Photon beam characterization and modelling for Monte Carlo treatment planning

Jun Deng, Steve B. Jiang, Ajay Kapur, Jinsheng Li, Todd Pawlicki, C. M. Ma

Research output: Contribution to journalArticle

112 Scopus citations

Abstract

Photon beams of 4, 6 and 15 MV from Varian Clinac 2100C and 2300C/D accelerators were simulated using the EGS4/BEAM code system. The accelerators were modelled as a combination of component modules (CMs) consisting of a target, primary collimator, exit window, flattening filter, monitor chamber, secondary collimator, ring collimator, photon jaws and protection window. A full phase space file was secondary directly above the upper photon jaws and analysed using beam data processing software, BEAMDP, to derive the beam characteristics, such as planar fluence, angular distribution, energy spectrum and the fractional contributions of each individual CM. A multiple- source model has been further developed to reconstruct the original phase space. Separate sources were created with accurate source intensity, energy, fluence and angular distributions for the target, primary collimator and flattening filter. Good agreement (within 2%) between the Monte Carlo calculations with the source model and those with the original phase space was achieved in the dose distributions for field sizes of 4 cm x 4 cm to 40 cm x 40 cm at source surface distances (SSDs) of 80-120 cm. The dose distributions in lung and bone heterogeneous phantoms have also been found to be in good agreement (within 2%) for 4, 6 and 15 MV photon beams for various field sizes between the Monte Carlo calculations with the source model and those with the original phase space.

Original languageEnglish (US)
Pages (from-to)411-427
Number of pages17
JournalPhysics in medicine and biology
Volume45
Issue number2
DOIs
StatePublished - Feb 2000

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Photon beam characterization and modelling for Monte Carlo treatment planning'. Together they form a unique fingerprint.

  • Cite this