8,704 research outputs found
Classical and all-floating FETI methods for the simulation of arterial tissues
High-resolution and anatomically realistic computer models of biological soft
tissues play a significant role in the understanding of the function of
cardiovascular components in health and disease. However, the computational
effort to handle fine grids to resolve the geometries as well as sophisticated
tissue models is very challenging. One possibility to derive a strongly
scalable parallel solution algorithm is to consider finite element tearing and
interconnecting (FETI) methods. In this study we propose and investigate the
application of FETI methods to simulate the elastic behavior of biological soft
tissues. As one particular example we choose the artery which is - as most
other biological tissues - characterized by anisotropic and nonlinear material
properties. We compare two specific approaches of FETI methods, classical and
all-floating, and investigate the numerical behavior of different
preconditioning techniques. In comparison to classical FETI, the all-floating
approach has not only advantages concerning the implementation but in many
cases also concerning the convergence of the global iterative solution method.
This behavior is illustrated with numerical examples. We present results of
linear elastic simulations to show convergence rates, as expected from the
theory, and results from the more sophisticated nonlinear case where we apply a
well-known anisotropic model to the realistic geometry of an artery. Although
the FETI methods have a great applicability on artery simulations we will also
discuss some limitations concerning the dependence on material parameters.Comment: 29 page
A 3D discrete model of the diaphragm and human trunk
In this paper, a 3D discrete model is presented to model the movements of the
trunk during breathing. In this model, objects are represented by physical
particles on their contours. A simple notion of force generated by a linear
actuator allows the model to create forces on each particle by way of a
geometrical attractor. Tissue elasticity and contractility are modeled by local
shape memory and muscular fibers attractors. A specific dynamic MRI study was
used to build a simple trunk model comprised of by three compartments: lungs,
diaphragm and abdomen. This model was registered on the real geometry.
Simulation results were compared qualitatively as well as quantitatively to the
experimental data, in terms of volume and geometry. A good correlation was
obtained between the model and the real data. Thanks to this model, pathology
such as hemidiaphragm paralysis can also be simulated.Comment: published in: "Lung Modelling", France (2006
In vivo measurement of human brain elasticity using a light aspiration device
The brain deformation that occurs during neurosurgery is a serious issue
impacting the patient "safety" as well as the invasiveness of the brain
surgery. Model-driven compensation is a realistic and efficient solution to
solve this problem. However, a vital issue is the lack of reliable and easily
obtainable patient-specific mechanical characteristics of the brain which,
according to clinicians' experience, can vary considerably. We designed an
aspiration device that is able to meet the very rigorous sterilization and
handling process imposed during surgery, and especially neurosurgery. The
device, which has no electronic component, is simple, light and can be
considered as an ancillary instrument. The deformation of the aspirated tissue
is imaged via a mirror using an external camera. This paper describes the
experimental setup as well as its use during a specific neurosurgery. The
experimental data was used to calibrate a continuous model. We show that we
were able to extract an in vivo constitutive law of the brain elasticity: thus
for the first time, measurements are carried out per-operatively on the
patient, just before the resection of the brain parenchyma. This paper
discloses the results of a difficult experiment and provide for the first time
in-vivo data on human brain elasticity. The results point out the softness as
well as the highly non-linear behavior of the brain tissue.Comment: Medical Image Analysis (2009) accept\'
Virtual reality surgery simulation: A survey on patient specific solution
For surgeons, the precise anatomy structure and its dynamics are important in the surgery interaction, which is critical for generating the immersive experience in VR based surgical training applications. Presently, a normal therapeutic scheme might not be able to be straightforwardly applied to a specific patient, because the diagnostic results are based on averages, which result in a rough solution. Patient Specific Modeling (PSM), using patient-specific medical image data (e.g. CT, MRI, or Ultrasound), could deliver a computational anatomical model. It provides the potential for surgeons to practice the operation procedures for a particular patient, which will improve the accuracy of diagnosis and treatment, thus enhance the prophetic ability of VR simulation framework and raise the patient care. This paper presents a general review based on existing literature of patient specific surgical simulation on data acquisition, medical image segmentation, computational mesh generation, and soft tissue real time simulation
Realistic tool-tissue interaction models for surgical simulation and planning
Surgical simulators present a safe and potentially effective method for surgical training, and can also be used in pre- and intra-operative surgical planning. Realistic modeling of medical interventions involving tool-tissue interactions has been considered to be a key requirement in the development of high-fidelity simulators and planners. The soft-tissue constitutive laws, organ geometry and boundary conditions imposed by the connective tissues surrounding the organ, and the shape of the surgical tool interacting with the organ are some of the factors that govern the accuracy of medical intervention planning.\ud
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This thesis is divided into three parts. First, we compare the accuracy of linear and nonlinear constitutive laws for tissue. An important consequence of nonlinear models is the Poynting effect, in which shearing of tissue results in normal force; this effect is not seen in a linear elastic model. The magnitude of the normal force for myocardial tissue is shown to be larger than the human contact force discrimination threshold. Further, in order to investigate and quantify the role of the Poynting effect on material discrimination, we perform a multidimensional scaling study. Second, we consider the effects of organ geometry and boundary constraints in needle path planning. Using medical images and tissue mechanical properties, we develop a model of the prostate and surrounding organs. We show that, for needle procedures such as biopsy or brachytherapy, organ geometry and boundary constraints have more impact on target motion than tissue material parameters. Finally, we investigate the effects surgical tool shape on the accuracy of medical intervention planning. We consider the specific case of robotic needle steering, in which asymmetry of a bevel-tip needle results in the needle naturally bending when it is inserted into soft tissue. We present an analytical and finite element (FE) model for the loads developed at the bevel tip during needle-tissue interaction. The analytical model explains trends observed in the experiments. We incorporated physical parameters (rupture toughness and nonlinear material elasticity) into the FE model that included both contact and cohesive zone models to simulate tissue cleavage. The model shows that the tip forces are sensitive to the rupture toughness. In order to model the mechanics of deflection of the needle, we use an energy-based formulation that incorporates tissue-specific parameters such as rupture toughness, nonlinear material elasticity, and interaction stiffness, and needle geometric and material properties. Simulation results follow similar trends (deflection and radius of curvature) to those observed in macroscopic experimental studies of a robot-driven needle interacting with gels
Modelling mitral valvular dynamics–current trend and future directions
Dysfunction of mitral valve causes morbidity and premature mortality and remains a leading medical problem worldwide. Computational modelling aims to understand the biomechanics of human mitral valve and could lead to the development of new treatment, prevention and diagnosis of mitral valve diseases. Compared with the aortic valve, the mitral valve has been much less studied owing to its highly complex structure and strong interaction with the blood flow and the ventricles. However, the interest in mitral valve modelling is growing, and the sophistication level is increasing with the advanced development of computational technology and imaging tools. This review summarises the state-of-the-art modelling of the mitral valve, including static and dynamics models, models with fluid-structure interaction, and models with the left ventricle interaction. Challenges and future directions are also discussed
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