Pulmonary Cytology in Transformation

Traditionally, pulmonary cytology has been used to diagnose and screen for a variety of respiratory diseases, including lung cancer. Owing to its rapid turnaround time compared with histological diagnosis, therapeutic decisions may occasionally need to be made based on cytological findings alone. In the era of precision medicine, however, biomarker assessment and molecular testing have become increasingly important, particularly in the management of lung cancer. In addition, the digitalization of pathological slides has facilitated the development of artificial intelligence (AI)-based diagnostic tools. The utility of these emerging technologies in pulmonary cytology is currently being actively investigated and continues to evolve, overcoming challenges including low input of tumor cells and three-dimensional nature of cytological specimens.

This review summarizes recent advances in pulmonary cytology, focusing on immunocytochemistry (ICC), proteomic analysis, and AI-assisted diagnostics. ICC provides crucial information not only for subclassification but also for the assessment of relevant therapeutic biomarkers. Proteomic analysis enables comprehensive characterization of thousands of protein expression profiles simultaneously, using limited cytology materials. But its future use in routine diagnostics must be established and tested in clinical trials. Furthermore, digitalized cytological slides can be utilized for AI-based analyses, potentially reducing diagnostic workload, and providing additional predictive information. Despite these advances, challenges remain regarding specimen preparation, standardization, and validation.

The integration of morphology with appropriately validated molecular and computational methods has the potential to transform the framework of pulmonary cytology, extending its role from morphological diagnosis toward comprehensive and clinically significant characterization of pulmonary tumors.