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Feasibility of fractal analysis for detecting primary bone changes in chronic periodontitis

Mohammad Amin Khajavi, Mustafa Saljoghinezhad, Nasser Sargolazaii


Background: Periodontitis is an inflammatory disease of the supporting tissues of teeth. Although several clinical and radiographic symptoms have been employed to detect periodontitis; however, no scheme has yet been introduced for the detection of gingivitis-to-periodontitis transition phase. Fractal analysis, as a mathematical tool to explore morphological features, has efficiently been used to investigate the complex structural pattern of alveolar bone texture. Aim: In this study, fractal analysis is examined for its feasibility to efficiently detect trabecular structure of interdental bone for individuals with healthy gums from patients with moderate periodontitis using digital images. Materials and Methods: Patients are divided into two groups of healthy individuals (H-group) and patients with moderate periodontitis (MP-group) (20 individuals in each sample group). Clinical indices involving pocket depth, attachment loss, and bleeding on probing, digital radiographic periapical images of posterior mandibles region are provided using phosphor plate system, and two rectangular regions out of interdental zone of mandibles molars are selected as regions of interest for each individual. The use of box-counting algorithm of image J software, fractal dimensions (FD) for both regions are then calculated, out of which the mean FD index is obtained for each patient. Clinical and FD indices are finally compared for both groups through a t-test examination. Results: Clinical indices for H-group are noticeably higher than those of MP-group (P ≤ 0.05). The mean FD for H- and MP- groups is 0.84 and 1.02, respectively. Statistical analysis proves a significant difference between the two groups for this index. Conclusion: Fractal analysis can efficiently quantify changes in trabecular pattern of bones, implying that temporal variation of such index may effectively demonstrate disease progression. The proposed scheme can be effective to detect and monitor variations due to periodontitis. Clinical Significance: Fractal analysis is a non-invasive method for early detection of moderate periodontitis.



Fractal analysis, fractal dimension, moderate periodontitis

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