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Considerations in assigning dose based on uncertainties from in vivo counting.

Lung counting is highly geometry dependent, especially at low photon energies. Monte Carlo simulations have been used to determine the magnitude of the errors obtained if it is assumed that the deposition is homogeneous, when in fact it is not. Simulation for a germanium lung counting system consist...

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Autor principal: Kramer, G H
Formato: Texto
Lenguaje:English
Publicado: 1997
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1469955/
https://www.ncbi.nlm.nih.gov/pubmed/9467050
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author Kramer, G H
author_facet Kramer, G H
author_sort Kramer, G H
collection PubMed
description Lung counting is highly geometry dependent, especially at low photon energies. Monte Carlo simulations have been used to determine the magnitude of the errors obtained if it is assumed that the deposition is homogeneous, when in fact it is not. Simulation for a germanium lung counting system consisting of four, 70 mm x 30 mm diameter thick detectors have been performed for 70 deposition patterns. The detector efficiencies for 20, 40, 60, 120, 240, 660, and 1000 kiloelectron volts were calculated for a homogeneous deposition and these efficiencies were used to estimate the bias when the deposition was heterogeneous. A bias of 800% was not unusual. Whole-body counting is prone to errors that can arise from the activity distribution and/or size of the subject. The latter are geometry dependent and, for example, a bias result of 200% can be obtained when measuring children in a chair geometry using a calibration factor based on reference man. Thyroid counting is the least prone to error. If the measurement is done correctly, biases can usually be kept below 20%. However, if the measurement is made with a collimator or if the detector is in contact with the subject's neck, biases exceeding 200% can be obtained.
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spelling pubmed-14699552006-06-01 Considerations in assigning dose based on uncertainties from in vivo counting. Kramer, G H Environ Health Perspect Research Article Lung counting is highly geometry dependent, especially at low photon energies. Monte Carlo simulations have been used to determine the magnitude of the errors obtained if it is assumed that the deposition is homogeneous, when in fact it is not. Simulation for a germanium lung counting system consisting of four, 70 mm x 30 mm diameter thick detectors have been performed for 70 deposition patterns. The detector efficiencies for 20, 40, 60, 120, 240, 660, and 1000 kiloelectron volts were calculated for a homogeneous deposition and these efficiencies were used to estimate the bias when the deposition was heterogeneous. A bias of 800% was not unusual. Whole-body counting is prone to errors that can arise from the activity distribution and/or size of the subject. The latter are geometry dependent and, for example, a bias result of 200% can be obtained when measuring children in a chair geometry using a calibration factor based on reference man. Thyroid counting is the least prone to error. If the measurement is done correctly, biases can usually be kept below 20%. However, if the measurement is made with a collimator or if the detector is in contact with the subject's neck, biases exceeding 200% can be obtained. 1997-12 /pmc/articles/PMC1469955/ /pubmed/9467050 Text en
spellingShingle Research Article
Kramer, G H
Considerations in assigning dose based on uncertainties from in vivo counting.
title Considerations in assigning dose based on uncertainties from in vivo counting.
title_full Considerations in assigning dose based on uncertainties from in vivo counting.
title_fullStr Considerations in assigning dose based on uncertainties from in vivo counting.
title_full_unstemmed Considerations in assigning dose based on uncertainties from in vivo counting.
title_short Considerations in assigning dose based on uncertainties from in vivo counting.
title_sort considerations in assigning dose based on uncertainties from in vivo counting.
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1469955/
https://www.ncbi.nlm.nih.gov/pubmed/9467050
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