ArticleQuantitative imaging in medicine and surgery2024
The combination of maximum standardized uptake value and clinical parameters for improving the accuracy in distinguishing primary mediastinal lymphomas from thymic epithelial tumors.
Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 4 citations in OpenAlex.
- A multiparameter diagnostic model based on MRI volumetric ADC histogram and clinical variables accurately differentiates thymic epithelial tumors from mediastinal lymphomas.BMC medical imaging · 2026Article
- Primary Mediastinal B-Cell Lymphoma and [18F]FDG PET/CT: What We Learned and What Is New.Hematology reports · 2025Review
- Practical value of fluorodeoxyglucose positron emission tomography in treatment strategies for thymic epithelial tumors: implications for more specific use in routine clinical practice.Mediastinum (Hong Kong, China) · 2025Review
- The significance of PET/CT combined with machine learning models for the classification of lymphoma involvement and metastases in enlarged lymph nodes.Frontiers in oncology · 2025Article
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Authors and funding
9 authors at 3 institutions in 1 country.
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Abstract
Background: Anterior mediastinal masses are relatively uncommon, and mediastinal lymphomas are the malignancies most likely to be confused with thymic epithelial tumors (TETs). The aim of this study was to investigate whether the combination of Methods: This retrospective study consecutively included 304 patients with anterior mediastinal masses (244 TETs and 60 lymphomas) who underwent Results: Lymphoma was significantly associated with younger patient age, higher LDH level, larger tumor size, and higher SUVmax compared to TETs (P<0.001). In the modeling cohort, age ≤40.5 years, LDH level ≥197 U/L, tumor size ≥10.72 cm, and SUVmax ≥11.95 were identified as independent predictors for lymphoma with odds ratios of 20.14 [95% confidence interval (CI): 6.02-67.40; P<0.001], 4.89 (95% CI: 1.27-18.89; P=0.021), 8.82 (95% CI: 2.31-33.69; P=0.001), and 30.01 (95% CI: 6.59-136.72; P<0.001), respectively. The accuracy of age, LDH, tumor size, and SUVmax in predicting lymphoma was 84.8%, 67.8%, 85.2%, and 78.3% respectively. The combination of the four above parameters could improve the predictive accuracy to 89.1%, and in the validation cohort, this combination increased the predictive accuracy to 87.8%. Conclusions: SUVmax on
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