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Published: 2016-02-11

CT Imaging Features in the Characterization of Non-Growing Solid Pulmonary Nodules in Non-Smokers

Simone Perandini, Gian Alberto Soardi, Massimiliano Motton, Raffaele Augelli, Lisa Zantedeschi, Stefania Montemezzi

(Department of Radiology, Azienda Ospedaliera Universitaria Integrata (AOUI) Verona, Verona, Italy)

Pol J Radiol 2016; 81:46-50

DOI: 10.12659/PJR.895307


BACKGROUND: A disappearing or persistent solid pulmonary nodule is a neglected clinical entity that still poses serious interpretative issues to date. Traditional knowledge deriving from previous reports suggests particular features, such as smooth edges or regular shape, to be significantly associated with benignity. A large number of benign nodules are reported among smokers in lung cancer screening programmes.
The aim of this single-center retrospective study was to correlate specific imaging features to verify if traditional knowledge as well as more recent acquisitions regarding benign SPNs can be considered reliable in a current case series of nodules collected in a non-smoker cohort of patients.
MATERIAL AND METHODS: Fifty-three solid SPNs proven as non-growing during follow-up imaging were analyzed with regard to their imaging features at thin-section CT, their predicted malignancy risk according to three major risk assessment models, minimum density analysis and contrast enhanced-CT in the relative subgroups of nodules which underwent such tests.
RESULTS: Eleven nodules disappeared during follow-up, 29 showed volume loss and 16 had a VDT of 1121 days or higher. There were 48 nodules located peripherally (85.71%). Evaluation of the enhancement after contrast media (n=29) showed mean enhancement ±SD of 25.72±35.03 HU, median of 18 HU, ranging from 0 to 190 HU. Minimum density assessment (n=30) showed mean minimum HU ±SD of –28.27±47.86 HU, median of –25 HU, ranging from –144 to 68 HU. Mean malignancy risk ±SD was 15.05±26.69% for the BIMC model, 17.22±19.00% for the Mayo Clinic model and 19.07±33.16% for the Gurney’s model... read more

Keywords: Lung Neoplasms, multidetector computed tomography, solitary pulmonary nodule



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