Variable 3D resolution in complex detector geometries for Monte Carlo simulations.

Area of Science:

• Computational physics and medical dosimetry.
• Development of advanced simulation techniques for radiation therapy.

Background:

• Current Monte Carlo simulation algorithms in GEANT4 struggle with variable spatial resolution in complex geometries.
• Accurate dose distribution analysis is crucial for optimizing radiation therapy, especially in brachytherapy.

Purpose of the Study:

• To develop and validate a novel Monte Carlo simulation and analysis workflow for customizable 3D scoring of physical quantities.
• To overcome limitations in spatial resolution scoring within complex, mesh-based geometries.
• To demonstrate the workflow's utility in ruthenium-106 (Ru-106) eye brachytherapy for intraocular tumors.

Main Methods:

• Implemented a universal scoring algorithm in GEANT4 combining particle tracking with external post-processing.
• Recorded spatial coordinates and deposited energy during simulation.
• Utilized post-processing to bin complex geometries into virtual volumes, enabling adjustable dose resolution independently from the simulation.

Main Results:

• Achieved variable and high-accuracy dose resolution across complex structures in a 3D eye model for Ru-106 brachytherapy.
• Demonstrated scalability and adaptability to various detector geometries and radiation modalities.
• Enabled precise post-simulation analysis, minimizing computational costs while maintaining data accuracy.

Conclusions:

• The developed workflow significantly advances Monte Carlo simulation capabilities for scoring in complex geometries.
• It offers a flexible, high-resolution tool for analyzing physical quantities, surpassing conventional algorithm limitations.
• The approach is adaptable to diverse clinical and computational scenarios beyond brachytherapy.