The Evolution of Anatomical Classification Systems for Sinonasal Malignancies
DOI:
https://doi.org/10.12775/QS.2026.49.67438Keywords
paranasal sinuses, CT/MRI imaging, carcinoma, prognostic factors, maxillectomyAbstract
Background. Malignant tumors of the nasal cavity and paranasal sinuses present unique diagnostic challenges. Due to their concealed location and nonspecific symptoms, over 70% of cases are diagnosed at an advanced stage, leading to high mortality. While modern oncology utilizes precise imaging (CT, MRI), earlier approaches relied on physical examination and topographical classifications. Understanding this evolution remains crucial for contemporary rhinosurgery.
Aim. This study analyzes historical concepts to understand how pioneers perceived anatomical barriers and tumor spread. It further links these perspectives to tumor biology and the evolution of modern strategies, including skull base surgery.
Materials and methods. This study synthesizes historical and contemporary data to trace the evolution of anatomical classifications. A search of PubMed, Google Scholar, and Web of Science databases was performed, focusing primarily on English-language articles relevant to sinonasal tumor surgery and imaging.
Results. Early classifications (Sebileau, 1906; Öhngren, 1933) relied on geometric planes for prognosis. The advent of CT/MRI and the TNM system (1977) shifted the paradigm from theoretical geometry to anatomical barriers, while Harrison (1976) proved the feasibility of skull base resection. Consequently, surgery evolved from rigid "en bloc" resections to "compartment theory" and endoscopic techniques based on wall infiltration. Future trends point towards multidimensional models integrating radiomics and molecular profiling, extending beyond anatomy to biological signatures.
Conclusions. The evolution of classification systems, from historical topographic lines to modern radiomic algorithms, reflects the progression from macroscopic assessment to digital precision. Despite the paradigm shift toward a functional approach, the precise delineation of tumor boundaries remains a critical challenge for optimizing surgical efficacy and minimizing complications
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