Implementation of a new EGSnrc particle source class for computed tomography: validation and uncertainty...

Area of Science:

• Medical Physics
• Radiological Physics
• Computational Dosimetry

Background:

• Personalized dose monitoring and risk management are crucial due to the increasing use of computed tomography (CT) examinations.
• High-quality Monte Carlo (MC) simulations are essential for advancing personalized CT dosimetry.
• Existing MC frameworks require extensions to accommodate CT-scanner-specific dose and image calculations.

Purpose of the Study:

• To extend the EGSnrc MC code with a novel particle source for CT simulations.
• To enable CT-scanner-specific dose and image calculations for any CT scanner.
• To facilitate personalized CT dosimetry, including effective dose estimation and CT image generation.

Main Methods:

• Implemented a new particle source class within the EGSnrc MC framework.
• Utilized user-derived input data based on experimental CT scanner characterization.
• Validated the new source through air kerma measurements and phantom studies, comparing simulations against experimental results.

Main Results:

• Successfully implemented a new particle source class adaptable to any CT scanner.
• Achieved a mean deviation of 2.36% for attenuation characteristics and agreement within 5.0% for phantom measurements.
• Quantified an uncertainty of 5.5% (k=1) for simulated air kerma values.

Conclusions:

• The developed particle source enables realistic CT scan simulations for personalized dosimetry.
• The method's adaptability to any CT scanner supports widespread application in CT dose monitoring.
• Validated simulations provide a reliable tool for risk management and optimizing CT protocols.