A GPU-based Monte Carlo framework for IMRT QA using EPID transit dosimetry
Ning Gao, Didi Li, Na Liu, Yankui Chang, Qiang Ren, Xi Pei, Zhi Wang, Xie George Xu

TL;DR
This paper introduces ARCHER-EPID, a GPU-accelerated Monte Carlo framework for accurate and efficient EPID transit dosimetry in IMRT QA, validated against experimental measurements with high gamma passing rates.
Contribution
The paper presents a novel GPU-based Monte Carlo framework, ARCHER-EPID, that enables rapid and accurate EPID transit dosimetry simulations for IMRT quality assurance.
Findings
Simulation time for complex IMRT fields is about 90 seconds.
Average gamma passing rates are above 97% for both phantoms.
High agreement between simulated and measured dose distributions.
Abstract
Purpose: We presented a GPU-based MC framework, ARCHER-EPID, specifically designed for EPID transit dosimetry, with improving accuracy and efficiency. Methods: A comprehensive MC framework was developed to perform full radiation transport simulations through three distinct zones: a detailed linear accelerator head model, a CT-based patient/phantom geometry, and a realistic, multi-layered EPID model. To convert the simulated absorbed dose to a realistic detector signal, a dose-response correction model was implemented. The framework was validated by comparing simulations against experimental measurements for 25 IMRT fields delivered to both a solid water phantom and a anthropomorphic phantom. Agreement was quantified using Gamma analysis. Results: The GPU-accelerated ARCHER-EPID framework can complete the simulation for a complex IMRT field in about 90 seconds. A 2D correction factor…
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