Characterizing and minimizing uncertainties in diagnostic X-ray beam calibrations using a Monte Carlo-based model and...

Area of Science:

• Medical Physics
• Radiation Dosimetry
• Computational Physics

Background:

• Accurate modeling of X-ray generator output is crucial for radiation therapy and diagnostics.
• Standardized radiation qualities (IEC 61267) are essential for consistent dosimetry.
• Geant4 is a versatile toolkit for simulating particle transport, but its application to specific X-ray generators requires careful validation.

Purpose of the Study:

• To develop and validate a flexible Geant4 application for simulating IEC 61267 radiation qualities for a HOPEWELL Designs 225 kV X-ray generator.
• To systematically analyze the impact of environmental and systematic factors on radiation output.
• To establish a reliable tool for optimizing dosimetric accuracy and minimizing uncertainties.

Main Methods:

• Replication of the LEGEX laboratory experimental setup using Geant4.
• Simulation of all IEC 61267 radiation qualities by adjusting beam parameters.
• Validation of the Geant4 model by comparing simulated Half-Value Layers (HVLs) and spectra with experimental data, SRS78 software, and IEC reference values.
• Quantification and correction of backscattered radiation effects.

Main Results:

• The Geant4 application accurately simulated IEC 61267 radiation qualities, showing strong agreement with experimental measurements and published data.
• Geometrical misalignment was identified as the primary source of deviation in Kinetic Energy Released per unit Mass (KERMA), followed by aluminum purity and diaphragm movement.
• Environmental factors were found to induce only minor fluctuations in KERMA.
• A function characterizing KERMA behavior in response to influencing factors was derived.

Conclusions:

• The developed Geant4 application is a validated and reliable tool for simulating IEC 61267 radiation qualities.
• The study provides a quantitative understanding of factors influencing dosimetric accuracy, with geometrical alignment being critical.
• This framework offers a cost-effective method for identifying and minimizing uncertainties in X-ray dosimetry simulations.