Literature DB >> 31446982

Lung cancers associated with cystic airspaces: CT features and pathologic correlation.

Yingran Shen1, Xinnan Xu1, Yunfei Zhang1, Weitong Li2, Jie Dai1, Siming Jiang1, Tong Wu3, Haomin Cai1, Alan Sihoe1, Jingyun Shi4, Gening Jiang5.   

Abstract

OBJECTIVE: Lung cancer associated with cystic airspaces (LCCA) is a rare entity. The diagnosis and treatment is often delayed due to lack of comprehension of this disease. We aimed to elucidate LCCA's clinicopathological characteristics and investigate imaging features correlated with pathological invasiveness.
METHOD: The preoperative computed tomographic (CT) scans of 10,835 patients diagnosed with NSCLC between January 2015 and December 2016 were reviewed by two thoracic radiologists for association with a cystic airspace. A clinicopathological and radiological feature analysis was done. RESULT: A total number of 123 LCCA patients were identified and four morphologic patterns were recognized: I, thin-walled type (n = 23, 18.7%); II, thick-walled type (n = 34, 27.6%); III, a cystic airspace with a mural nodule (CWN) type (n = 43, 35.0%); and IV, mixed type (n = 23, 18.7%). A solid component in the cyst wall predicted histological invasiveness in all four types of LCCA. The proportion of moderately/poorly (M/P)-differentiated subtype in type III (85.0%) was higher than in other three patterns (which were 50.0%, 50.0%, and 69.6%, respectively). Multivariate analysis revealed that type III pattern (odds ratio [OR], 6.5; 95% confidence interval [CI], 1.1-36.4; P = 0.035), part-solid/solid component in wall (part-solid: OR, 27.2; 95% CI, 5.6-3131.6; P < 0.001; solid: OR 614.6; 95% CI, 36.4-10,368.6; P < 0.001), and irregular inner surface of cyst (OR 7.0; 95% CI 1.9-26.2; P = 0.004) were independent risk factors for the M/P-differentiated subtype. EGFR mutations were the predominant genetic alterations in each type of LCCAs, but no significant difference was found among them.
CONCLUSIONS: In LCCA, morphological patterns and wall components were two important predictors for determining pathological invasiveness.
Copyright © 2019. Published by Elsevier B.V.

Entities:  

Keywords:  Computed tomography; Histological types of neoplasms; Lung adenocarcinoma

Mesh:

Substances:

Year:  2019        PMID: 31446982     DOI: 10.1016/j.lungcan.2019.05.012

Source DB:  PubMed          Journal:  Lung Cancer        ISSN: 0169-5002            Impact factor:   5.705


  4 in total

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  4 in total

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