Additional coronal images using low-milliamperage multidetector-row computed tomography: effectiveness in the diagnosis of bronchiectasis
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Updated: Sep 20, 2026

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
Published on: April 12, 2024
Yon Mi Sung1, Kyung Soo Lee, Chin A Yi
1Department of Radiology, Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Kangnam-Ku, Seoul 135-710, Korea.
Purpose:
The aim of our study was to evaluate the effectiveness of additional coronal images using low-milliamperage multidetector-row computed tomography (CT) in the diagnosis of bronchiectasis.
Methods:
Helical volumetric CT scans (120 kVp, 70 mA, 2.5-mm collimation, table speed of 15 mm/s, table rotation time of 1 second) using low-milliamperage multidetector-row CT were obtained through the thorax in 110 patients who were suspected of bronchiectasis. Both axial (2.5-mm section thickness) and coronal (1.3-2.0-mm section thickness) reformatted images were made and sent to picture archiving and communication system (PACS) monitors. Two independent observers assessed CT scans twice; with axial images only and with both axial and coronal images. The detection rates of bronchiectasis were compared between readings with axial images only and with both axial and coronal images by using a nonparametric method of clustered data. Confidence grades were given to the distribution and type of bronchiectasis.
Results:
With axial images only, the detection rates of bronchiectasis on a per-patient basis were 97% (213/220 patients, kappa = 0.888) whereas with both axial and coronal images, the detection rates were 100% (220/220 patients, kappa = 1.000) (P = 0.0001). Confidence to the distribution of bronchiectasis was greater with both axial and coronal images than with axial images only (P = 0.008).
Conclusions:
Additional coronal images using low-milliamperage multidetector-row CT are effective in the diagnosis of bronchiectasis by providing enhanced detection rates and confidence to the distribution of lesions.
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