X-ray physics- and bone composition-based estimation of thickness characteristics from clinical mandibular radiographs

https://doi.org/10.1016/j.compmedimag.2015.06.005Get rights and content
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Highlights

  • Normalized mandibular thickness distributions are derived from clinical panoramic radiographs.

  • X-ray physics is combined with cortical and trabecular porosity values.

  • Methods are intensity loss quantification and attenuation averaging in composites.

  • Thickness distribution appears asymmetric with respect to the face's symmetry axis.

  • Molar regions are identified as thicker than those close to incisor.

Abstract

In dentistry, clinical radiographs (also called X-ray images) reflect the intensity loss of an X-ray when being transmitted through the mandibular objects, and this loss is quantified in terms of grey values. While such images are standardly used for pathology detection by the experienced dentist, we here present a new method for getting more quantitative information out of such 2D radiographs, “extending” them into the third dimension. This “extension” requires consistent combination of X-ray physics (namely, X-ray intensity loss quantification along paths orthogonal to the panoramic clinical image and X-ray attenuation averaging for composite materials) with anatomically known upper and lower limits of vascular porosities in cortical and trabecular bone compartments. Correspondingly computed ranges of overall organ thicknesses are extremely narrow, suggesting adequate estimation of thickness characteristics from 2D radiographic panoramas used clinically, while predicted cortical and trabecular thickness ranges vary by ±8.47% and ±16.13%, respectively. The proposed method also identifies variations between thicknesses at similar anatomical locations left and right of the face's symmetry axis, and molar regions turn out to be thicker than those close to incisors. This paves the way to more detailed diagnostic activities, e.g. in combination with Finite Element simulations.

Keywords

Attenuation
Radiological analysis
Grey value distribution
Mandibular bone
Mathematical modeling

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