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Assessment of Clinical Stage IA Lung Adenocarcinoma with pN1/N2 Metastasis Using CT Quantitative Texture Analysis

Authors Zhu H, Xu Y, Liang N, Sun H, Huang Z, Xie S, Wang W

Received 27 February 2020

Accepted for publication 13 July 2020

Published 28 July 2020 Volume 2020:12 Pages 6421—6430

DOI https://doi.org/10.2147/CMAR.S251598

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 2

Editor who approved publication: Professor Lu-Zhe Sun


Haixu Zhu,1,2,* Yanyan Xu,2,* Nanxue Liang,2 Hongliang Sun,2 Zhenguo Huang,2 Sheng Xie,2 Wu Wang2

1Department of Radiology, People’s Hospital of Xinjiang Uyghur Autonomous Region, Urumqi 830001, People’s Republic of China; 2Department of Radiology, China–Japan Friendship Hospital, Beijing 100029, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Hongliang Sun Department of Radiology
China–Japan Friendship Hospital, Beijing 100029, People’s Republic of China
Tel +86 108-420-5514
Fax +86 1064222963
Email stentorsun@gmail.com

Objective: To explore the application of texture analysis basing on computed tomography (CT) images in predicting lymph-node metastasis in patients with clinical stage IA lung adenocarcinoma.
Methods: In total, 256 patients with clinical stage IA lung adenocarcinoma who had underwentgone preoperative CT examinations were enrolled. A total of 25 texture features using MaZda (version 4.6) software and conventional radiological features were extracted from raw CT data sets. Based on surgical results, patients were stratified into lymph node metastasis–positive and –negative groups. Independent-sample t-tests and Mann–Whitney U tests were used to compare continuous variables between the groups. Continuity-correction and χ2 tests were used for categorical variable comparison. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of lymph-node metastasis.
Results: In total, 256 clinical stage IA lung adenocarcinoma cases were proved by pathology: 39 (15.23%) cases with lymph-node metastasis (14 N1a, seven N1b, six N2a1, ten N2a2, and two N2b) and 217 (84.77%) cases without lymph-node metastasis. Univariate and multivariate logistic regression analyses demonstrated that total volume (OR 3.777, p=0.015), average CT value of whole tumor (OR 16.271, p< 0.001), three texture parameters (mean OR 8.473, p< 0.001; skewness OR 6.393, p=0.001; and entropy OR 0.343, p=0.049) were independent factors associated with lymph-node status. As such, early-stage lung adenocarcinoma with higher total volume (> 4.05 cm3), average CT value of whole tumor (>– 70 HU), mean (> 133.79), entropy (> 1.98), and lower skewness (≤ 0.02) pointed to positive lymph-node metastasis.
Conclusion: Texture parameters were independent factors associated with lymph-node status in clinical stage IA lung adenocarcinoma.

Keywords: lung adenocarcinoma, computed tomography, texture, lymph-node metastasis

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