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Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?

BACKGROUND: Dynamic contrast-enhanced computed tomography (DCE-CT) is a tool, which, in theory, can quantify the blood flow and blood volume of tissues. In structured qualitative analysis, parametric color maps yield a visual impression of the blood flow and blood volume within the tissue being stud...

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Autores principales: Harders, Stefan Walbom, Madsen, Hans Henrik, Nellemann, Hanne Marie, Rasmussen, Torben Riis, Thygesen, Jesper, Hager, Henrik, Andersen, Niels Trolle, Rasmussen, Finn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5453405/
https://www.ncbi.nlm.nih.gov/pubmed/28607762
http://dx.doi.org/10.1177/2058460117710053
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author Harders, Stefan Walbom
Madsen, Hans Henrik
Nellemann, Hanne Marie
Rasmussen, Torben Riis
Thygesen, Jesper
Hager, Henrik
Andersen, Niels Trolle
Rasmussen, Finn
author_facet Harders, Stefan Walbom
Madsen, Hans Henrik
Nellemann, Hanne Marie
Rasmussen, Torben Riis
Thygesen, Jesper
Hager, Henrik
Andersen, Niels Trolle
Rasmussen, Finn
author_sort Harders, Stefan Walbom
collection PubMed
description BACKGROUND: Dynamic contrast-enhanced computed tomography (DCE-CT) is a tool, which, in theory, can quantify the blood flow and blood volume of tissues. In structured qualitative analysis, parametric color maps yield a visual impression of the blood flow and blood volume within the tissue being studied, allowing for quick identification of the areas with the highest or lowest blood flow and blood volume. PURPOSE: To examine whether DCE-CT could be used to distinguish between malignant and benign lung tumors in patients with suspected lung cancer. MATERIAL AND METHODS: Fifty-nine patients with suspected lung cancer and a lung tumor on their chest radiograph were included for DCE-CT. The tumors were categorized using structured qualitative analysis of tumor blood flow patterns. Histopathology was used as reference standard. RESULTS: Using structured qualitative analysis of tumor blood flow patterns, it was possible to distinguish between malignant and benign lung tumors (Fisher–Freeman–Halton exact test, P = 0.022). The inter-reader agreement of this method of analysis was slight to moderate (kappa = 0.30; 95% confidence interval [CI] = 0.13–0.46). CONCLUSION: DCE-CT in suspected lung cancer using structured qualitative analysis of tumor blood flow patterns is accurate as well as somewhat reproducible. However, there are significant limitations to DCE-CT.
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spelling pubmed-54534052017-06-12 Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors? Harders, Stefan Walbom Madsen, Hans Henrik Nellemann, Hanne Marie Rasmussen, Torben Riis Thygesen, Jesper Hager, Henrik Andersen, Niels Trolle Rasmussen, Finn Acta Radiol Open Research BACKGROUND: Dynamic contrast-enhanced computed tomography (DCE-CT) is a tool, which, in theory, can quantify the blood flow and blood volume of tissues. In structured qualitative analysis, parametric color maps yield a visual impression of the blood flow and blood volume within the tissue being studied, allowing for quick identification of the areas with the highest or lowest blood flow and blood volume. PURPOSE: To examine whether DCE-CT could be used to distinguish between malignant and benign lung tumors in patients with suspected lung cancer. MATERIAL AND METHODS: Fifty-nine patients with suspected lung cancer and a lung tumor on their chest radiograph were included for DCE-CT. The tumors were categorized using structured qualitative analysis of tumor blood flow patterns. Histopathology was used as reference standard. RESULTS: Using structured qualitative analysis of tumor blood flow patterns, it was possible to distinguish between malignant and benign lung tumors (Fisher–Freeman–Halton exact test, P = 0.022). The inter-reader agreement of this method of analysis was slight to moderate (kappa = 0.30; 95% confidence interval [CI] = 0.13–0.46). CONCLUSION: DCE-CT in suspected lung cancer using structured qualitative analysis of tumor blood flow patterns is accurate as well as somewhat reproducible. However, there are significant limitations to DCE-CT. SAGE Publications 2017-05-30 /pmc/articles/PMC5453405/ /pubmed/28607762 http://dx.doi.org/10.1177/2058460117710053 Text en © The Foundation Acta Radiologica 2017 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page(https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Research
Harders, Stefan Walbom
Madsen, Hans Henrik
Nellemann, Hanne Marie
Rasmussen, Torben Riis
Thygesen, Jesper
Hager, Henrik
Andersen, Niels Trolle
Rasmussen, Finn
Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?
title Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?
title_full Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?
title_fullStr Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?
title_full_unstemmed Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?
title_short Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?
title_sort can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5453405/
https://www.ncbi.nlm.nih.gov/pubmed/28607762
http://dx.doi.org/10.1177/2058460117710053
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