Schinkel Colleen, Stavrev Pavel, Stavreva Nadia, Fallone B Gino
Department of Physics, University of Alberta, and Department of Medical Physics, Cross Cancer Institute, 11560 University Avenue, Edmonton, Alberta, T6G1Z2, Canada.
Med Phys. 2006 Sep;33(9):3444-59. doi: 10.1118/1.2237453.
This paper outlines a theoretical approach to the problem of estimating and choosing dose-volume constraints. Following this approach, a method of choosing dose-volume constraints based on biological criteria is proposed. This method is called "reverse normal tissue complication probability (NTCP) mapping into dose-volume space" and may be used as a general guidance to the problem of dose-volume constraint estimation. Dose-volume histograms (DVHs) are randomly simulated, and those resulting in clinically acceptable levels of complication, such as NTCP of 5 +/- 0.5%, are selected and averaged producing a mean DVH that is proven to result in the same level of NTCP. The points from the averaged DVH are proposed to serve as physical dose-volume constraints. The population-based critical volume and Lyman NTCP models with parameter sets taken from literature sources were used for the NTCP estimation. The impact of the prescribed value of the maximum dose to the organ, D(max), on the averaged DVH and the dose-volume constraint points is investigated. Constraint points for 16 organs are calculated. The impact of the number of constraints to be fulfilled based on the likelihood that a DVH satisfying them will result in an acceptable NTCP is also investigated. It is theoretically proven that the radiation treatment optimization based on physical objective functions can sufficiently well restrict the dose to the organs at risk, resulting in sufficiently low NTCP values through the employment of several appropriate dose-volume constraints. At the same time, the pure physical approach to optimization is self-restrictive due to the preassignment of acceptable NTCP levels thus excluding possible better solutions to the problem.
本文概述了一种用于估计和选择剂量体积约束问题的理论方法。遵循该方法，提出了一种基于生物学标准选择剂量体积约束的方法。这种方法被称为“反向正常组织并发症概率（NTCP）映射到剂量体积空间”，可作为剂量体积约束估计问题的一般指导。对剂量体积直方图（DVH）进行随机模拟，选择那些导致临床可接受并发症水平（如NTCP为5±0.5%）的直方图并求平均值，得到一个经证明会导致相同NTCP水平的平均DVH。建议将平均DVH中的点用作物理剂量体积约束。使用从文献来源获取参数集的基于群体的临界体积和莱曼NTCP模型进行NTCP估计。研究了器官最大剂量规定值D(max)对平均DVH和剂量体积约束点的影响。计算了16个器官的约束点。还研究了基于满足这些约束的DVH会导致可接受NTCP的可能性而需满足的约束数量的影响。从理论上证明，基于物理目标函数的放射治疗优化能够充分限制对危及器官的剂量，通过采用几个适当的剂量体积约束，使NTCP值足够低。同时，由于预先设定了可接受的NTCP水平，纯粹的物理优化方法具有自我限制性，从而排除了该问题可能的更好解决方案。
