Dosimetric validation of SmART-RAD Monte Carlo modelling for x-ray cabinet radiobiology irradiators

Mark A Hill*, Nick Staut, James M Thompson, Frank Verhaegen

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Accuracy and reproducibility in the measurement of radiation dose and associated reporting are critically important for the validity of basic and preclinical radiobiological studies performed with kilovolt x-ray radiation cabinets. This is essential not only to enable results of radiobiological studies to be repeated, as well as enable valid comparisons between laboratories. In addition, the commonly used single point dose value hides the 3D dose heterogeneity across the irradiated sample. This is particularly true for preclinical rodent models, and is generally difficult to measure directly. Radiation transport simulations integrated in an easy to use application could help researchers improve quality of dosimetry and reporting. Approach: this paper describes the use and dosimetric validation of a newly-developed Monte Carlo (MC) tool, SmART-RAD, to simulate the x-ray field in a range of standard commercial x-ray cabinet irradiators used for preclinical irradiations. Comparisons are made between simulated and experimentally determined dose distributions for a range of configurations to assess the potential use of this tool in determining dose distributions through samples, based on more readily available air-kerma calibration point measurements. Main results: simulations gave very good dosimetric agreement with measured depth dose distributions in phantoms containing both water and bone equivalent materials. Good spatial and dosimetric agreement between simulated and measured dose distributions was obtained when using beam-shaping shielding. Significance: the MC simulations provided by SmART-RAD provide a useful tool to go from a limited number of dosimetry measurements to detailed 3D dose distributions through a non-homogeneous irradiated sample. This is particularly important when trying to determine the dose distribution in more complex geometries. The use of such a tool can improve reproducibility and dosimetry reporting in preclinical radiobiological research.
Original languageEnglish
JournalPhysics in Medicine and Biology
Issue number9
DOIs
Publication statusE-pub ahead of print - 22 Mar 2024

Keywords

  • Monte Carlo
  • dosimetery
  • pre-clinical
  • radiobiology
  • x-ray

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