Skip to main content
SpringerLink
Log in

Optimization and Decision Support in Brachytherapy Treatment Planning

  • Chapter
Operations Research and Health Care

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 70))

  • 3004 Accesses

Summary

This chapter describes treatment planning optimization in brachytherapy and the design of a clinical decision support system. Brachytherapy refers to the placement of radioactive sources (seeds) inside a tumor site. The fundamental problem in treatment planning for brachytherapy is to determine where to place sources so as to deliver a sufficient radiation dose to kill the cancer, while limiting exposure of healthy tissue. We first present the sequence of steps that are involved in brachytherapy treatment planning. State-of-the-art mixed integer programming models are then described and some algorithmic approaches are outlined. The automated clinical decision support system allows for real-time generation of optimal seed configurations using ultrasound images acquired prior to seed implantation, and dynamic dose correction during the implantation process.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Interstitial Collaborative Working Group. (1990). Interstitial Brachytherapy. Physical, Biological, and Clinical Considerations. Raven Press, New York, 1990.

    Google Scholar 

  2. Sloboda, R.S. (1992). Optimization of brachytherapy dose distribution by simulated annealing. Medical Physics, 19, 964.

    Article  Google Scholar 

  3. Pouliot, J., D. Tremblay, J. Roy, and S. Filice (1996). Optimization of permanent I-125 prostate implants using fast simulated annealing. International Journal of Radiation Oncology Biology Physics, 36, 711–720.

    Article  CAS  Google Scholar 

  4. Yu, Y. and M.C. Schell (1996). A genetic algorithm for the optimization of prostate implants. Medical Physics, 23, 2085–2091.

    Article  ADS  PubMed  CAS  Google Scholar 

  5. Silvern, D.A., E.K. Lee, RJ. Gallagher, L.G. Stabile, R.D. Ennis, C.R. Moorthy, and M. Zaider (1997). Treatment planning for permanent prostate implants. Genetic algorithms versus integer programming. Medical and Biological Engineering Computing, 35, Suppl, Part 2, 850.

    Google Scholar 

  6. Gallagher, R.J. and E.K. Lee. (1997). Mixed integer programming optimization models for brachytherapy treatment planning. Proceedings of the American Medical Imaging Association Annual Fall Symposium, 278–282.

    Google Scholar 

  7. Silvern, D.A (1998). Automated OR prostate brachytherapy treatment planning using genetic optimization. PhD Dissertation, Columbia University, New York, NY.

    Google Scholar 

  8. Yang, G., L.E. Reinstein, S. Pai, Z. Xu, and D.L. Carroll. (1998). A new genetic algorithm technique in optimization of permanent I-125 prostate implants. Medical Physics, 25, 2308–2315.

    Article  ADS  PubMed  CAS  Google Scholar 

  9. Lee, E.K., RJ. Gallagher, D. Silvern, C.S. Wu, and M. Zaider (1999). Treatment planning for brachytherapy. An integer programming model, two computational approaches and experiments with permanent prostate implant planning. Physics in Medicine and Biology, 44, 145–165.

    Article  ADS  PubMed  CAS  Google Scholar 

  10. Lee, E.K. and M. Zaider (2003). Mixed integer programming approaches to treatment planning for brachytherapy. Annals of Operations Research, Optimization in Medicine, 119, 147–163.

    Article  Google Scholar 

  11. Anderson, L.L., R. Nath, A.J. Olch, et al. (1991). American Endocurietherapy Society recommendations for dose specifications in brachytherapy. Endocurietherapy Hypertherm Oncolology, 7, 1.

    Google Scholar 

  12. Brahme, A. (1995). Optimization of the 3-dimensional dose delivery and tomotherapy. International Journal of Imaging Systems and Technology, 6, 1.

    Article  Google Scholar 

  13. Zaider, M., M. Zelefsky, E.K. Lee, K. Zakian, H.A. Amols, J. Dyke, and J. Koutcher (2000). Treatment planning for prostate implants using MR spectroscopy imaging. International Journal of Radiation Oncology Biology Physics, 47, 1085–96.

    Article  CAS  Google Scholar 

  14. Lee, E.K. and M. Zaider (2001). Determining an effective planning volume for permanent prostate implants. International Journal of Radiation Oncology Biology Physics, 49, 1197–1206.

    Article  CAS  Google Scholar 

  15. Lee, E.K. and M. Zaider (2003). Intra-operative dynamic dose optimization in permanent prostate implants. International Journal of Radiation Oncology Biology Physics, 56, 854–861.

    Article  Google Scholar 

  16. Wuu, C.S. and M. Zaider (1998). A calculation of the relative biological effectiveness of 125I and 103Pd brachytherapy sources using the concept of proximity function. Medical Physics, 25, 2186–2189.

    Article  ADS  PubMed  CAS  Google Scholar 

  17. Wuu, C.S., P. Kliauga, M. Zaider, and H.I. Amols (1996). Microdosimetric evaluation of relative biological effectiveness for 103Pd, 125I, 241Am, and 192Ir brachytherapy sources. International Journal of Radiation Oncology, Biology, Physics, 36, 689–697.

    Article  PubMed  CAS  Google Scholar 

  18. Ling, C.C., W.X. Li, and L.L. Anderson (1995). The relative biological effectiveness of I-125 and Pd-103. International Journal of Radiation Oncology, Biology, Physics, 32, 373–378.

    Article  PubMed  CAS  Google Scholar 

  19. Nath, R., A.S. Meigooni, and A. Melillo (1992). Some treatment planning considerations for pd-103 and I-125 permanent interstitial implants. International Journal of Radiation Oncology, Biology, Physics, 22, 1131–1138.

    Article  PubMed  CAS  Google Scholar 

  20. Zellmer, D.L., J.D. Shadley, and M.T. Gillin (1994). Comparisons of measured biological response and predictions from microdosimetric data applicable to brachytherapy. Radiation Protection Dosimetry, 52, 395–403.

    CAS  Google Scholar 

  21. Zellmer, D.L., M.T. Gillin, and J.F. Wilson (1992). Microdosimetric single event spectra of yb-169 compared with commonly used brachytherapy sources and teletherapy beams. International Journal of Radiation Oncology, Biology, Physics, 23, 627–632.

    Article  PubMed  CAS  Google Scholar 

  22. International Commission on Radiation Units and Measurements (1980). Radiation Quantities and Units. International Commission on Radiation Units and Measurements, Washington, DC.

    Google Scholar 

  23. Lee, E.K. (2001). Branch-and-bound methods. In Mauricio, G.C., Resende, Pardalos, P.M., Eds., Handbook of Applied Optimization. Oxford University Press, New York.

    Google Scholar 

  24. Schrijver, A. (1986) Theory of Linear and Integer Programming. Wiley, Chichester, UK.

    Google Scholar 

  25. Nemhauser, G.L. and L.A. Wolsey (1988). Integer and Combinatorial Optimization. Wiley, New York.

    Google Scholar 

  26. Parker, R.G. and R.L. Rardin (1988). Discrete Optimization. Academic Press, Boston, MA.

    Google Scholar 

  27. Holland, J.H. (1974). Erratum. Genetic algorithms and the optimal allocation of trials. SIAM Journal on Computing, 3, 326.

    Article  MathSciNet  Google Scholar 

  28. Holland, J.H. (1973). Genetic algorithms and the optimal allocation of trials. SIAM Journal on Computing, 2, 88–105.

    Article  MATH  MathSciNet  Google Scholar 

  29. Buckles, B.P. and F. Petry (1992). Genetic Algorithms. IEEE Computer Society Press, Los Alamitos, CA.

    Google Scholar 

  30. Wasserman, P.D. (1993). Advanced Methods in Neural Computing. Van Nostrand Reinhold, New York.

    Google Scholar 

  31. Aarts, E.H.L. and J. Korst (1989). Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing. Wiley, Chichester, UK.

    Google Scholar 

  32. Kirkpatrick, S., C.D. Gelatt, and M.P. Vecchi (1983). Optimization by simulated annealing. Science, 220, 671–680.

    Article  ADS  MathSciNet  Google Scholar 

  33. Cerny, V. (1985). Thermodynamical approach to the traveling salesman problem. An efficient simulation algorithm. Journal of Optimization Theory and Applications, 45, 41–51.

    Article  MATH  MathSciNet  Google Scholar 

  34. Metropolis, N.A., A. Rosenbluth, M. Rosenbluth, A. Teller, and E. Teller (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21, 1087–1092.

    Article  CAS  Google Scholar 

  35. Aarts, E.H.L., J.H.M. Korst, and J.K. Lenstra (1997). Simulating annealing 8. In Aarts, E.H.L. and J.K. Lenstra, Eds., Local Search in Combinatorial Optimization. Wiley, Chichester, UK, 91–120.

    Google Scholar 

  36. Hajek, B. (1985). A tutorial of theory and applications of simulated annealing. Proceedings of the 24th Conference on Decision and Control, 755–759.

    Google Scholar 

  37. Anderson, LL. (1993). Plan optimization and dose evaluation in brachytherapy. Seminars in Radiation Oncology, 3, 290–300.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, 30332

    Eva K. Lee

  2. Department of Radiation Oncology, Emory University, Atlanta, GA, 30322

    Eva K. Lee

  3. Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY, 10021

    Marco Zaider

Authors
  1. Eva K. Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marco Zaider
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Stanford University, USA

    Margaret L. Brandeau

  2. Georgia Institute of Technology, USA

    François Sainfort

  3. University of California at Los Angeles, USA

    William P. Pierskalla

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer Science + Business Media, Inc.

About this chapter

Cite this chapter

Lee, E.K., Zaider, M. (2005). Optimization and Decision Support in Brachytherapy Treatment Planning. In: Brandeau, M.L., Sainfort, F., Pierskalla, W.P. (eds) Operations Research and Health Care. International Series in Operations Research & Management Science, vol 70. Springer, Boston, MA. https://doi.org/10.1007/1-4020-8066-2_28

Download citation

  • DOI: https://doi.org/10.1007/1-4020-8066-2_28

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-7629-9

  • Online ISBN: 978-1-4020-8066-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation