Fast Monte Carlo codes for occupational dosimetry in interventional radiology

V García Balcaza, A Camp, A Badal, M Andersson, A Almen, M Ginjaume, M A Duch

Research output: Contribution to journalArticlepeer-review

Abstract

PURPOSE: Interventional radiology techniques cause radiation exposure both to patient and personnel. The radiation dose to the operator is usually measured with dosimeters located at specific points above or below the lead aprons. The aim of this study is to develop and validate two fast Monte Carlo (MC) codes for radiation transport in order to improve the assessment of individual doses in interventional radiology. The proposed methodology reduces the number of required dosemeters and provides immediate dose results.

METHODS: Two fast MC simulation codes, PENELOPE/penEasyIR and MCGPU-IR, have been developed. Both codes have been validated by comparing fast MC calculations with the multipurpose PENELOPE MC code and with measurements during a realistic interventional procedure.

RESULTS: The new codes were tested with a computation time of about 120 s to estimate operator doses while a standard simulation needs several days to obtain similar uncertainties. When compared with the standard calculation in simple set-ups, MCGPU-IR tends to underestimate doses (up to 5%), while PENELOPE/penEasyIR overestimates them (up to 18%). When comparing both fast MC codes with experimental values in realistic set-ups, differences are within 25%. These differences are within accepted uncertainties in individual monitoring.

CONCLUSION: The study highlights the fact that computational dosimetry based on the use of fast MC codes can provide good estimates of the personal dose equivalent and overcome some of the limitations of occupational monitoring in interventional radiology. Notably, MCGPU-IR calculates both organ doses and effective dose, providing a better estimate of radiation risk.

Original languageEnglish
Pages (from-to)166-174
JournalPhysica Medica
Volume85
DOIs
Publication statusPublished - 2021 May

Subject classification (UKÄ)

  • Radiology, Nuclear Medicine and Medical Imaging

Keywords

  • Computer Simulation
  • Humans
  • Monte Carlo Method
  • Radiation Dosage
  • Radiation Dosimeters
  • Radiology, Interventional
  • Radiometry

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