TY  - JOUR
T1  - Giant Cells Lesions of Oral and Maxillofacial Region – A Proposed Diagnostic Algorithm
A1  - Harpreet Kaur
A1  - Deepika Mishra
A1  - Ajoy Roychoudhury
A1  - Mehar Chand Sharma
A1  - Ashu Seith Bhalla
A1  - Asit Ranjan Mridha
A1  - Aanchal Kakkar
A1  - Rahul Yadav
A1  - Sunny Kala
A1  - Shashwat Mishra
JF  - Clinical Cancer Investigation Journal
JO  - Clin Cancer Investig J
SN  - 2278-0513
Y1  - 2023
VL  - 12
IS  - 1
DO  - 10.51847/jT6kJbFKDg
SP  - 17
EP  - 26
N2  - Multinucleated giant cells are commonly encountered in histopathology and are mostly a clue to diagnosis but sometimes pose a diagnostic confusion. The present study elucidates a case series of giant cell lesions (GCL) with emphasis on differential diagnosis and other investigations that contribute towards arriving at a final diagnosis. We also intended to devise an algorithmic approach for the accurate pathological characterization of these lesions. All the cases reported in the department from January 2018 to June 2019 were reviewed by pathologists and the total number of lesions where giant cells were diagnostic or an additional finding were included in this study. Twenty-five cases out of 1000 biopsies were diagnosed based on giant cell morphology. The most frequent lesions were central giant cell granuloma, followed by cherubism, hyperparathyroidism, peripheral giant cell granuloma, tuberculosis, and hybrid lesion. A systematic approach towards differential diagnosis for such cases and a diagnostic algorithm was devised which is being followed as per the reported spectrum of GCL. Radiological, serology, and sometimes ancillary staining techniques are essential for the accurate histopathological diagnosis of giant cell lesions. Our diagnostic algorithm helps narrow down the spectrum of investigations necessary to characterize these lesions, enabling for a swifter and more confident identification of the pathologies.
UR  - https://ccij-online.org/article/giant-cells-lesions-of-oral-and-maxillofacial-region-ndash-a-proposed-diagnostic-algorithm-irg32aebm8ernr3
ER  -