- MeSH
- Air Bags trends MeSH
- Models, Anatomic MeSH
- Abdomen anatomy & histology MeSH
- Research Support as Topic MeSH
- Publication type
- Conference Proceedings MeSH
- MeSH
- Chick Embryo MeSH
- Models, Neurological MeSH
- Arthritis, Rheumatoid etiology MeSH
- Bone Diseases, Developmental physiopathology MeSH
- Animals MeSH
- Check Tag
- Chick Embryo MeSH
- Animals MeSH
- Publication type
- Review MeSH
- MeSH
- Aorta MeSH
- Biomechanical Phenomena MeSH
- Blood Vessels physiology MeSH
- Research Support as Topic MeSH
- Humans MeSH
- Linear Models MeSH
- Nonlinear Dynamics MeSH
- Elasticity MeSH
- Viscosity MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Review MeSH
- Comparative Study MeSH
A three-dimensional finite element model of a vascular smooth muscle cell is based on models published recently; it comprehends elements representing cell membrane, cytoplasm and nucleus, and a complex tensegrity structure representing the cytoskeleton. In contrast to previous models of eucaryotic cells, this tensegrity structure consists of several parts. Its external and internal parts number 30 struts, 60 cables each, and their nodes are interconnected by 30 radial members; these parts represent cortical, nuclear and deep cytoskeletons, respectively. This arrangement enables us to simulate load transmission from the extracellular space to the nucleus or centrosome via membrane receptors (focal adhesions); the ability of the model was tested by simulation of some mechanical tests with isolated vascular smooth muscle cells. Although material properties of components defined on the basis of the mechanical tests are ambiguous, modelling of different types of tests has shown the ability of the model to simulate substantial global features of cell behaviour, e.g. "action at a distance effect" or the global load-deformation response of the cell under various types of loading. Based on computational simulations, the authors offer a hypothesis explaining the scatter of experimental results of indentation tests.
- MeSH
- Finite Element Analysis MeSH
- Models, Biological MeSH
- Mechanotransduction, Cellular physiology MeSH
- Cytoskeleton MeSH
- Humans MeSH
- Stress, Mechanical MeSH
- Myocytes, Smooth Muscle chemistry cytology physiology MeSH
- Computer Simulation MeSH
- Muscle, Smooth, Vascular chemistry cytology physiology MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
In image-guided percutaneous interventions, a precise planning of the needle path is a key factor to a successful intervention. In this paper we propose a novel method for computing a patient-specific optimal path for such interventions, accounting for both the deformation of the needle and soft tissues due to the insertion of the needle in the body. To achieve this objective, we propose an optimization method for estimating preoperatively a curved trajectory allowing to reach a target even in the case of tissue motion and needle bending. Needle insertions are simulated and regarded as evaluations of the objective function by the iterative planning process. In order to test the planning algorithm, it is coupled with a fast needle insertion simulation involving a flexible needle model and soft tissue finite element modeling, and experimented on the use-case of thermal ablation of liver tumors. Our algorithm has been successfully tested on twelve datasets of patient-specific geometries. Fast convergence to the actual optimal solution has been shown. This method is designed to be adapted to a wide range of percutaneous interventions.
- MeSH
- Ablation Techniques MeSH
- Algorithms * MeSH
- Models, Anatomic * MeSH
- Surgery, Computer-Assisted methods MeSH
- Liver physiopathology surgery MeSH
- Humans MeSH
- Liver Neoplasms surgery MeSH
- Computer Simulation * MeSH
- Preoperative Period * MeSH
- User-Computer Interface MeSH
- Imaging, Three-Dimensional MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Image registration methods play a crucial role in computational neuroanatomy. This paper mainly contributes to the field of image registration with the use of nonlinear spatial transformations. Particularly, problems connected to matching magnetic resonance imaging (MRI) brain image data obtained from various subjects and with various imaging conditions are solved here. Registration is driven by local forces derived from multimodal point similarity measures which are estimated with the use of joint intensity histogram and tissue probability maps. A spatial deformation model imitating principles of continuum mechanics is used. Five similarity measures are tested in an experiment with image data obtained from the Simulated Brain Database and a quantitative evaluation of the algorithm is presented. Results of application of the method in automated spatial detection of anatomical abnormalities in first-episode schizophrenia are presented.
- MeSH
- Algorithms MeSH
- Financing, Organized MeSH
- Image Interpretation, Computer-Assisted methods MeSH
- Humans MeSH
- Magnetic Resonance Imaging methods MeSH
- Models, Neurological MeSH
- Brain anatomy & histology physiology MeSH
- Neuroanatomy methods MeSH
- Neurology methods MeSH
- Computer Simulation MeSH
- Elasticity MeSH
- Psychiatry methods MeSH
- Reproducibility of Results MeSH
- Pattern Recognition, Automated methods MeSH
- Sensitivity and Specificity MeSH
- Subtraction Technique MeSH
- Artificial Intelligence MeSH
- Image Enhancement methods MeSH
- Imaging, Three-Dimensional methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Evaluation Study MeSH
IMA volumes in mathematics and its applications ; vol. 121
1st ed. x, 317 s., obr.
A novel biofilm model is described which systemically couples bacteria, extracellular polymeric substances (EPS) and solvent phases in biofilm. This enables the study of contributions of rheology of individual phases to deformation of biofilm in response to fluid flow as well as interactions between different phases. The model, which is based on first and second laws of thermodynamics, is derived using an energetic variational approach and phase-field method. Phase-field coupling is used to model structural changes of a biofilm. A newly developed unconditionally energy-stable numerical splitting scheme is implemented for computing the numerical solution of the model efficiently. Model simulations predict biofilm cohesive failure for the flow velocity between [Formula: see text] and [Formula: see text] m s(-1) which is consistent with experiments. Simulations predict biofilm deformation resulting in the formation of streamers for EPS exhibiting a viscous-dominated mechanical response and the viscosity of EPS being less than [Formula: see text]. Higher EPS viscosity provides biofilm with greater resistance to deformation and to removal by the flow. Moreover, simulations show that higher EPS elasticity yields the formation of streamers with complex geometries that are more prone to detachment. These model predictions are shown to be in qualitative agreement with experimental observations.
- MeSH
- Bacteria cytology MeSH
- Bacterial Adhesion physiology MeSH
- Polysaccharides, Bacterial metabolism MeSH
- Biofilms growth & development MeSH
- Models, Biological * MeSH
- Bacterial Physiological Phenomena MeSH
- Stress, Mechanical MeSH
- Microfluidics methods MeSH
- Elastic Modulus physiology MeSH
- Shear Strength physiology MeSH
- Computer Simulation MeSH
- Cell Size MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH