Hristov D H, Fallone B G
Medical Physics Unit, McGill University, Montreal General Hospital, QC, Canada.
Med Phys. 1998 Feb;25(2):208-23. doi: 10.1118/1.598183.
Conventional inverse treatment planning attempts to calculate dose distributions that may not be feasible given the specified dose levels to various anatomical structures. A technique for inverse treatment planning has been developed that uses only target dose levels which are easily selectable to be feasible. A nonlinear constrained minimization problem is formulated to reflect the goal of sparing critical organs as much as possible while delivering a certain target dose within specified uniformity. The objective function is the squared dose delivered to critical organs. The constraints require the delivery of certain target dose within specified uniformity and non-negative pencil beam weights. A continuous penalty function method is introduced as a method for solving the large-scale constrained minimization problem. The performance of the continuous penalty function method is optimized by numerical investigation of few numerical integration schemes and a pair of weighting functions which influence the utility of the method. Clinical examples are presented that illustrate several features of the technique. The properties of the continuous penalty function method suggest that it may be a viable alternative to conventional inverse treatment planning.
传统的逆向治疗计划试图计算剂量分布，但鉴于对各种解剖结构指定的剂量水平，这种分布可能不可行。已开发出一种逆向治疗计划技术，该技术仅使用易于选择且可行的靶剂量水平。提出了一个非线性约束最小化问题，以反映在规定的均匀性范围内输送一定靶剂量的同时尽可能保护关键器官的目标。目标函数是输送到关键器官的剂量平方。约束条件要求在规定的均匀性范围内输送一定的靶剂量以及非负的笔形束权重。引入了一种连续惩罚函数方法作为解决大规模约束最小化问题的方法。通过对几种数值积分方案和一对影响该方法效用的加权函数进行数值研究，优化了连续惩罚函数方法的性能。给出了临床实例来说明该技术的几个特点。连续惩罚函数方法的特性表明，它可能是传统逆向治疗计划的一种可行替代方案。
