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Transient subsolid nodules in patients with extrapulmonary malignancies: their frequency and differential features

Cited 16 time in Web of Science Cited 16 time in Scopus
Authors

Choi, Won Seok; Park, Chang Min; Song, Yong Sub; Lee, Sang Min; Wi, Jae Yeon; Goo, Jin Mo

Issue Date
2015-04
Publisher
Taylor & Francis
Citation
Acta Radiologica, Vol.56 No.4, pp.428-437
Abstract
Background: For pulmonary subsolid nodules (SSNs) in patients with extrapulmonary malignancies, it is still unclear what proportion of SSNs is transient and how we can more accurately diagnose these transient SSNs. Purpose: To investigate the frequency of transient SSNs and their differentiating clinical and thin-section computed tomography (CT) features in patients with extrapulmonary malignancies. Material and Methods: From January 2005 to February 2012, 78 SSNs in 63 individuals (30 men and 33 women; mean age, 55.1 years +/- 15.5) with extrapulmonary malignancies were identified. Their clinical and thin-section CT characteristics were reviewed and compared between transient and persistent SSNs. Differentiating factors and their performance were also measured. Results: Thirty-six of the 78 SSNs (46.2%) were transient. Between transient and persistent SSNs, there were significant differences in patients' age, sex, detection mode, and the presence of eosinophilia, lesion multiplicity, lesion margin, and pleural retraction (P < 0.05). Multivariate analysis revealed that follow-up detected SSNs (adjusted odds ratio [OR], 38.88), multiple lesions (OR, 7.64), and an ill-defined nodular margin (OR, 11.93) were significant discriminators of transient SSNs (P < 0.05). Discrimination of transient SSNs was significantly better upon incorporating both clinical and thin-section CT features than using clinical features alone (P < 0.05). Conclusion: Approximately half of the SSNs detected in patients with extrapulmonary malignancies were transient. Transient SSNs in these patients can be very accurately differentiated using their thin-section CT and clinical features.
ISSN
0284-1851
URI
https://hdl.handle.net/10371/207245
DOI
https://doi.org/10.1177/0284185114528325
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  • College of Medicine
  • Department of Medicine
Research Area Radiology

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