ArticleEuropean radiology2024
Computed tomography characteristics of cN0 primary non-small cell lung cancer predict occult lymph node metastasis.
Article in European radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Development and external validation of a FDG PET-based radiomics model predicting occult lymph node metastasis in non-small cell lung cancer patients.European journal of nuclear medicine and molecular imaging · 2026Article
- Preoperative Contrast-enhanced CT Features Associated with Occult Lymph Node Metastasis in Early-Stage Solid Non-Small Cell Lung Cancer.Radiology. Imaging cancer · 2026Article
- Imaging and RNA sequencing-based radiogenomic analysis of occult lymph node metastasis and survival in lung adenocarcinoma staged non-metastatic.Communications medicine · 2025Article
- Low-dose ultrahigh-resolution PCCT enhances subsolid nodule characterization.La Radiologia medica · 2025Article
- CT-based radiomics-deep learning model predicts occult lymph node metastasis in early-stage lung adenocarcinoma patients: A multicenter study.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2025Article
- Case report: Occult lymph nodal metastasis in sub-centimeter lung cancer: a report of seven cases and review of literature.Frontiers in oncology · 2025Article
- AI-based prediction of pathological risk factors in lung adenocarcinoma from CT imaging: bridging innovation and clinical practice.Frontiers in oncology · 2025Review
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Authors and funding
13 authors.
Funding
Abstract
rationaleOccult lymph node metastasis (OLNM) is frequently found in patients with resectable non-small cell lung cancer (NSCLC), despite using diagnostic methods recommended by guidelines.
objectivesTo evaluate the risk of OLNM in NSCLC patients using the radiologic characteristics of the primary tumor on computed tomography (CT).
methodsWe retrospectively reviewed clinicopathologic features of 2042 clinical T1-4N0 NSCLC patients undergoing curative intent pulmonary resection. Unique radiological features (i.e., air-bronchogram throughout the whole tumor, heterogeneous ground-glass opacity (GGO), mainly cystic appearance, endobronchial location), percentage of solid portion, and shape of tumor margin were analyzed via a stepwise approach. We used multivariable logistic regression to assess the relationship between OLNM and tumor characteristics.
resultsCompared with the other unique features, endobronchial tumors were associated with the highest risk of OLNM (OR = 3.9, 95% confidence interval (CI) = 2.29-6.62), and heterogeneous GGO and mainly cystic tumors were associated with a low risk of OLNM. For tumors without unique features, the percentage of the solid portion was measured, and solid tumors were associated with OLNM (OR = 2.49, 95% CI = 1.86-3.35). Among part-solid tumors with solid proportion > 50%, spiculated margin, and peri-tumoral GGO were associated with OLNM.
conclusionsThe risk of OLNM could be assessed using radiologic characteristics on CT. This could allow us to adequately select optimal candidates for invasive nodal staging procedures (INSPs) and complete systematic lymph node dissection. CLINICAL RELEVANCE STATEMENT: These data may be helpful for clinicians to select appropriate candidates for INSPs and complete surgical systematic lymph node dissection in NSCLC patients. KEY POINTS: Lymph node metastasis status plays a key role in both prognostication and treatment planning. Solid tumors, particularly endobronchial tumors, were associated with occult lymph node metastasis (OLNM). The risk of OLNM can be assessed using radiologic characteristics acquired from CT images.
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