验证 CyberKnife 多叶准直器的蒙特卡罗剂量计算算法。
Validation of Monte Carlo dose calculation algorithm for CyberKnife multileaf collimator.
机构信息
Institute of Radiation Physics, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.
Radio-Oncology Department, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.
出版信息
J Appl Clin Med Phys. 2022 Feb;23(2):e13481. doi: 10.1002/acm2.13481. Epub 2021 Dec 1.
PURPOSE
To commission and evaluate the Monte Carlo (MC) dose calculation algorithm for the CyberKnife equipped with a multileaf collimator (MLC).
METHODS
We created a MC model for the MLC using an integrated module of the CyberKnife treatment planning software (TPS). Two parameters could be optimized: the maximum energy and the source full width at half-maximum (FWHM). The optimization was performed by minimizing the differences between the measured and the MC calculated tissue phantom ratios and profiles. MLC plans were calculated in the TPS with the MC algorithm and irradiated on different phantoms. The dose was measured using an A1SL ionization chamber and EBT3 Gafchromic films, and then compared to the TPS dose to obtain dose differences (ΔD). Finally, patient-specific quality assurances (QA) were performed with global gamma index criteria of 3%/1 mm.
RESULTS
The maximum energy and source FWHM showing the best agreement with measurements were 6.4 MeV and 1.8 mm. The output factors calculated with these parameters gave an agreement within ±1% with measurements. The ΔD showed that MC model systematically underestimated the dose with an average of -1.5% over all configurations tested. For depths deeper than 12 cm, the ΔD increased, up to -3.0% (maximum at 15.5 cm depth).
CONCLUSIONS
The MC model for MLC of CyberKnife is clinically acceptable but underestimates the delivered dose by an average of -1.5%. Therefore, we recommend using the MC algorithm with the MLC only in heterogeneous regions and for shallow-seated tumors.
目的
委托并评估配备多叶准直器（MLC）的 CyberKnife 的蒙特卡罗（MC）剂量计算算法。
方法
我们使用 CyberKnife 治疗计划软件（TPS）的集成模块为 MLC 创建了一个 MC 模型。可以优化两个参数：最大能量和源半峰全宽（FWHM）。通过最小化测量值和 MC 计算的组织体模比和轮廓之间的差异来进行优化。使用 MC 算法在 TPS 中计算 MLC 计划，并在不同的体模上进行照射。使用 A1SL 电离室和 EBT3 Gafchromic 胶片测量剂量，然后与 TPS 剂量进行比较，以获得剂量差异（ΔD）。最后，使用 3%/1 mm 的全局伽马指数标准进行特定于患者的质量保证（QA）。
结果
与测量结果最吻合的最大能量和源 FWHM 分别为 6.4 MeV 和 1.8 mm。使用这些参数计算的输出因子与测量值的一致性在±1%以内。ΔD 表明 MC 模型系统地低估了剂量，所有测试配置的平均低估率为-1.5%。对于深度大于 12 cm 的区域，ΔD 增加，最大可达-3.0%（最大深度为 15.5 cm）。
结论
CyberKnife 的 MLC 的 MC 模型在临床上是可以接受的，但平均低估了 1.5%的剂量。因此，我们建议仅在异质区域和浅层肿瘤中使用 MLC 的 MC 算法。
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