|
New insights for consummate diagnosis and management of oral submucous fibrosis using reactive and reparative fibrotic parameter derived algorithm
Ramya Ramadoss1, Rajkumar Krishnan1, V Vasanthi1, Divya Bose1, R Vijayalakshmi2, Rajashree Padmanabhan3, Balakumar Subramanian4
1 Department of Oral Pathology and Microbiology, SRM Dental College, SRMIST, Chennai, Tamil Nadu, India
2 Department of Mathematics, SRM Institute of Science and Technology, Ramapuram, Chennai, Tamil Nadu, India
3 CAS Crystallography and BioPhysics, University of Madras, Chennai, Tamil Nadu, India
4 National Centre for Nanoscience and Nanotechnology, University of Madras, Guindy Campus, Chennai, Tamil Nadu, India
Correspondence Address:
Ramya Ramadoss
Department of Oral Pathology and Microbiology, SRM Dental College, SRMIST, Ramapuram, Chennai - 600 089, Tamil Nadu
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jpbs.JPBS_822_20
|
|
Objective: Reproducibility of qualitative changes in histopathological diagnosis involving narrow variation is often challenging. This study aims to characterize the histological fibrotic events in detail so as to derive an in-depth multiparametric algorithm with individually quantified histological parameters for effective monitoring of the. disease process in oral submucous fibrosis and for potential therapeutic targets for early intervention. Methods: Formalin fixed paraffin embedded (FFPE) blocks of oral submucous fibrosis (OSMF), were taken and sections were stained with Hematoxylin & Eosin stain and Masson Trichrome stain. Photomicrographs were assessed for various morphometric parameters with Image J software version 1.8. Linear Regression was used to model the relationship using Inflammatory Cell Count, Extent of Inflammation collagen stained area, Epithelial thickness integrated density of collagen, MVPA, Area, Perimeter, were taken as variables. Result: Inflammatory cell count and the extent of inflammation also decreased with increasing grades of OSMF. Collagen proportionate area, integrated collagen density and epithelial thickness were compared among different grades of OSMF. Grade IV OSMF had greatest mean collagen proportionate area , highest integrated collagen density and lowest epithelial thickness when compared to other grades of OSMF. Linear regression model revealed smaller variation between Grade I to Grade II. Whereas Grade II to Grade IV exhibited larger variation suggestive of increased growth rate and all the coefficients were found to lie within 95% confidence limits Conclusion: Diagnostic algorithm with multiparametric regression model were derived and combinatorial therapeutic approaches have been suggested for more effective management of oral submucous fibrosis
|
