Treatment of large distal extremity skin wounds with autogenous full-thickness mesh skin grafts in 5 cats

Five cats with large, distal extremity abrasion wounds were treated with an autogenous, full-thickness, mesh skin graft. Survival of the mesh grafts in all five cats was considered between 90 and 100%. Successful grafting requires asepsis, an adequately prepared recipient bed consisting of healthy granulation tissue, proper harvesting and preparation of the graft, meticulous surgical technique and strict postoperative care. Factors that are essential for the survival of skin grafts include good contact between the graft and the recipient bed, normal tension on the sutured graft, strict immobilization after grafting and prevention of accumulation of blood or serum under the graft. Meshing the graft provides more graft flexibility over uneven surfaces and allows adequate drainage. In contrast to previous proposals, the authors recommend no bandage change before the fourth day after grafting. Full-thickness mesh skin grafting can be used to successfully treat large distal skin wounds in cats.

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.

Comparison of Mesh Adaptation Using the Adjoint Methodology and Truncation Error Estimates

Mesh adaptation based on error estimation has become a key technique to improve th eaccuracy o fcomputational-fluid-dynamics computations. The adjoint-based approach for error estimation is one of the most promising techniques for computational-fluid-dynamics applications. Nevertheless, the level of implementation of this technique in the aeronautical industrial environment is still low because it is a computationally expensive method. In the present investigation, a new mesh refinement method based on estimation of truncation error is presented in the context of finite-volume discretization. The estimation method uses auxiliary coarser meshes to estimate the local truncation error, which can be used for driving an adaptation algorithm. The method is demonstrated in the context of two-dimensional NACA0012 and three-dimensional ONERA M6 wing inviscid flows, and the results are compared against the adjoint-based approach and physical sensors based on features of the flow field.