中华放射医学与防护杂志  2022, Vol. 42 Issue (9): 671-677   PDF    
算法和射野设置对肺癌容积旋转调强计划的剂量学影响
郑万佳1 , 黎恩廷2 , 黄思娟3 , 朱韵婷4 , 连锦兴5 , 王明理3 , 黄晓延3 , 杨鑫3     
1. 中国人民解放军南部战区空军医院肿瘤科,广州 510050;
2. 广州新华学院生物医学工程学院,广州 510520;
3. 中山大学肿瘤防治中心 华南肿瘤学国家重点实验室 肿瘤医学协同创新中心 广东省鼻咽癌诊治研究重点实验室放疗科,广州 510060;
4. 广州市妇女儿童医疗中心神经内科,广州 510623;
5. 广州中医药大学第一附属医院放疗科,广州 510000
[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%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1776.44 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_5mm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。
[关键词] 肺癌    容积旋转调强放疗    射野设置    剂量计算    
Dosimetric effects of volumetric modulated arc therapy plans for lung cancer caused by different dose algorithms and radiation field settings
Zheng Wanjia1 , Li Enting2 , Huang Sijuan3 , Zhu Yunting4 , Lian Jinxing5 , Wang Mingli3 , Huang Xiaoyan3 , Yang Xin3     
1. Department of Oncology, Southern Theater Air Force Hospital of the People's Liberation Army, Guangzhou 510050, China;
2. Department of Biomedical Engineering, Guangzhou Xinhua College, Guangzhou 510520, China;
3. Department of Radiotherapy, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou 510060;
4. Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou 510623, China;
5. Department of Radiotherapy, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510000, China
[Abstract] Objective 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 V95%(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.
[Key words] Lung cancer    Volume modulated arc therapy    Irradiation field setting    Dose calculation algorithms    Dose difference analysis    

目前被广泛用于临床的容积旋转调强治疗技术(volume modulated arc therapy, VMAT)包括瑞典医科达公司的VMAT,以及美国瓦里安公司的RapidArc等。VMAT因其良好的剂量分布和靶区适形性,被越来越多的运用于临床放射治疗[1-4]。VAMT使用Monaco计划系统进行剂量计算,该计划系统采用了蒙特卡罗(MC)算法[5]。而RapidArc使用Eclipse计划系统进行剂量计算,该计划系统具有各向异性解析算法(anisotropic analytical algorithm, AAA)[6]和先进外照射光子剂量算法(acuros XB external beam algorithm, AXB)[7]两种算法。多项剂量学对比研究表明,AXB与MC的一致性要优于AAA与MC的一致性,特别在肺和其他非均匀介质中,AXB比AAA能提供更好的适形度和均匀性[8-13]。与AAA、MC相比,AXB在临床中使用的剂量学性能和计算速度方面具有更好的平衡性[14]

而在临床实践中,除了算法的影响,VMAT计划的优化还取决于各组计划参数的选择。例如弧的数目、射野数目等。Monaco提供了每野设置弧数的技术,1个照射野最多可设置4个弧。黄思娟等[15]的研究表明Monaco上1野2弧(1F2A)的放疗计划较1野1弧(1F1A)、2野2弧(2F2A),具备更优的靶区适形性和均匀性,同时1F2A计划对于直肠、膀胱等危及器官(organ at risk, OAR)有比较好的保护。还有研究结果显示,1F1A和1F2A计划在宫颈癌靶区和危及器官各指标上差异无统计学意义,但1F2A计划在保证剂量输出通过率的前提下,能显著减少计划实施时间[16]

为了探究不同算法和不同射野设置对肺癌VMAT计划的剂量学影响,本研究回顾性分析了20例肺癌患者,比较了不同算法的2F2A计划以及在MC算法下,1F2A与2F2A计划之间的剂量学差异,以期为肺癌放射治疗计划的设定提供参考。

资料与方法

1. 病例资料:回顾性入组2015-2018年中山大学肿瘤防治中心初诊无转移肺癌患者20例。排除既往手术史使得解剖结构发生明显改变,以及扫描图像有明显伪影的患者。其中男14例,女6例,中位年龄62岁。本研究所使用的病例资料、临床数据与实验结果,均已上传至RDD (Research Data Deposit,www.researchdata.org.cn) 平台,并通过审核(RDDA2019001188)。

2. 图像采集:所有患者仰卧位,双手上举,采用真空垫固定。使用荷兰Philips Brilliance Big Bore 16排大孔径CT模拟机扫描定位,将CT图像传输到Monaco(Version 5.11.03)。

3. 靶区勾画和处方剂量:在Monaco进行靶区以及危及器官勾画后,再将CT图像以及结构文件传输到Eclipse(Version 13.6)。

大体肿瘤靶区(gross target volume,GTV)为影像学可见的原发肿瘤。临床靶区(clinical target volume,CTV)为GTV外扩6 mm和涉及的淋巴结区域(CTV1包含了高危淋巴结引流区,CTV2包含了低危引流区和锁上引流区)。计划靶区(planning gross target volume,PGTV)为GTV外扩0.5~0.8 cm; PTV1和PTV2分别为CTV1和CTV2分别外扩0.5~0.8 cm所得[17]。其中:PGTV为6 500 cGy,PTV1为6 000 cGy,PTV2为4 500 cGy,总次数为26次。治疗计划设计过程中靶区和危及器官(OAR)的剂量符合美国国立综合癌症网络(NCCN)指南(Version 2.2021)[18]以及本中心的临床要求。

4. 靶区计划设计:为比较不同算法(MC、AAA、AXB)的2F2A计划,以及同一算法(MC)的1F2A和2F2A计划之间的剂量学差异,在Monaco的射野设置界面中设置每野内的弧数,至多每野可选择4个弧。分别在Monaco上设计(1F2A_MC和2F2A_MC) VMAT计划,每个弧设置为全弧,初始角度180°,小机头设置角度为15°。两组计划均基于具有160片Agility MLC、5 mm叶片宽度的Versa HD直线加速器,能量为6 MV,最大输出剂量率为600 MU/min。全部计划均采用MC算法进行剂量计算。

在Eclipse分别设计AAA算法(2F2A_AAA)、AXB算法(2F2A_AXB) 的2野2弧VMAT计划(181°~179°),小机头同样设置角度为15°。两组计划均基于120片(60对)多叶光栅(MLC),中心40对叶片宽度仅为5 mm,其他叶片为10 mm的Trilogy直线加速器,采用6 MV光子线和600 MU/min的最大剂量率。

5. 计划评估:所有计划均按照PGTV处方的95%覆盖进行归一后评估。

靶区的评价指标:1%的靶区体积所受到的剂量(D1%);受到95%和105%处方剂量所包绕的靶区相对体积(V95%V105%);以及平均剂量Dmean;均匀性指数(homogeneity index, HI)[19]和适形度指数(conformity index, CI)[20]。其中,

$ \mathrm{HI}=\frac{D_{2 \%}-D_{98 \%}}{D_{50 \%}} $ (1)
$ \mathrm{CI}=\frac{V_{\text {target 95% }}{ }^2}{V_{\text {target }} \times V_{\text {body 95% }}} $ (2)

式中,D2%D98%D50%分别为2%、98%、50%的靶区体积所受到的剂量。HI值越接近0,表示靶区剂量均匀性越好。Vtarget95%为95%处方剂量所包绕的靶区绝对体积;Vtarget为靶区绝对体积;Vbody95%为95%处方剂量所包绕的所有区域的绝对体积。CI值越接近1,表示适形度越好。

OAR的评价指标:食管(Dmax),全肺(V5 GyV20 GyV30 GyDmean),心脏(V20 GyV30 Gy),脊髓外扩3 mm(Dmax),Body_5 mm(V10 GyV20 GyV30 Gy)。其中,Body_5 mm为Body减去靶区外扩5 mm后剩下的体积。

6. 统计学处理:采用SPSS 26.0软件,首先对所有数据(靶区剂量、CI、HI、OAR剂量)进行正态性检验,其中,符合正态分布采用配对t检验,不符合正态分布的指标采用Wilcoxon符号秩和检验的统计方法。所得的剂量资料均用x±s表示。P < 0.05为差异有统计学意义。

结果

1. 不同算法2F2A的VMAT计划的剂量学差异:根据表 1可知,在相同射野和弧数设置(2F2A)的情况下,不同算法(MC、AAA、AXB)的结果。

表 1 不同计划靶区和危及器官的剂量 Table 1 Dose of different plans concerning targets and OARs

(1) 靶区剂量学差异:2F2A_MC在靶区上D1%均低于2F2A_AAA(PGTV:t=-2.44,P=0.03。同时,2F2A_MC在PGTV(t=2.34, P=0.03)和PTV1 (t=-2.11, P=0.04)的D1%上,也低于2F2A_AXB。在PTV1(z=2.21, P=0.03)和PTV2(z=-2.73, P=0.03)上,2F2A_AXB较2F2A_AAA降低了D1%。而在高剂量体积的表现上,2F2A_AAA的V105%在PGTV(与2F2A_MC: z=-2.09, P=0.04;与2F2A_AXB:z=-2.70, P=0.01)和PTV2(与2F2A_MC:z=-3.51, P < 0.01;与2F2A_AXB:z=-2.73, P=0.01)上均高于其他两组计划。仅在PTV1的V105%上,2F2A_AAA低于2F2A_MC(z=-3.02, P < 0.01)而高于2F2A_AXB(z=-1.89, P=0.04),且2F2A_AXB和2F2A_MC之间差异具有统计学意义(z=-3.14, P=0.02)。

2F2A_MC在PGTV (z=-2.04,P=0.04)和PTV1(z=-3.23,P < 0.01)的V95%均高于2F2A_AAA。其中,在PTV1上,2F2A_MC较2F2A_AXB的V95%高了1.90%(z=-3.21,P < 0.01)。2F2A_AAA(t=-2.75,P=0.01)和2F2A_AXB(t=0.27,P=0.03)在PGTV的Dmean上均高于2F2A_MC,在PTV1(t=5.58,P < 0.01)和PTV2(t=5.96,P=0.03)上,2F2A_AXB的Dmean均低于2F2A_AAA,且在PTV2上,2F2A_MC的Dmean较2F2A_AAA减少了66.97 cGy(z=-2.35,P=0.02)。

2F2A_AXB在靶区的CI表现上,略优于2F2A_AAA(PGTV: z=-3.66,P < 0.01。其中,2F2A_AXB(0.521)在PGTV上的CI略高于2F2A_MC (z=-2.02, P=0.04)。在靶区的剂量均匀性上,3组计划在PGTV上两两之间差异均无统计学意义(P>0.05)。2F2A_MC在PTV1的HI为0.20,较2F2A_AXB减少了0.05(z=-3.92,P < 0.01)。在PTV2上,2F2A_AXB的HI较2F2A_MC减少了0.028(z=-3.70,P < 0.01)。

(2) 危及器官剂量学差异:对于全肺的V5 Gy,2F2A_AXB和2F2A_MC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),但2F2A_AXB和2F2A_MC之间差异无统计学意义(P>0.05)。而在全肺V20 Gy上,2F2A_AAA较2F2A_MC减少了2.66%(z=-3.15,P=0.04)。3组计划在全肺V30 Gy上两两之间差异具有统计学意义(2F2A_MC与2F2A_AAA:z=-3.52,P < 0.01;2F2A_MC与2F2A_AXB:z=-3.52,P < 0.01;2F2A_AAA与2F2A_AXB:z=-2.69,P=0.01),其中2F2A_AXB的V30 Gy最低,为18.59%。2F2A_AXB减少了全肺Dmean,较2F2A_MC和2F2A_AAA分别减少了50.65 (t=2.67,P=0.02)和27.16 cGy(t=8.62,P < 0.01)。

食管的最大剂量Dmax在三者之间差异无统计意义(P>0.05)。对于心脏的保护,2F2A_AAA较2F2A_MC和2F2A_AXB的V20 Gy分别增加了2.01%和3.12%;而对于心脏V30 Gy,2F2A_AAA仍较2F2A_AXB增加了0.66% (t=4.11,P < 0.01),但2F2A_AAA和2F2A_MC在该指标上差异无统计学意义(P>0.05)。2F2A_AAA的脊髓Dmax为2202.24 cGy,高于2F2A_MC(z=-3.29,P=0.01)和2F2A_AXB(z=-3.17,P=0.02)。

对于非靶区体积剂量控制的表现,2F2A_AAA在Body_5mm的V10 Gy上显著高于2F2A_AXB(t=7.27,P < 0.01);2F2A_AAA较2F2A_AXB增加,而较2F2A_MC减少了Body_5 mm累计受到20和30 Gy剂量照射的体积,且三者两两之间差异具有统计学意义(2F2A_MC与2F2A_AAA:V20 Gyz=-2.58,P=0.01,V30 Gyz=-2.13,P=0.03;2F2A_MC与2F2A_AXB:V20 Gyz=-3.66,P < 0.01,V30 Gyt=1.74,P=0.01;2F2A_AAA与2F2A_AXB:V20 Gyz=-3.88,P < 0.01,V30 Gyt=5.68,P < 0.01)。

2. 相同算法不同射野设置的VMAT计划剂量差异

(1) 靶区剂量学差异:1F2A_MC与2F2A_MC对靶区(PGTV/PTV1/PTV2)中D1%V95%V105%Dmean上,差异均无统计学意义(P>0.05)。但在PTV1适形度指标CI上,1F2A_MC(0.712)较2F2A_MC高了0.01(t=2.61, P=0.02);在PTV2的HI上,1F2A_MC与2F2A_MC的HI分别为0.45和0.46(z=-2.20, P=0.03)。

(2) 危及器官剂量学差异:在危及器官的保护上,1F2A_MC相对于2F2A_MC来说,对于全肺的V5 Gy(t=2.16,P=0.04)和Dmean(t=2.28,P=0.04)分别增加了0.92%和26.29 cGy。同时,对于Body_5 mm的V10 Gy来说,1F2A_MC较2F2A_MC的低剂量区增加了1.05%(t=3.08,P=0.01)。在其他器官以及全肺的其他指标上,两组计划的统计指标差异无统计学意义(P>0.05)。

讨论

本研究通过3组的2F2A计划对比来探究不同算法对VAMT计划的剂量学影响。结果表明,2F2A_ AAA增加了靶区的Dmean。这与以往研究结果,AAA算法在不均匀密度介质中可能会高估靶区的最大剂量和平均剂量[21-22]结论符合。而Klunklin等[23]的研究结果表明,MC算法在靶区覆盖上有优势。本研究发现,2F2A_MC确实在PTV1靶区V95%指标上有更好的表现。同时,2F2A_MC和2F2A_AXB较2F2A_AAA有更好的质量控制(V105%D1%)。在靶区CI上,2F2A_AXB略优于2F2A_AAA。3组计划在PGTV的HI上差异无统计学意义,但在PTV1上,2F2A_MC的HI值低于2F2A_AXB;而2F2A_AXB在PTV2均匀性略优于2F2A_MC。

使用VMAT技术可实现更好的肿瘤剂量适形性,但其代价是靶区附近正常组织低剂量体积的增加[24]。根据以往的研究,全肺的V20 Gy是放射性肺炎的最佳预测指标,而全肺V5 GyV30 Gy以及全肺平均剂量Dmean,也被认为与放射性肺炎的发生高度相关[25]。且根据RTOG 0617的临床实验结果,将V20 Gy控制在35%以下可以最大限度地减少出现放射性肺炎的风险[26]。本研究中4组计划全肺V20 Gy均 < 35%,Dmean均 < 20 Gy。结果表明,在不同算法的相同射野设置的情况下,2F2A_AXB显示出了其对肺部剂量控制的优势:在V5 GyV30 Gy以及Dmean上均优于2F2A_MC和2F2A_AAA;而2F2A_AAA较2F2A_MC降低了V20 Gy,但2F2A_AXB与其他两组计划在V20 Gy上差异无统计学意义。心脏剂量的增加与患者生存结果相关,例如,V30 Gy与较高的死亡率相关[26]。本研究的四组计划对于心脏的V30 Gy均 < 15%,均符合NCCN指南对于心脏V50 Gy < 25% 的建议[18]。其中,2F2A_AXB的V30 Gy最低,但其仅与2F2A_AAA差异具有统计学意义。本研究结果表明,2F2A_AXB较2F2A_MC和2F2A_AAA可能有利于减少Body_5 mm的受照剂量。

本研究还探究了不同射野设置对于肺癌VMAT计划的影响,结果表明,在相同算法的两组计划上,1F2A_MC和2F2A_MC在靶区的高剂量控制以及靶区覆盖上差异无统计学意义,但在靶区的剂量均匀性与适形性上,1F2A_MC略好于2F2A_MC。黄思娟等[15]比较了Monaco不同弧设置在前列腺癌放疗的剂量差异,结果表明,1F2A有更好的靶区剂量适形性和均匀性,本研究结果与此一致。而对于危及器官的保护,2F2A_MC较1F2A_MC更有优势,2F2A_MC较1F2A_MC可以降低全肺的平均剂量以及Body_5 mm的V10 Gy

在计划设计时,除了技术以及算法,所设置的机器模型以及机头角度等相关参数可能也会影响计划剂量分布。以往研究表明,不同宽度的MLC会对剂量产生影响[27]。黄娜等[28]研究结果表明,在靶区与危及器官空间距离很近,较小宽度的MLC有明显优势。而多项研究均表明改变准直器角度会对放疗计划剂量分布产生影响[29]。本研究中小机头旋转角度设置均为15°,分析不同类型的MLC以及不同MLC旋转角度对剂量分布的影响,是接下来可完善的工作。

值得进一步研究的是,心脏各子结构的剂量差异。本研究所讨论的心脏为整个心脏体积,而对于其临床重要子区域,如心包、冠状动脉以及其他的心脏子体积,均并未做分析。这是由于CT上很难准确区分心脏各子结构,且尚不明确由放射治疗引起的不良反应与心脏各子结构的相关关系[26]。目前没有关于心脏子体积相关剂量体积限制建议,但临床正常组织效应的定量分析(QUANTEC)报告提供了心包剂量限制建议,其平均剂量 < 26 Gy,及V30 Gy < 46%,使得心包炎发生风险低于15%。对于使用不同VMAT技术和不同设置对心脏各子结构剂量的影响,可作为继续研究的方向。

综上,本研究通过分析不同射野设置及不同剂量计算算法对肺癌的剂量学差异,为VMAT的计划设计提供了参考。在相同射野设置,而有MC, AXB和AAA多种算法可选择时,综合推荐选择AXB算法或MC算法进行肺癌的VMAT计划设计。但在具体的临床要求下,MC算法适用于靶区优先;而AXB算法适用于危及器官优先。当仅有MC算法的情况下,不同的射野设置可对应不同的临床情况,在靶区优先的情况下,推荐选择1F2A;而在危及器官优先的情况下,推荐选择2F2A。

利益冲突  无

作者贡献声明  郑万佳负责撰写论文、参与数据分析;黎恩廷负责数据分析、参与论文撰写;黄思娟负责Monaco计划设计、修改论文;朱韵婷负责数据收集;连锦兴参与论文修改;王明理负责Eclipse计划设计;黄晓延、杨鑫指导论文撰写和论文修改

参考文献
[1]
Xu Y, Deng W, Yang S, et al. Dosimetric comparison of the helical tomotherapy, volumetric-modulated arc therapy and fixed-field intensity-modulated radiotherapy for stage ⅡB-ⅢB non-small cell lung cancer[J]. Sci Rep, 2017, 7(1): 14863. DOI:10.1038/s41598-017-14629-w
[2]
Xhaferllari I, El-Sherif O, Gaede S. Comprehensive dosimetric planning comparison for early-stage, non-small cell lung cancer with SABR: fixed-beam IMRT versus VMAT versus tomotherapy[J]. J Appl Clin Med Phys, 2016, 17(5): 329-340. DOI:10.1120/jacmp.v17i5.6291
[3]
Jiang X, Li T, Liu Y, et al. Planning analysis for locally advanced lung cancer: dosimetric and efficiency comparisons between intensity-modulated radiotherapy (IMRT), single-arc/ partial-arc volumetric modulated arc therapy (SA/PA-VMAT)[J]. Radiat Oncol, 2011, 6: 140. DOI:10.1186/1748-717X-6-140
[4]
Akcay M, Etiz D, Duruer K, et al. Dosimetric comparison of single-arc/partial-arc volumetric modulated arc therapy and intensity-modulated radiotherapy for peripheral and central lung cancer[J]. J Cancer Res Ther, 2021, 17(1): 80-87. DOI:10.4103/jcrt.JCRT_221_19
[5]
Rogers DW. Fifty years of Monte Carlo simulations for medical physics[J]. Phys Med Biol, 2006, 51(13): R287-R301. DOI:10.1088/0031-9155/51/13/R17
[6]
Reis CQM, Nicolucci P, Fortes SS, et al. Effects of heterogeneities in dose distributions under nonreference conditions: Monte Carlo simulation vs dose calculation algorithms[J]. Med Dosim, 2019, 44(1): 74-82. DOI:10.1016/j.meddos.2018.02.009
[7]
Vassiliev ON, Wareing TA, Davis IM, et al. Feasibility of a multigroup deterministic solution method for three-dimensional radiotherapy dose calculations[J]. Int J Radiat Oncol Biol Phys, 2008, 72(1): 220-227. DOI:10.1016/j.ijrobp.2008.04.057
[8]
Srivastava RP, Basta K, De Gersem W, et al. A comparative analysis of Acuros XB and the analytical anisotropic algorithm for volumetric modulation arc therapy[J]. Rep Pract Oncol Radiother, 2021, 26(3): 481-488. DOI:10.5603/RPOR.a2021.0050
[9]
Fogliata A, Nicolini G, Clivio A, et al. Critical appraisal of Acuros XB and anisotropic analytic algorithm dose calculation in advanced non-small-cell lung cancer treatments[J]. Int J Radiat Oncol Biol Phys, 2012, 83(5): 1587-1595. DOI:10.1016/j.ijrobp.2011.10.078
[10]
Kairn T, Livingstone AG, Crowe SB. Monte Carlo calculations of radiotherapy dose in "homogeneous" anatomy[J]. Phys Med, 2020, 78: 156-165. DOI:10.1016/j.ejmp.2020.09.019
[11]
Pokhrel D, Sood S, Badkul R, et al. Assessment of Monte Carlo algorithm for compliance with RTOG 0915 dosimetric criteria in peripheral lung cancer patients treated with stereotactic body radiotherapy[J]. J Appl Clin Med Phys, 2016, 17(3): 277-293. DOI:10.1120/jacmp.v17i3.6077
[12]
Adachi T, Nakamura M, Kakino R, et al. Dosiomic feature comparison between dose-calculation algorithms used for lung stereotactic body radiation therapy[J]. Radiol Phys Technol, 2022, 15(1): 63-71. DOI:10.1007/s12194-022-00651-9
[13]
Tsuruta Y, Nakata M, Nakamura M, et al. Dosimetric comparison of Acuros XB, AAA, and XVMC in stereotactic body radiotherapy for lung cancer[J]. Med Phys, 2014, 41(8): 081715. DOI:10.1118/1.4890592
[14]
Padmanaban S, Warren S, Walsh A, et al. Comparison of Acuros (AXB)and anisotropic analytical algorithm (AAA)for dose calculation in treatment of oesophageal cancer: effects on modelling tumour control probability[J]. Radiat Oncol, 2014, 9: 286. DOI:10.1186/s13014-014-0286-3
[15]
黄思娟, 何立儒, 孙文钊, 等. Monaco不同设计模式及不同调强放疗技术对前列腺癌的剂量学比较[J]. 广东医学, 2018, 39(15): 2312-2315.
Huang SJ, He LR, Sun WZ, et al. Dosimetric comparison of different Monaco design modes and different intensity-modulated radiotherapy techniques for prostate cancer[J]. Guangdong Med, 2018, 39(15): 2312-2315. DOI:10.13820/j.cnki.gdyx.20180809.001
[16]
薛涛, 何晓阳, 孙云川, 等. MONACO放疗计划系统VMAT计划照射野Arc数目对治疗计划影响的比较分析[J]. 中国医疗设备, 2019, 34(9): 74-76, 84.
Xue T, He XY, Sun YC, et al. Comparative analysis of the effect of arcs per beam of VMAT on the treatment plan in MONACO treatment planning system[J]. Chin Med Equip, 2019, 34(9): 74-76, 84. DOI:10.3969/j.issn.1674-1633.2019.09.019
[17]
Zhao H, Ren D, Liu H, et al. Comparison and discussion of the treatment guidelines for small cell lung cancer[J]. Thorac Cancer, 2018, 9(7): 769-774. DOI:10.1111/1759-7714.12765
[18]
Ettinger DS, Wood DE, Aisner DL, et al. NCCN guidelines insights: non-small cell lung cancer, version 2.2021[J]. J Natl Compr Canc Netw, 2021, 19(3): 254-266. DOI:10.6004/jnccn.2021.0013
[19]
International Commission on Radiation Units and Measurements. ICRU Report No. 83. Prescribing, recording and reporting photon beam intensity-modulated radiation therapy (IMRT) [R]. Bethesda: ICRU, 2010.
[20]
International commission on Radiation Units and Measurements ICRU Report No. 91. Prescribing, recording and reporting of stereotactic treatments with small photon beams[R]. Bethesda: ICRU, 2014.
[21]
Bufacchi A, Caspiani O, Rambaldi G, et al. Clinical implication in the use of the AAA algorithm versus the AXB in nasopharyngeal carcinomas by comparison of TCP and NTCP values[J]. Radiat Oncol, 2020, 15(1): 150. DOI:10.1186/s13014-020-01591-7
[22]
Hasenbalg F, Neuenschwander H, Mini R, et al. Collapsed cone convolution and analytical anisotropic algorithm dose calculations compared to VMC++ Monte Carlo simulations in clinical cases[J]. Phys Med Biol, 2007, 52(13): 3679-3691. DOI:10.1088/0031-9155/52/13/002
[23]
Klunklin P, Manoharn T, Wanwilairat S, et al. Analysis of the planned, delivered dose distributions and quality assurance for helical tomotherapy and volumetric modulated arc therapy in locally advanced non-small cell lung cancer[J]. Rep Pract Oncol Radiother, 2021, 26(6): 939-947. DOI:10.5603/RPOR.a2021.0113
[24]
Palma DA, Senan S, Tsujino K, et al. Predicting radiation pneumonitis after chemoradiation therapy for lung cancer: an international individual patient data meta-analysis[J]. Int J Radiat Oncol Biol Phys, 2013, 85(2): 444-450. DOI:10.1016/j.ijrobp.2012.04.043
[25]
Cheung EYW, Kwong VHY, Chan FYC, et al. Modified VMAT plans for locally advanced centrally located non-small cell lung cancer (NSCLC)[J]. Life (Basel), 2021, 11(10): 1085. DOI:10.3390/life11101085
[26]
Smyth G, Evans PM, Bamber JC, et al. Recent developments in non-coplanar radiotherapy[J]. Br J Radiol, 2019, 92(1097): 20180908. DOI:10.1259/bjr.20180908
[27]
Murtaza G, Shamshad M, Ahmed M, et al. Dosimetric sensitivity of leaf width on volumetric modulated arc therapy plan quality: an objective approach[J]. Rep Pract Oncol Radiother, 2022, 27(1): 76-85. DOI:10.5603/RPOR.a2022.0001
[28]
黄娜, 王培, 张德康, 等. 应用AAPM标准模体评估MLC宽度对VMAT计划的影响[J]. 中华放射肿瘤学杂志, 2016, 25(4): 376-380.
Huang N, Wang P, Zhang DK, et al. Influence of multileaf collimator leaf width on volumetric modulated arc therapy plans evaluated on AAPM standard phantom[J]. Chin J Radiat Oncol, 2016, 25(4): 376-380. DOI:10.3760/cma.j.issn.1004-4221.2016.04.015
[29]
Murtaza G, Mehmood S, Silvia Favretto M, et al. Optimal VMAT delivery for Elekta MLC beam modulator: a study of collimator rotation for head and neck planning[J]. J Med Imaging Radiat Sci, 2020, 51(2): 289-298. DOI:10.1016/j.jmir.2020.02.001