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Abdominal aortic aneurysm (AAA) is a critical health disorder, where the abdominal aorta dilates more than 50% of its normal diameter. Enlargement in abdominal aorta alters the hemodynamics and flow-induced forces on the AAA wall. Depending on the flow conditions, the hemodynamic forces on the wall may result in excessive mechanical stresses that lead to AAA rupture. The risk of rupture can be predicted using advanced computational techniques such as computational fluid dynamics (CFD) and fluid–structure interaction (FSI). For a reliable rupture risk assessment, formation of intraluminal thrombus (ILT) and uncertainty in arterial material properties should be taken into account, mainly due to the patient-specific differences and unknowns in AAAs. In this study, AAA models are computationally investigated by performing CFD simulations combined with FSI analysis. Various levels of ILT burdens are artificially generated in a realistic AAA geometry, and the peak effective stresses are evaluated to elucidate the effect of material models and ILT formation. The results indicate that increasing the ILT burden leads to lowered effective stresses on the AAA wall. The material properties of the artery and ILT are also effective on the stresses; however, these effects are limited compared to the effect of ILT volume in the AAA sac.

Collectively known as congenital heart defects (CHDs), cardiac abnormalities at birth are the most common forms of neonatal defects. Being principally responsible for the heart‘s pumping power, ventricles are particularly affected by developmental abnormalities, such as flow disturbances or genomic defects. Hypoplastic Right Heart Syndrome (HRHS) is a rare disease where the right ventricle is underdeveloped. In this study, we introduce a surgical procedure performed on chick embryo, termed right atrial ligation (RAL) for disturbing hemodynamics within the right heart aiming in order to generate an animal model of HRHS. RAL is a new surgical manipulation, similar to the well-studied left atrial ligation (LAL) surgery but it induces the hemodynamic change into the right side of the heart. After inducing RAL, We utilized techniques such as Doppler ultrasound, x-ray micro-CT, histology, and computational fluid dynamics (CFD) analysis, for a comprehensive functional and structural analysis of a developing heart. Our results displayed that RAL does not induce severe flow disturbance and ventricular abnormalities consistent with clinical findings. This study allows us to better understand the hemodynamics-driven CHD development and sensitivities of ventricles under disturbed flows.

Congenital heart defects (CHDs) affect a wide range of societies with an incidence rate of 1.0–1.2%. These defects initiate at the early developmental stage and result in critical health disorders. Although genetic factors play a role in the formation of CHDs, the occurrence of cases in families with no history of CHDs suggests that mechanobiological forces may also play a role in the initiation and progression of CHDs. Hypoplastic left heart syndrome (HLHS) is a critical CHD, which is responsible for 25–40% of all prenatal cardiac deaths. The comparison of healthy and HLHS hearts helps in understanding the main hemodynamic differences related to HLHS. Echocardiography is the most common imaging modality utilized for fetal cardiac assessment. In this study, we utilized echocardiographic images to compare healthy and HLHS human fetal hearts for determining the differences in terms of heart chamber dimensions, valvular flow rates, and hemodynamics. The cross-sectional areas of chamber dimensions are determined from 2D b-mode ultrasound images. Valvular flow rates are measured via Doppler echocardiography, and hemodynamic quantifications are performed with the use of computational fluid dynamics (CFD) simulations. The obtained results indicate that cross-sectional areas of the left and right sides of the heart are similar for healthy fetuses during gestational development. The left side of HLHS heart is underdeveloped, and as a result, the hemodynamic parameters such as flow velocity, pressure, and wall shear stress (WSS) are significantly altered compared to those of healthy hearts.

Flow-driven hemodynamic forces on the cardiac tissues have critical importance, and have a significant role in the proper development of the heart. These mechanobiological mechanisms govern the cellular responses for the growth and remodeling of the heart, where the altered hemodynamic environment is believed to be a major factor that is leading to congenital heart defects (CHDs). In order to investigate the mechanobiological development of the normal and diseased hearts, identification of the blood flow patterns and wall shear stresses (WSS) on these tissues are required for an accurate hemodynamic assessment. In this study, we focus on the left heart hemodynamics of the human fetuses throughout the gestational stages. Computational fetal left heart models are created for the healthy fetuses using the ultrasound images at various gestational weeks. Realistic inflow boundary conditions are implemented in the models using the Doppler ultrasound measurements for resolving the specific blood flow waveforms in the mitral valve. Obtained results indicate that WSS and vorticity levels in the fetal left heart decrease with the development of the fetus. The maximum WSS around the mitral valve is determined around 36 Pa at the gestational week of 16. This maximum WSS decreases to 11 Pa at the gestational week of 27, indicating nearly three-times reduction in the peak shear stress. These findings reveal the highly dynamic nature of the left heart hemodynamics throughout the development of the human fetus and shed light into the relevance of hemodynamic environment and development of CHDs.

Motile cilia are hair-like microscopic structures which generate directional flow to provide fluid transport in various biological processes. Ciliary beating is one of the sources of cerebrospinal flow (CSF) in brain ventricles. In this study, we investigated how the tilt angle, quantity, and phase relationship of cilia affect CSF flow patterns in the brain ventricles of zebrafish embryos. For this purpose, two-dimensional computational fluid dynamics (CFD) simulations are performed to determine the flow fields generated by the motile cilia. The cilia are modeled as thin membranes with prescribed motions. The cilia motions were obtained from a two-day post-fertilization zebrafish embryo previously imaged via light sheet fluorescence microscopy. We observed that the cilium angle significantly alters the generated flow velocity and mass flow rates. As the cilium angle gets closer to the wall, higher flow velocities are observed. Phase difference between two adjacent beating cilia also affects the flow field as the cilia with no phase difference produce significantly lower mass flow rates. In conclusion, our simulations revealed that the most efficient method for cilia-driven fluid transport relies on the alignment of multiple cilia beating with a phase difference, which is also observed in vivo in the developing zebrafish brain.

Calcification and bicuspid valve formation are important aortic valve disorders that disturb the hemodynamics and the valve function. The detailed analysis of aortic valve hemodynamics would lead to a better understanding of the disease’s etiology. We computationally modeled the aortic valve using simplified three-dimensional geometry and inlet velocity conditions obtained via echocardiography. We examined various calcification severities and bicuspid valve formation. Fluid-structure interaction (FSI) analyses were adapted using ANSYS Workbench to incorporate both flow dynamics and leaflet deformation accurately. Simulation results were validated by comparing leaflet movements in B-mode echo recordings. Results indicate that the biomechanical environment is significantly changed for calcified and bicuspid valves. High flow jet velocities are observed in the calcified valves which results in high transvalvular pressure difference (TPG). Wall shear stresses (WSS) increased with the calcification on both fibrosa (aorta side) and ventricularis (left ventricle side) surfaces of the leaflet. The WSS distribution is regular on the ventricularis, as the WSS values proportionally increase from the base to the tip of the leaflet. However, WSS patterns are spatially complex on the fibrosa side. Low WSS levels and spatially complex WSS patterns on the fibrosa side are considered as promoting factors for further calcification and valvular diseases.

Aortic valve calcification is an important cardiovascular disorder that deteriorates the accurate functioning of the valve leaflets. The increasing stiffness due to the calcification prevents the complete closure of the valve and therefore leads to significant hemodynamic alterations. Computational fluid dynamics (CFD) modeling enables the investigation of the entire flow domain by processing medical images from aortic valve patients. In this study, we computationally modeled and simulated a 3D aortic valve using patient-specific dimensions of the aortic root and aortic sinus. Leaflet stiffness is deteriorated in aortic valve disease due to calcification. In order to investigate the influence of leaflet calcification on flow dynamics, three different leaflet-stiffness values were considered for healthy, mildly calcified, and severely calcified leaflets. Time-dependent CFD results were used for applying the Lagrangian coherent structures (LCS) technique by performing finite-time Lyapunov exponent (FTLE) computations along with Lagrangian particle residence time (PRT) analysis to identify unique vortex structures at the front and backside of the leaflets. Obtained results indicated that the peak flow velocity at the valve orifice increased with the calcification rate. For the healthy aortic valve, a low-pressure field was observed at the leaflet tips. This low-pressure field gradually expanded through the entire aortic sinus as the calcification level increased. FTLE field plots of the healthy and calcified valves showed a variety of differences in terms of flow structures. When the number of fluid particles in the healthy valve model was taken as reference, 1.59 and 1.74 times more particles accumulated in the mildly and severely calcified valves, respectively, indicating that the calcified valves were not sufficiently opened to allow normal mass flow rates.

Abdominal aortic aneurysm (AAA) is the dilatation of the aorta beyond 50% of the normal vessel diameter. It is reported that 4–8% of men and 0.5–1% of women above 50 years of age bear an AAA and it accounts for ~15,000 deaths per year in the United States alone. If left untreated, AAA might gradually expand until rupture; the most catastrophic complication of the aneurysmal disease that is accompanied by a striking overall mortality of 80%. The precise mechanisms leading to AAA rupture remains unclear. Therefore, characterization of disturbed hemodynamics within AAAs will help to understand the mechanobiological development of the condition which will contribute to novel therapies for the condition. Due to geometrical complexities, it is challenging to directly quantify disturbed flows for AAAs clinically. Two other approaches for this investigation are computational modeling and experimental flow measurement. In computational modeling, the problem is first defined mathematically, and the solution is approximated with numerical techniques to get characteristics of flow. In experimental flow measurement, once the setup providing physiological flow pattern in a phantom geometry is constructed, velocity measurement system such as particle image velocimetry (PIV) enables characterization of the flow. We witness increasing number of applications of these complimentary approaches for AAA investigations in recent years. In this paper, we outline the details of computational modeling procedures and experimental settings and summarize important findings from recent studies, which will help researchers for AAA investigations and rupture mechanics.

The heart is the first functional organ in a developing embryo. Cardiac development continues throughout developmental stages while the heart goes through a serious of drastic morphological changes. Previous animal experiments as well as clinical observations showed that disturbed hemodynamics interfere with the development of the heart and leads to the formation of a variety of defects in heart valves, heart chambers, and blood vessels, suggesting that hemodynamics is a governing factor for cardiogenesis, and disturbed hemodynamics is an important source of congenital heart defects. Therefore, there is an interest to image and quantify the flowing blood through a developing heart. Flow measurement in embryonic fetal heart can be performed using advanced techniques such as magnetic resonance imaging (MRI) or echocardiography. Computational fluid dynamics (CFD) modeling is another approach especially useful when the other imaging modalities are not available and in-depth flow assessment is needed. The approach is based on numerically solving relevant physical equations to approximate the flow hemodynamics and tissue behavior. This approach is becoming widely adapted to simulate cardiac flows during the embryonic development. While there are few studies for human fetal cardiac flows, many groups used zebrafish and chicken embryos as useful models for elucidating normal and diseased cardiogenesis. In this paper, we explain the major steps to generate CFD models for simulating cardiac hemodynamics in vivo and summarize the latest findings on chicken and zebrafish embryos as well as human fetal hearts.

Intracranial aneurysm is the enlargement of an artery in the brain which may lead to rupture and result in serious health disorders. The exact mechanism of aneurysm formation is still unclear; however, the disturbed hemodynamics take part in the initiation of the vessel enlargement. In this study, a simplified intracranial aneurysm is numerically investigated to elucidate the disturbed flow conditions and the generated sound on the aneurysm wall. In order to determine the generated sound, the pressure fluctuations on the inner wall are obtained using computational fluid dynamics simulations. Large eddy simulation model is employed to find the unsteady flow pressures. The results indicate that the sound levels increase at the proximity of the intracranial aneurysm. The sound levels on the aneurysm are compared to the sound levels on the sites with normal vessel diameter, and it is seen that the aneurysm results in about 10 dB increase in the sound generation. This relative increase in the flow-generated sound is important in terms of the diagnosis of the intracranial aneurysms, which can be used as a diagnostic tool for the early detection of the aneurysm before facing with the serious symptoms.