Optimal Plane Selection for Measuring Post-prandial Blood Flow Increase within the Superior Mesenteric Artery: Analysis Using 4D Flow and Computational Fluid Dynamics

In the last few years, wall shear stress (WSS) has arisen as a new diagnostic indicator in patients with arterial disease. There is a substantial evidence that the WSS plays a significant role, together with hemodynamic indicators, in initiation and progression of the vascular diseases. Estimation of WSS values, therefore, may be of clinical significance and the methods employed for its measurement are crucial for clinical community. Recently, four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) has been widely used in a number of applications for visualization and quantification of blood flow, and although the sensitivity to blood flow measurement has increased, it is not yet able to provide an accurate three-dimensional (3D) WSS distribution. The aim of this work is to evaluate the aortic blood flow features and the associated WSS by the combination of 4D flow cardiovascular magnetic resonance (4D CMR) and computational fluid dynamics technique. In particular, in this work, we used the 4D CMR to obtain the spatial domain and the boundary conditions needed to estimate the WSS within the entire thoracic aorta using computational fluid dynamics. Similar WSS distributions were found for cases simulated. A sensitivity analysis was done to check the accuracy of the method. 4D CMR begins to be a reliable tool to estimate the WSS within the entire thoracic aorta using computational fluid dynamics. The combination of both techniques may provide the ideal tool to help tackle these and other problems related to wall shear estimation.

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Enhancing Magnetic Resonance Imaging With Computational Fluid Dynamics

Journal of Engineering and Science in Medical Diagnostics and Therapy ◽

10.1115/1.4045493 ◽

2019 ◽

Vol 2 (4) ◽

Author(s):

Giacomo Annio ◽

Ryo Torii ◽

Ben Ariff ◽

Declan P. O'Regan ◽

Vivek Muthurangu ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Blood Flow ◽

Magnetic Resonance ◽

Patient Specific ◽

Human Aorta ◽

Resonance Imaging ◽

4D Flow ◽

4D Flow Cmr

Abstract The analysis of the blood flow in the great thoracic arteries does provide valuable information about the cardiac function and can diagnose the potential development of vascular diseases. Flow-sensitive four-dimensional flow cardiovascular magnetic resonance imaging (4D flow CMR) is often used to characterize patients' blood flow in the clinical environment. Nevertheless, limited spatial and temporal resolution hinders a detailed assessment of the hemodynamics. Computational fluid dynamics (CFD) could expand this information and, integrated with experimental velocity field, enable to derive the pressure maps. However, the limited resolution of the 4D flow CMR and the simplifications of CFD modeling compromise the accuracy of the computed flow parameters. In this article, a novel approach is proposed, where 4D flow CMR and CFD velocity fields are integrated synergistically to obtain an enhanced MR imaging (EMRI). The approach was first tested on a two-dimensional (2D) portion of a pipe, to understand the behavior of the parameters of the model in this novel framework, and afterwards in vivo, to apply it to the analysis of blood flow in a patient-specific human aorta. The outcomes of EMRI are assessed by comparing the computed velocities with the experimental one. The results demonstrate that EMRI preserves flow structures while correcting for experimental noise. Therefore, it can provide better insights into the hemodynamics of cardiovascular problems, overcoming the limitations of MRI and CFD, even when considering a small region of interest. EMRI confirmed its potential to provide more accurate noninvasive estimation of major cardiovascular risk predictors (e.g., flow patterns, endothelial shear stress) and become a novel diagnostic tool.

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Pulsatile, non-pulsatile, ante- or retrograde aortic blood flow: all the same? A computational fluid dynamics study of different ECC techniques

The Thoracic and Cardiovascular Surgeon ◽

10.1055/s-0029-1246889 ◽

2010 ◽

Vol 58 (S 01) ◽

Author(s):

A Assmann ◽

AC Benim ◽

A Nahavandi ◽

D Schubert ◽

A Lichtenberg ◽

...

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Blood Flow ◽

Aortic Blood Flow ◽

Aortic Blood

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Enhancement of cerebrovascular 4D flow MRI velocity fields using machine learning and computational fluid dynamics simulation data

Scientific Reports ◽

10.1038/s41598-021-89636-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

David R. Rutkowski ◽

Alejandro Roldán-Alzate ◽

Kevin M. Johnson

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Velocity Fields ◽

Dynamics Simulation ◽

Patient Specific ◽

4D Flow Mri ◽

4D Flow ◽

Flow Phase ◽

Flow Mri ◽

Trained Network

AbstractBlood flow metrics obtained with four-dimensional (4D) flow phase contrast (PC) magnetic resonance imaging (MRI) can be of great value in clinical and experimental cerebrovascular analysis. However, limitations in both quantitative and qualitative analyses can result from errors inherent to PC MRI. One method that excels in creating low-error, physics-based, velocity fields is computational fluid dynamics (CFD). Augmentation of cerebral 4D flow MRI data with CFD-informed neural networks may provide a method to produce highly accurate physiological flow fields. In this preliminary study, the potential utility of such a method was demonstrated by using high resolution patient-specific CFD data to train a convolutional neural network, and then using the trained network to enhance MRI-derived velocity fields in cerebral blood vessel data sets. Through testing on simulated images, phantom data, and cerebrovascular 4D flow data from 20 patients, the trained network successfully de-noised flow images, decreased velocity error, and enhanced near-vessel-wall velocity quantification and visualization. Such image enhancement can improve experimental and clinical qualitative and quantitative cerebrovascular PC MRI analysis.

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A Simple Transient Poiseuille-Based Approach to Mimic the Womersley Function and to Model Pulsatile Blood Flow

Dynamics ◽

10.3390/dynamics1010002 ◽

2021 ◽

Vol 1 (1) ◽

pp. 9-17

Author(s):

Andrea Natale Impiombato ◽

Giorgio La Civita ◽

Francesco Orlandi ◽

Flavia Schwarz Franceschini Zinani ◽

Luiz Alberto Oliveira Rocha ◽

...

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Blood Flow ◽

Boundary Conditions ◽

Quadratic Function ◽

Pulsatile Blood Flow ◽

Flow Through ◽

Simplified Analysis ◽

Function Models ◽

Flow Reversals

As it is known, the Womersley function models velocity as a function of radius and time. It has been widely used to simulate the pulsatile blood flow through circular ducts. In this context, the present study is focused on the introduction of a simple function as an approximation of the Womersley function in order to evaluate its accuracy. This approximation consists of a simple quadratic function, suitable to be implemented in most commercial and non-commercial computational fluid dynamics codes, without the aid of external mathematical libraries. The Womersley function and the new function have been implemented here as boundary conditions in OpenFOAM ESI software (v.1906). The discrepancy between the obtained results proved to be within 0.7%, which fully validates the calculation approach implemented here. This approach is valid when a simplified analysis of the system is pointed out, in which flow reversals are not contemplated.

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