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IMRT Beam Angle Optimization Using Electromagnetism-Like Algorithm

Conference paper
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 8580)

Abstract

The selection of appropriate beam irradiation directions in radiotherapy – beam angle optimization (BAO) problem – is very important for the quality of the treatment, both for improving tumor irradiation and for better organs sparing. However, the BAO problem is still not solved satisfactorily and, most of the time, beam directions continue to be manually selected in clinical practice which requires many trial and error iterations between selecting beam angles and computing fluence patterns until a suitable treatment is achieved. The objective of this paper is to introduce a new approach for the resolution of the BAO problem, using an hybrid electromagnetism-like algorithm with descent search to tackle this highly non-convex optimization problem. Electromagnetism-like algorithms are derivative-free optimization methods with the ability to avoid local entrapment. Moreover, the hybrid electromagnetism-like algorithm with descent search has a high ability of producing descent directions. A set of retrospective treated cases of head-and-neck tumors at the Portuguese Institute of Oncology of Coimbra is used to discuss the benefits of the proposed algorithm for the optimization of the BAO problem.

Keywords

Electromagnetism-like mechanism Descent Search IMRT Beam Angle Optimization 
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References

  1. 1.
    Aleman, D.M., Kumar, A., Ahuja, R.K., Romeijn, H.E., Dempsey, J.F.: Neighborhood search approaches to beam orientation optimization in intensity modulated radiation therapy treatment planning. J. Global Optim. 42, 587–607 (2008)CrossRefzbMATHMathSciNetGoogle Scholar
  2. 2.
    Aleman, D.M., Romeijn, H.E., Dempsey, J.F.: A response surface approach to beam orientation optimization in intensity modulated radiation therapy treatment planning. INFORMS J. Comput.: Computat. Biol. Med. Appl. 21, 62–76 (2009)CrossRefGoogle Scholar
  3. 3.
    Birbil, S.I., Fang, S.-C.: An electromagnetism-like mechanism for global optimization. J. Global Optim. 25, 263–282 (2003)CrossRefzbMATHMathSciNetGoogle Scholar
  4. 4.
    Birbil, S.I., Fang, S.C., Sheu, R.L.: On the convergence of a population-based global optimization algorithm. J. Global Optim. 30, 301–318 (2004)CrossRefzbMATHMathSciNetGoogle Scholar
  5. 5.
    Bortfeld, T., Schlegel, W.: Optimization of beam orientations in radiation therapy: some theoretical considerations. Phys. Med. Biol. 38, 291–304 (1993)CrossRefGoogle Scholar
  6. 6.
    Craft, D.: Local beam angle optimization with linear programming and gradient search. Phys. Med. Biol. 52, 127–135 (2007)CrossRefGoogle Scholar
  7. 7.
    Das, S.K., Marks, L.B.: Selection of coplanar or non coplanar beams using three-dimensional optimization based on maximum beam separation and minimized nontarget irradiation. Int. J. Radiat. Oncol. Biol. Phys. 38, 643–655 (1997)CrossRefGoogle Scholar
  8. 8.
    Deasy, J.O., Blanco, A.I., Clark, V.H.: CERR: A Computational Environment for Radiotherapy Research. Med. Phys. 30, 979–985 (2003)CrossRefGoogle Scholar
  9. 9.
    Dias, J., Rocha, H., Ferreira, B.C., Lopes, M.C.: A genetic algorithm with neural network fitness function evaluation for IMRT beam angle optimization. Cent. Eur. J. Oper. Res. (in press) doi:10.1007/s10100-013-0289-4Google Scholar
  10. 10.
    Ehrgott, M., Holder, A., Reese, J.: Beam selection in radiotherapy design. Linear Algebra Appl. 428, 1272–1312 (2008)CrossRefzbMATHMathSciNetGoogle Scholar
  11. 11.
    Lee, E.K., Fox, T., Crocker, I.: Integer programming applied to intensity-modulated radiation therapy treatment planning. Ann. Oper. Res. 119, 165–181 (2003)CrossRefzbMATHGoogle Scholar
  12. 12.
    Lee, E.K., Fox, T., Crocker, I.: Simultaneous beam geometry and intensity map optimization in intensity-modulated radiation therapy. Int. J. Radiat. Oncol. Biol. Phys. 64, 301–320 (2006)CrossRefGoogle Scholar
  13. 13.
    Li, Y., Yao, D., Yao, J., Chen, W.: A particle swarm optimization algorithm for beam angle selection in intensity modulated radiotherapy planning. Phys. Med. Biol. 50, 3491–3514 (2005)CrossRefGoogle Scholar
  14. 14.
    Liu, H.H., Jauregui, M., Zhang, X., Wang, X., Dongand, L., Mohan, R.: Beam angle optimization and reduction for intensity-modulated radiation therapy of non-small-cell lung cancers. Int. J. Radiat. Oncol. Biol. Phys. 65, 561–572 (2006)CrossRefGoogle Scholar
  15. 15.
    Pugachev, A., Xing, L.: Computer-assisted selection of coplanar beam orientations in intensity-modulated radiation therapy. Phys. Med. Biol. 46, 2467–2476 (2001)CrossRefGoogle Scholar
  16. 16.
    Pugachev, A., Xing, L.: Incorporating prior knowledge into beam orientation optimization in IMRT. Int. J. Radiat. Oncol. Biol. Phys. 54, 1565–1574 (2002)CrossRefGoogle Scholar
  17. 17.
    Rocha, A.M.A.C., Fernandes, E.M.G.P.: Modified movement force vector in an electromagnetism-like mechanism for global optimization. Opt. Methods Softw. 24, 253–270 (2009)CrossRefzbMATHMathSciNetGoogle Scholar
  18. 18.
    Rocha, A.M.A.C., Fernandes, E.M.G.P.: Numerical study of augmented Lagrangian algorithms for constrained global optimization. Optimization 60, 10–11 (2011)CrossRefMathSciNetGoogle Scholar
  19. 19.
    Rocha, H., Dias, J.M., Ferreira, B.C., Lopes, M.C.: Beam angle optimization for intensity-modulated radiation therapy using a guided pattern search method. Phys. Med. Biol. 58, 2939–2953 (2013)CrossRefGoogle Scholar
  20. 20.
    Rocha, H., Dias, J.M., Ferreira, B.C., Lopes, M.C.: Selection of intensity modulated radiation therapy treatment beam directions using radial basis functions within a pattern search methods framework. J. Global Optim. 57, 1065–1089 (2013)CrossRefzbMATHMathSciNetGoogle Scholar
  21. 21.
    Rocha, H., Dias, J.M., Ferreira, B.C., Lopes, M.C.: Pattern search methods framework for beam angle optimization in radiotherapy design. Appl. Math. Comput. 219, 10853–10865 (2013)CrossRefMathSciNetGoogle Scholar
  22. 22.
    Romeijn, H.E., Ahuja, R.K., Dempsey, J.F., Kumar, A., Li, J.: A novel linear programming approach to fluence map optimization for intensity modulated radiation therapy treatment planing. Phys. Med. Biol. 48, 3521–3542 (2003)CrossRefGoogle Scholar
  23. 23.
    Schreibmann, E., Lahanas, M., Xing, L., Baltas, D.: Multiobjective evolutionary optimization of the number of beams, their orientations and weights for intensity-modulated radiation therapy. Phys. Med. Biol. 49, 747–770 (2004)CrossRefGoogle Scholar
  24. 24.
    Stein, J., Mohan, R., Wang, X.H., Bortfeld, T., Wu, Q., Preiser, K., Ling, C.C., Schlegel, W.: Number and orientation of beams in intensity-modulated radiation treatments. Med. Phys. 24, 149–160 (1997)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.INESC-CoimbraCoimbraPortugal
  2. 2.Departmento de Produção e Sistemas, Algoritmi Research CentreUniversidade do MinhoBragaPortugal
  3. 3.Faculdade de EconomiaUniversidade de CoimbraCoimbraPortugal
  4. 4.I3N, Departamento de FísicaUniversidade de AveiroAveiroPortugal
  5. 5.Serviço de Física Médica, IPOC-FG, EPECoimbraPortugal

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