ArticleCancer imaging : the official publication of the International Cancer Imaging Society2019
Quantitative computed tomography texture analysis: can it improve diagnostic accuracy to differentiate malignant lymph nodes?
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 20 citations in OpenAlex.
- Machine Learning-Driven Radiomics for an Early-Stage Predictive Model of Nodal Upstaging in Thoracic Oncology.Cancers · 2026Article
- Non-invasive multi-phase CT artificial intelligence for predicting pre-treatment enlarged lymph node status in colorectal cancer: a prospective validation study.European radiology · 2025Article
- A narrative review of imaging intratumor heterogeneity in non-small cell lung cancer: current advances.Translational lung cancer research · 2025Review
- Predicting pathological staging of non-small cell lung cancer using a multi-task radiomics model integrating intratumoral and peritumoral features.Oncology letters · 2025Article
- Diagnostic accuracy and reliability of CT-based Node-RADS for colon cancer.Abdominal radiology (New York) · 2025Article
- Clinical Variables and Radiomics Features for Predicting Pneumothorax in Patients Undergoing CT-guided Transthoracic Core Needle Biopsy.Radiology. Cardiothoracic imaging · 2024Article
- Transpedicular injection of rhBMP-2 with β-tricalcium phosphate to reduce the proximal junctional kyphosis after adult spinal deformity correction: preliminary study.Scientific reports · 2024Article
- Article
- Lymph node metastasis in cancer progression: molecular mechanisms, clinical significance and therapeutic interventions.Signal transduction and targeted therapy · 2023Review
- Impact of Noise Level on the Accuracy of Automated Measurement of CT Number Linearity on ACR CT and Computational Phantoms.Journal of biomedical physics & engineering · 2023Article
- CT texture analysis and node-RADS CT score of mediastinal lymph nodes - diagnostic performance in lung cancer patients.Cancer imaging : the official publication of the International Cancer Imaging Society · 2022Article
- Analysis of the value of enhanced CT combined with texture analysis in the differential diagnosis of pulmonary sclerosing pneumocytoma and atypical peripheral lung cancer: a feasibility study.BMC medical imaging · 2022Article
- Radiomics Texture Features in Advanced Colorectal Cancer: Correlation withRadiology. Imaging cancer · 2020Article
- Preoperatively Estimating the Malignant Potential of Mediastinal Lymph Nodes: A Pilot Study Toward Establishing a Robust Radiomics Model Based on Contrast-Enhanced CT Imaging.Frontiers in oncology · 2020Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveMediastinal lymph node (LN) staging in individuals with non-small-cell lung cancer plays an important role in staging and treatment planning. This study aimed to assess the accuracy of computed tomography (CT) texture analysis (CTTA) in differentiating benign and malignant mediastinal LNs.
methodsPathologically confirmed malignant and benign mediastinal LN samples, obtained using endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), were retrospectively reviewed, in addition to chest CT and 18-fluorodeoxyglucose (FDG) uptake positron emission tomography (PET) data. For each LN, CTTA was performed using "AVIEW" software (Coreline Soft, Republic of Korea) by drawing a region of interest.
resultsA total of 132 LNs from 80 patients were included and classified into two groups according to pathology results: malignant (n = 61) and benign (n = 71). In EBUS, size > 1 cm, round shape, heterogeneous echogenicity, and presence of coagulation necrosis sign were more prevalent in malignant than in benign LNs; length was the only feature that distinguished the two groups. Among CTTA features, compactness and normalized standard deviation (SD) showed differences between the two groups. The ability to distinguish malignant LNs was higher using high standard uptake value (SUV) on FDG PET/CT (SUV
conclusionsCTTA may be helpful in distinguishing between benign and malignant LNs; however, the diagnostic value was not high. Therefore, integrated evaluation with other imaging modalities is needed.
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