基于Eclipse计划系统等效均匀剂量在旋转调强放疗中的临床应用

      Clinical Application of Equivalent Uniform Dose in Intensity-Modulated Rotational Radiotherapy Based on Eclipse TPS

      • 摘要:
        目的 对等效均匀剂量(equivalent uniform dose, EUD)在旋转调强放疗中的应用进行研究,探讨调强计划质量的优化方法。
        方法 用Python分析EUD公式中a值对EUD曲线特征的影响。随机选取头颈部肿瘤、胸部肿瘤以及盆腔肿瘤各30例进行计划设计,分别用仅基于物理优化方式和物理约束条件配合EUD函数的优化方式对靶区和危及器官进行剂量优化,对两组计划的剂量分布、约束条件等指标进行比较,同时观察a的不同取值对计划结果的影响。
        结果 a值对EUD曲线特征变化的影响与对EUD计划优化结果的影响一致,当−15≤a≤−5时,靶区剂量分布较均匀;当1≤a≤7时,约束危及器官的均匀剂量及低剂量区效果较明显;当10≤a≤30时,约束危及器官高剂量区效果明显,靶区和危及器官的EUD在不同a值下表达不同。研究还发现,采用EUD优化方式的计划组靶区的剂量分布和对危及器官的保护均优于仅用物理优化方法的计划组。
        结论 a的取值对靶区和危及器官的剂量分布具有重要影响,为使用EUD优化调强计划时a值的设定提供了参考依据。EUD优化方法的使用能在保证靶区剂量分布的前提下,明显降低正常组织受量,减少并发症概率,具有一定临床应用价值。

         

        Abstract:
        Objective To investigate the application of equivalent uniform dose (EUD) in intensity-modulated rotational radiotherapy and to explore optimization methods for improving the quality of modulated treatment plans.
        Methods The impact of the parameter a in the EUD formula on the characteristics of the EUD curve was analyzed using Python. Thirty cases of head and neck tumors, thoracic tumors, and pelvic tumors were randomly selected for treatment planning. Dose optimization for the target area and organs at risk were performed using a physics-based optimization approach or an optimization approach that combines physical constraints with the EUD function. The dose distribution and compliance with constraints of the two groups of plans were compared, while also observing the effect of different values of a on the planning outcomes.
        Results The impact of the value of a on the changes in EUD curve characteristics was consistent with its impact on the results of EUD plan optimization. When −15≤a≤−5, the dose distribution in the target area was more uniform; when 1≤a≤7, the effect on the uniform dose and low-dose regions in organs at risk was more noticeable; when 10≤a≤30, the effect of constraining the high-dose regions in organs at risk was more pronounced, with the EUD for the target area and organs at risk exhibiting different expressions under different a values. The study also found that the target dose distribution and the protection of organs at risk in the EUD optimization group were better than those in the physical optimization group only.
        Conclusion The a-value has a significant impact on the, the dose distribution in the target area and the organ at risk, providing a reference for the setting of a-value while using EUD to optimize the intensity modulation plan. The using of EUD optimization method can not only achieve excellent dose distribution in the target area, but also significantly reduce the normal tissue dose and the probability of complications, which has certain clinical application value.

         

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