An Accelerated Multistart Derivative-Free Framework for the Beam Angle Optimization Problem in IMRT

被引:0
|
作者
Rocha, Humberto [1 ,2 ]
Dias, Joana M. [1 ,2 ]
Ventura, Tiago [3 ]
Ferreira, Brigida C. [4 ]
Lopes, Maria do Carmo [3 ]
机构
[1] Univ Coimbra, Fac Econ, P-3004512 Coimbra, Portugal
[2] INESC Coimbra, P-3030290 Coimbra, Portugal
[3] EPE, IPOC FG, Serv Fis Med, P-3000075 Coimbra, Portugal
[4] Sch Allied Hlth Technol, P-4400330 Oporto, Portugal
关键词
IMRT; Beam angle optimization; Multistart; Derivative-free optimization; NEIGHBORHOOD SEARCH; SELECTION;
D O I
10.1007/978-3-319-42085-1_18
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Radiation therapy, either alone or combined with surgery or chemotherapy, is one of the main treatment modalities for cancer. Intensity-modulated radiation therapy (IMRT) is an advanced form of radiation therapy, where the patient is irradiated using non-uniform radiation fields from selected beam angle directions. The goal of IMRT is to eradicate all cancer cells by delivering a radiation dose to the tumor volume, while attempting to spare, simultaneously, the surrounding organs and tissues. Although the use of non-uniform radiation fields can favor organ sparing, the selection of appropriate irradiation beam angle directions - beam angle optimization - is the best way to enhance organ sparing. The beam angle optimization (BAO) problem is an extremely challenging continuous non-convex multi-modal optimization problem. In this study, we present a novel approach for the resolution of the BAO problem, using a multistart derivative-free framework for a more thoroughly exploration of the search space of the highly non-convex BAO problem. As the objective function that drives the BAO problem is expensive in terms of computational time, and a multistart approach typically implies a large number of function evaluations, an accelerated framework is explored. A clinical case of an intra-cranial tumor treated at the Portuguese Institute of Oncology of Coimbra is used to discuss the benefits of the accelerated multistart approach proposed for the BAO problem.
引用
收藏
页码:232 / 245
页数:14
相关论文
共 50 条
  • [1] A derivative-free multistart framework for an automated noncoplanar beam angle optimization in IMRT
    Rocha, Humberto
    Dias, Joana
    Ventura, Tiago
    Ferreira, Brigida
    Lopes, Maria do Carmo
    MEDICAL PHYSICS, 2016, 43 (10) : 5514 - 5526
  • [2] BEAM ANGLE OPTIMIZATION USING DERIVATIVE-FREE ALGORITHMS
    Rocha, H.
    Matos Dias, J.
    Costa Ferreira, B.
    Lopes, M. D. C.
    RADIOTHERAPY AND ONCOLOGY, 2011, 99 : S125 - S126
  • [3] A Derivative-Free Filter Driven Multistart Technique for Global Optimization
    Fernandes, Florbela P.
    Costa, M. Fernanda P.
    Fernandes, Edite M. G. P.
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2012, PT III, 2012, 7335 : 103 - 118
  • [4] Multilocal Programming: A Derivative-Free Filter Multistart Algorithm
    Fernandes, Florbela P.
    Costa, M. Fernanda P.
    Fernandes, Edite M. G. P.
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, PT I, 2013, 7971 : 333 - 346
  • [5] Beam Line Optimization using Derivative-Free Algorithms
    Appel, S.
    Reimann, S.
    10TH INTERNATIONAL PARTICLE ACCELERATOR CONFERENCE, 2019, 1350
  • [6] AN ACCELERATED METHOD FOR DERIVATIVE-FREE SMOOTH STOCHASTIC CONVEX OPTIMIZATION
    Gorbunov, Eduard
    Dvurechensky, Pavel
    Gasnikov, Alexander
    SIAM JOURNAL ON OPTIMIZATION, 2022, 32 (02) : 1210 - 1238
  • [7] A computational framework for derivative-free optimization of cardiovascular geometries
    Marsden, Alison L.
    Feinstein, Jeffrey A.
    Taylor, Charles A.
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2008, 197 (21-24) : 1890 - 1905
  • [8] Autotune: A Derivative-free Optimization Framework for Hyperparameter Tuning
    Koch, Patrick
    Golovidov, Oleg
    Gardner, Steven
    Wujek, Brett
    Griffin, Joshua
    Xu, Yan
    KDD'18: PROCEEDINGS OF THE 24TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING, 2018, : 443 - 452
  • [9] Stochastic derivative-free optimization using a trust region framework
    Larson, Jeffrey
    Billups, Stephen C.
    COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2016, 64 (03) : 619 - 645
  • [10] Stochastic derivative-free optimization using a trust region framework
    Jeffrey Larson
    Stephen C. Billups
    Computational Optimization and Applications, 2016, 64 : 619 - 645