基于蒙卡算法的乳腺癌术中放疗模型的剂量学优化

目的：探讨蒙特卡罗算法在乳腺癌术中放疗（IORT）模型剂量学优化中的应用价值。方法采用MCTP的MCBEAM程序建立乳腺癌术中放疗模型，利用MCSIM程序对患者术前CT模拟术中影像模型进行剂量计算，分析其剂量学特点，并对靶区剂量进行优化。结果通过蒙卡计算，优化的乳腺癌术中放疗模型方案为：靶区表面添加2-3 mm等效材料，靶区后缘添加5 mm等效材料再加2 mm铅板，这可以使90%以上等剂量线包绕整个靶区，同时可以消除＞110%的热点区域，肺最大剂量＜1 Gy。结论蒙特卡罗算法在乳腺癌IORT模型剂量学优化中的应用能显著提高IORT靶区剂量的计算精度，优化剂量分布，值得临床推广。

Dose Optimization of IORT Model for Breast Cancer Based on Monte Carlo Algorithm

Objective To explore the value of Monte Carlo algorithm in the dose optimization of IORT model for breast cancer. Methods The IORT model for breast cancer was established with MCTP MCBEAM program. Then the dose calculation of the intraoperative image simulated by CT was conducted with MCBEAM program to analyze the dosimetric characteristics and optimize the target dose. Results Based on Monte Carlo calculation, the optimization scheme of IORT model for breast cancer was designed as the follow： adding 2-3 mm equivalent material on the target surface and adding 5 mm equivalent material and 2 mm lead plate on the trailing edge of the target. Thus the entire target region can be surrounded by more than 90% isodose line and more than 110% hot region can be eliminated while the maxium dose of the lung is less than 1 Gy. Conclusion The application of Monte Carlo algorithm in the dose optimization of IORT model for breast cancer can significantly improve the calculation precision of the target dose and optimize the dose distribution, which indicates that Monte Carlo algorithm is worth to be promoted in clinic.