Department of Oncology (R), Division of Radiophysics (52AA), Copenhagen University Hospital Herlev, Herlev Ringvej 75, DK-2730 Herlev, Denmark.
Phys Med Biol. 2010 Aug 21;55(16):4521-33. doi: 10.1088/0031-9155/55/16/S07. Epub 2010 Jul 29.
The pencil beam dose calculation method is frequently used in modern radiation therapy treatment planning regardless of the fact that it is documented inaccurately for cases involving large density variations. The inaccuracies are larger for higher beam energies. As a result, low energy beams are conventionally used for lung treatments. The aim of this study was to analyze the advantages and disadvantages of dynamic IMRT treatment planning for high and low photon energy in order to assess if deviating from the conventional low energy approach could be favorable in some cases. Furthermore, the influence of motion on the dose distribution was investigated. Four non-small cell lung cancer cases were selected for this study. Inverse planning was conducted using Varian Eclipse. A total number of 31 dynamic IMRT plans, distributed amongst the four cases, were created ranging from PTV conformity weighted to normal tissue sparing weighted. All optimized treatment plans were calculated using three different calculation algorithms (PBC, AAA and MC). In order to study the influence of motion, two virtual lung phantoms were created. The idea was to mimic two different situations: one where the GTV is located centrally in the PTV and another where the GTV was close to the edge of the PTV. PBC is in poor agreement with MC and AAA for all cases and treatment plans. AAA overestimates the dose, compared to MC. This effect is more pronounced for 15 than 6 MV. AAA and MC both predict similar perturbations in dose distributions when moving the GTV to the edge of the PTV. PBC, however, predicts results contradicting those of AAA and MC. This study shows that PB-based dose calculation algorithms are clinically insufficient for patient geometries involving large density inhomogeneities. AAA is in much better agreement with MC, but even a small overestimation of the dose level by the algorithm might lead to a large part of the PTV being underdosed. It is advisable to use low energy as a default for tumor sites involving lungs. However, there might be situations where it is favorable to use high energy. In order to deviate from the recommended low energy convention, an accurate dose calculation algorithm (e.g. MC) should be consulted. The study underlines the inaccuracies introduced when calculating dose using a PB-based algorithm in geometries involving large density variations. PBC, in contrast to other algorithms (AAA and MC), predicts a decrease in dose when the density is increased.
铅笔束剂量计算方法在现代放射治疗计划中经常被使用,尽管它在涉及大密度变化的情况下记录不准确。对于更高的束能,这种不准确性更大。因此,传统上使用低能束进行肺部治疗。本研究旨在分析高、低光子能量的动态调强治疗计划的优缺点,以评估在某些情况下偏离传统的低能方法是否有利。此外,还研究了运动对剂量分布的影响。本研究选择了四个非小细胞肺癌病例。使用 Variar Eclipse 进行反向规划。在这四个病例中,共创建了 31 个动态调强计划,从 PTV 适形加权到正常组织保护加权分布。所有优化后的治疗计划都使用三种不同的计算算法(PBC、AAA 和 MC)进行计算。为了研究运动的影响,创建了两个虚拟肺体模。其目的是模拟两种不同的情况:一种是 GTV 位于 PTV 的中心,另一种是 GTV 靠近 PTV 的边缘。对于所有病例和治疗计划,PBC 与 MC 和 AAA 都存在很大差异。与 MC 相比,AAA 高估了剂量。对于 15 MV 比 6 MV,这种影响更为明显。当将 GTV 移动到 PTV 的边缘时,AAA 和 MC 都预测了剂量分布的相似扰动。然而,PBC 预测的结果与 AAA 和 MC 相反。本研究表明,对于涉及大密度不均匀性的患者几何形状,基于 PB 的剂量计算算法在临床上是不足的。AAA 与 MC 更一致,但即使算法对剂量水平的微小高估也可能导致 PTV 的很大一部分剂量不足。对于涉及肺部的肿瘤部位,建议使用低能作为默认值。然而,在某些情况下,使用高能可能是有利的。为了偏离推荐的低能常规,应该咨询准确的剂量计算算法(例如 MC)。本研究强调了在涉及大密度变化的几何形状中使用基于 PB 的算法计算剂量时引入的不准确性。与其他算法(AAA 和 MC)相比,PBC 预测当密度增加时剂量会降低。