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Arterial hypertension, defined as an increase in systemic arterial pressure, is a major risk factor for the development of diseases affecting the cardiovascular system. Every year, 9.4 million deaths worldwide are caused by complications arising from hypertension. Despite well‐established approaches to diagnosis and treatment, fewer than half of all hypertensive patients have adequately controlled blood pressure. In this scenario, computational models of hypertension can be a practical approach for better quantifying the role played by different components of the cardiovascular system in the determination of this condition. In the present work we adopt a global closed‐loop multi‐scale mathematical model for the entire human circulation to reproduce a hypertensive scenario. In particular, we modify the model to reproduce alterations in the cardiovascular system that are cause and/or consequence of the hypertensive state. The adaptation does not only affect large systemic arteries and the heart but also the microcirculation, the pulmonary circulation and the venous system. Model outputs for the hypertensive scenario are validated through assessment of computational results against current knowledge on the impact of hypertension on the cardiovascular system. [ABSTRACT FROM AUTHOR]

Introduction: Pulmonary fibrosis is a destructive, progressive disease that dramatically reduces life quality of patients, ultimately leading to death. Therapeutic regimens for pulmonary fibrosis have shown limited benefits, hence justifying the efforts to evaluate the outcome of alternative treatments. Methods: Using a mouse model of bleomycin (BLM)-induced lung fibrosis, in the current work we asked whether treatment with pro-resolution molecules, such as pro-resolving lipid mediators (SPMs) could ameliorate pulmonary fibrosis. To this end, we injected aspirin-triggered resolvin D1 (7S,8R,17R-trihydroxy- 4Z,9E,11E,13Z,15E19Z-docosahexaenoic acid; ATRvD1; i.v.) 7 and 10 days after BLM (intratracheal) challenge and samples were two weeks later. Results and discussion: Assessment of outcome in the lung tissues revealed that ATRvD1 partially restored lung architecture, reduced leukocyte infiltration, and inhibited formation of interstitial edema. In addition, lung tissues from BLM- induced mice treated with ATRvD1 displayed reduced levels of TNF-α, MCP-1, IL-1-β, and TGF-β. Of further interest, ATRvD1 decreased lung tissue expression of MMP-9, without affecting TIMP-1. Highlighting the beneficial effects of ATRvD1, we found reduced deposition of collagen and fibronectin in the lung tissues. Congruent with the anti-fibrotic effects that ATRvD1 exerted in lung tissues, α-SMA expression was decreased, suggesting that myofibroblast differentiation was inhibited by ATRvD1. Turning to culture systems, we next showed that ATRvD1 impaired TGF-β-induced fibroblast differentiation into myofibroblast. After showing that ATRvD1 hampered extracellular vesicles (EVs) release in the supernatants from TGF-β-stimulated cultures of mouse macrophages, we verified that ATRvD1 also inhibited the release of EVs in the bronco-alveolar lavage (BAL) fluid of BLM-induced mice. Motivated by studies showing that BLM-induced lung fibrosis is linked to angiogenesis, we asked whether ATRvD1 could blunt BLM-induced angiogenesis in the hamster cheek pouch model (HCP). Indeed, our intravital microscopy studies confirmed that ATRvD1 abrogates BLM-induced angiogenesis. Collectively, our findings suggest that treatment of pulmonary fibrosis patients with ATRvD1 deserves to be explored as a therapeutic option in the clinical setting. [ABSTRACT FROM AUTHOR]

The one‐dimensional (1D) modeling of blood flow in complex networks of vessels and cardiovascular models can result in computationally expensive simulations. The complexity of such networks has significantly increased in the last years, in terms of both enhanced anatomical detail and modeling of physiological mechanisms and mechanical characteristics. To address such issue, the main goal of this work is to present a novel methodology to construct hybrid networks of coupled 1D and 0D vessels and to perform computationally efficient and accurate blood flow simulations in such networks. Departing from both the 1D and lumped‐parameter (0D) nonlinear models for blood flow, we propose high‐order numerical coupling strategies to solve the 1D, 0D, and hybrid coupling of vessels at junctions. To effectively construct hybrid networks, we explore different a‐priori model selection criteria focusing in obtaining the best possible trade‐off between computational cost of the simulations and accuracy of the computed solutions for the hybrid network with respect to the 1D network. The achievement of the expected order of accuracy is verified in several test cases. The novel methodology is applied to two different arterial networks, the 37‐artery network and the reduced ADAN56 model, where, in order to identify the best performing a‐priori model selection criteria, the quantitative assessment of CPU times and errors and the qualitative comparison between results are carried out and discussed. [ABSTRACT FROM AUTHOR]

We review a collection of published renal epithelial transport models, from which we build a consistent and reusable mathematical model able to reproduce many observations and predictions from the literature. The flexible modular model we present here can be adapted to specific configurations of epithelial transport, and in this work we focus on transport in the proximal convoluted tubule of the renal nephron. Our mathematical model of the epithelial proximal convoluted tubule describes the cellular and subcellular mechanisms of the transporters, intracellular buffering, solute fluxes, and other processes. We provide free and open access to the Python implementation to ensure our multiscale proximal tubule model is accessible; enabling the reader to explore the model through setting their own simulations, reproducibility tests, and sensitivity analyses. [ABSTRACT FROM AUTHOR]

A compartmental model of the cardiorespiratory system featuring pulsatile blood flow and gas transport, as well as closed loop mechanisms of cardiorespiratory regulation is presented. Short timescale regulatory action includes baroreflex, peripheral and central chemoreflex feedback. The cardiorespiratory model is composed by compartments to describe blood flow and gas exchange in the major systemic and pulmonic regions. The control systems include formulations to afferent activity of arterial baroreceptor and peripheral and central chemoreceptors. Simulations described here include situations of hypoxia, hypercapnia, and hemorrhage. The overall responses of our simulations agree with physiological (experimental) and theoretical data. Our results suggest that the present model could be used to further understand the interplay among major regulatory mechanisms in the functioning of the cardiovascular and respiratory systems in cases of normal and abnormal physiological conditions. [ABSTRACT FROM AUTHOR]

The characterization of vascular geometry is a fundamental step towards the correct interpretation of coronary artery disease. In this work, we report a comprehensive comparison of the geometry featured by coronary vessels as obtained from coronary computed tomography angiography (CCTA) and the combination of intravascular ultrasound (IVUS) with bi‐plane angiography (AX) modalities. We analyzed 34 vessels from 28 patients with coronary disease, which were deferred to CCTA and IVUS procedures. We discuss agreement and discrepancies between several geometric indexes extracted from vascular geometries. Such an analysis allows us to understand to which extent the coronary vascular geometry can be reliable in the interpretation of geometric risk factors, and as a surrogate to characterize coronary artery disease. [ABSTRACT FROM AUTHOR]

This paper presents features and advanced settings for a robot manipulator controller in a fully interconnected intelligent manufacturing system. Every system is made up of different agents. As also occurs in the Internet of Things and smart cities, the big issue here is to ensure not only that implementation is key, but also that there is better common understanding among the main players. The commitment of all agents is still required to translate that understanding into practice in Industry 4.0. Mutual interactions such as machine-to-machine and man-to-machine are solved in real time with cyber physical capabilities. This paper explores intelligent manufacturing through the context of industrial robot manipulators within a Smart Factory. An online communication algorithm with proven intelligent manufacturing abilities is proposed to solve real-time interactions. The algorithm is developed to manage and control all robot parameters in real-time. The proposed tool in conjunction with the intelligent manufacturing core incorporates data from the robot manipulators into the industrial big data to manage the factory. The novelty is a communication tool that implements the Industry 4.0 standards to allow communications among the required entities in the complete system. It is achieved by the developed tool and implemented in a real robot and simulation [ABSTRACT FROM AUTHOR]

In this work, a data assimilation method is proposed following an optimise-then-discretise approach, and is applied in the context of computational haemodynamics. The methodology aims to make use of phase-contrast magnetic resonance imaging to perform optimal flow control in computational fluid dynamic simulations. Flow matching between observations and model predictions is performed in luminal regions, excluding near-wall areas, improving the near-wall flow reconstruction to enhance the estimation of related quantities such as wall shear stresses. The proposed approach remarkably improves the flow field at the aortic root and reveals a great potential for predicting clinically relevant haemodynamic phenomenology. This work presents model validation against an analytical solution using the standard 3-D Hagen--Poiseuille flow, and validation with real data involving the flow control problem in a glass replica of a human aorta imaged with a 3T magnetic resonance scanner. In vitro experiments consist of both a numerically generated reference flow solution, which is considered as the ground truth, as well as real flow MRI data obtained from phase-contrast flow acquisitions. The validation against the in vitro flow MRI experiments is performed for different flow regimes and model parameters including different mesh refinements. [ABSTRACT FROM AUTHOR]

Atherosclerotic plaque rupture and erosion are the most important mechanisms underlying the sudden plaque growth, responsible for acute coronary syndromes and even fatal cardiac events. Advances in the understanding of the culprit plaque structure and composition are already reported in the literature, however, there is still much work to be done toward in-vivo plaque visualization and mechanical characterization to assess plaque stability, patient risk, diagnosis and treatment prognosis. In this work, a methodology for the mechanical characterization of the vessel wall plaque and tissues is proposed based on the combination of intravascular ultrasound (IVUS) imaging processing, data assimilation and continuum mechanics models within a high performance computing (HPC) environment. Initially, the IVUS study is gated to obtain volumes of image sequences corresponding to the vessel of interest at different cardiac phases. These sequences are registered against the sequence of the end-diastolic phase to remove transversal and longitudinal rigid motions prescribed by the moving environment due to the heartbeat. Then, optical flow between the image sequences is computed to obtain the displacement fields of the vessel (each associated to a certain pressure level). The obtained displacement fields are regarded as observations within a data assimilation paradigm, which aims to estimate the material parameters of the tissues within the vessel wall. Specifically, a reduced order unscented Kalman filter is employed, endowed with a forward operator which amounts to address the solution of a hyperelastic solid mechanics model in the finite strain regime taking into account the axially stretched state of the vessel, as well as the effect of internal and external forces acting on the arterial wall. Due to the computational burden, a HPC approach is mandatory. Hence, the data assimilation and computational solid mechanics computations are parallelized at three levels: (i) a Kalman filter level; (ii) a cardiac phase level; and (iii) a mesh partitioning level. To illustrate the capabilities of this novel methodology toward the in-vivo analysis of patient-specific vessel constituents, mechanical material parameters are estimated using in-silico and in-vivo data retrieved from IVUS studies. Limitations and potentials of this approach are exposed and discussed. [ABSTRACT FROM AUTHOR]

This work presents a detailed investigation of a parameter estimation approach on the basis of the reduced-order unscented Kalman filter (ROUKF) in the context of 1-dimensional blood flow models. In particular, the main aims of this study are (1) to investigate the effects of using real measurements versus synthetic data for the estimation procedure (i.e., numerical results of the same in silico model, perturbed with noise) and (2) to identify potential difficulties and limitations of the approach in clinically realistic applications to assess the applicability of the filter to such setups. For these purposes, the present numerical study is based on a recently published in vitro model of the arterial network, for which experimental flow and pressure measurements are available at few selected locations. To mimic clinically relevant situations, we focus on the estimation of terminal resistances and arterial wall parameters related to vessel mechanics (Young's modulus and wall thickness) using few experimental observations (at most a single pressure or flow measurement per vessel). In all cases, we first perform a theoretical identifiability analysis on the basis of the generalized sensitivity function, comparing then the results owith the ROUKF, using either synthetic or experimental data, to results obtained using reference parameters and to available measurements. [ABSTRACT FROM AUTHOR]

Objective: Intravascular ultrasound (IVUS) is a fundamental imaging technique for atherosclerotic plaque assessment, interventionist guidance, and, ultimately, as a tissue characterization tool. The studies acquired by this technique present the spatial description of the vessel during the cardiac cycle. However, the study frames are not properly sorted. As gating methods deal with the cardiac phase classification of the frames, the gated studies lack motion compensation between vessel and catheter. In this study, we develop registration strategies to arrange the vessel data into its rightful spatial sequence. Methods: Registration is performed by compensating longitudinal and transversal relative motion between vessel and catheter. Transversal motion is identified through maximum likelihood estimator optimization, while longitudinal motion is estimated by a neighborhood similarity estimator among the study frames. A strongly coupled implementation is proposed to compensate for both motion components at once. Loosely coupled implementations (DLT and DTL) decouple the registration process, resulting in more computationally efficient algorithms in detriment of the size of the set of candidate solutions. Results and Conclusions: The DTL outperforms DLT and coupled implementations in terms of accuracy by a factor of $1.9$ and $1.4$, respectively. Sensitivity analysis shows that perivascular tissue must be considered to obtain the best registration outcome. Evidences suggest that the method is able to measure axial strain along the vessel wall. Significance: The proposed registration sorts the IVUS frames for spatial location, which is crucial for a correct interpretation of the vessel wall kinematics along the cardiac phases. [ABSTRACT FROM PUBLISHER]

The article presents the discussion on cerebrotoxicity of antihypertensive therapy and risk factor cosmetics. Topics include patients with stiff arteries having a wide pulse pressure aggravated by bradycardia showing diastolic pressure being lower than the cuff pressure; and computer simulations using an anatomically detailed cerebrovascular architecture estimating the the blood pressure in the brachial artery.

In recent years, the complexity of vessel networks for one-dimensional blood flow models has significantly increased, because of enhanced anatomical detail or automatic peripheral vasculature generation, for example. This fact, along with the application of these models in uncertainty quantification and parameter estimation poses the need for extremely efficient numerical solvers. The aim of this work is to present a finite volume solver for one-dimensional blood flow simulations in networks of elastic and viscoelastic vessels, featuring high-order space-time accuracy and local time stepping (LTS). The solver is built on (i) a high-order finite volume type numerical scheme, (ii) a high-order treatment of the numerical solution at internal vertexes of the network, often called junctions, and (iii) an accurate LTS strategy. The accuracy of the proposed methodology is verified by empirical convergence tests. Then, the resulting LTS scheme is applied to arterial networks of increasing complexity and spatial scale heterogeneity, with a number of one-dimensional segments ranging from a few tens up to several thousands and vessel lengths ranging from less than a millimeter up to tens of centimeters, in order to evaluate its computational cost efficiency. The proposed methodology can be extended to any other hyperbolic system for which network applications are relevant. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Goal: Coronary intravascular ultrasound (IVUS) is a fundamental imaging technique for atherosclerotic plaque assessment. However, volume-based data retrieved from IVUS studies can be misleading due to the artifacts generated by the cardiac motion, hindering diagnostic, and visualization of the vessel condition. Then, we propose an image-based gating method that improves the performance of the preexisting methods, delivering a gating in an appropriate time for clinical practice. Methods: We propose a fully automatic method to synergically integrate motion signals from different gating methods to improve the cardiac phase estimation. Additionally, we present a local extrema identification method that provides a more accurate extraction of a cardiac phase and, also, a scheme for multiple phase extraction mandatory for elastography-type studies. Results: A comparison with three state-of-the-art methods is performed over 61 in-vivo IVUS studies including a wide range of physiological situations. The results show that the proposed strategy offers: 1) a more accurate cardiac phase extraction; 2) a lower frame oversampling and/or omission in the extracted phase data (error of $1.492 \pm 0.977$ heartbeats per study, mean $\pm$ SD); 3) a more accurate and robust heartbeat period detection with a Bland–Altman coefficient of reproducibility (RPC) of $0.23$ s, while the second closest method presents an RPC of $0.36$ s. Significance: The integration of motion signals performed by our method shown an improvement of the gating accuracy and reliability. [ABSTRACT FROM PUBLISHER]

Simulation platforms are increasingly becoming complementary tools for cutting-edge cardiovascular research. The interplay among structural properties of the arterial wall, morphometry, anatomy, wave propagation phenomena, and ultimately, cardiovascular diseases continues to be poorly understood. Accurate models are powerful tools to shed light on these open problems. We developed an anatomically detailed computational model of the arterial vasculature to conduct 1-D blood flow simulations to serve as simulation infrastructure to aid cardiovascular research. An average arterial vasculature of a man was outlined in 3-D space to serve as geometrical substrate for the mathematical model. The architecture of this model comprises almost every arterial vessel acknowledged in the medical/anatomical literature, with a resolution down to the luminal area of perforator arteries. Over 2000 arterial vessels compose the model. Anatomical, physiological, and mechanical considerations were employed for the set up of model parameters and to determine criteria for blood flow distribution. Computational fluid dynamics was used to simulate blood flow and wave propagation phenomena in such arterial network. A sensitivity analysis was developed to unveil the contributions of model parameters to the conformation of the pressure waveforms. In addition, parameters were modified to target model to a patient-specific scenario. On the light of the knowledge domain, we conclude that the present model features excellent descriptive and predictive capabilities in both patient-generic and patient-specific cases, presenting a new step toward integrating an unprecedented anatomical description, morphometric, and simulations data to help in understanding complex arterial blood flow phenomena and related cardiovascular diseases. [ABSTRACT FROM PUBLISHER]