Influence of Smoothing on Voxel-Based Mesh Accuracy in Micro-Finite Element

The interest in automatic volume meshing for finite element analysis (FEA) has grown more since the appearance of microfocus CT (μCT), due to its high resolution, which allows for the assessment of mechanical behaviour at a high precision. Nevertheless, the basic meshing approach of generating one hexahedron per voxel produces jagged edges. To prevent this effect, smoothing algorithms have been introduced to enhance the topology of the mesh. However, whether smoothing also improves the accuracy of voxel-based meshes in clinical applications is still under question. There is a trade-off between smoothing and quality of elements in the mesh. Distorted elements may be produced by excessive smoothing and reduce accuracy of the mesh. In the present work, influence of smoothing on the accuracy of voxel-based meshes in micro-FE was assessed. An accurate 3D model of a trabecular structure with known apparent mechanical properties was used as a reference model. Virtual CT scans of this reference model (with resolutions of 16, 32 and 64 μm) were then created and used to build voxel-based meshes of the microarchitecture. Effects of smoothing on the apparent mechanical properties of the voxel-based meshes as compared to the reference model were evaluated. Apparent Young’s moduli of the smooth voxel-based mesh were significantly closer to those of the reference model for the 16 and 32 μm resolutions. Improvements were not significant for the 64 μm, due to loss of trabecular connectivity in the model. This study shows that smoothing offers a real benefit to voxel-based meshes used in micro-FE. It might also broaden voxel-based meshing to other biomechanical domains where it was not used previously due to lack of accuracy. As an example, this work will be used in the framework of the European project ContraCancrum, which aims at providing a patient-specific simulation of tumour development in brain and lungs for oncologists. For this type of clinical application, such a fast, automatic, and accurate generation of the mesh is of great benefit.

Catheter ablation of atrial fibrillation as first-line therapy--a single-centre experience

The aims of the study were (i) to assess the characteristics of patients selected for atrial fibrillation (AF) ablation as first-line therapy, (ii) to identify current clinical criteria for such a strategy, and (iii) to analyse the outcome compared with patients who had failure of antiarrhythmic drug (AAD) therapy prior to ablation.

Molecular characterization of five porcine candidate genes for drip loss in pork

Drip loss is the loss of fluid from a piece of meat without mechanical force and represents an important meat quality trait. Previous work revealed a quantitative trait locus (QTL) for drip loss in pork in an experimental Duroc x Pietrain (DUPI) F2 family on SSC 5. Based on functional data indicating their possible involvement in water holding capacity and their expression in skeletal muscle, we selected five positional candidates (ACO2, ADSL, CBY1, KCNJ4, PLA2AG6) out of 130 predicted genes in the QTL interval for further analysis. We performed a mutation analysis of all coding exons and discovered 204 polymorphisms. We genotyped 39 single nucleotide polymorphisms (SNPs) in 192 Pietrain pigs with extreme drip loss phenotypes and detected a possible association with drip loss for one non-coding SNP in the ADSL gene (ss107793818, p(raw) = 0.021). Correspondingly, ADSL diplotypes were associated with drip loss and pH1 of M. longissimus dorsi. However, after correction for multiple testing, none of the tested SNPs were significantly associated with drip loss. One possible explanation for these results is that one of the QTL-alleles from the experimental DUPI family may be fixed or nearly fixed in the tested Pietrain population.

Long-term outcome of ablative therapy of post-operative atrial tachyarrhythmias in patients with tetralogy of Fallot: a European multi-centre study

Post-operative atrial tachyarrhythmias (AT) in patients with tetralogy of Fallot (ToF) are associated with congestive heart failure, stroke, and cardiac death. Effective treatment is therefore essential. The aim of the study is to evaluate long-term outcome of ablative therapy of AT in ToF patients and to study characteristics of AT recurrences.

The canine neuronal ceroid-lipofuscinosis: a review.

The present article gives a survey over the current scientific knowledge of the canine neuronal ceroid-lipofuscinosis (NCL). NCL is a heterogenous group of lysosomal storage diseases in humans and animals. In consequence of a gene mutation, there is an accumulation of ceroid-lipofuscin in neurons, cells of the retina and the skin and other cells. The stored ceroid-lipofuscin in neurons leads to an impaired cell function and subsequently to cell death. Recently, the underlying genetic defect was discovered in several dog breeds. Genetic testing permits an ante mortem diagnosis of the disease, which up to now was only possible with a positive biopsy result. Another advantage is the identification of carrier animals to eliminate the deleterious alleles.

Fast Prediction of Femoral Biomechanics Using Supervised Machine Learning and Statistical Shape Modeling

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.