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Accuracy of Radiographic Pixel Linear Analysis in Detecting Bone Loss in Periodontal Disease: Study in Diabetic Rats.

˜The œSaudi dental journal(2021)

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摘要
Introduction: Periodontitis, a complex infectious disease that may lead to irreversible loss of periodontium, is considered a predisposing agent for developing insulin resistance due to the release of inflammatory mediators, showing a bilateral relationship with diabetes mellitus. The investigation of periodontal disease requires a clinical approach and complete intraoral radiographs, even with increasing concerns about radiation exposure. Thus, this study assesses pixel linear analysis accuracy using digital radiography via Digora (R) in detecting alveolar bone destruction in diabetic rats with periodontal disease. Methodology: 40 rats were divided into groups (n = 10): control (C), rats with periodontal disease (PD), experimental diabetic rats (ED), experimental diabetic rats with periodontal disease (ED-PD). Diabetes was induced by streptozotocin and periodontal disease by periodontal ligature. After 30 days, maxillae bone destruction was obtained by linear analysis of vertical bone loss using digital radiography and then assessed by micro-CT and histology. Data were analyzed by ANOVA and Tukey's test (p < 0.05). Results: Radiographic, micro-CT and histological analysis presented accurate and similar results. PD and ED-PD groups showed higher bone destruction than C and ED groups (p < 0.05). Moreover, the ED-PD group had higher bone loss than the PD group (p < 0.05). Conclusion: The pixel linear analysis via digital radiography was an accurate, low-cost alternative in detecting alveolar bone loss in this rat model. Micro-CT and histological analysis may also be used to obtain linear measures to assess and compare periodontal bone destruction in diabetic rats. (C) 2021 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University.
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关键词
Experimental diabetes mellitus,Histology,Periodontal disease,Radiography,Emission-computed tomography
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