scholarly journals Assessing the methodology used to study the ascending aorta haemodynamics in bicuspid aortic valve

Author(s):  
Joy Edlin ◽  
Justin Nowell ◽  
Chris Arthurs ◽  
Alberto Figueroa ◽  
Marjan Jahangiri

Abstract Background Modern imaging techniques provide evermore-detailed anatomical and physiological information for use in computational fluid dynamics to predict the behaviour of physiological phenomena. Computer modelling can help plan suitable interventions. Our group used magnetic resonance imaging and computational fluid dynamics to study the haemodynamic variables in the ascending aorta in patients with bicuspid aortic valve before and after isolated tissue aortic valve replacement. Computer modelling requires turning a physiological model into a mathematical one, solvable by equations that undergo multiple iterations in four dimensions. Creating these models involves several steps with manual inputs, making the process prone to errors and limiting its inter- and intra-operator reproducibility. Despite these challenges we created computational models for each patient to study ascending aorta blood flow before and after surgery. Method Magnetic resonance imaging provided the anatomical and velocity data required for the blood flow simulation. Patient-specific in- and outflow boundary conditions were used for the computational fluid dynamics analysis. Results Haemodynamic variables pertaining to blood flow pattern and derived from the magnetic resonance imaging data were calculated. However, we encountered problems in our multi-step methodology, most notably processing the flow data. This meant that other variables requiring computation with computational fluid dynamics could not be calculated. Conclusion Creating a model for computational fluid dynamics analysis is as complex as the physiology under scrutiny. We discuss some of the difficulties associated with creating such models, along with suggestions for improvements in order to yield reliable and beneficial results.

Author(s):  
Giacomo Annio ◽  
Ryo Torii ◽  
Ben Ariff ◽  
Declan P. O'Regan ◽  
Vivek Muthurangu ◽  
...  

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.


Author(s):  
Yong He ◽  
Christi M. Terry ◽  
Scott A. Berceli ◽  
Alfred K. Cheung ◽  
Yan-Ting E. Shiu

An arteriovenous fistula (AVF) is the preferred vascular access for hemodialysis in end-stage renal disease. However, 60% of AVFs fail to achieve sufficient lumen dilation to allow adequate blood flow for chronic dialysis [1]. Although hemodynamics is likely an important modulator of AVF maturation and remodeling, the AVF hemodynamic spatial distribution profiles and their relationship with AVF maturation and remodeling are unclear [2]. Based on data collected from magnetic resonance imaging (MRI) of an AVF and computational fluid dynamics (CFD) simulations, we developed a protocol for longitudinal (over time) and noninvasive monitoring of geometry and hemodynamics of human AVF.


2020 ◽  
Vol 14 (4) ◽  
pp. 7609-7621
Author(s):  
Mohd Azrul Hisham Mohd Adib ◽  
Lim Sheh Hong ◽  
Mohd Shafie Abdullah ◽  
Radhiana Hassan ◽  
Shigeo Wada

Nowadays, the knowledge of precise blood flow patterns in human blood vessels, especially focusing on Carotid Bifurcations Artery (CBA) area by using computational and modern techniques are very important to develop our understanding regarding to human diseases for both essential research and clinical treatment. This paper tends to discuss the progress regarding to the integration between Phase Contrast Magnetic Resonance Imaging (PC-MRI) and Computational Fluid Dynamics (CFD), specifically to the human diseases. We technically define the model geometry reconstruction, review both PC-MRI and CFD methods to create mesh models, obtain boundary conditions, define the governing equations in CFD, define the material properties, and assumptions used in running the CFD simulations. Detailed information on PC-MRI and CFD is provided in tables, such as the MRI setup, software used, CFD model setup, measurement parameter, and summary of the result contribution from each reviewed article. Numerous fusions between PC-MRI and CFD are specified by summarizing the investigation carried out by significant group’s research, reviewing the important outcomes, and discussing the techniques, drawbacks and possibilities for further study. We hope that this perspective analysis will encourage a fusion of PC-MRI and CFD research contributing to continuous advancement of human health with close cooperation and collaboration among clinicians and engineers.


Sign in / Sign up

Export Citation Format

Share Document