ArticleTranslational cancer research2020
Correlation analysis between metabolic tumor burden measured by positron emission tomography/computed tomography and the 2015 World Health Organization classification of lung adenocarcinoma, with a risk prediction model of tumor spread through air spaces.
Article in Translational cancer research, 2020. 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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Who cites it
10 citing papers in PubMed.
- Article
- Imaging advances of predicting spread through air spaces (STAS) in lung cancer: a narrative review.Journal of thoracic disease · 2026Review
- Integrating Bioinformatics and Experimental Validation Identify CCNA2 as a Novel Prognostic Biomarker and Tumor Promoter via the PI3K/AKT Pathway in Lung Adenocarcinoma.International journal of general medicine · 2026Article
- Development and validation of a nomogram using interpretable machine learning to integrate CT radiomics and PET metabolic parameters for predicting benign-malignant differentiation of pulmonary space-occupying lesions.Frontiers in radiology · 2026Article
- Prediction of STAS positivity in operable non-small cell lung cancer.Turk gogus kalp damar cerrahisi dergisi · 2025Article
- Predicting spread through air space of lung adenocarcinoma based on deep learning and machine learning models.Journal of cardiothoracic surgery · 2025Article
- Preoperative nomogram for predicting spread through air spaces in clinical-stage IA non-small cell lung cancer usingJournal of cancer research and clinical oncology · 2024Article
- Predictive value of multiple imaging predictive models for spread through air spaces of lung adenocarcinoma: A systematic review and network meta‑analysis.Oncology letters · 2024Article
- Advances in the prediction of spread through air spaces with imaging in lung cancer: a narrative review.Translational cancer research · 2023Review
- Multivariate analysis based on the maximum standard unit value ofDiagnostic and interventional radiology (Ankara, Turkey) · 2023Article
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Authors and funding
6 authors.
Funding
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Abstract
backgroundTumor spread through air spaces (STAS) is an important pattern of invasion and impacts the frequency and location of recurrence. The objective was to assess the correlation between metabolic tumor burden of positron emission tomography/computed tomography (PET/CT) and 2015 World Health Organization (WHO) classification of lung adenocarcinoma, and to establish a risk prediction model of STAS.
methodsWe reviewed 127 consecutive patients. The SUV
resultsThe nodule types and SUV were significantly correlated with 2015 WHO pathological categories (P
conclusionsThe LPA appeared as non-solid nodule with low SUV without STAS has a good prognosis. SUV and TLG are valuable predictive indices in the prediction of STAS. The predictive model developed in predicting the incidence of STAS has good specificity and accuracy.
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