Intensity-Modulated Radiation Therapy Optimization for Acceptable and Remaining-One Unacceptable Dose-Volume and Mean-Dose Constraint Planning
Intensity-Modulated Radiation Therapy Optimization for Acceptable and Remaining-One Unacceptable Dose-Volume and Mean-Dose Constraint Planning
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DOI：
10.1155/2020/3096067
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发表时间：
2020-09
影响因子：
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通讯作者：
R. Nakada;Omar M. Abou Al-Ola;T. Yoshinaga
中科院分区：
文献类型：
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作者：
R. Nakada;Omar M. Abou Al-Ola;T. Yoshinaga
基于连续动力学方法的思想，提出了一种获得调强放疗（IMRT）优化解的新方法。该方法是一种由连续时间动力系统离散化而来的迭代算法，不仅可以直接处理剂量-体积约束，还可以直接处理IMRT治疗计划中的平均剂量约束。利用李雅普诺夫稳定性定理，给出了收敛于期望IMRT规划对应的平衡点的理论证明。通过引入“可接受”的概念，即存在满足给定剂量-体积和平均剂量约束的非空束重集，并使用所提出的方法进行可接受的IMRT规划，可以解决传统规划过程中目标和评估不同的问题。此外，在目标规划完全不可接受和部分可接受的情况下，除了一组剂量限制，我们给出了一个程序，使我们能够获得接近于不可接受规划的期望解的近最优解。通过模拟临床设置的数值实验，证实了所提出的方法在可接受或不可接受规划方面的性能。
We give a novel approach for obtaining an intensity-modulated radiation therapy (IMRT) optimization solution based on the idea of continuous dynamical methods. The proposed method, which is an iterative algorithm derived from the discretization of a continuous-time dynamical system, can handle not only dose-volume but also mean-dose constraints directly in IMRT treatment planning. A theoretical proof for the convergence to an equilibrium corresponding to the desired IMRT planning is given by using the Lyapunov stability theorem. By introducing the concept of “acceptable,” which means the existence of a nonempty set of beam weights satisfying the given dose-volume and mean-dose constraints, and by using the proposed method for an acceptable IMRT planning, one can resolve the issue that the objective and evaluation are different in the conventional planning process. Moreover, in the case where the target planning is totally unacceptable and partly acceptable except for one group of dose constraints, we give a procedure that enables us to obtain a nearly optimal solution close to the desired solution for unacceptable planning. The performance of the proposed approach for an acceptable or unacceptable planning is confirmed through numerical experiments simulating a clinical setup.