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A Tutorial on Radiation Oncology and Optimization

In: Tutorials on Emerging Methodologies and Applications in Operations Research

Author

Listed:
  • Allen Holder

    (Trinity University)

  • Bill Salter

    (University of Texas Health Science Center)

Abstract

Designing radiotherapy treatments is a complicated and important task that affects patient care, and modern delivery systems enable a physician more flexibility than can be considered. Consequently, treatment design is increasingly automated by techniques of optimization, and many of the advances in the design process are accomplished by a collaboration among medical physicists, radiation oncologists, and experts in optimization. This tutorial is meant to aid those with a background in optimization in learning about treatment design. Besides discussing several optimization models, we include a clinical perspective so that readers understand the clinical issues that are often ignored in the optimization literature. Moreover, we discuss many new challenges so that new researchers can quickly begin to work on meaningful problems.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:isochp:978-0-387-22827-3_4
    DOI: 10.1007/0-387-22827-6_4
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    Citations

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    Cited by:

    1. Luke Mason & Vicky Mak-Hau & Andreas Ernst, 2015. "A parallel optimisation approach for the realisation problem in intensity modulated radiotherapy treatment planning," Computational Optimization and Applications, Springer, vol. 60(2), pages 441-477, March.
    2. 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).
    3. 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.

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