ArticleAmerican journal of cancer research2023
CT-based radiomics nomogram for predicting visceral pleural invasion in peripheral T1-sized solid lung adenocarcinoma.
Article in American journal of cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- CT-based Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma ≤ 3 cm: Enhancing Deep Learning Specificity by Waiving Chest Wall Information.Annals of surgical oncology · 2026Article
- CT radiomics approach to predict response to bronchial arterial chemoembolization in advanced lung cancer by multicenter study.Scientific reports · 2026Article
- Contrast-enhanced CT-based radiomics for predicting visceral pleural invasion in early-stage non-small cell lung cancer.Insights into imaging · 2026Article
- Predicting visceral pleural invasion in invasive adenocarcinoma with a maximum diameter ≤ 3 cm based onEuropean journal of nuclear medicine and molecular imaging · 2026Article
- Tumoral and Peritumoral Radiomics for Preoperative Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma.Cancers · 2025Article
- Development of a predictive model for pneumothorax after microwave ablation based on radiomics and clinical baseline data.BMC pulmonary medicine · 2025Article
- Prediction of visceral pleural invasion of clinical stage IA lung adenocarcinoma based on computed tomography features.Translational cancer research · 2025Article
- Interpretable machine learning model integrating contrast-enhanced CT environmental radiomics and clinicopathological features for predicting postoperative recurrence in lung adenocarcinoma: a retrospective pilot study.Frontiers in oncology · 2025Article
- Development and validation of a nomogram for predicting visceral pleural invasion in patients with early-stage non-small cell lung cancer.Translational lung cancer research · 2024Article
- Nomogram using intratumoral and peritumoral radiomics for the preoperative prediction of visceral pleural invasion in clinical stage IA lung adenocarcinoma.Journal of cardiothoracic surgery · 2024Article
- Using the length of pleural tag to predetermine pleural invasion by lung adenocarcinomas.Frontiers in oncology · 2024Article
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Authors and funding
7 authors.
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Abstract
The preoperative assessment of visceral pleural invasion (VPI) in patients with early lung adenocarcinoma is vital for surgical treatment. This study aims to develop and validate a CT-based radiomics nomogram to predict VPI in peripheral T1-sized solid lung adenocarcinoma. A total of 203 patients were selected as subjects, and were divided into a training cohort (n=141; scanned with Brilliance iCT256, Brilliance 64, Somatom Force, and Optima CT660) and a test cohort (n=62; scanned with Somatom Definition AS+). Radiomics characteristics were extracted from CT images. Variance thresholding, SelectKBest, and least absolute shrinkage and selection operator (LASSO) method were applied to determine optimum characteristics to construct the radiomic signature (radscore). After multivariate logistic regression analysis, a nomogram was structured regarding clinical factors, conventional CT features, and radscore. The nomogram property was tested based on its area under the curve (AUC). The nomogram based on the radscore and two conventional CT features (tumor pleura relationship and lymph node enlargement) showed high discrimination with an AUC of 0.877 (95% CI: 0.820-0.935) and 0.837 (95% CI: 0.737-0.937) in the training and test cohorts, respectively. The calibration curve and decision curve analysis showed good consistency and high clinical value of the nomogram. In conclusion, The CT-based radiomics nomogram was helpful in predicting VPI in peripheral T1-sized solid lung adenocarcinoma.
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