ReviewDiagnostics (Basel, Switzerland)2024
Predicting the Invasiveness of Pulmonary Adenocarcinomas in Pure Ground-Glass Nodules Using the Nodule Diameter: A Systematic Review, Meta-Analysis, and Validation in an Independent Cohort.
Review in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 8 citations in OpenAlex.
- Value of a radiomics model based on high-resolution large matrix target reconstruction images in predicting the invasiveness of lung adenocarcinoma with pure ground-glass nodules.Biomedical engineering online · 2026Article
- Construction and validation of a prediction model for malignant pulmonary nodules based on imaging, demographic, and laboratory features.Frontiers in oncology · 2026Article
- The role ofFrontiers in medicine · 2026Article
- Article
- 3D computed tomography density of stage T1 lung cancer, which value is most stable for predicting its invasiveness?Quantitative imaging in medicine and surgery · 2025Article
- Assessment of intratumor heterogeneity for preoperatively predicting the invasiveness of pulmonary adenocarcinomas manifesting as pure ground-glass nodules.Quantitative imaging in medicine and surgery · 2025Article
- Exploration of optimal thresholds for predicting the invasive nature of stage T1 lung adenocarcinoma using artificial intelligence-based 3D solid component volume segmentation.Quantitative imaging in medicine and surgery · 2025Article
- Effects of herbal medicine on clinical characteristics and biological markers in pulmonary pure ground-glass nodules: study protocol for a multicenter randomized triple-blind controlled trial.Frontiers in medicine · 2025Article
- Imaging diagnostics of pulmonary ground-glass nodules: a narrative review with current status and future directions.Quantitative imaging in medicine and surgery · 2024Review
- Predicting High-Grade Patterns in Stage I Solid Lung Adenocarcinoma: A Study of 371 Patients Using Refined Radiomics and Deep Learning-Guided CatBoost Classifier.Technology in cancer research & treatmentArticle
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
The nodule diameter was commonly used to predict the invasiveness of pulmonary adenocarcinomas in pure ground-glass nodules (pGGNs). However, the diagnostic performance and optimal cut-off values were inconsistent. We conducted a meta-analysis to evaluate the diagnostic performance of the nodule diameter for predicting the invasiveness of pulmonary adenocarcinomas in pGGNs and validated the cut-off value of the diameter in an independent cohort. Relevant studies were searched through PubMed, MEDLINE, Embase, and the Cochrane Library, from inception until December 2022. The inclusion criteria comprised studies that evaluated the diagnostic accuracy of the nodule diameter to differentiate invasive adenocarcinomas (IAs) from non-invasive adenocarcinomas (non-IAs) in pGGNs. A bivariate mixed-effects regression model was used to obtain the diagnostic performance. Meta-regression analysis was performed to explore the heterogeneity. An independent sample of 220 pGGNs (82 IAs and 128 non-IAs) was enrolled as the validation cohort to evaluate the performance of the cut-off values. This meta-analysis finally included 16 studies and 2564 pGGNs (761 IAs and 1803 non-IAs). The pooled area under the curve, the sensitivity, and the specificity were 0.85 (95% confidence interval (CI), 0.82-0.88), 0.82 (95% CI, 0.78-0.86), and 0.73 (95% CI, 0.67-0.78). The diagnostic performance was affected by the measure of the diameter, the reconstruction matrix, and patient selection bias. Using the prespecified cut-off value of 10.4 mm for the mean diameter and 13.2 mm for the maximal diameter, the mean diameter showed higher sensitivity than the maximal diameter in the validation cohort (0.85 vs. 0.72,
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