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The influence of dose grid resolution on beam selection strategies in radiotherapy treatment design

In: Optimization in Medicine

Author

Listed:
  • Ryan Acosta

    (Stanford University)

  • Matthias Ehrgott

    (The University of Auckland)

  • Allen Holder

    (Trinity University
    University of Texas Health Science Center)

  • Daniel Nevin

    (Texas A&M University)

  • Josh Reese

    (Trinity University)

  • Bill Salter

    (University of Utah Huntsman Cancer Institute)

Abstract

Summary The design of a radiotherapy treatment includes the selection of beam angles (geometry problem), the computation of a fluence pattern for each selected beam angle (intensity problem), and finding a sequence of configurations of a multileaf collimator to deliver the treatment (realization problem). While many mathematical optimization models and algorithms have been proposed for the intensity problem and (to a lesser extent) the realization problem, this is not the case for the geometry problem. In clinical practice, beam directions are manually selected by a clinician and are typically based on the clinician’s experience. Solving the beam selection problem optimally is beyond the capability of current optimization algorithms and software. However, heuristic methods have been proposed. In this paper we study the influence of dose grid resolution on the performance of these heuristics for a clinical case. Dose grid resolution refers to the spatial arrangement and size of dose calculation voxels. In particular, we compare the solutions obtained by the heuristics with those achieved by a clinician using a commercial planning system. Our results show that dose grid resolution has a considerable influence on the performance of most heuristics.

Suggested Citation

  • Ryan Acosta & Matthias Ehrgott & Allen Holder & Daniel Nevin & Josh Reese & Bill Salter, 2008. "The influence of dose grid resolution on beam selection strategies in radiotherapy treatment design," Springer Optimization and Its Applications, in: Carlos J. S. Alves & Panos M. Pardalos & Luis Nunes Vicente (ed.), Optimization in Medicine, pages 1-23, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-73299-2_1
    DOI: 10.1007/978-0-387-73299-2_1
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