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

Karbalee, Mojtaba; Shahbazi Gahrouei, Daryoush; Tavakoli, Mohammad B.

doi:10.22038/ijmp.2018.12899

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

Document Type : Conference Proceedings

Authors

Mojtaba Karbalee ¹

Daryoush Shahbazi Gahrouei ²

Mohammad B. Tavakoli ²

¹ School of Allied Medical Sciences, Zabol University of Medical Sciences, Zabol, Iran

² Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

10.22038/ijmp.2018.12899

Abstract

Introduction:
An accurate and fast radiation dose calculation is essential for successful radiation radiotherapy. The aim of this study was to implement a new graphic processing unit (GPU) based radiation therapy treatment planning for accurate and fast dose calculation in radiotherapy centers.
Materials and Methods:
A program was written for parallel running based on GPU. The code validation was performed by EGSnrc/ DOSXYZnrc. Moreover, a semi-automatic, rotary, asymmetric phantom was designed and produced using a bone, the lung, and the soft tissue equivalent materials. All measurements were performed using a Mapcheck dosimeter. The accuracy of the code was validated using the experimental data, which was obtained from the anthropomorphic phantom as the gold standard.
Results:
The findings showed that, compared with those of DOSXYZnrc in the virtual phantom and for most of the voxels (>95%), <3% dose-difference or 3 mm distance-to-agreement (DTA) was found. Moreover, considering the anthropomorphic phantom, compared to the Mapcheck dose measurements, <5% dosedifference or 5 mm DTA was observed.

Conclusion:
Fast calculation speed and high accuracy of GPU-based Monte Carlo method in dose calculation may be useful in routine radiation therapy centers as the core and main component of a treatment planning verification system.

Keywords

Dosimetry

fast Monte Carlo

GPU

phantom

radiotherapy treatment planning