New Insights for Consummate Diagnosis and Management of Oral Submucous Fibrosis Using Reactive and Reparative Fibrotic Parameter Derived Algorithm

Abstract

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

Quantification of inflammatory, angiogenic, and fibrous components of reactive oral lesions with an insight into the pathogenesis

“…Collagen Proportionate area refers to the proportion of collagen stained area to the total area in the region of interest for each image, which is expressed in %. [ 13 ] The integrated density of collagen refers to the product of area and mean intensity of collagen stain. [ 14 ] [ Figure 2 ]…”

Oral Potentially Malignant Disorders: Etiology, Pathogenesis, and Transformation Into Oral Cancer

“…Histopathological grading involves immune infiltration count, epithelial thickness, collagen proportionate area, and blood vessel parameters. With an advanced stage, there is a decrease in immune localization and inflammation, whereas collagen density and epithelial thickness increases ( Ramadoss et al, 2021 ).…”