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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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Detalles Bibliográficos
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
Descripción
Sumario: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.