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Dual-layer spectral computed tomography: measuring relative electron density
BACKGROUND: X-ray and particle radiation therapy planning requires accurate estimation of local electron density within the patient body to calculate dose delivery to tumour regions. We evaluate the feasibility and accuracy of electron density measurement using dual-layer computed tomography (DLCT),...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103960/ https://www.ncbi.nlm.nih.gov/pubmed/30175319 http://dx.doi.org/10.1186/s41747-018-0051-8 |
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author | Mei, Kai Ehn, Sebastian Oechsner, Markus Kopp, Felix K. Pfeiffer, Daniela Fingerle, Alexander A. Pfeiffer, Franz Combs, Stephanie E. Wilkens, Jan J. Rummeny, Ernst J. Noël, Peter B. |
author_facet | Mei, Kai Ehn, Sebastian Oechsner, Markus Kopp, Felix K. Pfeiffer, Daniela Fingerle, Alexander A. Pfeiffer, Franz Combs, Stephanie E. Wilkens, Jan J. Rummeny, Ernst J. Noël, Peter B. |
author_sort | Mei, Kai |
collection | PubMed |
description | BACKGROUND: X-ray and particle radiation therapy planning requires accurate estimation of local electron density within the patient body to calculate dose delivery to tumour regions. We evaluate the feasibility and accuracy of electron density measurement using dual-layer computed tomography (DLCT), a recently introduced dual-energy CT technique. METHODS: Two calibration phantoms were scanned with DLCT and virtual monoenergetic images (VMIs) at 50 keV and 200 keV were generated. We investigated two approaches to obtain relative electron densities from these VMIs: to fit an analytic interaction cross-sectional model and to empirically calibrate a conversion function with one of the phantoms. Knowledge of the emitted x-ray spectrum was not required for the presented work. RESULTS: The results from both methods were highly correlated to the nominal values (R > 0.999). Except for the water and lung inserts, the error was within 1.79% (average 1.53%) for the cross-sectional model and 1.61% (average 0.87%) for the calibrated conversion. Different radiation doses did not have a significant influence on the measurement (p = 0.348, 0.167), suggesting that the methods are reproducible. Further, we applied these methods to routine clinical data. CONCLUSIONS: Our study shows a high validity of electron density estimation based on DLCT, which has potential to improve the procedure and accuracy of measuring electron density in clinical practice. |
format | Online Article Text |
id | pubmed-6103960 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-61039602018-08-30 Dual-layer spectral computed tomography: measuring relative electron density Mei, Kai Ehn, Sebastian Oechsner, Markus Kopp, Felix K. Pfeiffer, Daniela Fingerle, Alexander A. Pfeiffer, Franz Combs, Stephanie E. Wilkens, Jan J. Rummeny, Ernst J. Noël, Peter B. Eur Radiol Exp Original Article BACKGROUND: X-ray and particle radiation therapy planning requires accurate estimation of local electron density within the patient body to calculate dose delivery to tumour regions. We evaluate the feasibility and accuracy of electron density measurement using dual-layer computed tomography (DLCT), a recently introduced dual-energy CT technique. METHODS: Two calibration phantoms were scanned with DLCT and virtual monoenergetic images (VMIs) at 50 keV and 200 keV were generated. We investigated two approaches to obtain relative electron densities from these VMIs: to fit an analytic interaction cross-sectional model and to empirically calibrate a conversion function with one of the phantoms. Knowledge of the emitted x-ray spectrum was not required for the presented work. RESULTS: The results from both methods were highly correlated to the nominal values (R > 0.999). Except for the water and lung inserts, the error was within 1.79% (average 1.53%) for the cross-sectional model and 1.61% (average 0.87%) for the calibrated conversion. Different radiation doses did not have a significant influence on the measurement (p = 0.348, 0.167), suggesting that the methods are reproducible. Further, we applied these methods to routine clinical data. CONCLUSIONS: Our study shows a high validity of electron density estimation based on DLCT, which has potential to improve the procedure and accuracy of measuring electron density in clinical practice. Springer International Publishing 2018-08-22 /pmc/articles/PMC6103960/ /pubmed/30175319 http://dx.doi.org/10.1186/s41747-018-0051-8 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Mei, Kai Ehn, Sebastian Oechsner, Markus Kopp, Felix K. Pfeiffer, Daniela Fingerle, Alexander A. Pfeiffer, Franz Combs, Stephanie E. Wilkens, Jan J. Rummeny, Ernst J. Noël, Peter B. Dual-layer spectral computed tomography: measuring relative electron density |
title | Dual-layer spectral computed tomography: measuring relative electron density |
title_full | Dual-layer spectral computed tomography: measuring relative electron density |
title_fullStr | Dual-layer spectral computed tomography: measuring relative electron density |
title_full_unstemmed | Dual-layer spectral computed tomography: measuring relative electron density |
title_short | Dual-layer spectral computed tomography: measuring relative electron density |
title_sort | dual-layer spectral computed tomography: measuring relative electron density |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103960/ https://www.ncbi.nlm.nih.gov/pubmed/30175319 http://dx.doi.org/10.1186/s41747-018-0051-8 |
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