Abstract
Aim: To evaluate whether inflammation influences polarization colors of collagen fibers and to study their staining pattern in the connective tissue wall of infected and non-infected odontogenic keratocyst (OKC) using picrosirius red and polarizing microscopy. Materials and Methods: Histopathologically diagnosed 50 cases of OKC were studied. Degree of inflammation was examined on H and E stained slides and inflammatory density was graded on a 4-grade scale from 0 to 4. Cases were then divided into three groups, A to C according to the inflammatory score. Picrosirius red-stained sections were viewed under a polarized microscope for birefringence of collagen fibers and the colors for both thin [0.8μm or less] and thick [between 1.4 and 2.4 μm] fibers were noted. Polarization colors were divided into three groups: Group 1: Green, 2: Yellow and 3: Red. Analysis of variance (ANOVA) was used to find the significance of study parameters. Results: In the present study, there was no significant difference in the means of polarization color pattern of thin fibers in all the three groups. The majority of thin fibers were in range of green and yellow (~90%). Cases of Group 1 had highest mean values of thick green fibers at 27.31% and cases of Group 3 had highest mean values of thick red fibers at 56.37%. Differences in mean values of thick green, yellow and red fibers between Group 1 and Group 2 and between Group 1 and Group 3 were statistically significant. Conclusion: Cases of OKC with no or mild inflammation had majority of poorly packed fibers with green and yellow birefringence and moderate to severely inflamed cases had well-packed and thick fibers showing orange to red birefringence. Our study showed that inflammation influences polarization colors and packing of collagen fibers in the connective tissue wall of infected and non-infected OKC. Thus, the study of packing of collagen fibers in correlation with inflammation using polarizing microscopy in conjunction with picrosirius red staining can be effectively used to predict the biologic behavior of OKC.
Published Version
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