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- W4289260255 abstract "In-vivo measurements of 241Am using HPGe detectors become complicated when the active adjacent source organs interfere with the target organ measurements. It is important to calculate the contribution of confounding organs to estimate the activity of the target organ accurately. In the current study, numerical simulations were performed using FLUKA Monte Carlo code and International Commission on Radiological Protection (ICRP) computational reference phantoms to determine the calibration matrices consisting of the calibration and cross-talk coefficients for three interfering organs namely, lungs, liver and skeleton. It was found that the interference from adjacent organs contaminated with 241Am was found to be significant in the case of lungs and liver. Knee monitoring was least influenced by the activity possessed by other source organs due to their anatomical distance from the knee. A comparison between lung and liver coefficients obtained from the Lawrence Livermore National Laboratory (LLNL) torso phantom and thorax phantom derived from ICRP adult male voxel phantom was performed. It was found that variations in coefficients obtained from simulations and experiments range between 2% and 48%. The differences were attributed to the uncertainties arising from the composition of the phantoms and detectors, size and shape of organs, positional errors, and source distribution. A comparison of calibration matrices of adult male and adult female thorax voxel phantoms revealed that all the coefficients except knee as the target organ were larger for the female thorax phantom owing to the lesser bulk of attenuating tissues on its chest. The coefficients obtained from simulations for different phantoms also showed that the organ activity estimation can be significantly affected by the subject morphology." @default.
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- W4289260255 date "2022-10-01" @default.
- W4289260255 modified "2023-09-27" @default.
- W4289260255 title "Numerical estimation of calibration matrices for 241Am measurements using HPGe based in-vivo monitoring system" @default.
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- W4289260255 doi "https://doi.org/10.1016/j.apradiso.2022.110392" @default.
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