ArticleBMC cancer2025
Radiomics in thymic epithelial tumors: a scoping review of current status and advances.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Multi-modal prediction model for thymic epithelial tumors: Enhancing surgical decisions and recurrence risk assessment from CT datasets.European journal of radiology open · 2026Article
- Precision Oncology in Thymic Epithelial Tumors: Therapeutic Horizons and Implementation Barriers.International journal of molecular sciences · 2026Review
- Advanced thymic epithelial tumours after neoadjuvant therapy: a narrative review of surgical challenges and strategies.Mediastinum (Hong Kong, China) · 2026Review
- Development of Nomogram for Predicting Postoperative Progression Risk in High-Risk Thymoma and Thymic Carcinoma Utilizing Clinical and Preoperative CT Features.Clinical Medicine Insights. Oncology · 2026Article
- The Value of Baseline [Diagnostics (Basel, Switzerland) · 2025Review
- Multi-Level Oncological Management of a Rare, Combined Mediastinal Tumor: A Case Report.Current oncology (Toronto, Ont.) · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundThis scoping review aims to evaluate the current status and recent advances in the use of radiomics for the diagnosis, risk stratification, and staging of thymic epithelial tumors (TETs). The review also explores radiomics' potential in predicting the risk of myasthenia gravis (MG), an associated autoimmune condition in TETs patients.
methodsA comprehensive literature search was conducted using PubMed and Web of Science to identify studies published since 2012 on the application of radiomics in managing TETs. The studies were assessed for their methodologies, including imaging protocols, feature extraction techniques, and model performance metrics. The Radiomics Quality Score (RQS) was used to evaluate study quality.
resultsA total of 23 studies, including 4701 patients, were analyzed. Radiomics-based models showed high accuracy in distinguishing TETs from other mediastinal masses, predicting risk subtypes, and improving the accuracy of TNM and Masaoka-Koga (MK) staging. Additionally, radiomics demonstrated potential in predicting the risk of MG in thymoma patients. However, all studies were retrospective, and only 6 studies included external validation, with an average RQS of 13.87, accounting for 38.52% of the maximum score.
conclusionRadiomics shows great potential in advancing the diagnosis, risk stratification, and staging of TETs. However, its clinical implementation requires overcoming challenges in standardization, validation, and interpretability. Future research should focus on multi-center prospective studies, external validation, and integrating multi-modal imaging and molecular biomarkers to improve risk assessment and treatment strategies.
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