ArticleScientific reports2014
Predicting subtypes of thymic epithelial tumors using CT: new perspective based on a comprehensive analysis of 216 patients.
Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Analysis of MRI features correlated with TNM staging in thymic epithelial tumors.Lasers in medical science · 2026Article
- High-Risk Thymoma Hidden Within a Cystic Thymic Lesion: A Diagnostic Clue from Diffusion-Weighted MRI.Diagnostics (Basel, Switzerland) · 2026Article
- An interpretable machine learning approach using nnU-Net-based radiomics for preoperative risk stratification of thymic epithelial tumors: a multicenter study.BMC medical imaging · 2026Article
- Exploring the incidence rate and imaging differential diagnosis of anterior mediastinal lesions: an 11-year retrospective study based on 2,626 cases.Quantitative imaging in medicine and surgery · 2025Article
- Using optimized CT type to predict histological classifications of thymic epithelial tumors: a radiomics integrated analysis.Insights into imaging · 2025Article
- Incremental diagnostic value of tumor habitat radiomics for risk stratification in thymic epithelial tumors.Frontiers in oncology · 2025Article
- Differential diagnosis between low-risk and high-risk thymoma: Comparison of diagnostic performance of radiologists with and without deep learning model.Acta radiologica open · 2024Article
- Differentiating low-risk thymomas from high-risk thymomas: preoperative radiomics nomogram based on contrast enhanced CT to minimize unnecessary invasive thoracotomy.BMC medical imaging · 2024Article
- Quantitative CT parameters combined with preoperative systemic inflammatory markers for differentiating risk subgroups of thymic epithelial tumors.BMC cancer · 2023Article
- Prognostic CT features in patients with untreated thymic epithelial tumors.Scientific reports · 2023Article
- Peritumoral imaging features of thymic epithelial tumors for the prediction of transcapsular invasion: beyond intratumoral analysisDiagnostic and interventional radiology (Ankara, Turkey) · 2023Article
- Risk factor analysis for major mediastinal vessel invasion in thymic epithelial tumors based on multi-slice CT Imaging.Frontiers in oncology · 2023Article
- Contrast-enhanced CT-based radiomics model for differentiating risk subgroups of thymic epithelial tumors.BMC medical imaging · 2022Article
- Differentiating thymoma, thymic carcinoma and lymphoma based on collagen fibre patterns with T2- and diffusion-weighted magnetic resonance imaging.European radiology · 2022Article
- Micronodular thymoma with lymphoid stroma: Contrast-enhanced CT features with histopathological correlation in 10 patients.Frontiers in oncology · 2022Article
- Prognostic Significance of Metabolic Parameters byCancers · 2021Article
- Development and validation of a CT-texture analysis nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.Cancer imaging : the official publication of the International Cancer Imaging Society · 2020Article
- Dual-energy CT perfusion imaging for differentiating WHO subtypes of thymic epithelial tumors.Scientific reports · 2020Article
- Predicting pathological subtypes and stages of thymic epithelial tumors using DWI: value of combining ADC and texture parameters.European radiology · 2019Article
- Comparison between CT and MRI in the Diagnostic Accuracy of Thymic Masses.Journal of Cancer · 2019Article
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Authors and funding
9 authors.
Funding
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Abstract
It is highly necessary to identify low versus high risk thymic epithelial tumors (TETs) before operation to guide optimal treatment strategies. Current CT diagnostic parameters could not effectively achieve this goal. We evaluated three parameters of CT scan in a cohort of 216 TETs patients. Parameters of contrast enhancement, risk of aggressiveness, and nodule with fibrous septum were evaluated in low (A, AB) versus high risk (B1, B2, B3 and thymic carcinoma) TETs. Grade of contrast enhancement showed predictive value in classifying low and high risk TETs well. A maximal contrast-enhanced range of 25.5 HU could produce 78.8% sensitivity and 68.5% specificity in determining low risk subtypes. Additionally, risk of aggressiveness parameter was demonstrated to be associated with TETs subtype (r = 0.801, P < 0.001) and may add confidence in determining low versus high risk subtypes. Furthermore, multiple nodule with fibrous septum could suggest subtype AB. Findings from this study support role of studied parameters of CT manifestations in predicting the low and high risk stages of TETs. These findings provide empirical evidence for incorporating these parameters in clinical practice for identifying TETs stage before operation, if validated in additional studies.
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