Differentiation between mucus secretion and endoluminal tumors in the airway: Analysis and comparison of CT findings

Sae Rom Hong, Yeo Jin Lee, Yoo Jin Hong, Jin Hur, Young Jin Kim, Byoung Wook Choi, Hye Jeong Lee

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

OBJECTIVE. The objective of our study was to suggest CT features that help differentiate transient mucus secretion from airway tumors in the evaluation of soft-tissue nodular lesions confined within the airway lumen. MATERIALS AND METHODS. Forty-two patients with airway tumors (mean age, 57.6 ± 14.9 [SD] years) and 48 patients with secretion (mean age, 67.8 ± 13.4 years) were included. Two observers analyzed the following features on contrast-enhanced CT in consensus readings: shape (round, ovoid, lobulating, or complex); margin (circumscribed or uncircumscribed); size (including change in size between mediastinal and lung window images); location (anterior, posterior, or unclear); angle between the lesion and contacting airway wall (acute, obtuse, or unclear); attenuation (quantitative and qualitative analyses); and presence of air, fat, or calcification within the lesion. The positive predictive value (PPV) of each CT finding was calculated for secretion and tumor, respectively. RESULTS. Round (90.0%) or lobulating (92.9%) shape, uncircumscribed margin (100.0%), unclear location (87.5%), unclear angle (87.5%), a CT number of 21.7 HU or more (91.7%), and internal features such as fat (100.0%) or calcification (100.0%) showed high PPVs for tumors. Complex shape (100.0%), change in size of more than 15.9% (96.8%), a CT number of less than 21.7 HU (83.3%), and internal air density (100.0%) showed high PPVs for secretion. CONCLUSION. On contrast-enhanced CT, the evaluation of shape, change in size between mediastinal and lung window images, the measurement of CT number, and internal features such as air, fat, or calcification might help differentiate secretion from tumors.

Original languageEnglish
Pages (from-to)982-988
Number of pages7
JournalAmerican Journal of Roentgenology
Volume202
Issue number5
DOIs
Publication statusPublished - 2014 May

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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