Image-based vs. mesh-based statistical appearance models of the human femur: Implications for finite element simulations.

Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.

Refinement of tourniquet-induced peripheral ischemia/reperfusion injury in rats: comparison of 2 h vs 24 h reperfusion.

Prolonged ischemia of skeletal muscle tissue, followed by reperfusion, leads to ischemia/reperfusion injury (IRI), which is a feared local and systemic inflammatory reaction. With respect to the 3Rs, we wanted to determine which parameters for assessment of IRI require a reperfusion time of 24 h and for which 2 h of reperfusion are sufficient. Rats were subjected to 3 h of hind limb ischemia and 2 h or 24 h of reperfusion. Human plasma derived C1 inhibitor was used as a drug to prevent reperfusion injury. For 2 h of reperfusion the rats stayed under anesthesia throughout (severity grade 1), whereas for 24 h they were awake under analgesia during reperfusion (grade 2). The femoral artery was clamped and a tourniquet was placed, under maintenance of venous return. C1 esterase inhibitor was systemically administered 5 min before the induction of ischemia. No differences in local muscle edema formation and depositions of immunoglobulin G and immunoglobulin M were observed between 2 h and 24 h (P > 0.05), whereas lung edema was only observed after 24 h. Muscle viability was significantly lower after 24 h vs 2 h reperfusion (P < 0.05). Increased plasma creatine kinase (CK)-MM and platelet-derived growth factor (PDGF)-bb could be detected after 2 h, but not after 24 h of reperfusion. By contrast, depositions of C3b/c and fibrin in muscle were only detected after 24 h (P < 0.001). In conclusion, for a first screening of drug candidates to reduce IRI, 2 h reperfusions are sufficient, and these reduce the severity of the animal experiment. Twenty-four-hour reperfusions are only needed for in-depth analysis of the mechanisms of IRI, including lung damage.

Refinement of experimental design and conduct in laboratory animal research.

The scientific literature of laboratory animal research is replete with papers reporting poor reproducibility of results as well as failure to translate results to clinical trials in humans. This may stem in part from poor experimental design and conduct of animal experiments. Despite widespread recognition of these problems and implementation of guidelines to attenuate them, a review of the literature suggests that experimental design and conduct of laboratory animal research are still in need of refinement. This paper will review and discuss possible sources of biases, highlight advantages and limitations of strategies proposed to alleviate them, and provide a conceptual framework for improving the reproducibility of laboratory animal research.

Self-adaptive grids for noise mapping refinement

Noise maps are usually represented as contour or isolines maps describing the sound levels in a region. Using this kind of representation the user can easily find the noise level assigned to every location in the map. But the acoustic calculations behind the map are not performed for every single location on it; they are only performed in a grid of receivers. The results in this calculation grid are interpolated to draw the isolines or contours. Therefore, the resolution of the calculation grid and the way it was created (rectangular, triangulated, random…) have an effect on the resulting map. In this paper we describe a smart iterative procedure to optimize the quality of the map at a really low additional computational cost, using self-adaptive grids for the acoustic calculations. These self-adaptive grids add new receivers to the sampling grid in those locations where they are expected to be more useful, so that the performance at the output of the interpolator is enhanced. Self-adaptive sampling grids can be used for minimizing the overall error of the map (improving its quality), or for reducing calculation times, and can be also applied selectively to target areas or contour lines. This can be done by the user customizing the maximum number of iterations, the number of new receivers for each iteration, the target isolines, the target quality…