Carboxylated osteocalcin (cOC), produced during post-translational modification of osteocalcin (OC) in a vitamin K-dependent pathway, has a high affinity for calcium and hydroxyapatite. Despite the observed link between vitamin K deficiency and fracture risk, supplementation studies have not consistently demonstrated improvements in bone mineral density (BMD) or bone microarchitecture, though studies have reported improvement in cOC status. We hypothesise that these inconsistent findings are due to the lack of knowledge on the mechanisms by which cOC affects bone health. Hence, the aim of this study was to investigate the relationship between cOC and bone turnover markers, cortical and trabecular bone microarchitecture and strength. Forty-five patients who underwent hip arthroplasty for hip osteoarthritis were prospectively recruited. Patients with conditions or medications that could affect bone outcomes were excluded and intra-operative bloods and bone biopsies were collected. Cortical thickness and hip strength was measured with dual-energy X-ray absorptiometry and micro-computed tomography was used to determine trabecular bone microarchitecture. Cortical thickness, cross-sectional area, cross-sectional moment of inertia, femoral neck width and section modulus correlated positively with cOC (p<0.05, all). There was no association between partially or fully un-carboxylated fractions and hip strength variables. Further, cOC was found to be an independent predictor of bone alkaline phosphastase while the partially or fully un-carboxylated OC predicted c-terminal telopeptide of type 1 collagen. In conclusion, higher cOC concentrations were associated with improved femoral bone strength, and the effect is possibly mediated through higher bone mineralisation, independent of age, parathyroid hormone, kidney function, BMD and physical activity.

Bone biopsies are an important biological tool for investigating bone microarchitecture, which can be non-destructively imaged in 3D via micro-computed tomography (micro-CT). Image thresholding and delineation of a region of interest (ROI) are prerequisites for quantifying bone parameters. Validated automatic protocols enable quantification of biopsies that contain trabecular and cortical bone. However, irregularly shaped trabecular bone biopsies with peripheral and internal debris have required manual ROI delineation, which is time-intensive and subject to inter and intra-observer variance. We hypothesise that an automated workflow will be a suitable alternative to overcome these issues and objectively determine bone microarchitecture in surgical biopsies, at higher throughput suitable for clinical studies. Hence, the aim of this study was to develop an objective, reproducible and automated workflow to analyse microarchitecture of trabecular bone biopsies. To accomplish this aim, we tested six different methods of ROI delineation: a whole biopsy ROI, and both manual (slow) and automatically delineated (fast) reduced ROIs to remove peripheral debris, each with (adaptive thresholding and a set of morphological operations to remove debris) and without (global thresholding) processing in a subset (n = 8) of intertrochanteric femoral biopsies obtained from patients undergoing hip arthroplasty. Number of objects, bone volume to tissue volume (BV/TV), trabecular separation (Tb.Sp), structure model index (SMI) and Euler number and trabecular pattern factor (Tb.Pf) were compared between the six workflows using Friedman's test and post-hoc pairwise comparisons with Bonferroni correction was performed. The two most reproducible techniques were tested for validation in a larger cohort of arthroplasty patients (n = 60) and results were compared with appropriate t-test. Subset analysis indicated that the manual and automated ROI with processing increased the ability to resolve real differences between these groups in parameters BV/TV, Tb.Sp and Euler number compared to with no processing and whole biopsy ROI approach. A validation cohort consisted of thirty osteoarthritis patients with a mean age 68.25 ± 8.64 and thirty neck of femur fracture with a mean age 82.4 ± 8.9. The manual technique failed to detect differences in BV/TV, SMI and Tb.Pf between the two patient groups (p > 0.05, for all) while the automated workflow demonstrated significant differences in these parameters between the OA and the NOF patients (p < 0.05). This is probably due to irregularity in the reference VOI volume introduced by manual ROI delineation reducing morphometric precision, compared to the automated method. In conclusion, our automated workflow performed better than customary practice; it represents a user-independent, high throughput technique to measure bone microarchitecture accurately in surgical biopsies.