Generation and use of photon energy deposition kernels for diagnostic quality x rays

Parham Alaei, Bruce J Gerbi, Richard A. Geise

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Accurately determining the dose from low energy x rays is becoming increasingly important. This is especially so because of high doses in interventional radiology procedures and also because of the desire to model accurately the dose around low energy brachytherapy sources. Various methods to estimate the dose from specific procedures are available but they only give a general idea of the true dose to various organs. The use of sophisticated three-dimensional (3D) dose deposition algorithms designed originally for radiation therapy treatment planning can be extended to lower photon energy regions. The majority of modern 3D treatment planning systems use a variation of the convolution algorithm to calculate dose distributions. This could be extended into the diagnostic energy range with the availability of lower energy deposition kernels (< 100 keV). We have used version four of the Electron Gamma Shower (EGS4) system of Monte Carlo codes to generate photon energy deposition kernels in the energy range of 20-110 keV and have implemented them in a commercial 3D treatment planning system (Pinnacle, ADAC Laboratories, Milpitas, CA). The kernels were generated using the 'SCASPH' EGS4 user code by selecting the appropriate transport parameters suitable for the relative low energy of the incident photons. The planning system was subsequently used to model diagnostic quality beams and to calculate depth dose and cross profile curves. Comparisons of the calculated curves have been made with measurements performed in a homogeneous water phantom.

Original languageEnglish (US)
Pages (from-to)1687-1697
Number of pages11
JournalMedical Physics
Volume26
Issue number8
DOIs
StatePublished - Aug 1999

Keywords

  • Diagnostic dose calculations
  • Energy deposition kernels
  • Low energy x rays
  • Monte Carlo EGS4 method

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