Bone erosion is considered a typical characteristic of advanced or complicated cholesteatoma (CHO), although it is still a matter of debate if bone erosion is due to osteoclast action, being the specific literature controversial. The purpose of this study was to apply a novel scanning characterization approach, the BSE 3D image analysis, to study the pathological erosion on the surface of human incus bone involved by CHO, in order to definitely assess the eventual osteoclastic resorptive action. To do this, a comparison of BSE 3D image of resorption lacunae (resorption pits) from osteoporotic human femur neck (indubitably of osteoclastic origin) with that of the incus was performed. Surface parameters (area, mean depth, and volume) were calculated by the software Hitachi MountainsMap© from BSE 3D-reconstructed images; results were then statistically analyzed by SPSS statistical software. Our findings showed that no significant differences exist between the two groups. This quantitative approach implements the morphological characterization, allowing us to state that surface erosion of the incus is due to osteoclast action. Moreover, our observation and processing image workflow are the first in the literature showing the presence not only of bone erosion but also of matrix vesicles releasing their content on collagen bundles and self-immuring osteocytes, all markers of new bone formation on incus bone surface. On the basis of recent literature, it has been hypothesized that inflammatory environment induced by CHO may trigger the osteoclast activity, eliciting bone erosion. The observed new bone formation probably takes place at a slower rate in respect to the normal bone turnover, and the process is uncoupled (as recently demonstrated for several inflammatory diseases that promote bone loss) thus resulting in an overall bone loss. Novel scanning characterization approaches used in this study allowed for the first time the 3D imaging of incus bone erosion and its quantitative measurement, opening a new era of quantitative SEM morphology.
Copyright © 2020 Michela Relucenti et al.