• DocumentCode
    412732
  • Title

    A genetic algorithm approach to full beam configuration inverse planning in coplanar radiotherapy

  • Author

    Bevilacqua, Vitoantonio ; Mastronardi, Giuseppe ; Piscopo, Giuseppe

  • Author_Institution
    D.E.E., Politecnico di Bari, Italy
  • Volume
    3
  • fYear
    2003
  • fDate
    8-12 Dec. 2003
  • Firstpage
    2110
  • Abstract
    A unified evolutionary approach to coplanar radiotherapy inverse planning is proposed. It consists of a genetic algorithm-based framework that solves with little modification treatment planning for three different kinds of radiation therapy: conformal, so-called aperture-based and intensity modulated. Thanks to evolutionary optimisation techniques we have been able to search for full beam configurations, that is, beam intensity, beam shape and especially beam orientation. Unlike some previous works found in literature, our proposed solution automatically determines exact beam angles not relaying solely on a geometrical basis but involving beam intensity profiles, thus considering the effective delivered dose. Our dose distribution model has been validated through comparison with commercial system: fixed the same beam configuration, both calculated beam shapes and the DVH have been compared. Then we have tested the optimisation algorithm with real clinical cases: these involved both simple (convex target, far OARs) and complex (concave target, close OARs) ones. As stated by physician and by simulation with the same commercial system, our tools found good solutions in both cases using corresponding correct therapy.
  • Keywords
    dosimetry; genetic algorithms; optimisation; radiation therapy; beam angles; beam intensity; beam orientation; beam shape; commercial system; convex target; coplanar radiotherapy inverse planning; dose distribution model; evolutionary optimisation; full beam configuration inverse planning; full beam configurations; genetic algorithm; intensity modulated; optimisation algorithm; radiation therapy; treatment planning; unified evolutionary approach; Artificial neural networks; Biomedical applications of radiation; Evolutionary computation; Genetic algorithms; Intensity modulation; Medical treatment; Relays; Shape; Testing; Tumors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
  • Print_ISBN
    0-7803-7804-0
  • Type

    conf

  • DOI
    10.1109/CEC.2003.1299933
  • Filename
    1299933