The Human Monitoring Laboratory (Canada) has looked at parameters (lung volume, lung deposition pattern, etc.) that can affect the counting efficiency of its lung counting system. The calibration of the system is performed using the Lawrence Livermore National Laboratory (LLNL) torso phantom; however, the effect of respiratory motion cannot be accounted for using these phantoms. When measuring an internal deposition in the lungs of a subject, respiration causes a change in the volume of the lungs and the thoracic cavity and introduces a variable distance between the lungs and the detectors. These changes may have an impact on the counting efficiency and may need to be considered during a measurement. In this study, the HML has simulated the respiration motion using a 4D non-uniform rational b-spline (NURBS)-based Cardiac-Torso (NCAT) phantom and determined the impact of that motion on the counting efficiency of their lung counting system during measurement. The respiratory motion was simulated by a 16 timeframe cycled 4D NURBS-based NCAT phantom developed at the Department of Biomedical Engineering and Radiology, University of North Carolina. The counting efficiency of the four germanium detectors comprising the HML lung counting system was obtained using MCNPX version 2.6E for photon energies between 17 and 1,000 keV. The amount of uncertainty due to the breathing motion was estimated by looking at the efficiency bias, which was highest at low photon energies as expected due to attenuation and geometry effects. Also, to reduce the influence of the detectors' positioning, an array was calculated by adding the individual detector tallies for a given energy and timeframe. For photon energies of 40 keV and higher, the array efficiency bias showed an underestimation of about 5%. If compared to other parameters already studied by the HML, this value demonstrates the insignificant impact of the breathing motion.
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http://dx.doi.org/10.1097/HP.0000000000000156 | DOI Listing |
Hum Brain Mapp
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Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, Espoo, Finland.
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Arch Razi Inst
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Department of Food Science and Technology, Science and Research Branch, Islamic Azad University, Tehran, Iran.
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