Development of GPU-based Monte Carlo code for fast CT imaging dose calculation on CUDA Fermi architecture

This paper describes the development of a Graphics Processing Unit (GPU) accelerated Monte Carlo photon transport code, ARCHERGPU, to perform CT imaging dose calculations with good accuracy and performance. The code simulates interactions of photons with heterogeneous materials. It contains a detailed CT scanner model and a family of patient phantoms. Several techniques are used to optimize the code for the GPU architecture. In the accuracy and performance test, a 142 kg adult male phantom was selected, and the CT scan protocol involved a whole-body axial scan, 20-mm x-ray beam collimation, 120 kVp and a pitch of 1. A total of 9 x 108 photons were simulated and the absorbed doses to 28 radiosensitive organs/tissues were calculated. The average percentage difference of the results obtained by the general-purpose production code MCNPX and ARCHERGPU was found to be less than 0.38%, indicating an excellent agreement. The total computation time was found to be 8,689, 139 and 56 minutes for MCNPX, ARCHERCPU (6-core) and ARCHERGPU, respectively, indicating a decent speedup. Under a recent grant funding from the NIH, the project aims at developing a Monte Carlo code with the capability of sub-minute CT organ dose calculations. (authors)