An Approach in Radiation Therapy Treatment Planning: A Fast, GPU-Based Monte Carlo Method

Area of Science:

• Medical Physics
• Radiotherapy Technology
• Computational Science

Background:

• Accurate and rapid radiation dose calculation is critical for effective radiotherapy.
• Existing methods may face limitations in speed and precision for complex treatment plans.

Purpose of the Study:

• To implement and validate a novel graphic processing unit (GPU)-based system for radiation therapy treatment planning.
• To assess the accuracy and speed of GPU-accelerated Monte Carlo simulations for dose calculation.

Main Methods:

• Developed a GPU-based program for parallel radiation dose calculations.
• Validated the code against EGSnrc/DOSXYZnrc in a virtual phantom.
• Utilized a custom-designed anthropomorphic phantom with tissue-equivalent materials for experimental validation using a Mapcheck dosimeter.

Main Results:

• The GPU-based code achieved high accuracy, with over 95% of voxels showing <3% dose difference or 3 mm distance-to-agreement (DTA) compared to DOSXYZnrc.
• Experimental validation with the anthropomorphic phantom demonstrated <5% dose difference or 5 mm DTA compared to Mapcheck measurements.

Conclusions:

• The GPU-based Monte Carlo method provides a fast and accurate solution for radiation dose calculation.
• This technology holds significant potential for routine use in radiotherapy centers as a core component of treatment planning verification systems.