Correlation Between Fine Needle Aspiration Cytology with Histopathology of Non-Thyroidal Head and Neck Lesions: First Report from Somalia

Background: Fine needle aspiration cytology (FNAC) is a widely accepted, cost-effective, and minimally invasive diagnostic procedure used for the evaluation of head and neck masses. Despite its global utilization, no previous studies from Somalia have assessed the diagnostic accuracy of FNAC in non-thyroidal head and neck lesions. Objective: To evaluate the diagnostic accuracy, sensitivity, specificity, and predictive values of FNAC by correlating cytological findings with histopathological diagnoses in non-thyroidal head and neck masses. Methods: This retrospective study included 265 patients with non-thyroidal head and neck lesions who underwent FNAC followed by histopathological examination at a tertiary hospital in Somalia over five years. FNAC results were compared with corresponding biopsy findings. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were calculated using histopathology as the gold standard. Results: A total of 265 patients underwent both FNAC and histopathological examination for non-thyroidal head and neck lesions. Of these, 145 (54.7%) were males and 120 (45.3%) were females, yielding a male-to-female ratio of 1.2:1. Lymph node lesions comprised the majority of cases (60.8%), followed by salivary gland lesions (36.2%) and miscellaneous soft tissue/cystic masses (3.0%). FNAC showed highest sensitivity in lymph node lesions (99%) and highest specificity and accuracy in salivary gland lesions (98.8% and 98%, respectively). The overall sensitivity, specificity, and accuracy were 97.1%, 96.7%, and 98.5%, respectively. Lymphomas were the most frequent malignancy diagnosed, and most salivary gland lesions were benign, with pleomorphic adenoma being the most common. Conclusion: FNAC demonstrates high diagnostic performance in evaluating non-thyroidal head and neck lesions, supporting its role as a first-line diagnostic tool, especially in low-resource settings like Somalia.