Voronoi-based analysis of bone cell network from synchrotron radiation micro-CT images

With the development of the novel micro and nano-CT systems, bone cell analysis has gone beyond the limitation of the conventional 2D analysis. In particular synchrotron radiation micro-CT is well suited to image in 3D the lacuno-canalicular network (LCN) in bone tissue. This network is made of osteocyte lacunae connected by small channels called canaliculi. Due to the lack of quantitative data on this network, we propose here an automated method to extract geodesic Voronoi-based parameters to characterize the regions of influence of canaliculi. To this aim, after labeling each lacuna from the segmented LCN image, we generated geodesic Voronoi tessellations on each lacunar surface. Our proposed method was successfully applied to three SR micro-CT images of women tibial cortical samples. We believe that this method can serve to extract new information on the 3D morphometry of the LCN in more datasets.