Efficacy of argyrophilic nucleolar organizing region analysis using computer-assisted and manual in oral leukoplakia: A comparative study

• Published in: Indian journal of cancer Vol. 52; no. 1; p. 75
• Main Authors: Garg, Kavita Nitish, Raj, Vineet, Chandra, Shaleen
• Format: Journal Article
• Language: English
• Published: India Medknow Publications and Media Pvt. Ltd 01.01.2015; Medknow Publications & Media Pvt. Ltd
• Subjects: Antigens, Nuclear - biosynthesis; Antigens, Nuclear - genetics; Care and treatment; Cell Proliferation - genetics; Development and progression; Epithelium - pathology; Evaluation; Female; Humans; Image Processing, Computer-Assisted; Leukoplakia; Leukoplakia, Oral - diagnosis; Leukoplakia, Oral - genetics; Leukoplakia, Oral - pathology; Male; Medical computer applications; Molecular Imaging; Mouth Neoplasms - diagnosis; Mouth Neoplasms - genetics; Mouth Neoplasms - pathology; Precision medicine; Technology application
• ISSN: 0019-509X; 1998-4774
• DOI: 10.4103/0019-509X.175589

Nucleolar organizer regions are loops of DNA containing ribosomal RNA genes and presumably are associated with ribosomal RNA activity, protein synthesis, and cell proliferation. Argyrophilic nucleolar organizer region (AgNOR) count has been suggested as an objective method in differentiating dysplastic lesions from non-dysplastic lesions. This descriptive study was done on archival paraffin blocks (n = 60), consisting of 10 normal human oral epithelium, 22 cases of non-dysplastic leukoplakia (NDLK), and 28 cases of dysplastic leukoplakia (DLK). The AgNORs were counted with the aid of a manual using conventional light microscopy and photographs of the same were taken and analyzed using Image Pro Express 6.0 (Media Cybernetic Inc., USA) for windows. The mean AgNOR count per nucleus was found to be higher in patients with DLK as compared to NDLK and controls using both manual counting and image analysis method and on comparing both the techniques, image analysis provide a more accurate reflection of AgNOR counts than manual counting. To conclude, reliability of computerized image technique of AgNOR count is the most appropriate marker to differentiate between dysplastic and NDLK. Computer-assisted image analysis system was found to be an effective tool in achieving high reproducibility as compare to manual.