IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v387y2020ics0096300319307787.html
   My bibliography  Save this article

Optimization model applied to radiotherapy planning problem with dose intensity and beam choice

Author

Listed:
  • Freitas, Juliana Campos de
  • Florentino, Helenice de Oliveira
  • Benedito, Antone dos Santos
  • Cantane, Daniela Renata

Abstract

Optimization applied to radiotherapy planning is a complex scientific issue seeking to deliver both possible highest dose into tumor tissue and lowest one into adjacent tissues. It is composed of one or more of the following main problems: beam choice, dose intensity and blades opening. In this paper, a mixed integer nonlinear optimization model is developed for radiation treatment planned by intensity modulated radiotherapy treatment involving both dose intensity and beam choice optimization problems. Moreover, metaheuristics proposed to solve the beam optimization problem are coupled with exact methods, which in turn solve the dose intensity problem. The proposed model is applied to two real computerized tomography images of prostate cases, where it has been shown to be highly efficient.

Suggested Citation

  • Freitas, Juliana Campos de & Florentino, Helenice de Oliveira & Benedito, Antone dos Santos & Cantane, Daniela Renata, 2020. "Optimization model applied to radiotherapy planning problem with dose intensity and beam choice," Applied Mathematics and Computation, Elsevier, vol. 387(C).
  • Handle: RePEc:eee:apmaco:v:387:y:2020:i:c:s0096300319307787
    DOI: 10.1016/j.amc.2019.124786
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300319307787
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2019.124786?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. H. Edwin Romeijn & Ravindra K. Ahuja & James F. Dempsey & Arvind Kumar, 2006. "A New Linear Programming Approach to Radiation Therapy Treatment Planning Problems," Operations Research, INFORMS, vol. 54(2), pages 201-216, April.
    2. Anibal Azevedo & Aurelio Oliveira & Secundino Soares, 2009. "Interior point method for long-term generation scheduling of large-scale hydrothermal systems," Annals of Operations Research, Springer, vol. 169(1), pages 55-80, July.
    3. Allen Holder & Bill Salter, 2005. "A Tutorial on Radiation Oncology and Optimization," International Series in Operations Research & Management Science, in: H J. G (ed.), Tutorials on Emerging Methodologies and Applications in Operations Research, chapter 0, pages 4-1-4-45, Springer.
    4. David G. Luenberger & Yinyu Ye, 2008. "Linear and Nonlinear Programming," International Series in Operations Research and Management Science, Springer, edition 0, number 978-0-387-74503-9, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hanif Malekpoor & Nishikant Mishra & Sameer Kumar, 2022. "A novel TOPSIS–CBR goal programming approach to sustainable healthcare treatment," Annals of Operations Research, Springer, vol. 312(2), pages 1403-1425, May.
    2. Shahmohammadi, Ali & Sioshansi, Ramteen & Conejo, Antonio J. & Afsharnia, Saeed, 2018. "Market equilibria and interactions between strategic generation, wind, and storage," Applied Energy, Elsevier, vol. 220(C), pages 876-892.
    3. Alp Atakan & Mehmet Ekmekci & Ludovic Renou, 2021. "Cross-verification and Persuasive Cheap Talk," Papers 2102.13562, arXiv.org, revised Apr 2021.
    4. Arthur Medeiros & Thales Ramos & José Tavares de Oliveira & Manoel F. Medeiros Júnior, 2020. "Direct Voltage Control of a Doubly Fed Induction Generator by Means of Optimal Strategy," Energies, MDPI, vol. 13(3), pages 1-28, February.
    5. Ivorra, Benjamin & Mohammadi, Bijan & Manuel Ramos, Angel, 2015. "A multi-layer line search method to improve the initialization of optimization algorithms," European Journal of Operational Research, Elsevier, vol. 247(3), pages 711-720.
    6. Tanaka, Ken'ichiro & Toda, Alexis Akira, 2015. "Discretizing Distributions with Exact Moments: Error Estimate and Convergence Analysis," University of California at San Diego, Economics Working Paper Series qt7g23r5kh, Department of Economics, UC San Diego.
    7. Ashrafi, M. & Khanjani, M.J. & Fadaei-Kermani, E. & Barani, G.A., 2015. "Farm drainage channel network optimization by improved modified minimal spanning tree," Agricultural Water Management, Elsevier, vol. 161(C), pages 1-8.
    8. Z. Taşkın & J. Smith & H. Romeijn, 2012. "Mixed-integer programming techniques for decomposing IMRT fluence maps using rectangular apertures," Annals of Operations Research, Springer, vol. 196(1), pages 799-818, July.
    9. Sergey Badikov & Antoine Jacquier & Daphne Qing Liu & Patrick Roome, 2016. "No-arbitrage bounds for the forward smile given marginals," Papers 1603.06389, arXiv.org, revised Oct 2016.
    10. Szidarovszky, Ferenc & Luo, Yi, 2014. "Incorporating risk seeking attitude into defense strategy," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 104-109.
    11. Giorgio, 2019. "On Second-Order Optimality Conditions in Smooth Nonlinear Programming Problems," DEM Working Papers Series 171, University of Pavia, Department of Economics and Management.
    12. Matthias Ehrgott & Çiğdem Güler & Horst Hamacher & Lizhen Shao, 2010. "Mathematical optimization in intensity modulated radiation therapy," Annals of Operations Research, Springer, vol. 175(1), pages 309-365, March.
    13. Csaba I. Fábián, 2021. "Gaining traction: on the convergence of an inner approximation scheme for probability maximization," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 491-519, June.
    14. Bouslah, B. & Gharbi, A. & Pellerin, R., 2016. "Integrated production, sampling quality control and maintenance of deteriorating production systems with AOQL constraint," Omega, Elsevier, vol. 61(C), pages 110-126.
    15. Rafał Wiśniowski & Krzysztof Skrzypaszek & Tomasz Małachowski, 2020. "Selection of a Suitable Rheological Model for Drilling Fluid Using Applied Numerical Methods," Energies, MDPI, vol. 13(12), pages 1-17, June.
    16. Martins Barros, Rafael & Guimarães Lage, Guilherme & de Andrade Lira Rabêlo, Ricardo, 2022. "Sequencing paths of optimal control adjustments determined by the optimal reactive dispatch via Lagrange multiplier sensitivity analysis," European Journal of Operational Research, Elsevier, vol. 301(1), pages 373-385.
    17. Yuichi Takano & Renata Sotirov, 2012. "A polynomial optimization approach to constant rebalanced portfolio selection," Computational Optimization and Applications, Springer, vol. 52(3), pages 645-666, July.
    18. Timothy C. Y. Chan & Tim Craig & Taewoo Lee & Michael B. Sharpe, 2014. "Generalized Inverse Multiobjective Optimization with Application to Cancer Therapy," Operations Research, INFORMS, vol. 62(3), pages 680-695, June.
    19. Wei Chen & Yixin Lu & Liangfei Qiu & Subodha Kumar, 2021. "Designing Personalized Treatment Plans for Breast Cancer," Information Systems Research, INFORMS, vol. 32(3), pages 932-949, September.
    20. Misic, V.V. & Aleman, D.M. & Sharpe, M.B., 2010. "Neighborhood search approaches to non-coplanar beam orientation optimization for total marrow irradiation using IMRT," European Journal of Operational Research, Elsevier, vol. 205(3), pages 522-527, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:387:y:2020:i:c:s0096300319307787. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.