Particle-beam-dependent optimization for Monte Carlo simulation in hadrontherapy using tetrahedral geometries

Area of Science:

• Medical Physics
• Computational Biology
• Radiotherapy

Background:

• Monte Carlo dose calculation techniques are crucial for radiation therapy.
• Generating precise dose distributions with tetrahedral phantoms requires fine meshes, leading to time-consuming simulations.
• Existing methods for density calculation in tetrahedral phantoms are locally based on CT scans.

Purpose of the Study:

• To develop a novel method for patient-specific tetrahedral phantom density distribution.
• To coarsen tetrahedral meshes for improved Monte Carlo simulation performance.
• To guarantee precise dose distribution in the target volume while reducing computational time.

Main Methods:

• Defined patient-specific tetrahedral phantom density using CT scans and particle beam direction.
• Incorporated beam direction into density calculation to minimize water equivalent thickness error before the tumor.
• Applied the method to multi-layer and thorax computational phantoms using coarse meshes.

Main Results:

• Achieved better dose distribution within the tumor on a coarse mesh compared to other density mapping methods.
• Significantly reduced water equivalent path length error (e.g., from 9.65 mm to 0.62 mm for multi-layer phantom).
• Obtained similar dose coverage as refined meshes and reduced computational time by 25%.

Conclusions:

• Coarse tetrahedral meshes can achieve accurate dose distributions in radiation therapy.
• The proposed method respects water equivalent path length in the beam's direction.
• This approach enhances computational efficiency in Monte Carlo simulations for radiotherapy.