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Technical Note: A dose calculation framework for dynamic electron arc radiotherapy (DEAR) using VirtuaLinac Monte

Xiaorong Wang1, Daren Sawkey2, Qiuwen Wu1

  • 1Department of Radiation Oncology, Duke University Medical Center, Durham, NC, 27710, USA.

Medical Physics
|November 1, 2019
PubMed
Summary

A new framework integrates Monte Carlo simulation (VirtuaLinac) into treatment planning for dynamic electron arc radiotherapy (DEAR). This enables accurate dose calculation and a practical quality assurance method for DEAR treatments.

Keywords:
VirtuaLinac Monte Carlodynamic electron arc radiotherapyelectron dose calculationquality assurance

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Dosimetry

Background:

  • Dynamic electron arc radiotherapy (DEAR) offers precise dose delivery through simultaneous patient and machine motion.
  • Integrating advanced dose calculation engines into treatment planning systems is crucial for novel radiotherapy techniques.

Purpose of the Study:

  • To develop and validate a framework integrating the VirtuaLinac Monte Carlo (MC) engine with the Eclipse treatment planning system (TPS) for DEAR.
  • To establish a quality assurance (QA) procedure for DEAR dose calculations and measurements.

Main Methods:

  • Developed interfaces for CT image export, VirtuaLinac computation management via API, and dose matrix processing.
  • Validated the framework using static beams and DEAR plans with 6 and 9 MeV electrons.
  • Created a hybrid dose calculation technique by convolving precalculated kernels with beam trajectory for rapid QA.

Main Results:

  • VirtuaLinac demonstrated excellent agreement with eMC (3D γ pass rate >98% at 1%/1 mm).
  • Film measurements showed high agreement for DEAR plans (2D γ pass rate >94% at 2%/2 mm).
  • The hybrid method provided instant, identical dose distributions compared to full MC simulations.

Conclusions:

  • A validated framework for DEAR dose calculation using VirtuaLinac MC has been successfully developed.
  • A feasible and practical DEAR QA method using phantom measurements and a hybrid dose calculation technique is established.
  • The developed framework and QA method are efficient and suitable for clinical implementation of DEAR.