ArticleBMC cancer2019
Primary solid lung cancerous nodules with different sizes: computed tomography features and their variations.
Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06685458 (Combined With Clinical and Imaging Features, the Prediction Model of Benign and Malignant Solid Pulmonary Nodules Was Constructed), which is not on this map. Cited by 27 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Combined With Clinical and Imaging Features, the Prediction Model of Benign and Malignant Solid Pulmonary Nodules Was Constructed
Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it, 32 citations in OpenAlex.
- Systematic review and single-arm meta-analysis of the clinical value of multidisciplinary team-based multimodal interventions in pulmonary nodule management.Frontiers in oncology · 2026Pooled it
- Risk factors for malignant solid pulmonary nodules: a meta-analysis.BMC cancer · 2025Pooled it
- Density homogeneity as a crucial CT indicator for differentiating malignant and benign subcentimeter solid pulmonary nodules: A retrospective multi-center study.Insights into imaging · 2026Article
- The role of growth heterogeneity in solid nodular non-small cell lung cancer in clinical practice: a narrative review.Journal of thoracic disease · 2026Review
- Review
- Imaging appearances, CT evolution patterns, and surgical prognosis of stage I lung squamous cell carcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Computed tomography radiomics of intratumoral and peritumoral microenvironments for identifying the invasiveness of subcentimeter lung adenocarcinomas.BMC medical imaging · 2025Article
- Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography.BMC pulmonary medicine · 2025Article
- CT-Guided Transthoracic Core-Needle Biopsy of Pulmonary Nodules: Current Practices, Efficacy, and Safety Considerations.Journal of clinical medicine · 2024Review
- A prediction model based on computed tomography characteristics for identifying malignant from benign sub-centimeter solid pulmonary nodules.Journal of thoracic disease · 2024Article
- Integrating Clinical Data and Medical Imaging in Lung Cancer: Feasibility Study Using the Observational Medical Outcomes Partnership Common Data Model Extension.JMIR medical informatics · 2024Article
- The differential computed tomography features between small benign and malignant solid solitary pulmonary nodules with different sizes.Quantitative imaging in medicine and surgery · 2024Article
- Development of a combined radiomics and CT feature-based model for differentiating malignant from benign subcentimeter solid pulmonary nodules.European radiology experimental · 2024Article
- Article
- Solitary lung adenocarcinoma: follow-up CT, pathological-molecular characteristics, and surgical prognosis for different morphological classifications.Insights into imaging · 2023Article
- Diagnostic performance of a deep learning-based method in differentiating malignant from benign subcentimeter (≤10 mm) solid pulmonary nodules.Journal of thoracic disease · 2023Article
- Differentiation of pulmonary solid nodules attached to the pleura detected by thin-section CT.Insights into imaging · 2023Article
- Prognostic impact of highly solid component in early-stage solid lung adenocarcinoma.Quantitative imaging in medicine and surgery · 2023Article
- Computed-tomography-based radiomic nomogram for predicting the risk of indeterminate small (5-20 mm) solid pulmonary nodulesDiagnostic and interventional radiology (Ankara, Turkey) · 2023Article
- A Radiomics Approach on Chest CT Distinguishes Primary Lung Cancer from Solitary Lung Metastasis in Colorectal Cancer Patients.Journal of personalized medicine · 2022Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe computed tomography (CT) features of small solid lung cancers and their changing regularity as they grow have not been well studied. The purpose of this study was to analyze the CT features of solid lung cancerous nodules (SLCNs) with different sizes and their variations.
methodsBetween February 2013 and April 2018, a consecutive cohort of 224 patients (225 nodules) with confirmed primary SLCNs was enrolled. The nodules were divided into four groups based on tumor diameter (A: diameter ≤ 1.0 cm, 35 lesions; B: 1.0 cm < diameter ≤ 1.5 cm, 60 lesions; C: 1.5 cm < diameter ≤ 2.0 cm, 63 lesions; and D: 2.0 cm < diameter ≤ 3.0 cm, 67 lesions). CT features of nodules within each group were summarized and compared.
resultsMost nodules in different groups were located in upper lobes (groups A - D:50.8%-73.1%) and had a gap from the pleura (groups A - D:89.6%-100%). The main CT features of smaller (diameter ≤ 1 cm) and larger (diameter > 1 cm) nodules were significantly different. As nodule diameter increased, more lesions showed a regular shape, homogeneous density, clear but coarse tumor-lung interface, lobulation, spiculation, spinous protuberance, vascular convergence, pleural retraction, bronchial truncation, and beam-shaped opacity (p < 0.05 for all). The presence of halo sign in all groups was similar (17.5%-22.5%; p > 0.05).
conclusionsThe CT features vary among SLCNs with different sizes. Understanding their changing regularity is helpful for identifying smaller suspicious malignant nodules and early determining their nature in follow-up.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.