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

# metadata.dc.description.abstract[].value
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.

# metadata.dc.source[].value
Articles publicats en revistes (ISGlobal)

# metadata.dc.title[].value
Robust and Reproducible Quantification of the Extent of Chest
                Radiographic Abnormalities (And It's Free!)