Title:
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Robust and Reproducible Quantification of the Extent of Chest
Radiographic Abnormalities (And It's Free!)
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Author:
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Requena-Méndez, Ana; Aldasoro, Edelweiss; Muñoz, José; Moore, David A. J.
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Abstract:
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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. |
Subject(s):
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-Tuberculosi -Radiografia -Programari lliure -Processament d'imatges -Perú -Tuberculosis -Radiography -Open source software -Image processing -Peru |
Rights:
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cc by (c) Requena-Mendez et al., 2015
http://creativecommons.org/licenses/by/3.0/es/ |
Document type:
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Article Article - Published version |
Published by:
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Public Library of Science (PLoS)
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