Skip to main content
Top
Published in: BMC Cancer 1/2021

Open Access 01-12-2021 | Pathology | Research article

HRCT features between lepidic-predominant type and other pathological subtypes in early-stage invasive pulmonary adenocarcinoma appearing as a ground-glass nodule

Authors: Pengju Zhang, Tianran Li, Xuemin Tao, Xin Jin, Shaohong Zhao

Published in: BMC Cancer | Issue 1/2021

Login to get access

Abstract

Background

Different pathological subtypes of invasive pulmonary adenocarcinoma (IPA) have different surgical methods and heterogeneous prognosis. It is essential to clarify IPA subtypes before operation and high-resolution computed tomography (HRCT) plays a very important role in this regard. We aimed to investigate the HRCT features of lepidic-predominant type and other pathological subtypes of early-stage (T1N0M0) IPA appearing as a ground-glass nodule (GGN).

Methods

We performed a retrospective analysis on clinical data and HRCT features of 630 lesions in 589 patients with pathologically confirmed IPA (invasive foci > 5 mm) appearing as pure GGN (pGGN) and mixed GGN (mGGN) with consolidation-to-tumor ratio (CTR) ≤0.5 from January to December 2019. All GGNs were classified as lepidic-predominant adenocarcinoma (LPA) and nonlepidic-predominant adenocarcinoma (n-LPA) groups. Univariate analysis was performed to analyze the differences of clinical data and HRCT features between the LPA and n-LPA groups. Multivariate analysis was conducted to determine the variables to distinguish the LPA from n-LPA group independently. The diagnostic performance of different parameters was compared using receiver operating characteristic curves.

Results

In total, 367 GGNs in the LPA group and 263 GGNs in the n-LPA group were identified. In the univariate analysis, the CTR, mean CT values, and mean diameters as well as mixed GGN, deep lobulation, spiculation, vascular change, bronchial change, and tumor–lung interface were smaller in the LPA group than in the n-LPA group (P <  0.05). Logistic regression model was reconstructed including the mean CT value, CTR, deep lobulation, spiculation, vascular change, and bronchial change (P <  0.05). Area under the curve of the logistic regression model for differentiating LPA and n-LPA was 0.840 (76.4% sensitivity, 78.7% specificity), which was significantly higher than that of the mean CT value or CTR.

Conclusions

Deep lobulation, spiculation, vascular change, and bronchial change, CT value > − 472.5 HU and CTR > 27.4% may indicate nonlepidic predominant invasive pulmonary adenocarcinoma in GGNs.
Literature
6.
go back to reference Mansuet LA, Bobbio A, Blons H, et al. The new histologic classification of lung primary adenocarcinoma subtypes is a reliable prognostic marker and identifies tumors with different mutation status: the experience of a French cohor. Chest. 2014;146(3):633–43. https://doi.org/10.1378/chest.13-2499.CrossRef Mansuet LA, Bobbio A, Blons H, et al. The new histologic classification of lung primary adenocarcinoma subtypes is a reliable prognostic marker and identifies tumors with different mutation status: the experience of a French cohor. Chest. 2014;146(3):633–43. https://​doi.​org/​10.​1378/​chest.​13-2499.CrossRef
Metadata
Title
HRCT features between lepidic-predominant type and other pathological subtypes in early-stage invasive pulmonary adenocarcinoma appearing as a ground-glass nodule
Authors
Pengju Zhang
Tianran Li
Xuemin Tao
Xin Jin
Shaohong Zhao
Publication date
01-12-2021
Publisher
BioMed Central
Keyword
Pathology
Published in
BMC Cancer / Issue 1/2021
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-021-08821-5

Other articles of this Issue 1/2021

BMC Cancer 1/2021 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine