Inverse radiation therapy planning: a multiple objective optimization approach

  • Authors:
  • H. W. Hamacher;K. H. Küfer

  • Affiliations:
  • Department of Mathematics, Institute for Techno- and Business-Mathematics (ITWM), University of Kaiserslautern, Erwin-Schroedinger-Straβe, Postfach 3049, D-67653 Kaiserslautern, Germany;Department of Mathematics, Institute for Techno- and Business-Mathematics (ITWM), University of Kaiserslautern, Erwin-Schroedinger-Straße, Postfach 3049, D-67653 Kaiserslautern, Germany

  • Venue:
  • Discrete Applied Mathematics - Special issue: Third ALIO-EURO meeting on applied combinatorial optimization
  • Year:
  • 2002

Quantified Score

Hi-index 0.00

Visualization

Abstract

For some decades, radiation therapy has been proved successful in cancer treatment. It is the major task of clinical radiation treatment planning to realize, on the one hand, a high level dose of radiation in the cancer tissue in order to obtain maximum tumor control. On the other hand, it is obvious that it is absolutely necessary to keep the unavoidable radiation in the tissue outside the tumor, particularly in organs at risk, as low as possible. No doubt, these two objectives of treatment planning--high level dose in the tumor, low radiation outside the tumor-- have a basically contradictory nature. Thus, there is need to compromise between overdosing the organs at risk and underdosing the target volume. Differing from the currently used time consuming interactive approach between dosimetrists and physicians, we consider the radiation therapy planning problem as a multiple objective linear programming problem and build a data base of relatively few efficient solutions representing the set of Pareto solutions. This data base can be easily scanned by physicians looking for an adequate treatment plan with the aid of an appropriate online tool. The paper includes a report on first numerical experiments and a list of further research topics which is hoped to stimulate interest of the OR community in a subject, where OR methods can make a difference for many individual's lives.