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Scholars Journal of Applied Medical Sciences | Volume-3 | Issue-09
Clinicopathological Evaluation of Neck Masses
Dr. Hitender Basista, Dr. Amit Modwal, Dr. Beni Prasad
Published: Dec. 28, 2015 |
146
218
DOI: 10.36347/sjams.2015.v03i09.020
Pages: 3235-3241
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Abstract
FNAC is the most cost-effective invasive pre-operative investigation, whose simplicity and safety justify its
use for “selective” surgery in diagnosing different types of masses. Masses located in the head and neck most commonly
originates from cervical lymph nodes, thyroid, salivary glands and other neck masses. The primary objective of the study
was to assess the spectrum of head and neck masses and to determine the accuracy of FNAC in detection of various
lesions in National Institute of Medical Science and Research Hospital. A prospective study was conducted between the
period from December, 2013 to May, 2015 and patients willing to be a part of the study were included. The study was
time period specific i.e. the patients which came to NIMS OPD during the specific time period of our study, initiated on
December 2013 to May 2015. A total 55 patients were included in the study for statistical ease. All patients were
clinically examined. Out of 55 cases, FNAC was done in 52 cases and rest 03 cases were thyroglossal cyst (02) &
plunging ranula (01) which was diagnosed clinically & sonographically and later confirmed directly with histopath.
Histopathological examination was done in all 55 cases.The results of the FNAC were compared with the tissue
diagnosis obtained after surgical removal of the mass. Out of 55 patients diagnosed clinically, in 43 cases the
histopathological report confirmed the FNAC diagnosis. In 12 cases, the histopathology report was different. Out of the
55 patients, 13 (23.63%) were of lymph node, 26 (47%) were of thyroid, 7 (12.72%) were of salivary gland and 09
(16.36%) were of other neck masses. Our study evaluated 55 patients and found the overall sensitivity of FNAC in the
diagnosis of neck masses to be 78.03%, specificity to be 100% and accuracy 89.57%.