1E31 Fluid mechanics analysis of blood flow with aortic valve motion

2016 ◽  
Vol 2016.28 (0) ◽  
pp. _1E31-1_-_1E31-3_
Author(s):  
Takuya TERAHARA ◽  
Kenji TAKIZAWA ◽  
Tayfum E. TEZDUYAR
2014 ◽  
Vol 17 (5) ◽  
pp. 269
Author(s):  
Shinya Takahashi ◽  
Taiichi Takasaki ◽  
Futoshi Tadehara ◽  
Takahiro Taguchi ◽  
Keijiro Katayama ◽  
...  

An 86-year-old woman presented with chest pain and discomfort. Echocardiography revealed severe aortic valve stenosis and asymmetric septal hypertrophy. Aortic valve replacement and myectomy were performed using a curved knife. The blade was U-shaped in cross-section, and was curved upward along the long axis. Hypertrophic septal myocardium was removed along the long axis of the left ventricle (LV), and a groove for blood flow was constructed. The patient was discharged uneventfully without recurrence of her chest discomfort. Our result suggested that a curved knife is a reasonable option for transaortic septal myectomy in patients with obstructive LV hypertrophy.


Perfusion ◽  
2021 ◽  
pp. 026765912199854
Author(s):  
Mohammad Javad Ghasemi Pour ◽  
Kamran Hassani ◽  
Morteza Khayat ◽  
Shahram Etemadi Haghighi

Background and objectives: Fluid structure interaction (FSI) is defined as interaction of the structures with contacting fluids. The aortic valve experiences the interaction with blood flow in systolic phase. In this study, we have tried to predict the hemodynamics of blood flow through a normal and stenotic aortic valve in two relaxation and exercise conditions using a three-dimensional FSI method. Methods: The aorta valve was modeled as a three-dimensional geometry including a normal model and two others with 25% and 50% stenosis. The geometry of the aortic valve was extracted from CT images and the models were generated by MMIMCS software and then they were implemented in ANSYS software. The pulsatile flow rate was used for all cases and the numerical simulations were conducted based on a time-dependent domain. Results: The obtained results including the velocity, pressure, and shear stress contours in different systolic time sequences were explained and discussed. The maximum blood flow velocity in relaxation phase was obtained 1.62 m/s (normal valve), 3.78 m/s (25% stenosed valve), and 4.73 m/s (50% stenosed valve). In exercise condition, the maximum velocities are 2.86, 4.32, and 5.42 m/s respectively. The maximum blood pressure in relaxation phase was calculated 111.45 mmHg (normal), 148.66 mmHg (25% stenosed), and 164.21 mmHg (50% stenosed). However, the calculated values in exercise situation were 129.57, 163.58, and 191.26 mmHg. The validation of the predicted results was also conducted using existing literature. Conclusions: We believe that such model are useful tools for biomechanical experts. The further studies should be done using experimental data and the data are implemented on the boundary conditions for better comparison of the results.


1992 ◽  
Vol 114 (3) ◽  
pp. 274-282 ◽  
Author(s):  
R. M. Nerem

Atherosclerosis, a disease of large- and medium-size arteries, is the chief cause of death in the United States and in most of the western world. Severe atherosclerosis interferes with blood flow; however, even in the early stages of the disease, i.e. during atherogenesis, there is believed to be an important relationship between the disease processes and the characteristics of the blood flow in the arteries. Atherogenesis involves complex cascades of interactions among many factors. Included in this are fluid mechanical factors which are believed to be a cause of the highly focal nature of the disease. From in vivo studies, there is evidence of hemodynamic influences on the endothelium, on intimal thickening, and on monocyte recruitment. In addition, cell culture studies have demonstrated the important effect of a cell’s mechanical environment on structure and function. Most of this evidence is for the endothelial cell, which is believed to be a key mediator of any hemodynamic effect, and it is now well documented that cultured endothelial monolayers, in response to a fluid flow-imposed laminar shear stress, undergo a variety of changes in structure and function. In spite of the progress in recent years, there are many areas in which further work will provide important new information. One of these is in the engineering of the cell culture environment so as to make it more physiologic. Animal studies also are essential in our efforts to understand atherogenesis, and it is clear that we need better information on the pattern of the disease and its temporal development in humans and animal models, as well as the specific underlying biologic events. Complementary to this will be in vitro model studies of arterial fluid mechanics. In addition, one can foresee an increasing role for computer modelling in our efforts to understand the pathophysiology of the atherogenic process. This includes not only computational fluid mechanics, but also modelling the pathobiologic processes taking place within the arterial wall. A key to the atherogenic process may reside in understanding how hemodynamics influences not only intimal smooth muscle cell proliferation, but also the recruitment of the monocyte/macrophage and the formation of foam cells. Finally, it will be necessary to begin to integrate our knowledge of cellular phenomena into a description of the biologic processes within the arterial wall and then to integrate this into a picture of the disease process itself.


2012 ◽  
Vol 163 ◽  
pp. 133-137
Author(s):  
Ao Yu Chen ◽  
Xu Dong Pan ◽  
Guang Lin Wang

Traditional method of buoy gauge design is rather complicated, so an advanced method by building and solving fluid mechanics equations is proposed in this paper. The curve of the taper pipe inner surface is calculated, according to different buoy gravity and diameter. In order to examine the effect of this improved method, an experiment is carried out. Results show that linear property of the buoy gauge improved by new method is excellent.


2021 ◽  
Vol 12 ◽  
Author(s):  
Shantanu Bailoor ◽  
Jung-Hee Seo ◽  
Stefano Schena ◽  
Rajat Mittal

Patients who receive transcatheter aortic valve replacement are at risk for leaflet thrombosis-related complications, and can benefit from continuous, longitudinal monitoring of the prosthesis. Conventional angiography modalities are expensive, hospital-centric and either invasive or employ potentially nephrotoxic contrast agents, which preclude their routine use. Heart sounds have been long recognized to contain valuable information about individual valve function, but the skill of auscultation is in decline due to its heavy reliance on the physician’s proficiency leading to poor diagnostic repeatability. This subjectivity in diagnosis can be alleviated using machine learning techniques for anomaly detection. We present a computational and data-driven proof-of-concept analysis of a novel, auscultation-based technique for monitoring aortic valve, which is practical, non-invasive, and non-toxic. However, the underlying mechanisms leading to physiological and pathological heart sounds are not well-understood, which hinders development of such a technique. We first address this by performing direct numerical simulations of the complex interactions between turbulent blood flow in a canonical ascending aorta model and dynamic valve motion in 29 cases with healthy and stenotic valves. Using the turbulent pressure fluctuations on the aorta lumen boundary, we model the propagation of heart sounds, as elastic waves, through the patient’s thorax. The heart sound may be recorded on the epidermal surface using a stethoscope/phonocardiograph. This approach allows us to correlate instantaneous hemodynamic phenomena and valve motion with the acoustic response. From this dataset we extract “acoustic signatures” of healthy and stenotic valves based on principal components of the recorded sound. These signatures are used to train a linear discriminant classifier by maximizing correlation between recorded heart sounds and valve status. We demonstrate that this classifier is capable of accurate prospective detection of anomalous valve function and that the principal component-based signatures capture prominent audible features of heart sounds, which have been historically used by physicians for diagnosis. Further development of such technology can enable inexpensive, safe and patient-centric at-home monitoring, and can extend beyond transcatheter valves to surgical as well as native valves.


2020 ◽  
Vol 24 (4) ◽  
pp. 74-80
Author(s):  
V. V. Bazylev ◽  
R. M. Babukov ◽  
F. L. Bartosh ◽  
A. V. Gorshkova

Purpose: comparison of hemodynamic parameters of transaortic blood flow in patients with aortic stenosis depending on the bivalve or tricuspid structure of the aortic valve.Materials and methods. A study of 180 patients with isolated aortic valve stenosis (AC) with two – and threeleaf structure was conducted. Patients were ranked into 3 comparison subgroups by the area of the effective AC opening from 4 to 1.5 cm2; 1.5 to 1 cm2 and less than 1 cm2. An echocardiographic study was performed with the calculation of all the necessary parameters for the study.Results. The comparison subgroups were comparable in terms of effective orifice area (AVA), effective orifice area index (IAVA), body mass index (BMI), LV UO index, and LV FV (p > 0.05). However, the indicators Vmax, Gmean, and AT in patients with a bivalve AK structure in all comparison subgroups were significantly higher than in patients with a tricuspid structure. Comparison subgroup with AVA from 4 to 1.5 cm2: Vmax 2.8 ± 9 m/s and 2.5 ± 6 m/s p = 0.02. Gmean 18.6 ± 7.2 mm Hg and 15 ± 6 mm Hg p = 0.03, AT 82 ± 12 ms and 70 ± 10 ms p = 0.002. Comparison subgroup with AVA from 1.5 to 1 cm2: Vmax 3.7 ± 0.8 m/s and 3.5 ± 0.6 m/s p = 0.02. Average transaortic gradient 37 ± 10 mm Hg and 29 ± 5 mm Hg p = 0.04, AT 103 ± 11 ms and 94 ± 10 ms p = 0.02. Comparison subgroup with an effective area of less than 1 cm2: Vmax 5.7 ± 1.2 m/s and 4.7 ± 0.7 m/s p = 0.001, Gmean 54 ± 15 and 43 ± 11 mm Hg p < 0.001, AT 127 ± 20 ms and 112 ± 10 ms p = 0.002.Conclusion. Echocardiographic indicators of Vmax and Gmean in patients with bivalve AC structure have higher values than in patients with tricuspid AC structure with a comparable opening area.


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