个 多目标决策环境假设是，这种方法将导致计划， 更紧密地反映计划者的临床目标，以明确的方式纳入来自临床的数据 试验，应用不确定性下的决策原则，以一种更临床的方式， 可接受的计划，并考虑到病人和医生的喜好。我们的做法是 进一步发展我们的逆向规划能力，以有效地搜索帕累托的可能方案空间 多目标下的有效方案。这个规划系统将与一个 影响图影响图基于贝叶斯网络， 医生关于计划的3D剂量的重要参数的推理和判断 分布和患者相关状况。影响图将此图与效用节点结合在一起 包括医生或患者对可能结果的偏好。创新和 评估前列腺癌和头颈癌的影响图。

Current methods of inverse planning incorporate unsophisticated decision-making components. Some of the undesirable characteristics of these methods include the inability to deal with uncertainty, the reliance on crude forms (such as weighting factors) of user preferences, and the need to proceed through numerous, cumbersome trial-and-error inverse planning attempts in order to present the planner with plans that characterize the trade-offs inherent in the decision making process. We propose to develop an improved decision making process that couples multiobjective evolutionary algorithms with influence diagrams in a multiobjective decision making environment. The hypothesis is that such an approach will result in plans that more closely reflect the planner's clinical goals, that incorporate in an explicit manner the data from clinical trials, that apply the principles of decision making under uncertainty in a way that results in more clinically acceptable plans, and that take into account the preferences of the patient and physician. Our approach is to further develop our inverse planning capabilities to efficiently search the space of possible plans for Pareto efficient plans under the multiple objectives of a case. This planning system will be coupled with an influence diagram. The influence diagram is based on a Bayesian network that incorporates expert physicians' reasoning and judgements regarding the important parameters of both the plan's 3D dose distribution and patient-related conditions. The influence diagram combines this diagram with a utility node that includes physician or patient preferences regarding the possible outcomes. We will develop and evaluate influence diagrams for prostate cancer and for head & neck cancer.