《计算机应用研究》|Application Research of Computers

一种基于生物准则的IMRT方案优化方法

Plan optimization method of IMRT based on biological criteria

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作者 张丽媛,张鹏程,桂志国,舒华忠,杨婕
机构 1.中北大学 a.电子测试技术国家重点实验室;b.仪器科学与动态测试教育部重点实验室,太原 030051;2.东南大学 影像科学与技术实验室,南京 210096
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文章编号 1001-3695(2017)05-1303-05
DOI 10.3969/j.issn.1001-3695.2017.05.005
摘要 针对调强放射治疗方案优化中,物理准则无法准确描述生物组织在非均匀剂量分布下的生物反应的问题,提出了基于生物准则的方案优化方法。首先根据病人各组织的剂量约束条件,建立基于生物准则的方案优化目标函数;然后采用L-BFGS-B算法求解方案优化问题。实验结果表明,在保证靶区剂量覆盖率的同时,相较于基于物理准则的方案优化方法,该方案优化后的危及器官并发症概率下降6.86%;相较于采用L-BFGS算法进行方案优化,该方案优化后的危及器官并发症概率下降1.30%。分析实验结果可得,将生物因子引入方案优化,能够更精确地反映组织的生物效应;采用L-BFGS-B算法能够快速、精确地求解方案优化问题。
关键词 调强放射治疗;生物准则;L-BFGS-B;肿瘤控制率;正常组织并发症概率
基金项目 国家自然科学基金资助项目(61271357)
山西省自然科学基金资助项目(2015011046)
中北大学2013年校科学基金计划资助项目
本文URL http://www.arocmag.com/article/01-2017-05-005.html
英文标题 Plan optimization method of IMRT based on biological criteria
作者英文名 Zhang Liyuan, Zhang Pengcheng, Gui Zhiguo, Shu Huazhong, Yang Jie
机构英文名 1.a.NationalKeyLaboratoryforElectronicMeasurementTechnology,b.KeyLaboratoryofInstrumentationScience&DynamicMeasurement,NorthUniversityofChina,Taiyuan030051,China;2.LaboratoryofImageScience&Technique,SoutheastUniversity,Nanjing210096,China
英文摘要 Aiming at the problem that the physical indices cannot accurately describe the biological response, which is the bio-logical tissues under the non-uniform dose distribution for the plan optimization in the intensity modulated radiation therapy(IMRT), this paper described a new plan optimization method based on biological criteria. At first, the method established the objective function of the plan optimization based on biological criteria according to the dose constraints of various organizations in the patient’s. Then, it adopted the L-BFGS-B algorithm to solve the optimization problem. Experimented results show that, on the premise of guarantee the target dose coverage, compared with the plan optimization method based on physical criterion, the proposed method reduced the NTCP by 6.86%. Furthermore, the NTCP of the result optimized by the proposed method decreased by 1.30% compared with the method for solving the optimization problem by using the L-BFGS algorithm. The results show that the introduction of the biological factors into the plan optimization can reflects the biological effects more accurately. And using the L-BFGS-B algorithm can solve the problems of the plan optimization more quickly and accurately.
英文关键词 IMRT; biological criteria; L-BFGS-B; TCP; NTCP
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  [1] Bjarngard B, Kijewski P, Pashby C. Description of a computer controlled therapy machine[J] . International Journal of Radiation Oncology·Biology·Physics, 1977, 2(S2):142-143. [2] Wu Qiuwen, Mohan R, Niemierko A, et al. Optimization of intensity-modulated radiotherapy plans based on the equivalent uniform dose[J] . International Journal of Radiation Oncology·Biology·Physics, 2002, 52(1):224-235. [3] 朱健. 肿瘤调强放射治疗并发症预测模型[D] . 南京:东南大学, 2013. [4] Staverv P, Hirstov D, Warkentin B, et al. Inverse treatment planning by physically constrained minimization of a biological objective function[J] . Medical Physics, 2003, 30(11):2948-2958. [5] Choi B, Deasy J O. The generalized equivalent uniform dose function as a basis for intensity-modulated treatment planning[J] . Physics in Medicine and Biology, 2002, 47(20):3579-3589. [6] Romeijn H E, Dempsey J F, Li J G. A unifying framework for multi-criteria fluence map optimization models[J] . Physics in Medicine and Biology, 2004, 49(10):1991-2013. [7] Hoffmann A L, Siem A Y D, Den Hertog D, et al. Convex reformulation of biologically-based multi-criteria intensity-modulated radiation therapy optimization including fractionation effects[J] . Physics in Medicine and Biology, 2008, 53(22):6345-6362. [8] 张鹏程. 精确放射治疗剂量计算及方案优化方法研究[D] . 南京:东南大学, 2014. [9] Powell M J D. How bad are the BFGS and DFP methods when the objective function is quadratic?[J] . Mathematical Programming, 1985, 34(1):34-47. [10] Liu Dongchen, Nocedal J. On the limited memory BFGS method for large scale optimization[J] . Mathematical Programming, 1989, 45(3):503-528. [11] Byrd R H, Lu Peihuang, Nocedal J, et al. A limited memory algorithm for bound constrained optimization[J] . SIAM Journal on Scientific Computing, 1995, 16(5):1190-1208. [12] 孙小杨, 庞皓文, 杨波. 调强治疗计划中射野强度优化模型研究[J] . 泸州医学院学报, 2015(1):77-80. [13] Ei Naqa I, Suneja G, Lindsay P E, et al. Dose response explorer:an integrated open-source tool for exploring and modelling radiotherapy dose-volume outcome relationships[J] . Physics in Medicine and Biology, 2006, 51(22):5719-5736. [14] Niemierko A. Reporting and analyzing dose distributions:a concept of equivalent uniform dose[J] . Medical Physics, 1997, 24(1):103-110. [15] 廖雄飞, Yang J, Chen Y, 等. 等效均匀剂量优化法在肺癌调强放疗计划优化中的应用[J] . 肿瘤预防与治疗, 2012, 25(6):337-340. [16] Niemierko A. A generalized concept of equivalent uniform dose (EUD)[J] . Medical Physics, 1999, 26(6):1100. [17] 廖雄飞, Yang J, 黎杰, 等. 前列腺癌调强放疗计划等效均匀剂量法优化研究[J] . 中华放射肿瘤学杂志, 2013, 22(2):143-146. [18] 朱健, 白曈, 李宝生, 等. 肿瘤放疗并发症概率预测模型参数拟合方法[J] . 东南大学学报:自然科学版, 2015, 45(2):256-259. [19] Fowler J F. The linear-quadratic formula and progress in fractionated radiotherapy[J] . The British Journal of Radiology, 1989, 62(740):679-694. [20] Lyman J T. Complication probability as assessed from dose-volume histograms[J] . Radiation Research, 1985, 104(2s):13-19. [21] Kutcher G J, Burman C. Calculation of complication probability factors for non-uniform normal tissue irradiation:the effective volume method[J] . International Journal of Radiation Oncology·Biology·Physics, 1989, 16(6):1623-1630. [22] 朱健, 李宝生, 舒华忠, 等. 正常组织并发症概率模型综述[J] . 中国生物医学工程学报, 2014, 31(2):233-240. [23] Schultheiss T E, Orton C G, Peck R A. Models in radiotherapy:volume effects[J] . Medical Physics, 1983, 10(4):410-415. [24] Niemierko A. A unified model of tissue response to radiation[J] . Medical Physics, 1999, 26(6):1100. [25] 董云达. 数值优化引论[M] . 郑州:黄河水利出版社, 2007. [26] 周培德. 计算几何:算法设计与分析[M] . 北京:清华大学出版社, 2005. [27] Morales J L, Nocedal J. Remark on “Algorithm 778:L-BFGS-B:Fortran subroutines for large-scale bound constrained optimization”[J] . ACM Trans on Mathematical Software, 2011, 38(1):Article No. 7. [28] Zhu Ciyou, Byrd R H, Lu Peihuang, et al. Algorithm 778:L-BFGS-B:Fortran subroutines for large-scale bound-constrained optimization[J] . ACM Trans on Mathematical Software, 1997, 23(4):550-560. [29] Kessler M L, Mcshan D L, Epelman M A, et al. Costlets:a generalized approach to cost functions for automated optimization of IMRT treatment plans[J] . Optimization and Engineering, 2005, 6(4):421-448. [30] Wu Qiuwen, Mohan R. Algorithms and functionality of an intensity modulated radiotherapy optimization system[J] . Medical Physics, 2000, 27(4):701-711. [31] Deasy J O, Blanco A I, Clark V H. CERR:a computational environment for radiotherapy research[J] . Medical Physics, 2003, 30(5):979-985. [32] Ahnesjo A, Saxner M, Trepp A. A pencil beam model for photon dose calculation[J] . Medical Physics, 1992, 19(2):263-273. [33] Marks L B, Yorke E D, Jackson A, et al. Use of normal tissue complication probability models in the clinic[J] . International Journal of Radiation Oncology·Biology·Physics, 2010, 76(3):S10-S19. [34] 刘武松, 宋争放, 卢冰, 等. 前列腺癌放疗技术的现状及新认识[J] . 四川医学, 2015(3):427-431.
收稿日期 2016/5/2
修回日期 2016/6/18
页码 1303-1307
中图分类号 TP391.7
文献标志码 A