Finite element modeling of blood flow-induced mechanical forces in the outflow tract of chick embryonic hearts

Forces exerted by the flow of blood on the walls of the embryonic heart, such as pressures and shear stresses, influence heart development; and deviations from normal flow conditions lead to structural defects. To better understand the effect of blood flow on the development of the heart, it is important to characterize the hemodynamic forces that act on the heart walls. Other studies have attempted to quantify such forces. However, shear stresses on the heart walls cannot be measured directly, and quantifications using in vivo velocity measurements are not yet accurate due to the challenges of obtaining velocity profiles near the moving walls of a beating heart. The objective of this work is to quantify hemodynamic forces on the heart wall of chick embryos that are about 3.5 days of incubation (stage HH21), using a combination of physiological data and finite element (FE) models. We focused on the heart outflow tract (OFT) since at this stage the development of the OFT is very sensitive to hemodynamic forces. In this paper, we present a three-dimensional dynamic FE model that is based on a series of ultrasound images of the OFT. Simulations of the FE model, performed for the ventricular ejection phase of the cardiac cycle, showed a complex blood flow pattern within the OFT and gave temporal and spatial distributions of shear stresses and pressures at the inner surface of the OFT wall.     

Quantifying blood flow and wall shear stresses in the outflow tract of chick embryonic hearts

Wall shear stresses (WSS) exerted by blood flow on cardiac tissues modulate growth and development of the heart. To study the role of hemodynamic conditions on cardiac morphogenesis, here, we present a methodology that combines imaging and finite element modeling to quantify the in vivo blood flow dynamics and WSS in the cardiac outflow tract (OFT) of early chicken embryos (day 3 out of 21-day incubation period). We found a distinct blood flow field and heterogeneous distribution of WSS in the chicken embryonic heart OFT, which have physiological implications for OFT morphogenesis.     

On the influence of the wall shear stress vector form on hemodynamic indicators

Hemodynamic indicators such as the averaged wall shear stress (AWSS) and the oscillatory shear index (OSI) are well established to characterize areas of arterial walls with respect to the formation and progression of aneurysms. Here, we study two different forms for the wall shear stress vector from which AWSS and OSI are computed. One is commonly used as a generalization from the two-dimensional setting, the latter is derived from the full decomposition of the wall traction force given by the Cauchy stress tensor. We compare the influence of both approaches on hemodynamic indicators by numerical simulations under different computational settings. Namely, different (real and artificial) vessel geometries, and the influence of a physiological periodic inflow profile. The blood is modeled either as a Newtonian fluid or as a generalized Newtonian fluid with a shear rate dependent viscosity. Numerical results are obtained by using a stabilized finite element method. We observe profound differences in hemodynamic indicators computed by these two approaches, mainly at critical areas of the arterial wall.

     

Numerical simulations of pulsatile non-Newtonian flow in an end-to-side anastomosis model

A potential interaction between the local hemodynamics and the artery wall response has been suggested for vascular graft failure by intimal hyperplasia (IH). Among the various hemodynamic factors, wall shear has been implicated as the primary factor responsible for the development of IH. In order to explore the role of hemodynamics in the formation of IH in end-to-side anastomosis, computational fluid dynamics is employed. To validate the numerical simulations, comparisons with existing experimental data are performed for both steady and pulsatile flows. Generally, good agreement is observed with the velocity profiles whereas some discrepancies are found in wall shear stress (WSS) distributions. Using the same end-to-side anastomosis geometry, numerical simulations are extended using a femoral artery waveform to identify the possible role of unsteady hemodynamics. In the current simulations, Carreau–Yasuda model is used to account for the non-Newtonian nature of the blood. Computations indicated a disturbed flow field at the artery-graft junction leading to locally elevated shear stresses on the vascular wall. Furthermore, the shear stress distribution followed the same behavior with oscillating magnitude over the entire flow cycle. Thus, distal IH observed in end-to-side artery-graft models may be caused by the fluctuations in WSS’s along the wall.     

One-information suboptimal control repercussion on the fine structure of wall turbulence

The suboptimal control with the cost function directly connected to the wall shear and introduced for a while has been revisited through direct numerical simulations of high temporal and spatial resolution. Its effect on the fine structure of the wall turbulence has been analyzed in details, essentially through the spanwise vorticity transport mechanism. It is shown that only half of the viscous sublayer is mainly affected by the control. The actuation efficiency is limited in terms of the wall shear stress reduction, but is high as long as the turbulent wall activity is concerned. The wall shear stress is reduced due both to the reduction of the shear production in the viscous sublayer and to the contribution of the turbulent body force. The dissipation involving in the streamwise vorticity fluctuations transport equation increases significantly and overcomes the production in a thin layer near the wall leading to a drastic diminution of the turbulent wall shear stress fluctuations.     

Classification of cardiac sound signals using constrained tunable-Q wavelet transform

The features extracted from the cardiac sound signals are commonly used for detection and identification of heart valve disorders. In this paper, we present a new method for classification of cardiac sound signals using constrained tunable-Q wavelet transform (TQWT). The proposed method begins with a constrained TQWT based segmentation of cardiac sound signals into heart beat cycles. The features obtained from heart beat cycles of separately reconstructed heart sounds and murmur can better represent the various types of cardiac sound signals than that from containing both. Therefore, heart sounds and murmur have been separated using constrained TQWT. Then the proposed novel raw feature set has been created by the parameters that have been optimized while constraining the output of TQWT together with that of extracted by using time-domain representation and Fourier–Bessel (FB) expansion of separated heart sounds and murmur. However, the adaptively selected features have been used to obtain the final feature set for subsequent classification of cardiac sound signals using least squares support vector machine (LS-SVM) with various kernel functions. The performance of the proposed method has been validated with publicly available datasets and the results have been compared with the existing short-time Fourier transform (STFT) based method. The proposed method shows higher percentage classification accuracy of 94.01 as compared to 93.53 of STFT based method. In comparison with STFT based method, it is noteworthy that the proposed method uses well defined and lower dimensionality of feature vector that can reduce the computational complexity.     

Influence of wall elasticity in patient-specific hemodynamic simulations

Recent reports indicate that the rupture risk for cerebral aneurysms is less than the risk of surgical complications. Being able to predict the rupture of aneurysms would help making better-informed decisions and avoiding unnecessary surgical operations. The wall shear stress is known to play an important role in vascular diseases. We carry out computational fluid-structure interaction analyses to investigate the influence of the arterial-wall deformation on the hemodynamic factors, including the wall shear stress distribution. The results show various patterns of this influence, depending very much on the arterial geometry.     

Automatic identification of cardiac health using modeling techniques: A comparative study

Heart rate variability (HRV), a widely adopted quantitative marker of the autonomic nervous system can be used as a predictor of risk of cardiovascular diseases. Moreover, decreased heart rate variability (HRV) has been associated with an increased risk of cardiovascular diseases. Hence in this work HRV signal is used as the base signal for predicting the risk of cardiovascular diseases. The present study concerns nine cardiac classes that include normal sinus rhythm (NSR), congestive heart failure (CHF), atrial fibrillation (AF), ventricular fibrillation (VF), preventricular contraction (PVC), left bundle branch block (LBBB), complete heart block (CHB), ischemic/dilated cardiomyopathy (ISCH) and sick sinus syndrome (SSS). A total of 352 cardiac subjects belonging to the nine classes were analyzed in the frequency domain. The fast Fourier transforms (FFT) and three other modeling techniques namely, autoregressive (AR) model, moving average (MA) model and the autoregressive moving average (ARMA) model are used to estimate the power spectral densities of the RR interval variability. The spectral parameters obtained from the spectral analysis of the HRV signals are used as the input parameters to the artificial neural network (ANN) for classification of the different cardiac classes. Our findings reveal that the ARMA modeling technique seems to give better resolution and would be more promising for clinical diagnosis.     

Cascade force control for autonomous beating heart motion compensation

Robotic-assisted heart surgeries do not allow autonomous compensation of cardiac motion. This paper tackles this problem, based on a robotic control architecture that relies on force feedback, without requiring vision data. The algorithm merges two cascade loops. The inner one is based on the Kalman active observer (AOB) for model-reference adaptive control and the outer one based on a model predictive control (MPC) approach generates control references for beating heart motion compensation. A 4-DoF surgical robot generates desired surgical forces and a 3-DoF robot equipped with an ex vivo heart at the end-effector reproduces realistic heart motion.     

Blood flow dynamics and arterial wall interaction in a saccular aneurysm model of the basilar artery

Blood flow dynamics under physiologically realistic pulsatile conditions plays an important role in the growth, rupture and surgical treatment of intracranial aneurysms. This paper describes the flow dynamics and arterial wall interaction in a representative model of a terminal aneurysm of the basilar artery, and compares its wall shear stress, pressure, effective stress and wall deformation with those of a healthy basilar artery. The arterial wall was assumed to be elastic or hyperelastic, isotropic, incompressible and homogeneous. The flow was assumed to be laminar, Newtonian, and incompressible. The fully coupled fluid and structure models were solved with the finite elements package ADINA. The intra-aneurysmal pulsatile flow shows single recirculation region during both systole and diastole. The pressure and shear stress on the aneurysm wall exhibit large temporal and spatial variations. The wall thickness, the Young’s modulus in the elastic wall model and the hyperelastic Mooney-Rivlin wall model affect the aneurysm deformation and effective stress in the wall especially at systole.