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Evaluation of lung densitometric and volumetric changes in silicosis patients using three-dimensional software for multidetector CT and the relationship with profusion scores.
- Source :
-
Clinical radiology [Clin Radiol] 2021 May; Vol. 76 (5), pp. 393.e19-393.e24. Date of Electronic Publication: 2021 Jan 26. - Publication Year :
- 2021
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Abstract
- Aim: To evaluate the density and volume changes in the lungs of silicosis patients and their relationship with the disease severity classification of the International Labor Organization (ILO).<br />Materials and Methods: The multidetector computed tomography (CT) images of 44 patients diagnosed with silicosis and 32 controls that underwent thoracic CT due to trauma were evaluated. Patients with silicosis were divided into three categories according to the ILO classification. Data related to the total lung volume, total lung mean density, lung opacity score, percentage of lung high opacity, and mean density in the lower and upper lobes were obtained using three-dimensional (3D) software.<br />Results: There was no significant difference between the total lung mean densities of the silicosis and control groups (p=0.213); however, a significant difference was observed between the two groups in terms of the total lung volume (p<0.0001). According to the ILO classification, there was a significant difference between the disease severity categories in relation to the percentage of lung high opacity (p=0.000005). A strong correlation was detected between disease severity and high opacity percentage (p<0.0001, r=0.804). According to the ILO classification, there was also a significant difference between disease severity categories in terms of the lung opacity score (p=0.000144), as well as a moderate correlation between disease severity and opacity score (p<0.0001, r=0.580).<br />Conclusion: Total lung volume is a CT finding that shows variation in exposure to crystalline silica. The percentage of high opacity determined using multidetector CT is an effective parameter in evaluating disease severity.<br /> (Copyright © 2021 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1365-229X
- Volume :
- 76
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Clinical radiology
- Publication Type :
- Academic Journal
- Accession number :
- 33509607
- Full Text :
- https://doi.org/10.1016/j.crad.2020.12.015