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Image-based Absorbed Dosimetry of Radioisotope

DOI:10.14316/pmp.2016.27.2.86 期刊:Progress in Medical Physics 出版年份:2016 更新时间:2025-09-23 15:23:52
摘要: 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.
作者: Yong Sung Park,Yong Jin Lee,Wook Kim,Young Hoon Ji,Kum Bae Kim,Joo Hyun Kang,Sang Moo Lim,Sang-Keun Woo
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To measure the S-value for calculating the absorbed dose of each organ and tumor using a torso phantom and Monte Carlo simulation based on CT data, as existing methods cannot calculate absorbed dose for tumors.

The study successfully developed an image-based Monte Carlo simulation method for absorbed dose evaluation in organs and tumors, showing applicability for regions of varying size and location with an average difference of 12.3% from measured values, enabling personalized dosimetry and tumor dose assessment.

The method may have limitations in accuracy as indicated by the 12.3% difference between simulated and measured doses; potential areas for optimization include improving segmentation accuracy and simulation parameters for better precision.

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