Comparison of RTP dose distributions in heterogeneous phantoms with the BEAM Monte Carlo simulation system

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Dosimetry

Background:

• Radiotherapy treatment plan evaluation relies on accurate dose distribution calculations in target volumes and surrounding normal tissues.
• Tissue inhomogeneities significantly impact photon dose distributions, necessitating precise modeling in radiotherapy treatment planning (RTP) systems.

Purpose of the Study:

• To compare the accuracy of the FOCUS RTP system's Clarkson and MultiGrid Superposition (MGS) algorithms against the BEAM Monte Carlo code for photon dose distributions in heterogeneous phantoms.
• To evaluate the impact of tissue inhomogeneities, such as lung and bone, on dose calculations in clinically relevant geometries.

Main Methods:

• Utilized heterogeneous phantoms simulating lung, bone, and mediastinum with densities of 0.20, 0.31, and 2.40 g/cm³.
• Compared dose distributions calculated by the measurement-based Clarkson and model-based MGS algorithms with the benchmark BEAM Monte Carlo code.
• Evaluated 5x5 cm² and 10x10 cm² fields for 6- and 15-MV photon beams.

Main Results:

• The MGS model demonstrated dose agreement within 3% or 3 mm compared to the BEAM Monte Carlo code across all tested phantoms.
• The MGS model accurately predicted dose build-up/build-down at tissue interfaces and penumbra broadening in lung, unlike the Clarkson model.
• The Clarkson model overestimated lung dose by up to 10% compared to BEAM and failed to account for interface effects.

Conclusions:

• The MGS model offers superior accuracy for dose calculations in heterogeneous tissues compared to the Clarkson model for photon beams.
• The findings suggest disabling the effective path length inhomogeneity correction in the Clarkson model for lung treatments to improve accuracy.
• Accurate dose calculation in heterogeneous media is crucial for effective radiotherapy treatment planning and patient outcomes.