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Quantitative image analysis using chest computed tomography in the evaluation of lymph node involvement in pulmonary sarcoidosis and tuberculosis

PURPOSE: To evaluate the feasibility of quantitative analysis of chest computed tomography (CT) scans for the assessment of lymph node (LN) involvement in patients with pulmonary tuberculosis and sarcoidosis. METHODS: In 47 patients with tuberculosis (n = 26) or sarcoidosis (n = 21), 115 lymph nodes...

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Autores principales: Lee, Chang Un, Chong, Semin, Choi, Hye Won, Choi, Jae Chol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6258228/
https://www.ncbi.nlm.nih.gov/pubmed/30475907
http://dx.doi.org/10.1371/journal.pone.0207959
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author Lee, Chang Un
Chong, Semin
Choi, Hye Won
Choi, Jae Chol
author_facet Lee, Chang Un
Chong, Semin
Choi, Hye Won
Choi, Jae Chol
author_sort Lee, Chang Un
collection PubMed
description PURPOSE: To evaluate the feasibility of quantitative analysis of chest computed tomography (CT) scans for the assessment of lymph node (LN) involvement in patients with pulmonary tuberculosis and sarcoidosis. METHODS: In 47 patients with tuberculosis (n = 26) or sarcoidosis (n = 21), 115 lymph nodes (tuberculous, 55; sarcoid, 60) were visually analyzed on chest CT scans according to their size, location, attenuation and shape. Each node was manually segmented using image analysis tool, which was quantitatively analyzed using the following variables: Feret’s diameter, perimeter, area, circularity, mean grey value (Mean), standard deviation (SD) of grey value, minimum grey value (Min), maximum grey value (Max), median grey value (Median), skewness, kurtosis, and net enhancement. We statistically analyzed the visual and quantitative CT features of tuberculous and sarcoid LNs. RESULTS: In visual CT analysis, the mean node size in sarcoidosis was significantly greater than that in tuberculosis. There were no statistical differences between tuberculous and sarcoid LNs in terms of location and shape. Central low attenuation and peripheral rim enhancement were more frequently observed in tuberculous LNs than in the sarcoid ones. In quantitative CT analysis, there were significant differences in the values of the Feret’s diameter, perimeter, area, circularity, mean grey value, SD, median, skewness, and kurtosis between tuberculous and sarcoid LNs. CONCLUSIONS: Quantitative CT analysis using CT parameters with pixel-by-pixel measurements can help to differentiate of tuberculous and sarcoid LNs.
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spelling pubmed-62582282018-12-06 Quantitative image analysis using chest computed tomography in the evaluation of lymph node involvement in pulmonary sarcoidosis and tuberculosis Lee, Chang Un Chong, Semin Choi, Hye Won Choi, Jae Chol PLoS One Research Article PURPOSE: To evaluate the feasibility of quantitative analysis of chest computed tomography (CT) scans for the assessment of lymph node (LN) involvement in patients with pulmonary tuberculosis and sarcoidosis. METHODS: In 47 patients with tuberculosis (n = 26) or sarcoidosis (n = 21), 115 lymph nodes (tuberculous, 55; sarcoid, 60) were visually analyzed on chest CT scans according to their size, location, attenuation and shape. Each node was manually segmented using image analysis tool, which was quantitatively analyzed using the following variables: Feret’s diameter, perimeter, area, circularity, mean grey value (Mean), standard deviation (SD) of grey value, minimum grey value (Min), maximum grey value (Max), median grey value (Median), skewness, kurtosis, and net enhancement. We statistically analyzed the visual and quantitative CT features of tuberculous and sarcoid LNs. RESULTS: In visual CT analysis, the mean node size in sarcoidosis was significantly greater than that in tuberculosis. There were no statistical differences between tuberculous and sarcoid LNs in terms of location and shape. Central low attenuation and peripheral rim enhancement were more frequently observed in tuberculous LNs than in the sarcoid ones. In quantitative CT analysis, there were significant differences in the values of the Feret’s diameter, perimeter, area, circularity, mean grey value, SD, median, skewness, and kurtosis between tuberculous and sarcoid LNs. CONCLUSIONS: Quantitative CT analysis using CT parameters with pixel-by-pixel measurements can help to differentiate of tuberculous and sarcoid LNs. Public Library of Science 2018-11-26 /pmc/articles/PMC6258228/ /pubmed/30475907 http://dx.doi.org/10.1371/journal.pone.0207959 Text en © 2018 Lee et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lee, Chang Un
Chong, Semin
Choi, Hye Won
Choi, Jae Chol
Quantitative image analysis using chest computed tomography in the evaluation of lymph node involvement in pulmonary sarcoidosis and tuberculosis
title Quantitative image analysis using chest computed tomography in the evaluation of lymph node involvement in pulmonary sarcoidosis and tuberculosis
title_full Quantitative image analysis using chest computed tomography in the evaluation of lymph node involvement in pulmonary sarcoidosis and tuberculosis
title_fullStr Quantitative image analysis using chest computed tomography in the evaluation of lymph node involvement in pulmonary sarcoidosis and tuberculosis
title_full_unstemmed Quantitative image analysis using chest computed tomography in the evaluation of lymph node involvement in pulmonary sarcoidosis and tuberculosis
title_short Quantitative image analysis using chest computed tomography in the evaluation of lymph node involvement in pulmonary sarcoidosis and tuberculosis
title_sort quantitative image analysis using chest computed tomography in the evaluation of lymph node involvement in pulmonary sarcoidosis and tuberculosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6258228/
https://www.ncbi.nlm.nih.gov/pubmed/30475907
http://dx.doi.org/10.1371/journal.pone.0207959
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