Ultra-high-resolution imaging of the osteocyte lacuno-canalicular network (LCN) three-dimensionally (3D) in a high-throughput fashion has greatly improved the morphological knowledge about the constituent structures – positioning them as potential biomarkers. Technologies such as serial focused ion beam/scanning electron microscopy (FIB/SEM) and confocal scanning laser microscopy (CLSM) can image in extremely high resolution, yet only capture a small number of lacunae. Synchrotron radiation computed tomography (SR-CT) can image with both high resolution and high throughput but has a limited availability. Desktop micro-computed tomography (micro-CT) provides an attractive balance: high-throughput imaging on the micron level without the restrictions of SR-CT availability. In this study, accuracy, reproducibility, and sensitivity of large-scale quantification of human osteocyte lacunar morphometries were assessed by ultra-high-resolution desktop micro-computed tomography. For this purpose, thirty-one transiliac human bone biopsies containing trabecular and cortical regions were imaged using ultra-high-resolution desktop micro-CT at a nominal isotropic voxel resolution of 1.2 µm. The resulting 3D images were segmented, component labeled, and the following morphometric parameters of 7.71 million lacunae were measured: Lacunar number (Lc.N), density (Lc.N/BV), porosity (Lc.TV/BV), volume (Lc.V), surface area (Lc.S), surface area to volume ratio (Lc.S/Lc.V), stretch (Lc.St), oblateness (Lc.Ob), sphericity (Lc.Sr), equancy (Lc.Eq), and angle (Lc.θ). Accuracy was quantified by comparing automated lacunar identification to manual identification. Mean true positive rate (TPR), false positive rate (FPR), and false negative rate (FNR) were 89.0%, 3.4%, and 11.0%, respectively. Regarding the reproducibility of lacunar morphometry from repeated measurements, precision errors were low (0.2–3.0%) and intraclass correlation coefficients were high (0.960–0.999). Significant differences between cortical and trabecular regions (p<0.001) existed for Lc.N/BV, Lc.TV/BV, local lacunar surface area (<Lc.S>), and local lacunar volume (<Lc.V>), all of which demonstrate the sensitivity of the method and are possible biomarker candidates. This study provides the foundation required for future large-scale morphometric studies using ultra-high-resolution desktop micro-CT and high-throughput analysis of millions of osteocyte lacunae in human bone samples.
All Science Journal Classification (ASJC) codes
- Endocrinology, Diabetes and Metabolism