Computer-Aided Segmentation and Volumetry of Artificial Ground-Glass Nodules at Chest CT
Publication year
2013Source
American Journal of Roentgenology, 201, 2, (2013), pp. 295-300ISSN
Publication type
Article / Letter to editor

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Organization
Radiology
Journal title
American Journal of Roentgenology
Volume
vol. 201
Issue
iss. 2
Page start
p. 295
Page end
p. 300
Subject
N4i 3: Poverty-related infectious diseases ONCOL 5: Aetiology, screening and detection; ONCOL 5: Aetiology, screening and detectionAbstract
OBJECTIVE. The purpose of this study was to investigate a new software program for semiautomatic measurement of the volume and mass of ground-glass nodules (GGNs) in a chest phantom and to investigate the influence of CT scanner, reconstruction filter, tube voltage, and tube current. MATERIALS AND METHODS. We used an anthropomorphic chest phantom with eight artificial GGNs with two different CT attenuations and four different volumes. CT scans were obtained with four models of CT scanner at 120 kVp and 25 mAs with a soft and a sharp reconstruction filter. On the 256-MDCT scanner, the tube current-exposure time product and tube voltage settings were varied. GGNs were measured with software that automatically segmented the nodules. Absolute percentage error (APE) was calculated for volume, mass, and density. Wilcoxon signed rank, Mann-Whitney U, and Kruskal-Wallis tests were used for analysis. RESULTS. Volume and mass did not differ significantly from the true values. When measurements were expressed as APE, the error range was 2-36\% for volume and 5-46\% for mass, which was significantly different from no error. We did not find significant differences in APE between CT scanners with filters for lower tube current for volume or lower tube voltage for mass. CONCLUSION. Computer-aided segmentation and mass and volume measurements of GGNs with the prototype software had promising results in this study.
This item appears in the following Collection(s)
- Academic publications [229134]
- Electronic publications [111496]
- Faculty of Medical Sciences [87758]
- Open Access publications [80319]
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