  Recently, X-ray imaging dose from computed tomography (CT) or cone beam CT
(CBCT) scans has become a serious concern. Patient-specific imaging dose
calculation has been proposed for the purpose of dose management. While Monte
Carlo (MC) dose calculation can be quite accurate for this purpose, it suffers
from low computational efficiency. In response to this problem, we have
successfully developed a MC dose calculation package, gCTD, on GPU architecture
under the NVIDIA CUDA platform for fast and accurate estimation of the x-ray
imaging dose received by a patient during a CT or CBCT scan. Techniques have
been developed particularly for the GPU architecture to achieve high
computational efficiency. Dose calculations using CBCT scanning geometry in a
homogeneous water phantom and a heterogeneous Zubal head phantom have shown
good agreement between gCTD and EGSnrc, indicating the accuracy of our code. In
terms of improved efficiency, it is found that gCTD attains a speed-up of ~400
times in the homogeneous water phantom and ~76.6 times in the Zubal phantom
compared to EGSnrc. As for absolute computation time, imaging dose calculation
for the Zubal phantom can be accomplished in ~17 sec with the average relative
standard deviation of 0.4%. Though our gCTD code has been developed and tested
in the context of CBCT scans, with simple modification of geometry it can be
used for assessing imaging dose in CT scans as well.
