Mesoscale porosity at the dentin-enamel junction could affect the biomechanical properties of teeth. (15th March 2017) - Vennat, Elsa; Wang, Wenlong; Genthial, Rachel; David, Bertrand; Dursun, Elisabeth; Gourrier, Aurélien
Graphical abstract: Abstract: In this paper, the 3D-morphology of the porosity in dentin is investigated within the first 350 μm from the dentin-enamel junction (DEJ) by fluorescence confocal laser scanning microscopy (CLSM). We found that the porous microstructure exhibits a much more complex geometry than classically described, which may impact our fundamental understanding of the mechanical behavior of teeth and could have practical consequences for dental surgery. Our 3D observations reveal numerous fine branches stemming from the tubules which may play a role in cellular communication or mechanosensing during the early stages of dentinogenesis. The effect of this highly branched microstructure on the local mechanical properties is investigated by means of numerical simulations. Under simplified assumptions on the surrounding tissue characteristics, we find that the presence of fine branches negatively affects the mechanical properties by creating local stress concentrations. However, this effect is reduced by the presence of peritubular dentin surrounding the tubules. The porosity was also quantified using the CSLM data and compared to this derived from SEM imaging. A bimodal distribution of channel diameters was found near the DEJ with a mean value of 1.5–2 μm for the tubules and 0.3–0.5 μm for the fine branches which contribute to 30% of the total porosity (∼1.2%). A gradient in the branching density was observed from the DEJ towards the pulp, independently of the anatomical location. Our work constitutes an incentive towards more elaborate multiscale studies of dentin microstructure to better assess the effect of aging and for the design of biomaterials used in dentistry, e.g. to ensure more efficient bonding to dentin. Finally, our analysis of the tubular network structure provides valuable data to improve current numerical models.