Acuros XB、各向异性解析算法与蒙特卡罗算法在非均匀组织中剂量计算准确性对比研究

发布时间：2018-06-06 14:20

本文选题：蒙特卡罗 + Acuros　；参考：《中国医学物理学杂志》2016年04期

【摘要】：目的:对比Acuros XB算法(AXB)、各向异性解析算法(AAA)和蒙特卡罗(MC)算法在非均匀组织中剂量计算准确性。方法:在Eclipse计划系统上分别设置两种类型的非均匀模体(水-肺-水模体、水-骨-水模体),并设定3个不同大小的0°照射野,源皮距=100 cm。采用AXB、AAA及MC算法进行剂量计算,提取射野中心轴百分深度剂量,以MC计算结果为基准,计算AXB和AAA两种算法与MC算法的相对偏差,提取非均匀组织及高梯度区(即4.5~15.5 cm)的数据做对比分析。结果:AXB算法3个射野相对偏差绝对值分别为4.186±1.451、0.834±0.300、0.726±0.165(水-肺-水模体)和1.694±0.374、1.325±0.328、0.343±0.244(水-骨-水模体)。AAA算法在两模体的对应值分别为6.679±4.694、4.151±1.789、4.353±2.546(肺)和3.270±0.826、5.971±1.587、2.406±0.574(骨)。采用配对样本t检验,P值均小于0.05。结论:在非均匀组织及其边界,AXB算法计算精度比AAA算法更为准确,基本接近MC算法。
[Abstract]:Aim: to compare the accuracy of the Acuros XB algorithm with that of the anisotropic analytical algorithm (AAA) and the Monte Carlo method (MC) in the dose calculation of inhomogeneous tissues. Methods: two types of inhomogeneous motifs (water-lung water motif, water-bone-water motif) were set up on Eclipse planning system, and three different 0 掳irradiation fields were set up, with a skin distance of 100 cm. The dose calculation was carried out by using AAA and MC algorithm. The relative deviation between AXB and AAA algorithms and MC algorithm was calculated based on MC calculation results. The data of non-uniform tissue and high gradient region (i.e. 4. 5 ~ 15. 5 cm) were extracted for comparative analysis. Results the absolute values of the relative deviations of the three ejection fields in the two models were 4.186 卤1.451n 0.834 卤0.300,0.726 卤0.165 (water-lung motif) and 1.694 卤0.374U 1.325 卤0.328C 0.343 卤0.244 (water bone-water motif. AAA = 6.679 卤4.694 卤1.789 卤4.353 卤2.546 (lung) and 3.270 卤0.8265.971 卤1.5872.406 卤0.574 respectively) in the two motifs. The absolute values of the relative deviations were 6.679 卤4.694 卤1.789 卤4.353 卤2.546 (lung) and 3.270 卤0.8265.971 卤1.5872.406 卤0.574 respectively. The P value of paired sample t test was less than 0.05. Conclusion: the accuracy of the AAA algorithm is more accurate than that of the AAA algorithm in the nonuniform structure and its boundary. It is close to the MC algorithm.
【作者单位】：佳木斯大学附属第一医院放化疗科;北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科/恶性肿瘤发病机制及转化研究教育部重点实验室;
【基金】：国家自然科学基金(11505012) 质检公益性行业科研专项(201510001-002) 北京市医院管理局“青苗”计划专项(QML20151004)
【分类号】：R730.55

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