摘要目的:分析不同剂量计算算法和不同射野设置对肺癌容积旋转调强计划(VMAT)的剂量学差异，为临床计划设计提供参考。方法:选择20例肺癌患者，分别设计4组VMAT计划：基于各向异性解析算法(AAA)的2野2弧(2F2A_AAA)、基于外照射光子剂量算法(AXB)射的2野2弧(2F2A_AXB)、基于蒙特卡罗算法(MC)的2野2弧(2F2A_MC)、基于MC算法的1野2弧(1F2A_MC)。分别对不同算法、不同射野设置的计划，在靶区覆盖、高量控制、剂量均匀性指数(HI)、适形性指数(CI)，以及危及器官(OARs)受照剂量进行评估。结果:3组不同算法的2F2A计划靶区结果表明，2F2A_MC在PGTV的 D1%和 V95%(受到95%处方剂量所包绕的靶区相对体积)上均优于2F2A_AAA( D1%： t＝－2.44， P＝0.03； V95%： z＝－2.04， P＝0.04)和2F2A_AXB( D1%： t＝2.34, P＝0.03; z＝－3.21， P<0.01)。2F2A_AXB在PGTV的CI表现上优于2F2A_AAA( z＝－3.66， P<0.01)，与2F2A_MC相当。就危及器官而言，2F2A_AXB和2F2A_MC全肺的 V5 Gy上分别较2F2A_AAA减少了0.68%( z＝－2.69， P＝0.01)和3.05%( z＝－3.52， P<0.01)。2F2A_AXB计划在全肺 Dmean为1 776.44 cGy，均优于2F2A_MC( t＝2.67， P＝0.02)和2F2A_AAA( t＝8.62， P<0.01)。2F2A_AXB的Body_5 mm在 V20 Gy相较于2F2A_AAA和2F2A_MC分别减少了1.45%( z＝－3.88， P<0.01)和2.01%( z＝－3.66, P<0.01)。而不同射野设置的两组计划结果表明，1F2A_MC在PTV1的CI和PTV2的HI上均优于2F2A_MC(CI: t＝2.61, P＝0.02; HI: z＝－2.20, P＝0.03)。1F2A_MC在全肺 Dmean相对于2F2A_MC增加了26.29 cGy( t＝2.28， P＝0.04)。 结论:在进行肺癌VMAT计划设计时，MC算法适用于靶区优先，AXB算法适用于危及器官优先；而仅有MC算法的情况下，靶区优先时推荐选择1F2A，危及器官优先时推荐选择2F2A。

abstractsObjective:To analyze the dosimetric differences of volumetric modulated arc therapy (VMAT) plans for lung cancer caused by different dose calculation algorithms and radiation field settings and thus to provide a reference for designing clinical VMAT plans for lung cancer.Methods:This study randomly selected 20 patients with lung cancer and divided them into four groups of VMAT plans, namely, a group adopting two fields and two arcs based on the AAA algorithm (2F2A_AAA), a group employing two fields and two arcs based on the AXB algorithm (2F2A_AXB), a group using two fields and two arcs based on the MC algorithm (2F2A_MC), and a group adopting one field and two arcs based on the MC algorithm (1F2A_MC). Then, this study evaluated the target coverage, high-dose control, dose homogeneity index (HI), conformity index (CI), and organs at risk (OARs) of the plans using different algorithms and radiation field settings.Results:The planning target volume (PTV) results of two fields combined with two arcs (2F2A) of three groups using different algorithms are as follows. 2F2A_MC achieved better results in both D1% and V 95% (the relative volume of the target volume surrounded by 95% of the prescribed dose) of planning gross target volume (PGTV) than 2F2A_AAA (D1%: t=-2.44, P=0.03; V95%:z=-2.04, P=0.04) and 2F2A_AXB (D1%: t=2.34, P=0.03; z=-3.21, P < 0.01). 2F2A_AXB outperformed 2F2A_AAA ( z=-3.66, P < 0.01) and was comparable to 2F2A_MC in terms of the CI of PGTV. Regarding OARs, 2F2A_AXB and 2F2A_MC decreased the V5 Gy of the whole lung by 0.68% ( z=-2.69, P=0.01) and 3.05% ( z=-3.52, P < 0.01), respectively compared to 2F2A_AAA. 2F2A_AXB achieved a whole-lung Dmean of 1776.44 cGy, which was superior to that of 2F2A_MC ( t=2.67, P=0.02) and 2F2A_AAA ( t=8.62, P < 0.01). Compared to 2F2A_AAA and 2F2A_MC, 2F2A_AXB decreased the V20 Gy of Body_5 mm by 1.45% ( z=-3.88, P < 0.01) and 2.01% ( z=-3.66, P < 0.01), respectively. The results of the two groups with different field settings showed that 1F2A_MC was superior to 2F2A_MC in both the CI of PTV1 and the HI of PTV2 (CI: t=2.61, P=0.02; HI: z=-2.20, P=0.03). Moreover, 1F2A_MC increased the Dmean of the whole lung by 26.29 cGy compared to 2F2A_MC ( t=2.28, P=0.04). Conclusions:Regarding the design of VMAT plans for lung cancer, the MC algorithm is suitable for the target priority and the AXB algorithm is suitable for the OAR priority. When only the MC algorithm is available, it is recommended to choose 1F2A in the case of target priority and select 2F2A in the case of OAR priority.