Convergence analysis of pressure reconstruction methods from discrete velocities

Magnetic resonance imaging allows the measurement of the three-dimensional velocity field in blood flows. Therefore, several methods have been proposed to reconstruct the pressure field from such measurements using the incompressible Navier- Stokes equations, thereby avoiding the use of invasive technologies. However, those measurements are obtained at limited spatial resolution given by the voxel sizes in the image. In this paper, we propose a strategy for the convergence analysis of state-of-the-art pressure reconstruction methods. The methods analyzed are the so-called Pressure Poisson Estimator (PPE) and Stokes Estimator (STE). In both methods, the right-hand side corresponds to the terms that involving the field velocity in the Navier- Stokes equations, with a piecewise linear interpolation of the exact velocity. In the theoretical error analysis, we show that many terms of different order of convergence appear. These are certainly dominated by the lowest-order term, which in most cases stems from the interpolation of the velocity field. However, the numerical results in academic examples indicate that only the PPE may profit of increasing the polynomial order, and that the STE presents a higher accuracy than the PPE, but the interpolation order of the velocity field always prevails. Furthermore, we compare the pressure estimation methods on real MRI data, assessing the impact of different spatial resolutions and polynomial degrees on each method. Here, the results are consistent with the academic test cases in terms of sensitivity to polynomial order as well as the STE showing to be potentially more accurate when compared to reference pressure measurements.</p

Convergence analysis of pressure reconstruction methods from discrete velocities

Magnetic resonance imaging allows the measurement of the three-dimensional velocity field in blood flows. Therefore, several methods have been proposed to reconstruct the pressure field from such measurements using the incompressible Navier- Stokes equations, thereby avoiding the use of invasive technologies. However, those measurements are obtained at limited spatial resolution given by the voxel sizes in the image. In this paper, we propose a strategy for the convergence analysis of state-of-the-art pressure reconstruction methods. The methods analyzed are the so-called Pressure Poisson Estimator (PPE) and Stokes Estimator (STE). In both methods, the right-hand side corresponds to the terms that involving the field velocity in the Navier- Stokes equations, with a piecewise linear interpolation of the exact velocity. In the theoretical error analysis, we show that many terms of different order of convergence appear. These are certainly dominated by the lowest-order term, which in most cases stems from the interpolation of the velocity field. However, the numerical results in academic examples indicate that only the PPE may profit of increasing the polynomial order, and that the STE presents a higher accuracy than the PPE, but the interpolation order of the velocity field always prevails. Furthermore, we compare the pressure estimation methods on real MRI data, assessing the impact of different spatial resolutions and polynomial degrees on each method. Here, the results are consistent with the academic test cases in terms of sensitivity to polynomial order as well as the STE showing to be potentially more accurate when compared to reference pressure measurements.</p

Fractional-step schemes for the coupling of distributed and lumped models in hemodynamics

International audienceIn three-dimensional (3D) blood flow simulations, lumped parameter models (0D) are often used to model the neglected parts of the downstream circulatory system. We analyze two 3D-0D coupling approaches in which a fractional-step projection scheme is used in the fluid. Our analysis shows that explicit approaches might yield numerical instabilities, particularly in the case of realistic geometries with multiple outlets. We introduce and analyze an implicitly 3D-0D coupled formulation with enhanced stability properties and which requires a negligible additional computational cost. Furthermore, we also address the extension of these methods to fluid-structure interaction problems. The theoretical stability results are confirmed by meaningful numerical experiments in patient specific geometries coming from medical imaging

Multiple motion encoding in Phase-Contrast MRI:A general theory and application to elastography imaging

While MRI allows to encode the motion of tissue in the magnetization’s phase, it remains yet a challenge to obtain high fidelity motion images due to wraps in the phase for high encoding efficiencies. Therefore, we propose an optimal multiple motion encoding method (OMME) and exemplify it in Magnetic Resonance Elastography (MRE) data. OMME is formulated as a non-convex least-squares problem for the motion using an arbitrary number of phase-contrast measurements with different motion encoding gradients (MEGs). The mathematical properties of OMME are proved in terms of standard deviation and dynamic range of the motion’s estimate for arbitrary MEGs combination which are confirmed using synthetically generated data. OMME’s performance is assessed on MRE data from in vivo human brain experiments and compared to dual encoding strategies. The unwrapped images are further used to reconstruct stiffness maps and compared to the ones obtained using conventional unwrapping methods. OMME allowed to successfully combine several MRE phase images with different MEGs, outperforming dual encoding strategies in either motion-to-noise ratio (MNR) or number of successfully reconstructed voxels with good noise stability. This lead to stiffness maps with greater resolution of details than obtained with conventional unwrapping methods. The proposed OMME method allows for a flexible and noise robust increase in the dynamic range and thus provides wrap-free phase images with high MNR. In MRE, the method may be especially suitable when high resolution images with high MNR are needed

Sequential parameter estimation for fluid-structure problems. Application to hemodynamics

International audienceWe present a robust and computationally efficient parameter estimation strategy for fluid-structure interaction problems. The method is based on a filtering algorithm restricted to the parameter space, known as the reduced order Unscented Kalman Filter. It does not require any adjoint or tangent problems. In addition, it can easily be run in parallel, which is of great interest in fluid-structure problems where the computational cost of the forward simulation is already a challenge in itself. We illustrate our methodology with the estimation of the artery wall stiffness from the wall displacement measurements - as they could be extracted from medical imaging - in a three-dimensional idealized abdominal aortic aneurysm. We also show preliminary results about the estimation of the proximal Windkessel resistance, which is an important parameter for setting appropriate fluid boundary conditions

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Problèmes Directs et Inverses en Interaction Fluide-Structure. Application à l'hémodynamique

In this thesis we deal with the simulation of fluid-structure interac- tion (FSI) problems in hemodynamics, with the emphasis in data assimilation and simulation in physiological regimes. The first part presents and analyzes a semi-implicit coupling scheme between the three-dimensional Navier-Stokes equations (NSE) and lumped parameter models, when the NSE are solved in a projection framework. This allows to simulate fluid and FSI problems more robustly, i.e., avoiding instabilities that may occur when dealing with realistic test-cases. The second part of the work is devoted to the study of sequential data assimila- tion techniques in FSI. We first present a study about the application of a reduced- order Unscented Kalman Filter for the effective estimation of relevant physical pa- rameters, like the stiffness distribution of the vessel wall and the proximal resistance in the fluid, from displacement measurements at the fluid-structure interface. Next, we analyze some Luenberger observers from solid mechanics in FSI, with the aim to construct tractable state estimators for large-scale FSI problems. In the third and final part, we apply some of the aforementioned methodologies to real physical problems. First, we perform the estimation of the wall stiffness (for linear and non-linear solid models) from data coming from MR-images of a silicone rubber aortic phantom. To finish, we deal with the forward analysis of a real aorta with repaired coarctation and we test the estimation techniques with synthetic data and show some results with the patient's data.Dans cette thèse nous traitons de la simulation d'interaction fluide- structure (FSI) dans les problèmes en hémodynamique, en mettant l'accent sur l'assimilation de données et sur la simulation dans les conditions physiologiques. La première partie présente et analyse un schéma de couplage semi-implicite des équations de Navier-Stokes (NSE) et d'un modèle de conditions aux limites réduit, lorsque les NSE sont résolues avec une méthode de projection. Cela permet de simuler des problèmes de mécanique de fluides et de FSI de fac ̧on plus robuste, c'est à dire en évitant les possibles instabilités associées à des cas-tests réalistes. La deuxième partie est consacrée à l'assimilation des données avec des méthodes séquentielles en FSI. Nous présentons d'abord une étude sur l'application d'un fil- tre de Kalman réduit pour l'estimation efficace des paramètres physiques d'intérêt, comme la distribution de la rigidité de la paroi de l'artère et la résistance proximale dans le fluide, à partir des mesures de deplacement à l'interface fluide-structure. Ensuite, nous analysons certains observateurs de Luenberger utilisés pour la mé- canique des solides en FSI, dans le but de construire des estimateurs d'état efficaces pour des problèmes FSI de grande taille. Dans la troisième et dernière partie, nous appliquons les méthodologies mention- nées ci-dessus aux problèmes physiques réels. Tout d'abord, la rigidité de la paroi est estimée (pour des modèles solides linéaires et non linéaires) à partir de données provenant d'un tube de silicone simulant une aorte. Pour finir, nous analysons une aorte réelle avec une coarctation réparée, nous testons les techniques d'estimation avec des données synthétiques et nous montrons quelques résultats obtenues à partir de données issues du patient

Inverse problems in blood flow modeling: A review

Mathematical and computational modeling of the cardiovascular system is increasingly providing non-invasive alternatives to traditional invasive clinical procedures. Moreover, it has the potential for generating additional diagnostic markers. In blood flow computations, the personalization of spatially distributed (i.e., 3D) models is a key step which relies on the formulation and numerical solution of inverse problems using clinical data, typically medical images for measuring both anatomy and function of the vasculature. In the last years, the development and application of inverse methods has rapidly expanded, most likely due to the increased availability of data in clinical centers and the growing interest of modelers and clinicians in collaborating. Therefore, this work aims to provide a wide and comparative overview of literature within the last decad