Wangerin K, Culbertson C N, Jevremovic T
Laboratory for Neutronics and Geometry Computation, NEGE, School of Nuclear Engineering, Purdue University, West Lafayette, IN 47907, USA.
Health Phys. 2005 Aug;89(2):135-44. doi: 10.1097/01.hp.0000160545.46907.fe.
The goal of this study was to evaluate the COG Monte Carlo radiation transport code, developed and tested by Lawrence Livermore National Laboratory, for gadolinium neutron capture therapy (GdNCT) related modeling. The validity of COG NCT model has been established for this model, and here the calculation was extended to analyze the effect of various gadolinium concentrations on dose distribution and cell-kill effect of the GdNCT modality and to determine the optimum therapeutic conditions for treating brain cancers. The computational results were compared with the widely used MCNP code. The differences between the COG and MCNP predictions were generally small and suggest that the COG code can be applied to similar research problems in NCT. Results for this study also showed that a concentration of 100 ppm gadolinium in the tumor was most beneficial when using an epithermal neutron beam.
本研究的目的是评估由劳伦斯利弗莫尔国家实验室开发并测试的COG蒙特卡罗辐射传输代码，用于与钆中子俘获疗法（GdNCT）相关的建模。该模型已确定了COG NCT模型的有效性，在此将计算扩展到分析不同钆浓度对GdNCT模式的剂量分布和细胞杀伤效果的影响，并确定治疗脑癌的最佳治疗条件。将计算结果与广泛使用的MCNP代码进行了比较。COG和MCNP预测之间的差异通常较小，这表明COG代码可应用于NCT中的类似研究问题。本研究结果还表明，当使用超热中子束时，肿瘤中钆浓度为100 ppm最为有利。
