Monte Carlo calculation of specific absorbed fractions: variance reduction techniques

Area of Science:

• Medical Physics
• Computational Biology
• Radiological Dosimetry

Background:

• Accurate calculation of specific absorbed fractions (SAFs) is crucial for internal dosimetry.
• Monte Carlo simulations are standard for SAFs but can be computationally intensive, especially for complex geometries or low photon energies.
• Variance reduction techniques are essential to improve simulation efficiency and reduce statistical uncertainties.

Purpose of the Study:

• To calculate SAFs using variance reduction techniques.
• To assess the effectiveness of interaction forcing and an ant colony algorithm in improving simulation efficiency.
• To evaluate these techniques for large source-to-organ distances and small target organs.

Main Methods:

• Monte Carlo simulations using the PENELOPE code.
• Application of interaction forcing and an ant colony algorithm for variance reduction.
• Utilized a mathematical phantom (MIRD-type adult) with the thyroid as the source organ and various organs as targets.
• Simulations covered photon energies from 30 keV to 2 MeV.

Main Results:

• For photon energies above 100 keV, both interaction forcing and the ant colony method achieved relative uncertainties below 4%.
• Combining both techniques reduced uncertainty by a factor of 0.5 or less.
• Adapted initialization of the ant colony algorithm was necessary for energies below 100 keV.
• Realistic SAF values were obtained with sufficient accuracy for inter-code and inter-phantom comparisons.

Conclusions:

• Interaction forcing and the ant colony algorithm are effective variance reduction techniques for SAF calculations.
• These methods significantly improve simulation efficiency and reduce statistical uncertainties.
• The described methodology is applicable to various radiation types, phantom models, and source-target organ configurations.