[1]周云泷.不同剂量计算算法在晚期宫颈癌调强放疗计划中的比较[J].医学信息,2023,36(02):80-84.[doi:10.3969/j.issn.1006-1959.2023.02.016]
 ZHOU Yun-long.Comparison of Different Dose Calculation Algorithms in Intensity-Modulated Radiotherapy Plans for Advanced Cervical Cancer[J].Journal of Medical Information,2023,36(02):80-84.[doi:10.3969/j.issn.1006-1959.2023.02.016]
点击复制

不同剂量计算算法在晚期宫颈癌调强放疗计划中的比较()
分享到:

医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
36卷
期数:
2023年02期
页码:
80-84
栏目:
论著
出版日期:
2023-01-15

文章信息/Info

Title:
Comparison of Different Dose Calculation Algorithms in Intensity-Modulated Radiotherapy Plans for Advanced Cervical Cancer
文章编号:
1006-1959(2023)02-0080-05
作者:
周云泷
(江油市第二人民医院放疗科,四川 江油 621702)
Author(s):
ZHOU Yun-long
(Department of Radiation Oncology,Jiangyou Second People’s Hospital,Jiangyou 621702,Sichuan,China)
关键词:
调强放疗计划叠加算法快速叠加算法卷积算法
Keywords:
IMRT planSuperpositionalgorithmFast superposition algorithmConvolution algorithm
分类号:
R737.33
DOI:
10.3969/j.issn.1006-1959.2023.02.016
文献标志码:
A
摘要:
目的 比较CMS XIO 4.8计划系统中3种剂量计算算法在晚期宫颈癌调强放疗计划的剂量学差异。方法 选择江油市第二人民医院2018年1月-2020年12月接受放射治疗的25例晚期宫颈癌患者的调强放疗计划,均为系统默认的S算法,在射野方向、权重等设置条件不改变前提下,改用FS算法、卷积C算法进行重新计算。比较3种不同剂量计算算法计划的靶区和危及器官的剂量学参数、γ通过率、计划时间、治疗时间、机器跳数。结果 3种不同剂量计算算法靶区评估参数、危及器官评估参数比较,差异无统计学意义(P>0.05)。卷积C算法的计划计算时间短于S算法,差异有统计学意义(P<0.05)。3种不同剂量计算算法的单野和合成野γ通过率均在95%以上,组间比较,差异无统计学意义(P>0.05)。结论 3种不同剂量计算算法的靶区和危及器官剂量学参数和剂量验证无差异,但卷积C算法运算速度较S算法更快。因此,推荐卷积C算法在剂量精度没有显著变化的前提下,能够节约计划计算时间。
Abstract:
Objective To compare the dosimetric differences of three dose calculation algorithms in CMS XIO 4.8 treatment planning system for advanced cervical cancer.Methods The intensity-modulated radiotherapy plan of 25 patients with advanced cervical cancer who received radiotherapy from January 2018 to December 2020 in Jiangyou Second People ’s Hospital was selected. All of them were the default S algorithm of the system. Under the premise that the setting conditions such as field direction and weight did not change, FS algorithm and convolution C algorithm were used for recalculation. The dosimetric parameters, γ pass rate, planning time, treatment time and machine hops of the target area and organs at risk planned by three different dose calculation algorithms were compared.Results There was no significant difference in target area evaluation parameters and organ at risk evaluation parameters among the three different dose calculation algorithms (P>0.05). The planning calculation time of the convolution C algorithm was shorter than that of the S algorithm, and the difference was statistically significant (P<0.05). The γ passing rates of single field and synthetic field of the three different dose calculation algorithms were all above 95 %, and there was no significant difference among the three different dose calculation algorithms (P>0.05).Conclusion Because the dosimetry parameters and dose verification of all target areas and organs at risk of the three algorithms are not statistically different, the calculation speed of the convolution C algorithm is faster than that of the S algorithm. Therefore, the recommended convolution C algorithm can save the planning calculation time under the premise that the dose accuracy does not change significantly.

参考文献/References:

[1]Bray F,Ferlay J,Soerjomataram I,et al.Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J].CA Cancer J Clin,2018,68(6):394-424.[2]刘佳琪,李朋飞,纪妹,等.基于中国子宫颈癌临床诊疗大数据的子宫颈癌诊疗规范化调查分析[J].中国实用妇科与产科杂志,2021,37(1):82-86.[3]孟令昊,胥秋艳,李科,等.1990~2019年中国女性宫颈癌疾病负担变化的分析[J].中国循证医学杂志,2021,21(6):648-653.[4]Holt JG,Laughlin JS,Moroney JP.The extension of the concept of tissue-air ratios (TAR) to high-energy x-ray beams[J].Radiology,1970,96(2):437-46.[5]Xing Y,Nguyen D,Lu W,et al.Technical Note: A feasibility study on deep learning-based radiotherapy dose calculation[J].Med Phys,2020,47(2):753-758.[6]Akpochafor MO,Madu CB,Habeebu MY,et al.Development of pelvis phantom for verification of treatment planning system using convolution,fast superposition,and superposition algorithms[J].Journal of Clinical Sciences,2017,14(2):74.[7]Miften M,Wiesmeyer M,Monthofer S,et al.Implementation of FFT convolution and multigrid superposition models in the FOCUS RTP system[J].Physics in Medicine & Biology,2000,45(4):817-833.[8]Muralidhar KR,Murthy NP,Raju AK,et al.Comparative study of convolution, superposition, and fast superposition algorithms in conventional radiotherapy, three-dimensional conformal radiotherapy, and intensity modulated radiotherapy techniques for various sites, done on CMS XIO planning system[J].J Med Phys,2009,34(1):12-22.[9]García-Vicente F,Mi?觡ambres A,Jerez I,et al.Experimental validation tests of fast Fourier transform convolution and multigrid superposition algorithms for dose calculation in low-density media[J].Radiother Oncol,2003,67(2):239-249.[10]Kohno R,Kitou S,Hirano E,et al.Dosimetric verification in inhomogeneous phantom geometries for the XiO radiotherapy treatment planning system with 6-MV photon beams[J].Radiol Phys Technol,2009,2:87-96.[11]Chavaudra J,Bridier A.Definition of volumes in external radiotherapy: ICRU reports 50 and 62[J].Cancer Radiother,2001,5(5):472-478.[12]王琦,龚恋,严文广,等.旋转误差对直肠癌容积旋转调强放射治疗验证计划γ通过率的影响[J].中南大学学报(医学版),2020,45(9):1104-1108.[13]胡兴刚,熊盾,杨波,等.射野区域的剂量验证研究[J].中国医学物理学杂志,2020,37(1):44-48.[14]Figueira A,Monteiro A,Meireles P,et al.IMRT Plan Evaluation according to ICRU Report 83[J].Fuel & Energy Abstracts,2011,81(2):S849.[15]王磊,王晓梅,陈维平,等.调强放疗计划中两种不同剂量算法的比较[J].中国医学物理学杂志,2015,32(3):401-403.[16]Bragg CM,Wingate K,Conway J.Clinical implications of the anisotropic analytical algorithm for IMRT treatment planning and verification[J].Radiother Oncol,2008,86(2):276-284.[17]国家癌症中心/国家肿瘤质控中心.调强放疗剂量验证实践指南[J].中华放射肿瘤学杂志,2020,29(12):1021-1024.[18]郭妍妍,蒋胜鹏,戴越,等.治疗床及体位固定装置对放疗剂量精确性的影响及解决方法[J].国际生物医学工程杂志,2015,38(4):214-217.[19]郭跃信,裴运通,马阳光,等.IMRT不同剂量验证技术差异性分析[J].中华放射肿瘤学杂志,2017,26(6):657-660.[20]孔旭东,孔栋.MatriXX调强验证在精确放疗质量控制中的作用[J].中国医疗设备,2021,36(12):54-57,65.

更新日期/Last Update: 1900-01-01