Advertisement

Influence of Sampling in Radiation Therapy Treatment Design

  • Humberto Rocha
  • Joana M. Dias
  • Brigida C. Ferreira
  • Maria do Carmo Lopes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6784)

Abstract

Computer-based optimization simulations have made significant contributions to the improvement of intensity modulated radiation therapy (IMRT) treatment planning. Large amounts of data are typically involved in radiation therapy optimization problems. Regardless the formulation used, the problem size is always the biggest challenge to overcome. The most common strategy to address this problem is sampling which may have a significant impact on the quality of the results. There are few studies on sampling for optimization in radiation therapy, mostly devoted to propose new sampling approaches that accelerate IMRT optimization. However, the gain in computational time comes at a cost: as sampling becomes progressively coarse, the quality of the solution deteriorates. A clinical example of a head and neck case is used to discuss the influence of sampling in radiation therapy treatment design, emphasizing the influence on parotid sparing. Procedures on the choice of the most adequate sample rate are highlighted.

Keywords

OR in medicine radiotherapy sampling mathematical models optimization inverse planning 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Acosta, R., Ehrgott, M., Holder, A., Nevin, D., Reese, J., Salter, B.: Comparing beam selection strategies in radiotherapy treatment design: the influence of dose point resolution. In: Alves, C., Pardalos, P., Vicente, L.N. (eds.) Optimization in Medicine. Springer Optimization and Its Applications, pp. 1–24. Springer, New York (2008)CrossRefGoogle Scholar
  2. 2.
    Ai-dong, W., Yi-can, W., Sheng-xiang, T., Jiang-hui, Z.: Effect of CT Image-based Voxel Size On Monte Carlo Dose Calculation. In: Proc. 27th Annu. Conf. Engineering in Medicine and Biology, pp. 6449–6451. IEEE Press, Shanghai (2006)Google Scholar
  3. 3.
    Bahr, G.K., Kereiakes, J.G., Horwitz, H., Finney, R., Galvin, J., Goode, K.: The method of linear programming applied to radiation treatment planning. Radiology 91, 686–693 (1968)CrossRefGoogle Scholar
  4. 4.
    Borffeld, T.: IMRT: a review and preview. Phys. Med. Biol. 51, 363–379 (2006)CrossRefGoogle Scholar
  5. 5.
    Censor, Y.: Mathematical optimization for the inverse problem of intensity-modulated radiation therapy. In: Palta, J.R., Mackie, T.R. (eds.) Intensity-Modulated Radiation Therapy: The State of The Art, American Association of Physicists in Medicine (AAPM). Medical Physics Monograph, vol. (29), pp. 25–49. Medical Physics Publishing, Wisconsin (2003)Google Scholar
  6. 6.
    Cheong, K., Suh, T., Romeijn, H., Li, J., Dempsey, J.: Fast Nonlinear Optimization with Simple Bounds for IMRT Planning. Med. Phys. 32, 1975 (2005)CrossRefGoogle Scholar
  7. 7.
  8. 8.
    Craft, D., Halabi, T., Shih, H., Bortfeld, T.: Approximating convex Pareto surfaces in multiobjective radiotherapy planning. Med. Phys. 33, 3399–3407 (2006)CrossRefGoogle Scholar
  9. 9.
    Deasy, J.O., Blanco, A.I., Clark, V.H.: CERR: A Computational Environment for Radiotherapy Research. Med. Phys. 30, 979–985 (2003)CrossRefGoogle Scholar
  10. 10.
    Deasy, J.O., Lee, E.K., Bortfeld, T., Langer, M., Zakarian, K., Alaly, J., Zhang, Y., Liu, H., Mohan, R., Ahuja, R., Pollack, A., Purdy, J., Rardin, R.: A collaboratory for radiation theraphy planning optimization research. Ann. Oper. Res. 148, 55–63 (2006)CrossRefzbMATHGoogle Scholar
  11. 11.
    Ehrgott, M., Guler, C., Hammacher, H.W., Shao, L.: Mathematical optimization in intensity modulated radiation therapy. 4OR 6, 199–262 (2008)CrossRefzbMATHMathSciNetGoogle Scholar
  12. 12.
    Ferris, M.C., Lim, J.-H., Shepard, D.M.: Optimization approaches for treatment planning on a Gamma Knife. SIAM J. Optim. 13, 921–937 (2003)CrossRefzbMATHGoogle Scholar
  13. 13.
    Ferris, M.C., Lim, J.-H., Shepard, D.M.: Radiosurgery treatment planning via nonlinear programming. Ann. of Oper. Res. 119, 247–260 (2003)CrossRefzbMATHGoogle Scholar
  14. 14.
    Ferris, M.C., Einarsson, R., Jiang, Z., Shepard, D.M.: Sampling issues for optimization in radiotherapy. Ann. of Oper. Res. 148, 95–115 (2006)CrossRefzbMATHGoogle Scholar
  15. 15.
    Holder, A., Salter, B.: A tutorial on radiation oncology and optimization. In: Greenber, H. (ed.) Emerging Methodologies and Applications in Operations Research. Kluwer Academic Press, Boston (2004)Google Scholar
  16. 16.
    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
  17. 17.
    Lee, E.K., Fox, T., Crocker, I.: Integer programing applied to intensity-modulated radiation therapy treatment planning. Ann. Oper. Res. 119, 165–181 (2003)CrossRefzbMATHGoogle Scholar
  18. 18.
    Lim, G.J., Ferris, M.C., Wright, S.J., Shepard, D.M., Earl, M.A.: An optimization framework for conformal radiation treatment planning. INFORMS J. Comput. 19, 366–380 (2007)CrossRefzbMATHMathSciNetGoogle Scholar
  19. 19.
    Lim, G.J., Lee, E.K.: Optimization in Medicine and Biology. Auerbach Publications, Taylor and Francis, New York (2008)CrossRefGoogle Scholar
  20. 20.
    Lim, G.J., Choi, J., Mohan, R.: Iterative solution methods for beam angle and fluence map optimization in intensity modulated radiation therapy planning. OR Spectrum 30, 289–309 (2008)CrossRefzbMATHMathSciNetGoogle Scholar
  21. 21.
    Martin, B.C., Bortfeld, T.R., Castanon, D.A.: Accelerating IMRT optimization by voxel sampling. Phys. Med. Biol. 52, 7211–7228 (2007)CrossRefGoogle Scholar
  22. 22.
    MATLAB, The MathWorks Inc., http://www.mathworks.com
  23. 23.
    Misic, V.V., Aleman, D.M., Sharpe, M.B.: Neighborhood search approaches to non-coplanar beam orientation optimization for total marrow irradiation using IMRT. Eur. J. Oper. Res. 3, 522–527 (2010)CrossRefzbMATHMathSciNetGoogle Scholar
  24. 24.
  25. 25.
    Preciado-Walters, F., Langer, M.P., Rardin, R.L., Thai, V.: Column generation for IMRT cancer therapy optimization with implementable segments. Ann. Oper. Res. 148, 65–79 (2006)CrossRefzbMATHGoogle Scholar
  26. 26.
    Rocha, H., Dias, J.M.: On the optimization of radiation therapy planning. Inescc Research Report (15/2009), http://www.inescc.pt/documentos/15_2009.PDF
  27. 27.
    Romeijn, H.E., Ahuja, R.K., Dempsey, J.F., Kumar, A.: A new linear programming approach to radiation therapy planning problems. Oper. Res. 54, 201–216 (2006)CrossRefzbMATHMathSciNetGoogle Scholar
  28. 28.
    Romeijn, H.E., Ahuja, R.K., Dempsey, J.F., Kumar, A.: A column generation approach to radiation therapy treatment planning using aperture modulation. SIAM J. Optim. 15, 838–862 (2005)CrossRefzbMATHGoogle Scholar
  29. 29.
    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
  30. 30.
    Romeijn, H.E., Dempsey, J.F., Li, J.: A unifying framework for multi-criteria fluence map optimization models. Phys. Med. Biol. 49, 1991–2013 (2004)CrossRefGoogle Scholar
  31. 31.
    Spirou, S., Chui, C.-S.: A gradient inverse planning algoritm with dose-volume constraints. Med. Phys. 25, 321–333 (1998)CrossRefGoogle Scholar
  32. 32.
    Thieke, C., Nill, S., Oelfke, U., Bortfeld, T.: Acceleration of intensity-modulated radiotherapy dose calculation by importance sampling of the calculation matrices. Med. Phys. 29, 676–681 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Humberto Rocha
    • 1
  • Joana M. Dias
    • 1
    • 2
  • Brigida C. Ferreira
    • 3
    • 4
  • Maria do Carmo Lopes
    • 4
  1. 1.INESC-CoimbraCoimbraPortugal
  2. 2.Faculdade de EconomiaUniversidade de CoimbraCoimbraPortugal
  3. 3.I3N, Departamento de FísicaUniversidade de AveiroAveiroPortugal
  4. 4.Serviço de Física MédicaIPOC-FG, EPECoimbraPortugal

Personalised recommendations