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Updated: Jun 8, 2026

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Pulmonary mycobacterial disease: diagnostic performance of low-dose digital tomosynthesis as compared with chest
Eun Young Kim1, Myung Jin Chung, Ho Yun Lee
1Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Purpose:
To compare the diagnostic performance of a low-radiation-dose digital tomosynthesis (DTS) technique with that of conventional radiography in the detection of lung lesions in patients with pulmonary mycobacterial disease.
Materials And Methods:
The institutional review board approved this study, and all patients provided informed consent. In this study, 100 patients (65 study patients, 35 control patients) underwent multidetector computed tomography (CT), chest radiography, and low-dose DTS (effective doses: 3.4, 0.02, and 0.05 mSv, respectively). Two radiologists evaluated radiographs and DTS images for the presence of parenchymal lesions and the number of cavities in each patient; CT served as the reference standard. Wilcoxon signed rank and McNemar tests and κ statistics were used.
Results:
The accuracies of DTS and radiography in depicting mycobacterial disease were 97% and 89%, respectively, for observer 1 (P = .039) and 99% and 93%, respectively, for observer 2 (P = .031). The accuracies of DTS and radiography in depicting each lesion type were, respectively, 95% and 77% for bronchiolitis, 92% and 76% for nodules, 86% and 79% for consolidation, and 93% and 70% for cavities. Interobserver agreement with DTS (κ = 0.62-0.94) was superior to that with radiography (κ = 0.46-0.62). Of a total of 141 cavities found with CT, means of 27 (19%) cavities at chest radiography and 108 (77%) cavities at DTS (P < .01) were detected by the two observers.
Conclusion:
DTS performed with a low-dose technique is superior to radiography for the detection of lung lesions in patients with pulmonary mycobacterial disease.
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