首页> 外文期刊>Medical dosimetry: official journal of the American Association of Medical Dosimetrists >Determination of peripheral underdosage at the lung-tumor interface using Monte Carlo radiation transport calculations
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Determination of peripheral underdosage at the lung-tumor interface using Monte Carlo radiation transport calculations

机译:使用蒙特卡洛辐射传输计算确定肺肿瘤界面周围的剂量不足

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Prediction of dose distributions in close proximity to interfaces is difficult. In the context of radiotherapy of lung tumors, this may affect the minimum dose received by lesions and is particularly important when prescribing dose to covering isodoses. The objective of this work is to quantify underdosage in key regions around a hypothetical target using Monte Carlo dose calculation methods, and to develop a factor for clinical estimation of such underdosage. A systematic set of calculations are undertaken using 2 Monte Carlo radiation transport codes (egsnrc and geant4). Discrepancies in dose are determined for a number of parameters, including beam energy, tumor size, field size, and distance from chest wall. Calculations were performed for 1-mm 3 regions at proximal, distal, and lateral aspects of a spherical tumor, determined for a 6-MV and a 15-MV photon beam. The simulations indicate regions of tumor underdose at the tumor-lung interface. Results are presented as ratios of the dose at key peripheral regions to the dose at the center of the tumor, a point at which the treatment planning system (TPS) predicts the dose more reliably. Comparison with TPS data (pencil-beam convolution) indicates such underdosage would not have been predicted accurately in the clinic. We define a dose reduction factor (DRF) as the average of the dose in the periphery in the 6 cardinal directions divided by the central dose in the target, the mean of which is 0.97 and 0.95 for a 6-MV and 15-MV beam, respectively. The DRF can assist clinicians in the estimation of the magnitude of potential discrepancies between prescribed and delivered dose distributions as a function of tumor size and location. Calculation for a systematic set of "generic" tumors allows application to many classes of patient case, and is particularly useful for interpreting clinical trial data.
机译:很难预测界面附近的剂量分布。在对肺肿瘤进行放射治疗的情况下,这可能会影响病变所接受的最小剂量,并且在开处方剂量以覆盖等位基因时尤其重要。这项工作的目的是使用蒙特卡洛剂量计算方法对假设目标周围关键区域的剂量不足进行量化,并为这种剂量不足的临床估计开发一个因素。使用2个蒙特卡洛辐射传输代码(egsnrc和geant4)进行了系统的计算。确定许多参数的剂量差异,包括射束能量,肿瘤大小,视野大小和距胸壁的距离。针对6-MV和15-MV光子束,对球形肿瘤近端,远端和侧面的1-mm 3区域进行了计算。模拟表明在肿瘤-肺界面处肿瘤剂量不足的区域。结果以关键周围区域的剂量与肿瘤中心的剂量之比表示,在这一点上,治疗计划系统(TPS)更可靠地预测剂量。与TPS数据(铅笔束卷积)的比较表明,这种剂量不足在临床上无法准确预测。我们将剂量减少因子(DRF)定义为6个基本方向上外围剂量的平均值除以目标中的中心剂量,对于6-MV和15-MV束,其平均值分别为0.97和0.95 , 分别。 DRF可以帮助临床医生根据肿瘤的大小和位置来估计处方剂量和输送剂量之间潜在差异的大小。系统的一组“遗传性”肿瘤的计算可应用于多种类型的患者病例,并且对于解释临床试验数据特别有用。

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