Literature DB >> 34993112

Benign and malignant pulmonary part-solid nodules: differentiation via thin-section computed tomography.

Wang-Jia Li1, Fa-Jin Lv1, Yi-Wen Tan2, Bin-Jie Fu1, Zhi-Gang Chu1.   

Abstract

BACKGROUND: Pulmonary part-solid nodules (PSNs) reportedly have a high possibility of malignancy, while benign PSNs are common. This study aimed to reveal the differences between benign and malignant PSNs by comparing their thin-section computed tomography (CT) features.
METHODS: Patients with PSNs confirmed by postoperative pathological examination or follow-up (at the same period) were retrospectively enrolled from March 2016 to January 2020. The clinical data of patients and CT features of benign and malignant PSNs were reviewed and compared. Binary logistic regression analysis was performed to reveal the predictors of malignant PSNs.
RESULTS: A total of 119 PSNs in 117 patients [age (mean ± standard deviation), 56±11 years; 70 women] were evaluated. Of the 119 PSNs, 44 (37.0%) were benign, and 75 (63.0%) were malignant (12 adenocarcinomas in situ, 22 minimally invasive adenocarcinomas, and 41 invasive adenocarcinomas). There were significant differences in the patients' age and smoking history between benign and malignant PSNs. In terms of CT characteristics, malignant and benign lesions significantly differed in the following CT features: whole nodule, internal solid component, and peripheral ground-glass opacity. The binary logistic regression analysis revealed that well-defined border [odds ratio (OR), 4.574; 95% confidence interval (CI), 1.186-17.643; P=0.027] and lobulation (OR, 61.739; 95% CI, 5.230-728.860; P=0.001) of the nodule, as well as irregular shape (OR, 9.502; 95% CI, 1.788-50.482; P=0.008) and scattered distribution (OR, 13.238; 95% CI, 1.359-128.924; P=0.026) of the internal solid components were significant independent predictors distinguishing malignant PSNs. However, the lesion shape, density, and margin were similar between malignant and benign lesions.
CONCLUSIONS: Well-defined and lobulated PSNs with irregular and scattered solid components are highly likely to be malignant. 2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Entities:  

Keywords:  Part-solid nodules (PSNs); benignity; computed tomography (CT); malignancy; solid component

Year:  2022        PMID: 34993112      PMCID: PMC8666726          DOI: 10.21037/qims-21-145

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  23 in total

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Authors:  Ryu Nakajima; Tomoyuki Yokose; Ryutaro Kakinuma; Kanji Nagai; Yutaka Nishiwaki; Atsushi Ochiai
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2.  Multidetector CT features of pulmonary focal ground-glass opacity: differences between benign and malignant.

Authors:  L Fan; S-Y Liu; Q-C Li; H Yu; X-S Xiao
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Review 4.  Ground-Glass Opacity Lung Nodules in the Era of Lung Cancer CT Screening: Radiology, Pathology, and Clinical Management.

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5.  CT screening for lung cancer: frequency and significance of part-solid and nonsolid nodules.

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6.  Correlation of the solid part on high-resolution computed tomography with pathological scar in small lung adenocarcinomas.

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7.  Persistent pulmonary nodular ground-glass opacity at thin-section CT: histopathologic comparisons.

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8.  Use of relative CT values to evaluate the invasiveness of pulmonary subsolid nodules in patients with emphysema.

Authors:  Bo-Wei Zhang; Yu Zhang; Jian-Ding Ye; Jin-Wei Qiang
Journal:  Quant Imaging Med Surg       Date:  2021-01

9.  Clinical, pathological, and radiological characteristics of solitary ground-glass opacity lung nodules on high-resolution computed tomography.

Authors:  Zhi-Xin Qiu; Yue Cheng; Dan Liu; Wei-Ya Wang; Xia Wu; Wei-Lu Wu; Wei-Min Li
Journal:  Ther Clin Risk Manag       Date:  2016-09-20       Impact factor: 2.423

10.  Preoperative nomogram for identifying invasive pulmonary adenocarcinoma in patients with pure ground-glass nodule: A multi-institutional study.

Authors:  Yunlang She; Lilan Zhao; Chenyang Dai; Yijiu Ren; Junyan Zha; Huikang Xie; Sen Jiang; Jingyun Shi; Shunbin Shi; Weirong Shi; Bing Yu; Gening Jiang; Ke Fei; Yongbing Chen; Chang Chen
Journal:  Oncotarget       Date:  2017-03-07
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  3 in total

1.  Development, Validation, and Comparison of Image-Based, Clinical Feature-Based and Fusion Artificial Intelligence Diagnostic Models in Differentiating Benign and Malignant Pulmonary Ground-Glass Nodules.

Authors:  Xiang Wang; Man Gao; Jicai Xie; Yanfang Deng; Wenting Tu; Hua Yang; Shuang Liang; Panlong Xu; Mingzi Zhang; Yang Lu; ChiCheng Fu; Qiong Li; Li Fan; Shiyuan Liu
Journal:  Front Oncol       Date:  2022-06-07       Impact factor: 5.738

2.  Clinical and Computed Tomography Characteristics of Solitary Pulmonary Nodules Caused by Fungi: A Comparative Study.

Authors:  Jin Jiang; Zhuo-Ma Lv; Fa-Jin Lv; Bin-Jie Fu; Zhang-Rui Liang; Zhi-Gang Chu
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3.  Sensitivity and specificity of computed tomography hypodense sign when differentiating pulmonary inflammatory and malignant mass-like lesions.

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Journal:  Quant Imaging Med Surg       Date:  2022-09
  3 in total

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