In this work, a fluid-solid interaction (FSI) analysis of a healthy and a stenotic human trachea was studied to evaluate flow patterns, wall stresses, and deformations under physiological and pathological conditions. The two analyzed tracheal geometries, which include the first bifurcation after the carina, were obtained from computed tomography images of healthy and diseased patients, respectively. A finite element-based commercial software code was used to perform the simulations. The tracheal wall was modeled as a fiber reinforced hyperelastic solid material in which the anisotropy due to the orientation of the fibers was introduced. Impedance-based pressure waveforms were computed using a method developed for the cardiovascular system, where the resistance of the respiratory system was calculated taking into account the entire bronchial tree, modeled as binary fractal network. Intratracheal flow patterns and tracheal wall deformation were analyzed under different scenarios. The simulations show the possibility of predicting, with FSI computations, flow and wall behavior for healthy and pathological tracheas. The computational modeling procedure presented herein can be a useful tool capable of evaluating quantities that cannot be assessed in vivo, such as wall stresses, pressure drop, and flow patterns, and to derive parameters that could help clinical decisions and improve surgical outcomes.

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The aim of this work is to present a methodology to model the passive mechanical behavior of the human abdomen during physiological movements. From a mechanical point of view, it is possible to predict where hernia formation is likely to occur since the areas that support higher stresses can be identified as the most vulnerable ones. For this purpose, a realistic geometry of the human abdomen is obtained from magnetic resonance imaging. The model defines different anatomical structures of the abdomen, including muscles and aponeuroses, and anisotropic mechanical properties are assigned. The finite element model obtained from the geometric human model, which includes initial strains, is used to simulate the anisotropic passive behavior of the healthy human abdomen under intra-abdominal pressure. This study demonstrates that the stiffest structures, namely aponeuroses and particularly the linea alba, are the structures that perform the most work in the abdomen. Thus, the linea alba is the most important unit contributing to the mechanical stability of the abdominal wall.

In this study, we develop structured tree outflow boundary conditions for modelling the human carotid haemodynamics. The model geometry was reconstructed through computerised tomography scan. Unsteady-state computational fluid dynamic analyses were performed under different conditions using a commercial software package ADINA R&D, Inc., (Watertown, MA, USA) in order to assess the impact of the boundary conditions on the flow variables. In particular, the results showed that the peripheral vessels massively impact the pressure while the flow is relatively unaffected. As an example of application of these outflow conditions, an unsteady fluid-structure interaction (FSI) simulation was carried out and the dependence of the wall shear stress (WSS) on the arterial wall compliance in the carotid bifurcation was studied. In particular, a comparison between FSI and rigid-wall models was conducted. Results showed that the WSS distributions were substantially affected by the diameter variation of the arterial wall. In particular, even similar WSS distributions were found for both cases, and differences in the computed WSS values were also found.

Solving the electric activity of the heart posses a big challenge, not only because of the structural complexities inherent to the heart tissue, but also because of the complex electric behaviour of the cardiac cells. The multiscale nature of the electrophysiology problem makes difficult its numerical solution, requiring temporal and spatial resolutions of 0.1 ms and 0.2 mm respectively for accurate simulations, leading to models with millions degrees of freedom that need to be solved for thousand time steps. Solution of this problem requires the use of algorithms with higher level of parallelism in multi-core platforms. In this regard the newer programmable graphic processing units (GPU) has become a valid alternative due to their tremendous computational horsepower. This paper presents results obtained with a novel electrophysiology simulation software entirely developed in Compute Unified Device Architecture (CUDA). The software implements fully explicit and semi-implicit solvers for the monodomain model, using operator splitting. Performance is compared with classical multi-core MPI based solvers operating on dedicated high-performance computer clusters. Results obtained with the GPU based solver show enormous potential for this technology with accelerations over 50× for three-dimensional problems.

Nowadays, interventions associated with the implantation of tracheal prostheses in patients with airway pathologies are very common. This surgery may promote problems such as migration of the prosthesis, development of granulation tissue at the edges of the stent with overgrowth of the tracheal lumen or accumulation of secretions inside the prosthesis. Among the movements that the trachea carries out, swallowing seems to have harmful consequences for the tracheal tissues surrounding the prosthesis. In this work, a finite-element-based tool is presented to construct patient-specific tracheal models, introducing the endotracheal prosthesis and analysing the mechanical consequences of this surgery during swallowing. A complete description of a patient-specific tracheal model is given, and a fully experimental characterization of the tracheal tissues is presented. To construct patient-specific grids, a mesh adaptation algorithm has been developed and the implantation of a tracheal prosthesis is simulated. The ascending deglutition movement of the trachea is recorded using real data from each specific patient from fluoroscopic images before and after implantation. The overall behaviour of the trachea is modified when a prosthesis is introduced. The presented tool has been particularized for two different patients (patient A and patient B), allowing prediction of the consequences of this kind of surgery. In particular, patient A had a decrease of almost 30 per cent in his ability to swallow, and an increase in stresses that were three times higher after prosthesis implantation. In contrast, patient B, who had a shorter trachea and who seemed to undergo more damaging effects, did not have a significant reduction in his ability to swallow and did not present an increase in stress in the tissues. In both cases, there are clinical studies that validate our results: namely, patient A underwent a further intervention whereas the outcome of patient B's * Author for correspondence (amaya@unizar.es). surgery was completely successful. Notwithstanding the fact that there are a lot of uncertainties relating to the implantation of endotracheal prostheses, the present work gives a new insight into these procedures, predicting their mechanical consequences. This tool could be used in the future as pre-operative planning software to help thoracic surgeons in deciding the optimal prosthesis as well as its size and positioning.

In this work a pancreatic surgery simulator is developed that provides the user with haptic feedback. The simulator is based on the use of model order reduction techniques, particularly Proper Generalized Decomposition methods. The just developed simulator presents some notable advancements with respect to existing works in the literature, such as the consideration of non-linear hyperelasticity for the constitutive modeling of soft tissues, an accurate description of contact between organs and momentum and energy conserving time integration schemes. Pancreas, liver, gall bladder, and duodenum are modeled in the simulator, thus providing with a very realistic and immersive perception to the user.

Image-processing pipelines require the design of complex workflows combining many different steps that bring the raw acquired data to a final result with biological meaning. In the image-processing domain of cryo-electron microscopy single-particle analysis (cryo-EM SPA), hundreds of steps must be performed to obtain the three-dimensional structure of a biological macromolecule by integrating data spread over thousands of micrographs containing millions of copies of allegedly the same macromolecule. The execution of such complicated workflows demands a specific tool to keep track of all these steps performed. Additionally, due to the extremely low signal-to-noise ratio (SNR), the estimation of any image parameter is heavily affected by noise resulting in a significant fraction of incorrect estimates. Although low SNR and processing millions of images by hundreds of sequential steps requiring substantial computational resources are specific to cryo-EM, these characteristics may be shared by other biological imaging domains. Here, we present Scipion, a Python generic open-source workflow engine specifically adapted for image processing. Its main characteristics are: (a) interoperability, (b) smart object model, (c) gluing operations, (d) comparison operations, (e) wide set of domain-specific operations, (f) execution in streaming, (g) smooth integration in high-performance computing environments, (h) execution with and without graphical capabilities, (i) flexible visualization, (j) user authentication and private access to private data, (k) scripting capabilities, (l) high performance, (m) traceability, (n) reproducibility, (o) self-reporting, (p) reusability, (q) extensibility, (r) software updates, and (s) non-restrictive software licensing.