Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary Adenocarcinoma

Background and objective Subsolid pulmonary nodules are common computed tomography (CT) findings of primary lung adenocarcinoma. It is of clinical value to determine the clinical treatment strategies based on CT features. The aim of this study is to find the valuable CT characteristics on differenti...

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Main Authors: Fangfang GUO, Xinling LI, Xinyue WANG, Wensong ZHENG, Qing WANG, Wenjing SONG, Tielian YU, Yaguang FAN, Ying WANG
Format: Article
Language:zho
Published: Chinese Anti-Cancer Association; Chinese Antituberculosis Association 2018-06-01
Series:Chinese Journal of Lung Cancer
Subjects:
Online Access:http://dx.doi.org/10.3779/j.issn.1009-3419.2018.06.05
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spelling doaj-e7561492187548f4ae1fce14595fe4fc2020-11-24T20:49:46ZzhoChinese Anti-Cancer Association; Chinese Antituberculosis AssociationChinese Journal of Lung Cancer1009-34191999-61872018-06-0121645145710.3779/j.issn.1009-3419.2018.06.05Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary AdenocarcinomaFangfang GUO0Xinling LI1Xinyue WANG2Wensong ZHENG3Qing WANG4Wenjing SONG5Tielian YU6Yaguang FAN7Ying WANG8Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, ChinaDepartment of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, ChinaDepartment of Radiology, Shijiazhuang First Hospital, Shijiazhuang 050011, ChinaDepartment of Radiology, The Third Hospital of Hebei Medical University, Shijiazhuang 050001, ChinaDepartment of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, ChinaDepartment of Pathology, Tianjin Medical University General Hospital, Tianjin 300052, ChinaDepartment of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, ChinaTianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin 300052, ChinaDepartment of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, ChinaBackground and objective Subsolid pulmonary nodules are common computed tomography (CT) findings of primary lung adenocarcinoma. It is of clinical value to determine the clinical treatment strategies based on CT features. The aim of this study is to find the valuable CT characteristics on differential diagnosis and the degree of invasion prediction by a retrospectively analysis of three groups subsolid nodules, including benign, and invasive adenocarcinoma. Methods The CT findings of 106 cases of resected sub-solid nodules were retrospectively analyzed. The nodules were firstly divided into benign and malignant groups and the malignant group was further divided into non/micro-invasive group (atypical adenomatous hyperplasia/adenocarcinoma in situ/minimally invasive adenocarcinoma) and invasive adenocarcinoma group. The nodule size, proportion of solid components, tumor-lung interface, shape, margin, pleural traction, air bronchus sign, vascular abnormalities inside the nodule were evaluated. The univariate analysis (χ2 test, non-parametric test Mann-Whitney U test) was performed to screen statistically significant variables and then enrolled in further multivariate Logistic regression analysis. Results Multivariate logistic regression analysis showed that a clear tumor-lung interface, air bronchus sign, and pulmonary vascular abnormalities were important indicators of malignant nodules with hazard ratios of 38.1 (95%CI: 5.0-287.7; P<0.01), 7.9 (95%CI: 1.3-49.3; P=0.03), 7.2 (95%CI: 1.4-37.0; P=0.02), respectively. The proportion of solid components was the only significant indicator for identifying invasive adenocarcinoma from AAH/AIS/MIA , with a risk ratio of 1.04 (95%CI: 1.01-1.06, P=0.01). Conclusion SSNs with clear tumor-lung interface, air bronchus sign, and pulmonary vascular abnormality inside nodule are more likely to be malignant. A higher percentage of solid components indicates a higher likelihood to be an invasive lesion in malignant SPNs.http://dx.doi.org/10.3779/j.issn.1009-3419.2018.06.05Lung neoplasmsSubsolid nodulesComputed tomographyQuantitative variablesQualitative variablesBenignMalignant
collection DOAJ
language zho
format Article
sources DOAJ
author Fangfang GUO
Xinling LI
Xinyue WANG
Wensong ZHENG
Qing WANG
Wenjing SONG
Tielian YU
Yaguang FAN
Ying WANG
spellingShingle Fangfang GUO
Xinling LI
Xinyue WANG
Wensong ZHENG
Qing WANG
Wenjing SONG
Tielian YU
Yaguang FAN
Ying WANG
Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary Adenocarcinoma
Chinese Journal of Lung Cancer
Lung neoplasms
Subsolid nodules
Computed tomography
Quantitative variables
Qualitative variables
Benign
Malignant
author_facet Fangfang GUO
Xinling LI
Xinyue WANG
Wensong ZHENG
Qing WANG
Wenjing SONG
Tielian YU
Yaguang FAN
Ying WANG
author_sort Fangfang GUO
title Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary Adenocarcinoma
title_short Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary Adenocarcinoma
title_full Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary Adenocarcinoma
title_fullStr Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary Adenocarcinoma
title_full_unstemmed Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary Adenocarcinoma
title_sort value of ct features on differential diagnosis of pulmonary subsolid nodules and degree of invasion prediction in pulmonary adenocarcinoma
publisher Chinese Anti-Cancer Association; Chinese Antituberculosis Association
series Chinese Journal of Lung Cancer
issn 1009-3419
1999-6187
publishDate 2018-06-01
description Background and objective Subsolid pulmonary nodules are common computed tomography (CT) findings of primary lung adenocarcinoma. It is of clinical value to determine the clinical treatment strategies based on CT features. The aim of this study is to find the valuable CT characteristics on differential diagnosis and the degree of invasion prediction by a retrospectively analysis of three groups subsolid nodules, including benign, and invasive adenocarcinoma. Methods The CT findings of 106 cases of resected sub-solid nodules were retrospectively analyzed. The nodules were firstly divided into benign and malignant groups and the malignant group was further divided into non/micro-invasive group (atypical adenomatous hyperplasia/adenocarcinoma in situ/minimally invasive adenocarcinoma) and invasive adenocarcinoma group. The nodule size, proportion of solid components, tumor-lung interface, shape, margin, pleural traction, air bronchus sign, vascular abnormalities inside the nodule were evaluated. The univariate analysis (χ2 test, non-parametric test Mann-Whitney U test) was performed to screen statistically significant variables and then enrolled in further multivariate Logistic regression analysis. Results Multivariate logistic regression analysis showed that a clear tumor-lung interface, air bronchus sign, and pulmonary vascular abnormalities were important indicators of malignant nodules with hazard ratios of 38.1 (95%CI: 5.0-287.7; P<0.01), 7.9 (95%CI: 1.3-49.3; P=0.03), 7.2 (95%CI: 1.4-37.0; P=0.02), respectively. The proportion of solid components was the only significant indicator for identifying invasive adenocarcinoma from AAH/AIS/MIA , with a risk ratio of 1.04 (95%CI: 1.01-1.06, P=0.01). Conclusion SSNs with clear tumor-lung interface, air bronchus sign, and pulmonary vascular abnormality inside nodule are more likely to be malignant. A higher percentage of solid components indicates a higher likelihood to be an invasive lesion in malignant SPNs.
topic Lung neoplasms
Subsolid nodules
Computed tomography
Quantitative variables
Qualitative variables
Benign
Malignant
url http://dx.doi.org/10.3779/j.issn.1009-3419.2018.06.05
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