AU - Fallah Mohammadi1, Gh.R. AU - Riyahi Alam, N. AU - Geraily, Gh. AU - Paydar, R. TI - Thorax organ dose estimation in computed tomography based on patient CT data using Monte Carlo simulation PT - JOURNAL ARTICLE TA - Int-J-Radiat-Res JN - Int-J-Radiat-Res VO - 14 VI - 4 IP - 4 4099 - http://ijrr.com/article-1-1816-en.html 4100 - http://ijrr.com/article-1-1816-en.pdf SO - Int-J-Radiat-Res 4 ABĀ  - Background: This study presents patient specific and organ dose estimation in computed tomography (CT) imaging of thorax directly from patient CT image using Monte Carlo simulation. Patient's CT image is considered as the patient specific phantom and the best representative of patient physical index in order to calculate specific organ dose. Materials and Methods: EGSnrc /BEAMnrc Monte Carlo (MC) System was used for CT scanner simulation and DOSXYZnrc was used in order to produce patient specific phantom and irradiation of photons to phantom in step and shoot mode (axial mode). In order to calculate patient thorax organ dose, patient CT image of thorax as voxelized phantom was divided to a 64x64x20 matrix and 6.25 x 6.25 x 6.25 mm3 voxel size and this phantom was imported to DOSXYZnrc code. MC results in unit of Gy/particle were converted to absorbed dose in unit of mGy by a conversion factor (CF). We calculated patient thorax organ dose in MC simulation from all irradiated slices, in 120 kV and 80 kV photon energies. Results: Effective dose was obtained from organ dose and organ weighting factor. Esophagus and spinal cord received the lowest, and bone received the highest dose. In our study, effective dose in CT of thorax was 7.4 mSV and 1.8 mSv in 120 and 80 kV, respectively. Conclusion: The results of this study might be used to provide the actual patient organ dose in CT imaging and calculation of real effective dose based on organ dose. CP - IRAN IN - Department of Medical Physics and Biomedical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Ira LG - eng PB - Int-J-Radiat-Res PG - 313 PT - Short Report YR - 2016