Compressive strength of interbody cages in the lumbar spine: the effect of cage shape, posterior instrumentation and bone density

One goal of interbody fusion is to increase the height of the degenerated disc space. Interbody cages in particular have been promoted with the claim that they can maintain the disc space better than other methods. There are many factors that can affect the disc height maintenance, including graft or cage design, the quality of the surrounding bone and the presence of supplementary posterior fixation. The present study is an in vitro biomechanical investigation of the compressive behaviour of three different interbody cage designs in a human cadaveric model. The effect of bone density and posterior instrumentation were assessed. Thirty-six lumbar functional spinal units were instrumented with one of three interbody cages: (1) a porous titanium implant with endplate fit (Stratec), (2) a porous, rectangular carbon-fibre implant (Brantigan) and (3) a porous, cylindrical threaded implant (Ray). Posterior instrumentation (USS) was applied to half of the specimens. All specimens were subjected to axial compression displacement until failure. Correlations between both the failure load and the load at 3 mm displacement with the bone density measurements were observed. Neither the cage design nor the presence of posterior instrumentation had a significant effect on the failure load. The loads at 3 mm were slightly less for the Stratec cage, implying lower axial stiffness, but were not different with posterior instrumentation. The large range of observed failure loads overlaps the potential in vivo compressive loads, implying that failure of the bone-implant interface may occur clinically. Preoperative measurements of bone density may be an effective tool to predict settling around interbody cages.

Cell shape-dependent early responses of fibroblasts to cyclic strain

Randomly spread fibroblasts on fibronectin-coated elastomeric membranes respond to cyclic strain by a varying degree of focal adhesion assembly and actin reorganization. We speculated that the individual shape of the cells, which is linked to cytoskeletal structure and pre-stress, might tune these integrin-dependent mechanotransduction events. To this aim, fibronectin circles, squares and rectangles of identical surface area (2000μm(2)) were micro-contact printed onto elastomeric substrates. Fibroblasts plated on these patterns occupied the corresponding shapes. Cyclic 10% equibiaxial strain was applied to patterned cells for 30min, and changes in cytoskeleton and cell-matrix adhesions were quantified after fluorescence staining. After strain, megakaryocytic leukemia-1 protein translocated to the nucleus in most cells, indicating efficient RhoA activation independently of cell shape. However, circular and square cells (with radial symmetry) showed a significantly greater increase in the number of actin stress fibers and vinculin-positive focal adhesions after cyclic strain than rectangular (bipolar) cells of identical size. Conversely, cyclic strain induced larger changes in pY397-FAK positive focal complexes and zyxin relocation from focal adhesions to stress fibers in bipolar compared to symmetric cells. Thus, radially symmetric cells responded to cyclic strain with a larger increase in assembly, whereas bipolar cells reacted with more pronounced reorganization of actin stress fibers and matrix contacts. We conclude that integrin-mediated responses to external mechanical strain are differentially modulated in cells that have the same spreading area but different geometries, and do not only depend on mere cell size.

Multiscale methods for shape constraints in deconvolution: Confidence statements for qualitative features

We derive multiscale statistics for deconvolution in order to detect qualitative features of the unknown density. An important example covered within this framework is to test for local monotonicity on all scales simultaneously. We investigate the moderately ill-posed setting, where the Fourier transform of the error density in the deconvolution model is of polynomial decay. For multiscale testing, we consider a calibration, motivated by the modulus of continuity of Brownian motion. We investigate the performance of our results from both the theoretical and simulation based point of view. A major consequence of our work is that the detection of qualitative features of a density in a deconvolution problem is a doable task, although the minimax rates for pointwise estimation are very slow.

The influence of yield surface shape and damage in the depth-dependent response of bone tissue to nanoindentation using spherical and Berkovich indenters

Prevention and treatment of osteoporosis rely on understanding of the micromechanical behaviour of bone and its influence on fracture toughness and cell-mediated adaptation processes. Postyield properties may be assessed by nonlinear finite element simulations of nanoindentation using elastoplastic and damage models. This computational study aims at determining the influence of yield surface shape and damage on the depth-dependent response of bone to nanoindentation using spherical and conical tips. Yield surface shape and damage were shown to have a major impact on the indentation curves. Their influence on indentation modulus, hardness, their ratio as well as the elastic-to-total work ratio is well described by multilinear regressions for both tip shapes. For conical tips, indentation depth was not statistically significant (p<0.0001). For spherical tips, damage was not a significant parameter (p<0.0001). The gained knowledge can be used for developing an inverse method for identification of postelastic properties of bone from nanoindentation.

Comparison of partial least squares regression and principal component regression for pelvic shape prediction.

This paper studied two different regression techniques for pelvic shape prediction, i.e., the partial least square regression (PLSR) and the principal component regression (PCR). Three different predictors such as surface landmarks, morphological parameters, or surface models of neighboring structures were used in a cross-validation study to predict the pelvic shape. Results obtained from applying these two different regression techniques were compared to the population mean model. In almost all the prediction experiments, both regression techniques unanimously generated better results than the population mean model, while the difference on prediction accuracy between these two regression methods is not statistically significant (α=0.01).

Expectation Conditional Maximization-Based Deformable Shape Registration

This paper addresses the issue of matching statistical and non-rigid shapes, and introduces an Expectation Conditional Maximization-based deformable shape registration (ECM-DSR) algorithm. Similar to previous works, we cast the statistical and non-rigid shape registration problem into a missing data framework and handle the unknown correspondences with Gaussian Mixture Models (GMM). The registration problem is then solved by fitting the GMM centroids to the data. But unlike previous works where equal isotropic covariances are used, our new algorithm uses heteroscedastic covariances whose values are iteratively estimated from the data. A previously introduced virtual observation concept is adopted here to simplify the estimation of the registration parameters. Based on this concept, we derive closed-form solutions to estimate parameters for statistical or non-rigid shape registrations in each iteration. Our experiments conducted on synthesized and real data demonstrate that the ECM-DSR algorithm has various advantages over existing algorithms.

Fully Automatic Segmentation of AP Pelvis X-rays via Random Forest Regression and Hierarchical Sparse Shape Composition

Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.

How Welfare States Shape the Democratic Public: Policy Feedback, Participation, Voting and Attitudes

This crucial volume significantly advances the study of policy feedbacks. With contributions from many subfields and methodological approaches, it offers both sophisticated theorizing and new empirical examples that show how policies make politics in a variety of ways. Innovative research designs provide more convincing inference than ever. And the normative questions engaged about welfare performance, evaluation, participation, and accountability could not be more important or timely in this era of austerity and discord over the future of welfare states.’