ArticleJournal of thoracic disease2014
Size of solitary pulmonary nodule was the risk factor of malignancy.
Article in Journal of thoracic disease, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- Incidence and risk factors for malignancy in patients with incidental solitary pulmonary nodules: a systematic review and meta-analysis.Annals of medicine · 2026Pooled it
- A new framework for pulmonary nodules: how terminology impacts management.European radiology · 2026Review
- The role of radiological imaging in differentiating malignant and benign pulmonary nodules: a retrospective study.BMC medical imaging · 2026Article
- Automated Lesion Segmentation in Medical Imaging via Integration of nnU-Net Optimization and SAM Approach.Biomedical engineering and computational biology · 2026Article
- Analysis of Factors Related to Pulmonary Nodules in Patients With Fatty Liver: A Large-Scale Cohort Study Based on a Physical Examination Population.International journal of general medicine · 2025Article
- The value of non-enhanced CT 3D visualization in differentiating stage Ⅰ invasive lung adenocarcinoma between LPA and non-LPA.European journal of radiology open · 2024Article
- Enhancing the differential diagnosis of small pulmonary nodules: a comprehensive model integrating plasma methylation, protein biomarkers, and LDCT imaging features.Journal of translational medicine · 2024Observational
- Statistical Analysis of nnU-Net Models for Lung Nodule Segmentation.Journal of personalized medicine · 2024Article
- Decreased levels of sex hormones in females with solitary pulmonary nodules were risk factors for malignancy.Journal of cardiothoracic surgery · 2024Article
- The efficacy and safety of percutaneous CT-guided iodine-125 brachytherapy combined with standard chemotherapy and brachytherapy alone for lung malignant nodule: a retrospective comparative cohort study.Journal of thoracic disease · 2024Article
- Value of dual-layer spectral detector CT in predicting lymph node metastasis of non-small cell lung cancer.Quantitative imaging in medicine and surgery · 2024Article
- Construction of a predictive model of 2-3 cm ground-glass nodules developing into invasive lung adenocarcinoma using high-resolution CT.Frontiers in medicine · 2024Article
- Value of dual-layer spectral detector computed tomography in the diagnosis of benign/malignant solid solitary pulmonary nodules and establishment of a prediction model.Frontiers in oncology · 2023Article
- CT imaging indications correlate with the degree of lung adenocarcinoma infiltration.Frontiers in oncology · 2023Article
- Ciliated muconodular papillary tumor of the lung with cavitary change: A case report with 11-year preoperative follow-up.Thoracic cancer · 2022Article
- A predictive model based on ground glass nodule featuresFrontiers in surgery · 2022Article
- Hybrid models for lung nodule malignancy prediction utilizing convolutional neural network ensembles and clinical data.Journal of medical imaging (Bellingham, Wash.) · 2020Article
- A Novel Computer-Aided Diagnosis Scheme on Small Annotated Set: G2C-CAD.BioMed research international · 2019Article
- Relationship between computed tomography morphology and prognosis of patients with stage I non-small cell lung cancer.OncoTargets and therapy · 2017Article
- Multi-slice computed tomography characteristics of solitary pulmonary ground-glass nodules: Differences between malignant and benign.Thoracic cancer · 2016Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe purpose of this study was to analyze the role of the sizes of solitary pulmonary nodules (SPNs) in predicting their potential malignancies.
methodsA total of 379 patients with pathologically confirmed SPNs were enrolled in this study. They were divided into three groups based on the SPN sizes: ≤10, 11-20, and >20 mm. The computed tomography (CT) findings of these SPNs were analyzed in these three groups to identify the malignant and benign SPNs. The risk factors were analyzed using binary logistic regression analysis.
resultsOf these 379 patients, 120 had benign SPNs and 259 had malignant SPNs. In the ≤10 mm SPN group, air cavity density was the risk factor for malignancy, with the sensitivity, specificity, and accuracy being 77.8%, 75.0%, and 76.3%. In the 11-20 mm SPN group, age, glitches and vascular aggregation were the risk factors for malignancy, with the sensitivity, specificity, and accuracy being 91.3%, 56.9%, and 81.5%. In the >20 mm SPN group, age, lobulation, and vascular aggregation were the risk factors for malignancy, with the sensitivity, specificity, and accuracy being 88.6%, 57.1%, and 79.1%.
conclusionsAccording to CT findings of SPNs, age, glitches, lobulation, vascular aggregation, and air cavity density are the risk factors of malignancy, whereas calcification and satellite lesions are the protective factors. During the course of development from small to large nodules, air cavity density could be firstly detected in early stages, followed by glitches and vascular aggregation. Lobulation is associated with relatively large lesions.
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