ArticleJournal of thoracic disease2024
Intratumoral and peritumoral radiomics combined with computed tomography features for predicting the invasiveness of lung adenocarcinoma presenting as a subpleural ground-glass nodule with a consolidation-to-tumor ratio ≤50.
Article in Journal of thoracic disease, 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.
- Radiomic model with SHAP-based interpretability for predicting invasiveness of pure ground-glass nodules: a retrospective study based on high-resolution computed tomography (HRCT) volumetric datasets.Journal of cardiothoracic surgery · 2026Article
- Multicenter peritumoral radiomics in oncology: advances, challenges, and future directions.Radiation oncology (London, England) · 2026Review
- Machine learning models based on tumoral, 4 mm-peritumoral, and combined radiomic features for evaluating the invasiveness of lung adenocarcinoma manifesting as ground-glass nodules.World journal of surgical oncology · 2026Article
- A radiomics-based nomogram for preoperatively predicting the invasiveness of nodular lung adenocarcinoma: a multicenter study.Translational lung cancer research · 2026Article
- A nomogram for preoperative prediction of invasiveness in solitary pulmonary adenocarcinoma: a multicenter study.Journal of thoracic disease · 2025Article
- Prediction model for growth trends of subpleural subsolid nodules using CT radiomics and radiological features.Scientific reports · 2025Article
- Development and validation of growth prediction models for multiple pulmonary ground-glass nodules based on CT features, radiomics, and deep learning.Translational lung cancer research · 2025Article
- Article
- Development of a clinical prediction model for benign and malignant pulmonary nodules with a CTR ≥ 50% utilizing artificial intelligence-driven radiomics analysis.BMC medical imaging · 2025Article
- Prognostic significance of visceral pleural changes in stage IA lung adenocarcinoma: a retrospective study.Frontiers in oncology · 2025Article
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13 authors.
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Abstract
Background: Preoperative accurate judgment of the degree of invasiveness in subpleural ground-glass lung adenocarcinoma (LUAD) with a consolidation-to-tumor ratio (CTR) ≤50% is very important for the choice of surgical timing and planning. This study aims to investigate the performance of intratumoral and peritumoral radiomics combined with computed tomography (CT) features for predicting the invasiveness of LUAD presenting as a subpleural ground-glass nodule (GGN) with a CTR ≤50%. Methods: A total of 247 patients with LUAD from our hospital were randomly divided into two groups, i.e., the training cohort (n=173) and the internal validation cohort (n=74) (7:3 ratio). Furthermore, 47 patients from three other hospitals were collected as the external validation cohort. In the training cohort, the differences in clinical-radiological features were compared using univariate and multivariate analyses. The gross tumor volume (GTV) and gross peritumoral tumor volume (GPTV5, GPTV10, and GPTV15) radiomics models were constructed based on intratumoral and peritumoral (5, 10, and 15 mm) radiomics features. Additionally, the radscore of the best radiomics model and clinical risk factors were used to construct a combined model and the predictive efficacy of the model was evaluated in the validation cohorts. Finally, the receiver operating characteristics (ROC) curve and area under the curve (AUC) value were used to evaluate the discriminative ability of the model. Results: Tumor size and CTR were independent risk factors for predicting the invasiveness of LUAD. The GPTV10 model outperformed the other radiomics models, with AUC values of 0.910, 0.870, and 0.887 in the three cohorts. The AUC values of the combined model were 0.912, 0.874, and 0.892. Conclusions: A nomogram based on GPTV10-radscore, tumor size, and CTR exhibited high predictive efficiency for predicting the invasiveness of LUAD.
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