ArticleJournal of cardiothoracic surgery2024
Nomogram using intratumoral and peritumoral radiomics for the preoperative prediction of visceral pleural invasion in clinical stage IA lung adenocarcinoma.
Article in Journal of cardiothoracic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- CT-based nomogram for estimating visceral pleural invasion in solid pulmonary adenocarcinoma nodules with pleural contact: a retrospective single-center study.BMC medical imaging · 2026Article
- CT predictors of visceral pleural invasion in subsolid nodular pulmonary adenocarcinoma: differences between direct and indirect tumor-pleura contact.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Observational
- Multicenter peritumoral radiomics in oncology: advances, challenges, and future directions.Radiation oncology (London, England) · 2026Review
- Radiomics to understand pre-treatment tumor biology for resectable non-small cell lung cancer.Frontiers in oncology · 2026Review
- Tumoral and Peritumoral Radiomics for Preoperative Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma.Cancers · 2025Article
- Visceral Pleural Invasion as a Determinant of Surgical Strategy in Non-Small Cell Lung Cancer: A Multicenter Study.Cancers · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundAccurate prediction of visceral pleural invasion (VPI) in lung adenocarcinoma before operation can provide guidance and help for surgical operation and postoperative treatment. We investigate the value of intratumoral and peritumoral radiomics nomograms for preoperatively predicting the status of VPI in patients diagnosed with clinical stage IA lung adenocarcinoma.
methodsA total of 404 patients from our hospital were randomly assigned to a training set (n = 283) and an internal validation set (n = 121) using a 7:3 ratio, while 81 patients from two other hospitals constituted the external validation set. We extracted 1218 CT-based radiomics features from the gross tumor volume (GTV) as well as the gross peritumoral tumor volume (GPTV
resultsThe GPTV
conclusionsThe nomogram, integrating radiomics features and CT morphological features, exhibits good performance in predicting VPI status in lung adenocarcinoma.
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