Abstract
Abstract
Objectives
Prediction of bone adaptation in response to mechanical loading is useful in the clinical management of osteoporosis. However, few studies have investigated the effect of repeated mechanical loading in the mouse tibia. Therefore, this study uses a combined experimental and computational approach to evaluate the effect of mechanical loading on bone adaptation in a mouse model of osteoporosis.
Methods
Six female C57BL/6 mice were ovariectomised (OVX) at week 14 and scanned using in vivo micro computed tomography (10.4µm/voxel) at week 14, 16, 18, 20 and 22. The right tibiae were mechanically loaded in vivo at week 19 and 21 with a 12N peak load, 40 cycles/day, 3 days/week. Linear isotropic homogeneous finite element (microFE) models were created from the tissue mineral density calibrated microCT images. Changes in bone adaptation, densitometric and spatial analyses were measured by comparing the longitudinal images after image registration.
Results
Mechanical loading increased periosteal apposition between weeks 18–20, which reduced slightly between weeks 20–22. Periosteal resorption reduced between weeks 18–20. At weeks 20–22, it remained lower than before treatment, but was up to 70% higher than after the first week of loading. Average SED increased due to OVX before decreasing due to mechanical loading. The highest increase in SED was at the proximal tibia between weeks 14 to 16 (102%), whereas the highest reduction (40%) occurred after the second week of loading in the proximal tibia.
Conclusions
The decrease/increase in bone apposition/resorption between weeks 20–22, despite the similar strain distributions between weeks 18–20 and 20–22, suggests that the first application of mechanical loading had a greater effect on reversing the adverse effects of the disease than the second. This imply that a systematic increase in peak load or loading rate may be required to achieve a similar bone adaptation rate with time.
Declaration of Interest
(b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.
