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Algorithmic Approach to Salivary Gland FNA: An Overview

  • William C. Faquin
  • Celeste N. Powers
Part of the Essentials in Cytopathology Series book series (EICP, volume 5)

This book uses a simplified and practical algorithmic approach to evaluate and diagnose a wide range of non-neoplastic, benign, and malignant entities encountered in salivary gland cytopathology (Fig. 3.1). After verifying that the FNA sample is indeed satisfactory for evaluation, the cytotechnologist or pathologist focuses upon the general types of cells, matrix, and inflammatory components that are present to fit the aspirate into 1 of 3 major arms of the algorithm based upon the overall cytomorphologic pattern. This will result in a focused differential diagnosis for the lesion. Detailed application of this algorithmic approach and distinction between different entities within the differential diagnoses are discussed and illustrated within specific subsequent chapters of this book. Because some salivary gland tumors can exhibit more than one general cytomorphologic pattern (e.g., mucoepidermoid carcinoma can be cystic, high-grade, or oncocytic), several entities will be presented and discussed in the differential diagnosis of more than one arm of the algorithm.

Keywords

Salivary Gland Adenoid Cystic Carcinoma Pleomorphic Adenoma Salivary Gland Tumor MUCOEPIDERMOID Carcinoma 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • William C. Faquin
    • 1
  • Celeste N. Powers
    • 2
  1. 1.Department of Pathology, Massachusetts General HospitalHarvard Medical SchoolBostonUSA
  2. 2.Department of Pathology, Medical College of Virginia HospitalsVirginia Commonwealth UniversityRichmondUSA

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