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23 January 2017Simulation of computed tomography dose based on voxel phantom
Computed Tomography (CT) is one of the preferred and the most valuable imaging tool used in diagnostic radiology, which provides a high-quality cross-sectional image of the body. It still causes higher doses of radiation to patients comparing to the other radiological procedures. The Monte-Carlo method is appropriate for estimation of the radiation dose during the CT examinations. The simulation of the Computed Tomography Dose Index (CTDI) phantom was developed in this paper. Under a similar conditions used in physical measurements, dose profiles were calculated and compared against the measured values that were reported. The results demonstrate a good agreement between the calculated and the measured doses. From different CT exam simulations using the voxel phantom, the highest absorbed dose was recorded for the lung, the brain, the bone surface. A comparison between the different scan type shows that the effective dose for a chest scan is the highest one, whereas the effective dose values during abdomen and pelvis scan are very close, respectively. The lowest effective dose resulted from the head scan. Although, the dose in CT is related to various parameters, such as the tube current, exposure time, beam energy, slice thickness and patient size, this study demonstrates that the MC simulation is a useful tool to accurately estimate the dose delivered to any specific organs for patients undergoing the CT exams and can be also a valuable technique for the design and the optimization of the CT x-ray source.
Chunyu Liu,Xiangbo Lv, andZhaojun Li
"Simulation of computed tomography dose based on voxel phantom", Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103221H (23 January 2017); https://doi.org/10.1117/12.2266124
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Chunyu Liu, Xiangbo Lv, Zhaojun Li, "Simulation of computed tomography dose based on voxel phantom," Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103221H (23 January 2017); https://doi.org/10.1117/12.2266124