Keywords
mandible
bone architecture
morphometry
computed tomography
fractal dimension
How to Cite
Abstract
In press
Background. The study of mandibular bone architecture is crucial for understanding remodeling, osteogenesis, and resorption processes under normal and pathological conditions. Traditional morphometric methods often rely on limited regions of interest and do not account for the hierarchical self-organization of bone tissue or the complexity of its surface configuration. There is a need for a modified fractal analysis technique focused on assessing the surface complexity of the entire bone slice rather than just its volume filling.
Aim. To develop an original modification of the contour smoothing method for studying mandibular bone architecture on computed tomography images, enabling the analysis of whole bone slices independent of region of interest selection.
Materials & Methods. The methodological study utilized digital cone-beam computed tomography images of the mandibular bone. The fractal dimension was calculated using a custom "contour smoothing" algorithm across six stages with increasing smoothing radii (2, 4, 8, 16, 32 pixels). Statistical data processing included the calculation of linear regression and the coefficient of determination to assess fractal properties; calculations and graphical visualization were performed using Excel 2016 (Microsoft, USA). The study was conducted as part of the initiative research project "Development of clinical and morphological methods of researching the structures of the human body" (State Registration No.0123U100367, 2023–2025).
Research Ethics. The study was approved by the Ethics and Bioethics Committee of Kharkiv National Medical University.
Results. The analysis revealed that the dependence of variables remained linear during the first four stages (smoothing radii 2–8 pixels). At these stages, the bone trabeculae demonstrated monofractal properties. At stages 5 and 6 (radii 16–32 pixels), linearity was disrupted due to the loss of cortical plate contours, leading to a decrease in the approximation coefficient. Consequently, the optimal scaling range for the mandibular bone was determined to be stages 1–4.
Conclusions. The developed contour smoothing algorithm effectively quantifies the complexity of endosteal surface configurations and internal bone contours. This method offers a robust, resolution-independent approach for evaluating bone remodeling and resorption activity, suitable for diagnosing osteoporosis and assessing implant integration.
Keywords: theoretical and experimental medicine, mandible, bone architecture, morphometry, computed tomography, fractal dimension.
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