Comparisons between MCNP, EGS4 and experiment for clinical electron beams

Area of Science:

• Medical Physics
• Computational Science
• Radiation Dosimetry

Background:

• Monte Carlo codes are crucial for accurate simulations in medical physics.
• Understanding their limitations is vital to prevent systematic errors and guide code development.
• MCNP and EGS4 are widely used Monte Carlo codes in the field.

Purpose of the Study:

• To compare and evaluate the performance of MCNP and EGS4.
• To assess their accuracy against experimental electron depth dose and backscatter data.
• To identify differences in physical models and algorithms impacting simulation results.

Main Methods:

• Comparison of MCNP and EGS4 using clinical radiotherapy beams.
• Evaluation against experimental electron depth dose data.
• Assessment of experimental backscatter results.
• Performance timing study.

Main Results:

• MCNP's default version overestimates electron penetration; ITS-style algorithm improves accuracy.
• EGS4 underpredicts electron backscattering in high-Z materials, with slight improvement using PRESTA-I parameters.
• MCNP accurately simulates backscattering, even for high-Z materials.
• EGS4 is generally faster than MCNP.
• Large numbers of scoring voxels significantly slow MCNP, while geometry voxels have minimal impact.

Conclusions:

• Both MCNP and EGS4 have distinct strengths and weaknesses for specific simulation tasks.
• Algorithm selection (e.g., ITS-style in MCNP) and parameter tuning (e.g., PRESTA-I in EGS4) are critical for accuracy.
• Computational efficiency varies, with EGS4 generally faster and MCNP sensitive to scoring voxel count.