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一种用于优化永久性¹²⁵I前列腺植入的新遗传算法技术。

A new genetic algorithm technique in optimization of permanent 125I prostate implants.

作者信息

Yang G, Reinstein L E, Pai S, Xu Z, Carroll D L

机构信息

Department of Radiation Oncology, SUNY at Stony Brook 11794-7028, USA.

出版信息

Med Phys. 1998 Dec;25(12):2308-15. doi: 10.1118/1.598460.

Abstract

Real time optimized treatment planning at the time of the implant is desirable for ultrasound-guided transperineal 125I permanent prostate implants. Currently available optimization algorithms are too slow to be used in the operating room. The goal of this work is to develop a robust optimization algorithm, which is suitable for such application. Three different genetic algorithms (sGA, sureGA and securGA) were developed and compared in terms of the number of function evaluations and the corresponding fitness. The optimized dose distribution was achieved by searching the best seed distribution through the minimization of a cost function. The cost function included constraints on the periphery dose of the planned target volume, the dose uniformity within the target volume, and the dose to the critical structure. Adjustment between the peripheral dose, the dose uniformity and critical structure dose can be achieved by varying the weighting factors in the cost function. All plans were evaluated in terms of the dose nonuniformity ratio, the conformation number and the dose volume histograms. Among these three GA algorithms, the securGA provided the best performance. Within 2500 function evaluations, the near optimum results were obtained. For a large target volume (5 cm x 4 cm x 4.5 cm) including urethra with 20 needles, the computer time needed for the optimization was less than 5 min on a HP735 workstation. The results showed that once the best set of parameters was found, they were applicable for all sizes of prostate volume. For a fixed needle geometry, the optimized plan showed much better dose distribution than that of nonoptimized plan. If the critical structure was considered in the optimization, the dose to the critical structure could be minimized. In the cases of irregular and skewed needle geometry, the optimized treatment plans were almost as good as ideal needle geometry. It is concluded that this new genetic algorithm (securGA) allows for an efficient and rapid optimization of dose distribution, which is suitable for real time treatment planning optimization for ultrasound-guided prostate implant.

摘要

对于超声引导下经会阴¹²⁵I永久性前列腺植入术而言,在植入时进行实时优化治疗计划是很有必要的。目前可用的优化算法速度太慢,无法在手术室中使用。这项工作的目标是开发一种适用于此类应用的强大优化算法。开发了三种不同的遗传算法(sGA、sureGA和securGA),并在函数评估次数和相应适应度方面进行了比较。通过最小化成本函数来搜索最佳种子分布,从而实现优化的剂量分布。成本函数包括对计划靶体积周边剂量、靶体积内剂量均匀性以及关键结构剂量的约束。通过改变成本函数中的加权因子,可以实现周边剂量、剂量均匀性和关键结构剂量之间的调整。所有计划均根据剂量不均匀率、适形数和剂量体积直方图进行评估。在这三种遗传算法中,securGA表现最佳。在2500次函数评估内,获得了接近最优的结果。对于一个包含尿道、大小为5 cm×4 cm×4.5 cm的大靶体积,使用20根针,在HP735工作站上进行优化所需的计算机时间不到5分钟。结果表明,一旦找到最佳参数集,它们适用于所有大小的前列腺体积。对于固定的针几何形状,优化后的计划显示出比未优化计划更好的剂量分布。如果在优化中考虑关键结构,则可以将其剂量降至最低。在针几何形状不规则和倾斜的情况下,优化后的治疗计划几乎与理想针几何形状一样好。结论是,这种新的遗传算法(securGA)能够实现剂量分布的高效快速优化,适用于超声引导前列腺植入的实时治疗计划优化。

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