An automated bi-level optimization approach for IMRT

被引:3
作者
Carrasqueira, P. [1 ]
Alves, M. J. [1 ,2 ]
Dias, J. M. [1 ,2 ]
Rocha, H. [1 ,2 ]
Ventura, T. [1 ,3 ]
Ferreira, B. C. [1 ,4 ]
Lopes, M. C. [1 ,3 ]
机构
[1] Univ Coimbra, INESCC, Rua Silvio Lima, P-3030290 Coimbra, Portugal
[2] Univ Coimbra, FEUC, CeBER, Av Dias Silva 165, P-3004512 Coimbra, Portugal
[3] EPE, IPOC FG, Av Bissaya Barreto 98, P-3000075 Coimbra, Portugal
[4] Univ Lisbon, Fac Sci, IBEB, Campo Grande, P-1749016 Lisbon, Portugal
关键词
bi-level optimization; derivative-free optimization; noncoplanar IMRT; automated treatment planning; BEAM ANGLE OPTIMIZATION; PATTERN SEARCH METHODS; EVOLUTIONARY OPTIMIZATION; ORIENTATION OPTIMIZATION; FRAMEWORK; ALGORITHM; SELECTION;
D O I
10.1111/itor.13068
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Intensity-modulated radiation therapy is used worldwide to treat cancer patients. The objective of this treatment is to deliver a prescribed radiation dose to the tumor while sparing, as much as possible, all the healthy tissues, especially organs at risk (OAR). This means that the planning of a radiotherapy treatment should take into consideration conflicting objectives: to be able to spare as much as possible the OAR guaranteeing, at the same time, that the desired radiation is delivered to the volumes to treat. While the volumes to treat can be adequately irradiated from almost any set of directions, the radiation directions that are chosen have a determinant impact on the OAR. This means that those directions that provide an improved OAR sparing should be selected. The choice of radiation directions (beam angles) can thus be interpreted as being fundamentally determined by the OAR, with the radiation intensities associated with each of these directions being determined by the needed radiation to be delivered to the volumes to treat. In this work, we interpret the radiotherapy treatment planning problem as a bi-level optimization problem. At the upper level, OAR control the choice of the beam angles, which are selected aiming at OAR sparing. At the lower level, the optimal radiation intensities are decided by the volumes to treat, considering the beam angle ensemble obtained at the upper level. The proposed bi-level approach was tested using 10 clinical head-and-neck cancer cases already treated at the Portuguese Institute of Oncology in Coimbra.
引用
收藏
页码:224 / 238
页数:15
相关论文
共 50 条
  • [31] Bi-level optimization based on fuzzy if-then rule
    Singh, Vishnu Pratap
    Chakraborty, Debjani
    CROATIAN OPERATIONAL RESEARCH REVIEW, 2019, 10 (02) : 315 - 328
  • [32] A Bi-level optimization approach to reduce the pollution burden of lake water with ecological compensation
    He, Linhuan
    Yao, Liming
    Varbanov, Petar Sabev
    ECOLOGICAL INDICATORS, 2023, 151
  • [33] A Bi-Level Optimization Formulation of Priority Service Pricing
    Mou, Yuting
    Papavasiliou, Anthony
    Chevalier, Philippe
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2020, 35 (04) : 2493 - 2505
  • [34] A robust bi-level optimization modelling approach for municipal solid waste management; a real case study of Iran
    Pouriani, Sepideh
    Asadi-Gangraj, Ebrahim
    Paydar, Mohammad Mahdi
    JOURNAL OF CLEANER PRODUCTION, 2019, 240
  • [35] Functional deep echo state network improved by a bi-level optimization approach for multivariate time series classification
    Huang, Zhaoke
    Yang, Chunhua
    Chen, Xiaofang
    Zhou, Xiaojun
    Chen, Guo
    Huang, Tingwen
    Gui, Weihua
    APPLIED SOFT COMPUTING, 2021, 106
  • [36] Automated Audio Data Augmentation Network Using Bi-Level Optimization for Sound Event Localization and Detection
    Zhang, Wenjie
    Yu, Peng
    Yin, Jun
    Jiang, Xiaoheng
    Xu, Mingliang
    IEEE SIGNAL PROCESSING LETTERS, 2024, 31 : 2770 - 2774
  • [37] A bi-level transformation based evolutionary algorithm framework for equality constrained optimization
    Chen, Lei
    Liu, Haosen
    Liu, Hai-Lin
    Gu, Fangqing
    MEMETIC COMPUTING, 2022, 14 (04) : 423 - 432
  • [38] Deep convolutional neural network architecture design as a bi-level optimization problem
    Louati, Hassen
    Bechikh, Slim
    Louati, Ali
    Hung, Chih-Cheng
    Said, Lamjed Ben
    NEUROCOMPUTING, 2021, 439 : 44 - 62
  • [39] A Competitive Approach for Bi-level Co-evolution
    Kieffer, Emmanuel
    Danoy, Gregoire
    Bouvry, Pascal
    Nagih, Anass
    2018 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW 2018), 2018, : 609 - 618
  • [40] Centralized Spatial and Temporal Decomposition Charging Strategy for Electric Vehicles: A Bi-level Optimization Approach
    Zhao, Tianyang
    Zhang, LeiLei
    Liu, Wenxia
    Zhang, Jianhua
    Liu, ZongQi
    2014 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO (ITEC) ASIA-PACIFIC 2014, 2014,