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Robust and Reproducible Quantification of the Extent of Chest Radiographic Abnormalities (And It’s Free!)

RATIONALE: Objective, reproducible quantification of the extent of abnormalities seen on a chest radiograph would improve the user-friendliness of a previously proposed severity scoring system for pulmonary tuberculosis and could be helpful in monitoring response to therapy, including in clinical tr...

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Autores principales: Requena-Méndez, Ana, Aldasoro, Edelweiss, Muñoz, Jose, Moore, David A. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4440724/
https://www.ncbi.nlm.nih.gov/pubmed/25996917
http://dx.doi.org/10.1371/journal.pone.0128044
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author Requena-Méndez, Ana
Aldasoro, Edelweiss
Muñoz, Jose
Moore, David A. J.
author_facet Requena-Méndez, Ana
Aldasoro, Edelweiss
Muñoz, Jose
Moore, David A. J.
author_sort Requena-Méndez, Ana
collection PubMed
description RATIONALE: Objective, reproducible quantification of the extent of abnormalities seen on a chest radiograph would improve the user-friendliness of a previously proposed severity scoring system for pulmonary tuberculosis and could be helpful in monitoring response to therapy, including in clinical trials. METHODS: In this study we report the development and evaluation of a simple tool using free image editing software (GIMP) to accurately and reproducibly quantify the area of affected lung on the chest radiograph of tuberculosis patients. As part of a pharmacokinetic study in Lima, Peru, a chest radiograph was performed on patients with pulmonary tuberculosis and this was subsequently photographed using a digital camera. The GIMP software was used by two independent and trained readers to estimate the extent of affected lung (expressed as a percentage of total lung area) in each radiograph and the resulting radiographic SCORE. RESULTS: 56 chest radiographs were included in the reading analysis. The Intraclass correlation coefficient (ICC) between the 2 observers was 0.977 (p<0.001) for the area of lung affected and was 0.955 (p<0.001) for the final score; and the kappa coefficient of Interobserver agreement for both the area of lung affected and the score were 0.9 (p<0.001) and 0.86 (p<0.001) respectively. CONCLUSIONS: This high level of between-observer agreement suggests that this freely available software could constitute a simple and useful tool for robust evaluation of individual and serial chest radiographs.
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spelling pubmed-44407242015-05-29 Robust and Reproducible Quantification of the Extent of Chest Radiographic Abnormalities (And It’s Free!) Requena-Méndez, Ana Aldasoro, Edelweiss Muñoz, Jose Moore, David A. J. PLoS One Research Article RATIONALE: Objective, reproducible quantification of the extent of abnormalities seen on a chest radiograph would improve the user-friendliness of a previously proposed severity scoring system for pulmonary tuberculosis and could be helpful in monitoring response to therapy, including in clinical trials. METHODS: In this study we report the development and evaluation of a simple tool using free image editing software (GIMP) to accurately and reproducibly quantify the area of affected lung on the chest radiograph of tuberculosis patients. As part of a pharmacokinetic study in Lima, Peru, a chest radiograph was performed on patients with pulmonary tuberculosis and this was subsequently photographed using a digital camera. The GIMP software was used by two independent and trained readers to estimate the extent of affected lung (expressed as a percentage of total lung area) in each radiograph and the resulting radiographic SCORE. RESULTS: 56 chest radiographs were included in the reading analysis. The Intraclass correlation coefficient (ICC) between the 2 observers was 0.977 (p<0.001) for the area of lung affected and was 0.955 (p<0.001) for the final score; and the kappa coefficient of Interobserver agreement for both the area of lung affected and the score were 0.9 (p<0.001) and 0.86 (p<0.001) respectively. CONCLUSIONS: This high level of between-observer agreement suggests that this freely available software could constitute a simple and useful tool for robust evaluation of individual and serial chest radiographs. Public Library of Science 2015-05-21 /pmc/articles/PMC4440724/ /pubmed/25996917 http://dx.doi.org/10.1371/journal.pone.0128044 Text en © 2015 Requena-Méndez 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Requena-Méndez, Ana
Aldasoro, Edelweiss
Muñoz, Jose
Moore, David A. J.
Robust and Reproducible Quantification of the Extent of Chest Radiographic Abnormalities (And It’s Free!)
title Robust and Reproducible Quantification of the Extent of Chest Radiographic Abnormalities (And It’s Free!)
title_full Robust and Reproducible Quantification of the Extent of Chest Radiographic Abnormalities (And It’s Free!)
title_fullStr Robust and Reproducible Quantification of the Extent of Chest Radiographic Abnormalities (And It’s Free!)
title_full_unstemmed Robust and Reproducible Quantification of the Extent of Chest Radiographic Abnormalities (And It’s Free!)
title_short Robust and Reproducible Quantification of the Extent of Chest Radiographic Abnormalities (And It’s Free!)
title_sort robust and reproducible quantification of the extent of chest radiographic abnormalities (and it’s free!)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4440724/
https://www.ncbi.nlm.nih.gov/pubmed/25996917
http://dx.doi.org/10.1371/journal.pone.0128044
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