English

Using Stable Distributions to Characterize Proton Pencil Beams

Medical Physics 2018-03-29 v1

Abstract

Purpose: To introduce and evaluate the use of stable distributions as a means of describing the behavior of charged particle pencil beams in a medium, with specific emphasis on proton beam scanning (PBS). Methods: The proton pencil beams of a clinically commissioned proton treatment facility are replicated in a Monte Carlo simulation system (FLUKA). For each available energy the beam deposition in water medium is characterized by the dose deposition. Using an alpha--stable distribution methodology each beam with a nominal energy EE is characterized by the lateral spread at depth zz: S(z;α,γ,E)S(z;\alpha,\gamma,E) and a total energy deposition ID(z)I_D(z). The beams are then described as a function of the variation of the parameters at depth. Finally, an implementation in a freely available open source dose calculation suite (matRad, DKFZ, Heidelberg, Germany) is proposed. Results: Quantitatively, the fit of the stable distributions, compared to those implemented in standard treatment planning systems, are equivalent. The efficiency of the representation is better (2 compared to 3 and more parameters needed). The meta--parametrization (i.e. the description of the dose deposition by only providing the fitted parameters) allows for interpolation of non--measured data. In the case of the clinical data used in this paper, it was possible to only commission 1 out of 5 nominal energies to obtain a viable data set. Conclusions: Alpha--stable distributions are intrinsically suited to describe charged particle pencil beams in a medium and can be easily implemented in existing treatment planning systems. The use of alpha-distributions can easily be extended to other particles.

Keywords

Cite

@article{arxiv.1611.08871,
  title  = {Using Stable Distributions to Characterize Proton Pencil Beams},
  author = {Frank Van den Heuvel and Francesca Fiorini and Niek Schreuder and Ben George},
  journal= {arXiv preprint arXiv:1611.08871},
  year   = {2018}
}
R2 v1 2026-06-22T17:05:29.523Z