FINE NEEDLE ASPIRATION CYTOLOGY OF THE HEAD AND NECK MASSES: ONE YEAR PROSPECTIVE STUDY.
Journal Title: International Journal of Advanced Research (IJAR) - Year 2018, Vol 6, Issue 10
Abstract
Background: Fine needle aspiration cytology is a technique for obtaining cells from a lesion for cytological examination and evaluation. In the head and neck region, FNAC is of great value because of the multiplicity of accessible organs and heterogenous pathologies encountered. Aims and objectives: The present study aimed at studying the spectrum of various lesions presenting in the head and neck region based on cytological findings and to assess distribution amongst neoplastic and non neoplastic lesions. Methodology: A prospective study was conducted in the postgraduate department of Pathology, GMC, Jammu from 1st November, 2014 to 31st October, 2015. Results: A total of 900 aspirations were performed in the head and neck region. Swellings arising from lymphnodes formed the largest group 441(49%) cases, thyroid gland group comprised of 175(19.44%) cases, salivary gland origin lesions comprised of 67(7.45%) cases and miscellaneous group 217(24.11%) lesions. Aspiration was satisfactory in861(95.67%) and cytodiagnostic yield was 850(94.44%) in the study. In the lymph node group the most common diagnosis was reactive lymphadenitis in 191(43.31%) cases followed by tubercular lymphadenitis in 125(28.34%).In the thyroid gland group, most common pathology was colloid goiter in 93(53.14%) cases among non neoplastic category and papillary carcinoma in 7(4%) in neoplstic category. Sialadenitis and pleomorphic adenoma(35.82%) each was the most frequent diagnosis in salivary gland group. Epidermal incusion cyst(33.18%) was the most common diagnosis in miscellaneous group. Conclusion: FNAC is a simple, safe and inexpensive tool for the assessment of patients with head and neck swellings. It can differentiate non neoplastic lesions from neoplastic ones and avoid unnecessary surgeries.
Authors and Affiliations
Swati Arora, Ravi Kumar, Kuldeep Singh
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