CLASSIFYING SALIVARY GLAND LESIONS BASED ON MILAN'S SYSTEM FOR REPORTING SALIVARY GLAND CYTOPATHOLOGY AND EVALUATING THE RISK OF MALIGNANCY: A RETROSPECTIVE COHORT STUDY AT PRM MEDICAL COLLEGE & HOSPITAL, BARIPADA, INDIA.
DOI:
https://doi.org/10.51168/sjhrafrica.v5i3.1071Keywords:
Tumor, neoplasm, inflammation, LesionsAbstract
Background
Fine needle aspiration cytology (FNAC) is a very vital mode in the detection for defects in salivary glands (SG). The Milan System for Reporting Salivary Gland Cytopathology (MSRSGC) is classified into 6 groups which help the doctors to account for the chances of cancer in every group. The prime goal of this research is to utilize MSRSGC for the categorization of SG tumors.
Methods and materials
A retrospective cohort analysis was carried out at PRM Medical College & Hospital, Baripada. 200 patients were included having suspicion of salivary gland lesions in this research. After taking the patient history, sample for FNAC, histopathological findings, their pathological characteristics were examined and subjects were grouped as group 1 (Non-diagnostic), group 2 (Non-neoplastic), group 3 (Atypia of undetermined significance, group 4a (Neoplasm benign), group 4b (salivary gland neoplasm), group 5 (suspicious of malignancy), group 6 (Malignant).
Results
In this study, 110 male and 90 female subjects participated, with 30 under 20 years old, 80 aged 20-40, 44 aged 41-60, and 36 aged 61-80. Parotid gland involvement was predominant (119 cases), followed by the submandibular gland (60 cases) and minor salivary glands (21 cases). Salivary gland lesions were categorized via the Milan system as Group 1 (n=18), Group 2 (n=17), Group 3 (n=4), Group 4a (n=2), Group 4b (n=32), Group 5 (n=43), and Group 6 (n=84).
Conclusion
The responsiveness of 95% and precision of 98.9% to differentiate between non-cancerous and benign tumors and malignancy proclaimed the great correctness of SG fine needle aspiration cytology.
Recommendation
FNAC has great precision and responsiveness which differentiates benign and malignant tumors. Milan's system of categorization is also very effective and valuable.
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Copyright (c) 2024 Atanu Kumar Bal, Bibendu Bal, Devidutta Ramani Ranjan Rout, Subhasis Mishra, Lipika Behera, Shushruta Mohanty, Mamta Gupta
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