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GENETIC ALGORITHM-BASED DYNAMIC INTRAOPERATIVE TREATMENT PLANNING FOR PROSTATE BRACHYTHERAPY

机译:基于遗传算法的前列腺近距离放射治疗的动态术中治疗计划

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This paper reports on the use of a genetic algorithm (GA) for dynamic intraoperative treatment planning (DITP) with stepwise replanning for the prostate implant. The study applied a simple needle and seed reconstruction model to simulate the seed displacement. The simulation of DITP consists of an initial plan and four re-optimized plans. The results show that, on average, the total number of seeds required by each re-plan increased. The average maximum urethral dose and maximum rectal dose showed a slight increase during the first two replanning steps, but increased substantially during the latter two replanning steps. Several issues are discussed regarding the limitation and future improvement of GA-based DITP.
机译:本文报道了使用遗传算法(GA)进行动态术中治疗计划(DITP),其具有前列腺植入物的逐步重新替换。该研究应用了一个简单的针和种子重建模型来模拟种子位移。 DITP的模拟包括初始计划和四个重新优化的计划。结果表明,平均而言,每次重新计划所需的种子总数增加。在前两个重新替换步骤期间,平均最大尿道剂量和最大直肠剂量显示出略微增加,但在后两种重新替换步骤期间基本上增加。关于基于GA的DITP的限制和未来改进讨论了几个问题。

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