Iterative prescription refinement in fully discretized inverse problems of radiation therapy planning

Yair Censor, Lei Xing

Research output: Contribution to journalArticlepeer-review


We formulate the method of iterative prescription refinement for inverse planning in any fully discretized model of radiation therapy. The method starts out from an ideal dose prescription and repeatedly refines it into a refined dose prescription. This is done computationally without human interaction until a prespecified stopping rule is met, at which point the refined dose vector and the accompanying beamlet intensities vector are evaluated and presented to the planner. The algorithmic regime is general enough to encompass various physical models that may use different particles (photons, protons, etc.) It is formulated for a general inversion operator thus different objective functions or approaches to the optimization problem (such as DVH, gEUD, or TCP and NTCP cost functions) may all be applied. Although not limited to this model, we demonstrate that the approach at all works on two exemplary cases from photon intensity-modulated radiation therapy.

Original languageEnglish
Pages (from-to)1125-1137
Number of pages13
JournalInverse Problems in Science and Engineering
Issue number8
StatePublished - Dec 2011

Bibliographical note

Funding Information:
We heartily thank Dr Pavel Lougovski for his help in all phases of the work on this article. We thank three anonymous referees whose constructive comments helped us to improve an earlier version of this work. This work was partially supported by Award Number R01HL070472 from the National Heart, Lung, and Blood Institute at the National Institutes of Health (NIH), and by US Department of Army award number W81XWH-10-1-0170 and United States-Israel Binational Science Foundation (BSF) grant No. 2009012.


  • Fully discretized model
  • Inverse problem
  • Iterative data refinment
  • Iterative prescription refinment
  • Radiation therapy

ASJC Scopus subject areas

  • General Engineering
  • Computer Science Applications
  • Applied Mathematics


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