The mechanoresponse of bone is closely related to the osteocyte lacunocanalicular network architecture.

Organisms rely on mechanosensing mechanisms to adapt to changes in their mechanical environment. Fluid-filled network structures not only ensure efficient transport but can also be employed for mechanosensation. The lacunocanalicular network (LCN) is a fluid-filled network structure, which pervades our bones and accommodates a cell network of osteocytes. For the mechanism of mechanosensation, it was hypothesized that load-induced fluid flow results in forces that can be sensed by the cells. We use a controlled in vivo loading experiment on murine tibiae to test this hypothesis, whereby the mechanoresponse was quantified experimentally by in vivo micro-computed tomography (µCT) in terms of formed and resorbed bone volume. By imaging the LCN using confocal microscopy in bone volumes covering the entire cross-section of mouse tibiae and by calculating the fluid flow in the three-dimensional (3D) network, we could perform a direct comparison between predictions based on fluid flow velocity and the experimentally measured mechanoresponse. While local strain distributions estimated by finite-element analysis incorrectly predicts preferred bone formation on the periosteal surface, we demonstrate that additional consideration of the LCN architecture not only corrects this erroneous bias in the prediction but also explains observed differences in the mechanosensitivity between the three investigated mice. We also identified the presence of vascular channels as an important mechanism to locally reduce fluid flow. Flow velocities increased for a convergent network structure where all of the flow is channeled into fewer canaliculi. We conclude that, besides mechanical loading, LCN architecture should be considered as a key determinant of bone adaptation.

Experimental investigation of the effect of surface roughness on bone-cement-implant shear bond strength.

Debonding of cemented bone implants is regarded as a major contributor to complications. The relationship between shear bond strength and surface roughness has been investigated, however there are inconsistencies in the trends reported in different studies. The shear strength between poly(methyl methacrylate) bone-cement and sand blasted cobalt-chromium and titanium alloy surfaces was measured to investigate the relationship between interfacial shear strength and surface topology. Surface roughness was quantified by a power law relationship fitted to Fourier spectra as well as three traditional parameters (arithmetical average roughness (Ra), volume of interdigitation (Rr), and RMS slope (Rdq)). We found that the interfacial shear strength is directly proportional to the exponent of the surfaces power spectra (P2) and Rdq, but not to Ra and Rr. However, Rdq is shown to be critically dependent on sampling frequency, making it sensitive to measurement settings. P2 was found to be a robust measure of the surface roughness being independent of sampling frequency.