Human bone ultrastructure in 3D: Multimodal correlative study combining nanoscale X-ray computed tomography and quantitative polarized Raman spectroscopy

Abstract

Unique mechanical properties of cortical bone are defined by the arrangement and ratio of its organic and inorganic constituents. This arrangement can be influenced by ageing and disease, urging the understanding of normal and deviant morphological patterns down to the nanoscale level, as much as the exploration of techniques able to grant that knowledge. Here, the ultrastructure and composition of seven samples taken from the femoral neck cortical bone of a single donor (52 y.o. female, no metabolic bone disease) is assessed with emerging characterization techniques. Laboratory-based nanoscale X-ray computed tomography providing ∼50 nm spatial resolution at (16 nm)³ voxel size resolves not only the lacuno-canalicular network but also the mineral ellipsoids associated with mineralized collagen fibrils (MCF). Site-matching 3D data with quantitative polarized Raman spectroscopy provides, in turn, complementary information on relative mineral and organic composition, while both techniques allow to quantify the MCF orientation. Bone matrix composition and lacuna-canalicular network organization are shown to vary between the osteonal and interstitial zones. Both plywood and gradual oscillating motifs of bone lamellation are observed, in line with existing theories. By combining these two methods, future studies can concentrate on other bone ultrastructural units of interest like interlamellar and cement interfaces, the structure of MCF around lacunae and near Haversian channels, as well as the influence of metabolic diseases on bone ultrastructure.

Statement of significance

This study provides new insights into bone hierarchical organization, revealing local composition and lacuno-canalicular network organization within osteonal and interstitial bone zones, as well as their mineralized collagen fiber (MCF) orientation within the lamella. Synchrotron-like resolution was achieved on a laboratory-based nano-CT by exposing the volumes of interest from the bulk sample and applying machine learning segmentation algorithms. Site-matched analysis with quantitative Polarized Raman spectroscopy (qPRS) provided indirect access to relative mineral and organic composition variations and local MCF out-of-plane angle, with good agreement between the two methods. The proposed correlative experiment workflow greatly facilitates the characterization of bone ultrastructure and can be applied to other fields dealing with ordered hierarchical materials of similar feature sizes.