808 research outputs found

    Mitral valve regurgitation assessed by intraventricular CMR 4D-flow: a systematic review on the technological aspects and potential clinical applications.

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    Cardiac magnetic resonance (CMR) four-dimensional (4D) flow is a novel method for flow quantification potentially helpful in management of mitral valve regurgitation (MVR). In this systematic review, we aimed to depict the clinical role of intraventricular 4D-flow in MVR. The reproducibility, technical aspects, and comparison against conventional techniques were evaluated. Published studies on SCOPUS, MEDLINE, and EMBASE were included using search terms on 4D-flow CMR in MVR. Out of 420 screened articles, 18 studies fulfilled our inclusion criteria. All studies (n = 18, 100%) assessed MVR using 4D-flow intraventricular annular inflow (4D-flowAIM) method, which calculates the regurgitation by subtracting the aortic forward flow from the mitral forward flow. Thereof, 4D-flow jet quantification (4D-flowjet) was assessed in 5 (28%), standard 2D phase-contrast (2D-PC) flow imaging in 8 (44%) and the volumetric method (the deviation of left ventricle stroke volume and right ventricular stroke volume) in 2 (11%) studies. Inter-method correlations among the 4 MVR quantification methods were heterogeneous across studies, ranging from moderate to excellent correlations. Two studies compared 4D-flowAIM to echocardiography with moderate correlation. In 12 (63%) studies the reproducibility of 4D-flow techniques in quantifying MVR was studied. Thereof, 9 (75%) studies investigated the reproducibility of the 4D-flowAIM method and the majority (n = 7, 78%) reported good to excellent intra- and inter-reader reproducibility. Intraventricular 4D-flowAIM provides high reproducibility with heterogeneous correlations to conventional quantification methods. Due to the absence of a gold standard and unknown accuracies, future longitudinal outcome studies are needed to assess the clinical value of 4D-flow in the clinical setting of MVR

    Study of a medical device to treat aortic dissection with Finite Element Analysis

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    Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2022-2023. Tutor/Director: Carmona Flores, Manuel, Soudah Prieto, EduardoThe aortic dissection is a cardiovascular disease that results from the rupture of the inner layer of the aorta. Type B aortic dissections commonly become a chronic disease with a high long-term morbidity and mortality rates. Current treatments include open surgery repair and thoracic endovascular aortic repair (TEVAR). However, new non-invasive treatments are being developed that favour the own regeneration of the tissue, avoiding the permanent presence of a foreign device in the body. This project focuses on the understanding of a new treatment with a medical device, an aortic patch, by in silico testing. The goal is to determine the performance of the patch in a simulated aortic dissection and then compare it with the current treatment with the stent graft (TEVAR), to determine if it would avoid the hypertension that can be caused by the stent. To do the first part, it was created a model of the aortic dissection, but due to complications with the simulation, this part of the project couldn’t be finished, and the performance of the patch in the aortic dissection couldn’t be determined. To do the second part three models were created: healthy aorta, aortic dissection with stent graft and aortic dissection with patch. A transient simulation was run for the three models and the pressure waveform was analyzed. The results show that the pressure in the stent graft model is higher, and the patch has a similar response to the healthy aorta. However, all the models presented hypertension (including the healthy aorta) and the differences between the models are too small to be concluding, so it cannot be assured that the patch is a better option than the stent graft to avoid causing hypertension in the aortic dissection treatment

    4D Flow cardiovascular magnetic resonance consensus statement: 2023 update

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    Hemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 '4D Flow CMR Consensus Statement'. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards

    4D Flow cardiovascular magnetic resonance consensus statement: 2023 update

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    4D Flow MRI; Hemodynamics; RecommendationsRessonància magnètica de flux 4D; Hemodinàmica; RecomanacionsResonancia magnética de flujo 4D; Hemodinámica; RecomendacionesHemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 ‘4D Flow CMR Consensus Statement’. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards.1R01HL149787-01A1 (S. Schnell, M. Markl), 1R21NS122511-01 (S. Schnell), 1R01CA233878-01 (J.Collins) J.Sotelo thanks to ANID–Millennium Science Initiative Program–ICN2021_004 and FONDECYT de iniciación en investigación #11200481. Dr. Oechtering receives funding from the German Research Foundation (OE 746/1-1)

    Data-driven generation of 4D velocity profiles in the aneurysmal ascending aorta

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    Background and Objective: Numerical simulations of blood flow are a valuable tool to investigate the pathophysiology of ascending thoratic aortic aneurysms (ATAA). To accurately reproduce in vivo hemodynamics, computational fluid dynamics (CFD) models must employ realistic inflow boundary conditions (BCs). However, the limited availability of in vivo velocity measurements, still makes researchers resort to idealized BCs. The aim of this study was to generate and thoroughly characterize a large dataset of synthetic 4D aortic velocity profiles sampled on a 2D cross-section along the ascending aorta with features similar to clinical cohorts of patients with ATAA. Methods: Time-resolved 3D phase contrast magnetic resonance (4D flow MRI) scans of 30 subjects with ATAA were processed through in-house code to extract anatomically consistent cross-sectional planes along the ascending aorta, ensuring spatial alignment among all planes and interpolating all velocity fields to a reference configuration. Velocity profiles of the clinical cohort were extensively characterized by computing flow morphology descriptors of both spatial and temporal features. By exploiting principal component analysis (PCA), a statistical shape model (SSM) of 4D aortic velocity profiles was built and a dataset of 437 synthetic cases with realistic properties was generated. Results: Comparison between clinical and synthetic datasets showed that the synthetic data presented similar characteristics as the clinical population in terms of key morphological parameters. The average velocity profile qualitatively resembled a parabolic-shaped profile, but was quantitatively characterized by more complex flow patterns which an idealized profile would not replicate. Statistically significant correlations were found between PCA principal modes of variation and flow descriptors. Conclusions: We built a data-driven generative model of 4D aortic inlet velocity profiles, suitable to be used in computational studies of blood flow. The proposed software system also allows to map any of the generated velocity profiles to the inlet plane of any virtual subject given its coordinate set

    Enhancing magnetic resonance imaging with computational fluid dynamics

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    Quantitative assessment of haemodynamics has been utilised for better understanding of cardiac function and assisting diagnostics of cardiovascular diseases. To study haemodynamics, magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) are widely used because of their non-invasive nature. It has been demonstrated that the two approaches are complementary to each other with their own advantages and limitations. Four dimensional cardiovascular magnetic resonance (4D Flow CMR) imaging enables direct measurement of blood flow velocity in vivo while spatial and temporal resolutions as well as region of image acquisition are limited to achieve a detailed assessment of the haemodynamics. CFD, on the other hand, is a powerful tool that has the potential to expand the image-obtained velocity fields with some problem-specific assumptions such as rigid arterial walls. We suggest a novel approach in which 4D Flow CMR and CFD are integrated synergistically in order to obtain an enhanced 4D Flow CMRI (EMRI). The enhancement will consist in overcoming the spatial-resolution limitations of the original 4D Flow CMRI, which will enable more accurate quantification of flow dependent bio-mechanical quantities (e.g. endothelial shear stress) as well as non-invasive estimation of blood pressure. At the same time, it will reduce a number of assumptions in conventional haemodynamic CFD such as in/outflow conditions including the effect of valves, the impact of patient-specific vessel wall motion and the effect of the surrounding tissues. The approach was first tested on a 2D portion of a pipe, to understand the behaviour of the parameters of the model in this novel framework. Afterwards the methodology was tested on patient specific data, to apply it to the analysis of blood flow in a patient specific human aorta, in 2D. The outcomes of EMRI are assessed by comparing the computed velocities with the 4D Flow CMR one. A fundamental step to allow the translation to clinics of this methodology was the validation. The study was performed on an idealised-simplified model of the human aortic arch – a U bend – with a sinusoidal inflow applied by a pump. Firstly, phase resolved particle image velocimetry (PIV) (an experimental technique enables high spatial-temporal resolution) was performed in 5 different time points of the pump cycle, using a blood alike fluid with the same refractive index matched of the clear silicon phantom, and seeded with silver coated hollow glass spheres. Real time 4D Flow CMR was then performed on the phantom with MRI. Lastly using the pump flow rate and the phantom geometry, a computation of the flow through the U bend was conducted using Ansys CFX. The flow patterns obtained from the 3 methods were compared in the middle plane of the phantom. The methodology was then applied to study a patient specific aorta in 3D, and retrieve flow patterns and flow dependent parameters. Finally, the validated methodology was applied to study atherogenesis, and in particular to investigate the relation between EMRI retrieved flow quantities (e.g. wall shear stress (WSS)) and temperature heterogeneity. A carotid artery phantom was realised and studied with CFD, MRT and EMRI. All the results demonstrate that EMRI preserves flow structures while correcting for experimental noise. Therefore it can provide better insights of the haemodynamics of cardiovascular problems, overcoming the limitations of 4D Flow CMR and CFD, even when considering a small region of interest. These findings were supported by the validation experiment that showed how EMRI retrieved flow patterns were much more consistent with the one measured with high resolution PIV, compensating for 4D Flow CMR errors. These findings lead to the application to the atherogenesis problem, allowing higher resolution flow patterns, more suitable to be compared to the temperature distribution and highlighted how flow patterns exert an influence on the temperature distribution on the vessel wall. EMRI confirmed its potential to provide more accurate non-invasive estimation of flow derived and flow dependent quantities and become a novel diagnostic tool
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