The use of the Maximum Likelihood Estimator and the Dynamically Penalized Likelihood methods in inverse radiation therapy planning

  • Jorge Llacer
  • Timothy D. Solberg
  • Claus Promberger
  • Alexander Kuzmany
Conference paper

Abstract

In November 1997, the first author of this paper published a description of the Dynamically Penalized Likelihood (DPL) method of inverse therapy planning1. It responded to the evident need at that time to treat voxels corresponding to Organs at Risk (OAR) in a manner different from those of the Planning Target Volume (PTV) by specifying for the former a desired maximum dose, for example, but otherwise allowing those voxels complete freedom to receive any dose lower than that maximum. Since that time, that need has been recognized by other workers, with perhaps the most used algorithm that incorporates that thinking being that of Spirou and Chui2. Since 1997 the DPL has evolved considerably and we feel that it is now nearly ready to be used in therapy in conjunction with a commercial therapy planning software package. This paper will describe the present form of the DPL, give a brief description of its theoretical foundation and describe its use together with the Maximum Likelihood Estimator (MLE) in order to achieve a useful degree of controllability. Two examples (a relatively “easy” and a “difficult” one) and the corresponding results will be given to facilitate the description of the algorithm.

Keywords

Adenoma Meningioma Cali Timothy 

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References

  1. 1.
    Llacer J 1997 Inverse radiation treatment planning using the Dynamically Penalized Likelihood method, Med. Phys. 24, (11), 1751–1764PubMedCrossRefGoogle Scholar
  2. 2.
    Spirou S V and Chui C S 1998 A gradient inverse planning algorithm with dose-volume constraints, Med. Phys. 25, (3), 321–333PubMedCrossRefGoogle Scholar
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    Llacer J, Veklerov E and Nunez J 1989 Statistically based image reconstruction for emission tomography, Int. Journal of Imaging Syst. and Technology 1, 132–148CrossRefGoogle Scholar
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    Shepp LA and Vardi Y 1982, Maximum likelihood reconstruction for emission tomography, IEEE Trans. Med. Imaging MI-1 113–121CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Jorge Llacer
    • 1
  • Timothy D. Solberg
    • 2
  • Claus Promberger
    • 3
  • Alexander Kuzmany
    • 3
  1. 1.EC Engineering Consultants LLCLos GatosUSA
  2. 2.Dept. of Radiation OncologyUniversity of CaliforniaLos AngelesUSA
  3. 3.BrainLAB AGHeimstettenGermany

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