A peer-reviewed journal published by K. N. Toosi University of Technology

‎Toward a Monte Carlo-driven 3D dose verification framework for IMRT‎: ‎A pilot implementation for nasopharyngeal carcinoma‎

Document Type : Research Article

Authors

1 Physics Department‎, ‎Faculty of Science‎, ‎Ferdowsi University of Mashhad‎, ‎Mashhad‎, ‎Iran

2 Research and Education Department‎, ‎Reza Radiotherapy and Oncology Center‎, ‎Mashhad‎, ‎Iran

3 Department of Radiation Oncology, Medicine Faculty of Van Yüzüncü Yıl University, Van, Turkey

4 Radiation Oncology Department‎, ‎Reza Radiotherapy and Oncology Center‎, ‎Mashhad‎, ‎Iran

Abstract
Monte Carlo (MC) methods are considered a complementary method for dose verification in radiation therapy‎. ‎This study aims to simulate the Artiste head and the Siemens 160 Multileaf Collimator (MLC) using MCNPX 2.6.0 to enhance dose verification accuracy in Intensity-Modulated Radiation Therapy (IMRT) treatment plans‎. The MC-based calculations were benchmarked against commissioning-measured data and an MLC test field‎. ‎A comparison between MC-based and treatment planning system (TPS)-based dose maps was made for beams of a typical complicated IMRT plan‎. ‎The results demonstrated a 3D gamma passing rate (GPR) of 97.1% with 3%/3mm criteria and a 10% dose threshold‎, ‎indicating the accuracy of the MC model‎. Based on the acceptable GPRs‎, ‎the provided model has sufficient accuracy‎. ‎It has been confirmed that the MC calculations can be carried out within a reasonable computation time‎, ‎taking approximately 10 minutes per beam and less than 2 hours for a typical 9-beam IMRT plan‎. ‎This is possible with a specific‎, ‎powerful CPU configuration used for MC verification of such a complicated IMRT plan‎.

Highlights

  • A full Monte Carlo simulation of the Siemens Artiste linac and 160-leaf MLC was implemented using MCNPX 2.6.0.
  • The framework achieved a 3D gamma passing rate of 97.1% (3%/3 mm) for a nasopharyngeal carcinoma plan.
  • The model establishes the foundation for a localized, patient-specific Monte Carlo verification tool.

Keywords


Copyright
RPE is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

Conflict of Interest
The authors declare no potential conflict of interest regarding the publication of this work‎.

Funding
‎The authors declare that no funds‎, ‎grants‎, ‎or other financial support were received during the preparation of this manuscript‎.

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Volume 7, Issue 2
Spring 2026
Pages 45-55

  • Receive Date 29 October 2025
  • Revise Date 27 December 2025
  • Accept Date 02 May 2026