Implementation of a simple clinical linear accelerator beam model in MCNP6 and comparison with measured beam characteristics

Tara Gray, Nema Bassiri, Neil Kirby, Sotirios Stathakis, Kathryn M. Mayer

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Monte Carlo N-Particle 6 (MCNP6) is the latest version of Los Alamos National Laboratory's powerful Monte Carlo software designed to compute general photon, neutron, and electron transport using stochastic algorithms. Here we provide a case study of modeling the photon beam of a Varian 600C Clinical Linear Accelerator (linac), which is used to deliver radiation therapy, along with a comparison to experimentally measured beam characteristics. The source definition parameters in MCNP6, including the energy spectrum and angular spectrum of the photons, secondary and tertiary collimators, and a water phantom that tallied dose delivered at different points along the phantom are included. The experimental data for comparison was in the form of a percent depth dose curve as well as crossline and inline beam profiles. Experimental depth dose curve and beam profiles were acquired using a standard 0.125 cc ion chamber within a water phantom. In the computational model, the simulated depth dose curve was computed by tallying the total energy deposited in a stack of vertical slices down the depth of the phantom for percent depth dose curves. The simulated beam profiles were computed in a similar fashion, by tallying the energy deposited in a horizontal row, both in the x- and y-directions of cubic cells located at various depths. For the percent depth dose curve, a mean absolute percentage difference of 1.02%, 1.07%, and 1.94% were calculated for field sizes of 5 × 5 cm2, 10 × 10 cm2 and 20 × 20 cm2, respectively, between the model and experimental measurements were calculated. We present our model as an example to guide other MCNP6 users in the medical physics community to create similar beam models for biomedical dose estimation and research calculations for predicting dose to newly developed phantoms.

Original languageEnglish (US)
Article number108925
JournalApplied Radiation and Isotopes
StatePublished - Jan 2020


  • Clinical linear accelerator
  • Computational modeling
  • Medical physics
  • Monte Carlo simulation
  • Radiation oncology

ASJC Scopus subject areas

  • Radiation


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