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Purpose <p>This study presents an automated quality assurance (QA) method for LINAC (linear accelerator) performance verification using EPID-based imaging (electronic portal imaging device), combined with a custom image processing algorithm integrated into the QAtrack+ platform.</p> Methods <p>An in-house Python algorithm, developed and validated for this study using the Pylinac library, was implemented on an Elekta Versa HD LINAC equipped with an iViewGT EPID system. The algorithm automatically analyzes EPID images to extract key dosimetric metrics, field size, flatness, symmetry and dose linearity, and stores results within QAtrack + for centralized tracking and long-term trend evaluation. Calibration followed IAEA TRS-398 standards, and image quality was verified according to AAPM TG-58 recommendations.</p> Results <p>The algorithm demonstrated high repeatability and reproducibility (coefficient of variation &lt; 2%) and a strong linear relationship between EPID signal and monitor units (R² &gt; 0.99). Agreement with Quickcheck Webline measurements confirmed high accuracy across photon energies. Automated data processing substantially reduced manual workload and inter-operator variability.</p> Conclusion <p>The developed and validated EPID-based algorithm integrated into QAtrack+ provides a rapid, low-cost and clinically scalable framework for daily LINAC QA. This system enhances traceability, enables early detection of performance deviations and supports data-driven QA management, contributing to safer, more consistent patient treatments and reinforcing the culture of automation and standardization in modern radiotherapy practice.</p>

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Evaluation of a rapid and cost-effective tool for centralized LINAC EPID dosimetry in a radiotherapy department

  • 期刊论文

  • 发表日期：

    2026年5月29日

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  • Oussama El Mouden,
  • Hamza Sekkat,
  • Ahmed Bannan,
  • Mustapha Bougteb,
  • Mounir Mkimel,
  • Abdellah Khallouqi,
  • Yasmina Berrada,
  • Omar El rhazouani

摘要

Purpose

This study presents an automated quality assurance (QA) method for LINAC (linear accelerator) performance verification using EPID-based imaging (electronic portal imaging device), combined with a custom image processing algorithm integrated into the QAtrack+ platform.

Methods

An in-house Python algorithm, developed and validated for this study using the Pylinac library, was implemented on an Elekta Versa HD LINAC equipped with an iViewGT EPID system. The algorithm automatically analyzes EPID images to extract key dosimetric metrics, field size, flatness, symmetry and dose linearity, and stores results within QAtrack + for centralized tracking and long-term trend evaluation. Calibration followed IAEA TRS-398 standards, and image quality was verified according to AAPM TG-58 recommendations.

Results

The algorithm demonstrated high repeatability and reproducibility (coefficient of variation < 2%) and a strong linear relationship between EPID signal and monitor units (R² > 0.99). Agreement with Quickcheck Webline measurements confirmed high accuracy across photon energies. Automated data processing substantially reduced manual workload and inter-operator variability.

Conclusion

The developed and validated EPID-based algorithm integrated into QAtrack+ provides a rapid, low-cost and clinically scalable framework for daily LINAC QA. This system enhances traceability, enables early detection of performance deviations and supports data-driven QA management, contributing to safer, more consistent patient treatments and reinforcing the culture of automation and standardization in modern radiotherapy practice.