Treatment planning using a dose-volume feasibility search algorithm

George Starkschall, Alan Pollack, Craig W. Stevens

Research output: Contribution to journalArticle

31 Scopus citations

Abstract

Purpose: An approach to treatment plan optimization is presented that inputs dose-volume constraints and utilizes a feasibility search algorithm that seeks a set of beam weights so that the calculated dose distributions satisfy the dose-volume constraints. In contrast to a search for the 'best' plan, this approach can quickly determine feasibility and point out the most restrictive of the predetermined constraints Methods and Materials: The cyclic subgradient projection (CSP) algorithm was modified to incorporate dose-volume constraints in a treatment plan optimization schema. The algorithm was applied to determine beam weights for several representative three-dimensional treatment plans.Results: Using the modified CSP algorithm, we found that either a feasible solution to the dose-volume constraint problem was found or the program determined, after a predetermined set of iterations was performed, that no feasible solution existed for the particular set of dose-volume constraints. If no feasible solution existed, we relaxed several of the dose-volume constraints and were able to achieve a feasible solution. Conclusion: Feasibility search algorithms can be used in radiation treatment planning to generate a treatment plan that meets the dose-volume constraints established by the radiation oncologist. In the absence of a feasible solution, these algorithms can provide information to the radiation oncologist as to how the dose-volume constraints may be modified to achieve a feasible solution.

Original languageEnglish (US)
Pages (from-to)1419-1427
Number of pages9
JournalInternational Journal of Radiation Oncology Biology Physics
Volume49
Issue number5
DOIs
StatePublished - Apr 1 2001

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Keywords

  • Dose prescription
  • Inverse planning
  • Optimization
  • Treatment planning

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Radiation

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