cc This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. An absorbed dose calculation method using a digital phantom is implemented in normal organs. This method cannot be employed for calculating the absorbed dose of tumor. In this study, we measure the S-value for calculating the absorbed dose of each organ and tumor. We inject a radioisotope into a torso phantom and perform Monte Carlo simulation based on the CT data. The torso phantom has lung, liver, spinal, cylinder, and tumor simulated using a spherical phantom. The radioactivity of the actual absorbed dose is measured using the injected dose of the radioisotope, which is Cu-64 73.85 MBq, and detected using a glass dosimeter in the torso phantom. To perform the Monte Carlo simulation, the information on each organ and tumor acquired using the PET/CT and CT data provides anatomical information. The anatomical information is offered above mean value and manually segmented for each organ and tumor. The residence time of the radioisotope in each organ and tumor is calculated using the time activity curve of Cu-64 radioactivity. The S-values of each organ and tumor are calculated based on the Monte Carlo simulation data using the spatial coordinate, voxel size, and density information. The absorbed dose is evaluated using that obtained through the Monte Carlo simulation and the S-value and the residence time in each organ and tumor. The absorbed dose in liver, tumor1, and tumor2 is 4.52E-02, 4.61E-02, and 5.98E-02 mGy/MBq, respectively. The difference in the absorbed dose measured using the glass dosimeter and that obtained through the Monte Carlo simulation data is within 12.3%. The result of this study is that the absorbed dose obtained using an image can evaluate each difference region and size of a region of interest.
Image-based Absorbed Dosimetry of Radioisotope