Purpose: To prospectively compare bronchial measurements obtained with three-dimensional quantitative thin-section computed tomography (CT) with those obtained with thin-section CT scores in the assessment of the severity of pulmonary cystic fibrosis (CF).
Materials And Methods: Ethics committee approval was obtained. Sixteen patients with CF (mean age, 26.6 years; range, 18-42 years) and five healthy volunteers (mean age, 27.4 years; range, 21-44 years) gave written informed consent, underwent multi-detector row CT and a pulmonary function test (PFT), and were divided into three groups: group A, healthy volunteers; group B, patients with mild CF (forced expiratory volume in 1 second [FEV(1)] > 80%); and group C, patients with severe CF (FEV(1) < 80%). Two observers obtained thin-section CT scores with eight scoring systems. Bronchial cross-sectional wall area (WA), lumen area (LA), airway area, and wall thickness (WT) were measured with customized software and were normalized on the basis of subject body surface. Morphologic characteristics, PFT results, thin-section CT scores, and quantitative measurements were compared among the three groups with analysis of variance. Correlations among bronchial measurements, PFT results, and CT scores were calculated with the Spearman correlation coefficient.
Results: Thin-section CT scores were different between group C and either group A or group B (P < .05). WA and WT were significantly different among all groups (P < .05). Interscore correlations and correlations between bronchial parameters and scores were high (r > 0.89, P < .0001). Scores, WA, and WT were significantly correlated with PFT obstructive indexes (P < .047).
Conclusion: WA and WT assessed with dedicated software on multi-detector row CT images allow evaluation of the severity of pulmonary CF.
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http://dx.doi.org/10.1148/radiol.2422060030 | DOI Listing |
Diagnostics (Basel)
December 2024
Department of Respiratory Medicine, JSS Medical College, JSS Academy of Higher Education & Research (JSS AHER), Mysore 570004, Karnataka, India.
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January 2025
Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, China. Electronic address:
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Diagn Pathol
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Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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BMC Cancer
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