ReviewMediastinum (Hong Kong, China)2026
Approach to mediastinal cytopathology: a diagnostic overview.
Review in Mediastinum (Hong Kong, China), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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2 authors.
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Abstract
The mediastinum contains a diverse array of tissues, giving rise to a wide spectrum of benign, inflammatory, and malignant lesions. Accurate diagnosis is essential for determining appropriate management strategies, ranging from observation to targeted therapy. Fine-needle aspiration (FNA) has become the cornerstone of mediastinal evaluation, particularly with the advent of endobronchial and endoscopic ultrasound-guided techniques [endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and endoscopic ultrasound-guided FNA (EUS-FNA)], which allow minimally invasive access to all mediastinal compartments. Cytologic evaluation of these specimens, however, presents diagnostic challenges due to overlapping morphologic features and limited material for ancillary testing. This comprehensive review outlines a systematic approach to mediastinal cytopathology, emphasizing specimen adequacy, cytomorphologic interpretation, and integration with ancillary studies. Key entities include reactive lymphoid hyperplasia, granulomatous inflammation, cystic lesions, and a range of neoplastic processes such as thymic epithelial tumors, lymphomas, germ cell tumors (GCTs), mesenchymal neoplasms, and metastatic malignancies. Ancillary techniques-immunocytochemistry (ICC), flow cytometry, and molecular testing-play pivotal roles in confirming lineage, assessing clonality, and enabling targeted therapeutic decisions. Advances in next-generation sequencing (NGS) have expanded the use of cytology specimens for molecular profiling, while digital cytology and artificial intelligence (AI) are emerging as promising tools to improve accuracy and reproducibility. The review also highlights common diagnostic pitfalls, including confusion between thymic lesions and metastatic carcinoma, lymphoma and thymoma, or GCTs and poorly differentiated carcinomas. An algorithmic diagnostic workflow that combines cytomorphology with clinical, radiologic, and molecular data enhances accuracy and efficiency.
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