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Robust optimization in lung treatment plans accounting for geometric uncertainty

机译:肺部治疗计划中的稳健优化解决了几何不确定性

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Robust optimization generates scenario‐based plans by a minimax optimization method to find optimal scenario for the trade‐off between target coverage robustness and organ‐at‐risk (OAR) sparing. In this study, 20 lung cancer patients with tumors located at various anatomical regions within the lungs were selected and robust optimization photon treatment plans including intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were generated. The plan robustness was analyzed using perturbed doses with setup error boundary of ±3 mm in anterior/posterior (AP), ±3 mm in left/right (LR), and ±5 mm in inferior/superior (IS) directions from isocenter. Perturbed doses for D99, D98, and D95 were computed from six shifted isocenter plans to evaluate plan robustness. Dosimetric study was performed to compare the internal target volume‐based robust optimization plans (ITV‐IMRT and ITV‐VMAT) and conventional PTV margin‐based plans (PTV‐IMRT and PTV‐VMAT). The dosimetric comparison parameters were: ITV target mean dose (Dmean), R95(D95/Dprescription), Paddick's conformity index (CI), homogeneity index (HI), monitor unit (MU), and OAR doses including lung (Dmean, V20 Gy and V15 Gy), chest wall, heart, esophagus, and maximum cord doses. A comparison of optimization results showed the robust optimization plan had better ITV dose coverage, better CI, worse HI, and lower OAR doses than conventional PTV margin‐based plans. Plan robustness evaluation showed that the perturbed doses of D99, D98, and D95 were all satisfied at least 99% of the ITV to received 95% of prescription doses. It was also observed that PTV margin‐based plans had higher MU than robust optimization plans. The results also showed robust optimization can generate plans that offer increased OAR sparing, especially for normal lungs and OARs near or abutting the target. Weak correlation was found between normal lung dose and target size, and no other correlation was observed in this study.
机译:稳健的优化通过最小极大优化方法生成基于方案的计划,以找到最佳方案,以在目标覆盖范围的稳健性和有风险的组织(OAR)保留之间进行权衡。在这项研究中,选择了20名肺癌患者,这些患者的肿瘤位于肺部不同的解剖区域,并生成了包括强度调制放射疗法(IMRT)和体积调制弧光疗法(VMAT)在内的强大的优化光子治疗计划。使用扰动剂量分析计划的稳健性,其等距点的前/后(AP)误差±3 mm,左/右(LR)误差±3 mm,下/上(IS)方向误差±5 mm。 D 99 ,D 98 和D 95 的扰动剂量是从六个偏移等中心线计划中计算得出的,以评估计划的鲁棒性。进行剂量学研究以比较基于内部目标量的稳健优化计划(ITV-IMRT和ITV-VMAT)和传统的基于PTV裕量的计划(PTV-IMRT和PTV-VMAT)。剂量学比较参数为:ITV目标平均剂量(D mean ),R 95 (D 95 / D 处方),帕迪克的合格指数(CI),均匀性指数(HI),监测单位(MU)和OAR剂量,包括肺脏(D mean ,V 20 Gy 和V 15 Gy ),胸壁,心脏,食道和最大脊髓剂量。对优化结果的比较显示,与传统的基于PTV保证金的计划相比,强大的优化计划具有更好的ITV剂量覆盖率,更好的CI,更差的HI和更低的OAR剂量。计划健壮性评估表明,D 99 ,D 98 和D 95 的干扰剂量至少满足ITV的99%接受了95%的处方剂量。还观察到,基于PTV保证金的计划具有比健壮的优化计划更高的MU。结果还表明,强大的优化可以生成增加OAR保留的计划,尤其是对于正常肺和目标附近或邻接目标的OAR。在正常肺部剂量和目标大小之间发现弱相关性,在这项研究中未观察到其他相关性。

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