A review study on blood in human coronary artery: Numerical approach

Numerical investigation of LDL nanoparticle collision in coronary artery grafts with porous wall and different implantation angles and two state of inlet velocity

This study aimed to reduce the risk of graft occlusion by evaluating the two-phase flow of blood and LDL nanoparticles in coronary artery grafts. The study considered blood as an incompressible Newtonian fluid, with the addition of LDL nanoparticles, and the artery wall as a porous medium. Two scenarios were compared, with constant inlet velocity (CIV) and other with pulsatile inlet velocity (PIV), with LDL nanoparticles experiencing drag, wall-induced lift, and induced Saffman lift forces, or drag force only. The study also evaluated the concentration polarization of LDLs (CP of LDLs) near the walls, by considering the artery wall with and without permeation. To model LDL nanoparticles, the study randomly injected 100, 500, and 1000 nanoparticles in three release states at each time step, using different geometries. Numerical simulations were performed using COMSOL software, and the results were presented as relative collision of nanoparticles to the walls in tables, diagrams, and shear stress contours. The study found that a graft implantation angle of 15° had the most desirable conditions compared to larger angles, in terms of nanoparticle collision with surfaces and occlusion. The nanoparticle release modes behaved similarly in terms of collision with the surfaces. A difference was observed between CIV and PIV. Saffman lift and wall-induced lift forces having no effect, possibly due to the assumption of a porous artery wall and perpendicular outlet flow. In case of permeable artery walls, relative collision of particles with the graft wall was larger, suggesting the effect of CP of LDLs.

Experimental and numerical investigation of the stenosed coronary artery taken from the clinical setting and modeled in terms of hemodynamics

The study was carried out to investigate the effect of the artery with different pulse values and stenosis rates on the pressure drop, the peristaltic pump outlet pressure, fractional flow reserve (FFR) and most importantly the amount of power consumed by the peristaltic pump. For this purpose, images taken from the clinical environment were produced as models (10 mm inlet diameter) with 0% and 70% percent areal stenosis rates (PSR) on a three-dimensional (3D) printer. In the experimental system, pure water was used as the fluid at 54, 84, 114, 132, and 168 bpm pulse values. In addition, computational fluid dynamics (CFD) analyzes of the test region were performed using experimental boundary conditions with the help of ANSYS-Fluent software. The findings showed that as PSR increases in the arteries, the pressure drop in the stenosis region increases and this amount increases dramatically with increasing effort. An increase of approximately 40% was observed in the pump outlet pressure value from 54 bpm to 168 bpm in the PSR 0% model and 51% increase in the PSR 70% model. It has been observed that the pump does more work to overcome the increased pressure difference due to increased pulse rate and PSR. With the effect of contraction, the power consumption of the pump increased from 9.2% for 54 bpm to 13.8% for 168 bpm. In both models, the Wall Shear Stress (WSS) increased significantly. WSS increased abruptly in the stenosis and arcuate regions, while sudden decreases were observed in the flow separation region.

Effect of rheological models on pulsatile hemodynamics in a multiply afflicted descending human aortic network

In the cardiovascular diseased (CVD) conditions, it is essential to choose a suitable rheological model for capturing the correct physics behind the hemodynamic in the multiply afflicted diseased arterial network. This study investigates the effect of blood rheology on hemodynamics in a blood vessel with abdominal aortic aneurysm (AAA) and right internal iliac stenosis (RIIAS). A model with AAA and RIIAS is reconstructed from a human subject's computed tomography (CT) data. Localized mesh generation and pulsatile inflow condition are considered. Non-Newtonian models such as the Power-law, Carreau, Cross, and Herschel Berkley models are used in simulations. The outcome from a validated computational model is compared with the Newtonian model to identify the suitable model for dealing with pathological complications under consideration. The capabilities and significance of various rheological models are also examined via Wall Pressure (WP), Wall Shear Stress (WSS), velocity, Global non-Newtonian importance factor (IG), Vorticity Streamlines, and Swirling Strength. It is noted that during the entire cardiac cycle, the IG factor of the cross model is found to be relatively more significant. Power Law depicts larger IG factor during peak systole and early diastole. Also, the cross model depicts larger WSS, WPS, swirling strength distribution and vorticity during the peak systolic and diastolic phases It is noted that IG ∼0.02 is an appropriate non-Newtonian blood activity cut-off value in the descending abdominal artery having AAA and RIIAS. The critical important WSS values are in the range of 0-9 Pa which is stated in WSS contour plot.

Modelling blood flow in coronary arteries: Newtonian or shear-thinning non-Newtonian rheology?

BACKGROUND

The combination of medical imaging and computational hemodynamics is a promising technology to diagnose/prognose coronary artery disease (CAD). However, the clinical translation of in silico hemodynamic models is still hampered by assumptions/idealizations that must be introduced in model-based strategies and that necessarily imply uncertainty. This study aims to provide a definite answer to the open question of how to properly model blood rheological properties in computational fluid dynamics (CFD) simulations of coronary hemodynamics.

METHODS

The geometry of the right coronary artery (RCA) of 144 hemodynamically stable patients with different stenosis degree were reconstructed from angiography. On them, unsteady-state CFD simulations were carried out. On each reconstructed RCA two different simulation strategies were applied to account for blood rheological properties, implementing (i) a Newtonian (N) and (ii) a shear-thinning non-Newtonian (non-N) rheological model. Their impact was evaluated in terms of wall shear stress (WSS magnitude, multidirectionality, topological skeleton) and helical flow (strength, topology) profiles. Additionally, luminal surface areas (SAs) exposed to shear disturbances were identified and the co-localization of paired N and non-N SAs was quantified in terms of similarity index (SI).

RESULTS

The comparison between paired N vs. shear-thinning non-N simulations revealed remarkably similar profiles of WSS-based and helicity-based quantities, independent of the adopted blood rheology model and of the degree of stenosis of the vessel. Statistically, for each paired N and non-N hemodynamic quantity emerged negligible bias from Bland-Altman plots, and strong positive linear correlation (r > 0.94 for almost all the WSS-based quantities, r > 0.99 for helicity-based quantities). Moreover, a remarkable co-localization of N vs. non-N luminal SAs exposed to disturbed shear clearly emerged (SI distribution 0.95 [0.93, 0.97]). Helical flow topology resulted to be unaffected by blood rheological properties.

CONCLUSIONS

This study, performed on 288 angio-based CFD simulations on 144 RCA models presenting with different degrees of stenosis, suggests that the assumptions on blood rheology have negligible impact both on WSS and helical flow profiles associated with CAD, thus definitively answering to the question "is Newtonian assumption for blood rheology adequate in coronary hemodynamics simulations?".

A simplified coronary model for diagnosis of ischemia-causing coronary stenosis

BACKGROUND AND OBJECTIVE

The functional assessment of the severity of coronary stenosis from coronary computed tomography angiography (CCTA)-derived fractional flow reserve (FFR) has recently attracted interest. However, existing algorithms run at high computational cost. Therefore, this study proposes a fast calculation method of FFR for the diagnosis of ischemia-causing coronary stenosis.

METHODS

We combined CCTA and machine learning to develop a simplified single-vessel coronary model for rapid calculation of FFR. First, a zero-dimensional model of single-vessel coronary was established based on CCTA, and microcirculation resistance was determined through the relationship between coronary pressure and flow. In addition, a coronary stenosis model based on machine learning was introduced to determine stenosis resistance. Computational FFR (cFFR) was then obtained by combining the zero-dimensional model and the stenosis model with inlet boundary conditions for resting (cFFRr) and hyperemic (cFFRh) aortic pressure, respectively. We retrospectively analyzed 75 patients who underwent clinically invasive FFR (iFFR), and verified the model accuracy by comparison of cFFR with iFFR.

RESULTS

The average computing time of cFFR was less than 2 s. The correlations between cFFRr and cFFRh with iFFR were r = 0.89 (p < 0.001) and r = 0.90 (p < 0.001), respectively. Diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio for cFFRr and cFFRh were 90.7%, 95.0%, 89.1%, 76.0%, 98.0%, 8.7, 0.1 and 92.0%, 95.0%, 90.9%, 79.2%, 98.0%, 10.5, 0.1, respectively.

CONCLUSIONS

The proposed model enables rapid prediction of cFFR and exhibits high diagnostic performance in selected patient cohorts. The model thus provides an accurate and time-efficient computational tool to detect ischemia-causing stenosis and assist with clinical decision-making.

Contrast-Enhanced Ultrasound Feasibility in Assessing Carotid Plaque Vulnerability-Narrative Review

The risk assessment for carotid atherosclerotic lesions involves not only determining the degree of stenosis but also plaque morphology and its composition. Recently, carotid contrast-enhanced ultrasound (CEUS) has gained importance for evaluating vulnerable plaques. This review explores CEUS's utility in detecting carotid plaque surface irregularities and ulcerations as well as intraplaque neovascularization and its alignment with histology. Initial indications suggest that CEUS might have the potential to anticipate cerebrovascular incidents. Nevertheless, there is a need for extensive, multicenter prospective studies that explore the relationships between CEUS observations and patient clinical outcomes in cases of carotid atherosclerotic disease.

The Application of Deep Learning for the Segmentation and Classification of Coronary Arteries

In recent years, the prevalence of coronary artery disease (CAD) has become one of the leading causes of death around the world. Accurate stenosis detection of coronary arteries is crucial for timely treatment. Cardiologists use visual estimations when reading coronary angiography images to diagnose stenosis. As a result, they face various challenges which include high workloads, long processing times and human error. Computer-aided segmentation and classification of coronary arteries, as to whether stenosis is present or not, significantly reduces the workload of cardiologists and human errors caused by manual processes. Moreover, deep learning techniques have been shown to aid medical experts in diagnosing diseases using biomedical imaging. Thus, this study proposes the use of automatic segmentation of coronary arteries using U-Net, ResUNet-a, UNet++, models and classification using DenseNet201, EfficientNet-B0, Mobilenet-v2, ResNet101 and Xception models. In the case of segmentation, the comparative analysis of the three models has shown that U-Net achieved the highest score with a 0.8467 Dice score and 0.7454 Jaccard Index in comparison with UNet++ and ResUnet-a. Evaluation of the classification model's performances has shown that DenseNet201 performed better than other pretrained models with 0.9000 accuracy, 0.9833 specificity, 0.9556 PPV, 0.7746 Cohen's Kappa and 0.9694 Area Under the Curve (AUC).

Alteration in membrane-based pumping flow with rheological behaviour: A mathematical model

BACKGROUND AND OBJECTIVE

Blood is complex fluids exhibits the non-Newtonian characters and rheological properties of the blood vary person to person. Typically, the rheological properties of blood are very similar to Carreau fluids which is considered in the present model. The main objective of this study is to examine how a typical membrane-based pumping model will function with varying rheological properties (shear-thinning, Newtonian, and shear-thickening) of fluids.

METHODS

A mathematical formulation is constructed for the membrane-based pumping model using the conservation principles of mass and momentum, and stress-strain relationship based on Carreau fluids model. Velocity slip condition is adopted for this model to discuss the possibility of fluids velocity at the wall surface. The perturbation method is employed to derive the series solution for the governing equations subjected to physical boundary conditions with suitable assumptions.

RESULTS

From numerical results, it is found that the pressure inside the microchannel reduces for the shear-thinning fluid and increases for the shear-thickening fluid with increasing the Weissenberg. In the membrane region, the chaos of the flow field is occurred due to the local pressure gradient by the rhythmic membrane propagation. It is further reported that shear-driven flow is responsible for the decrement in fluid velocity.

CONCLUSIONS

This model provides a framework for estimating the effects of rheological properties and velocity slip for membrane-based pumping model which help in designing the smart pumps for various needs in the fields of biomedical engineering and fluid industries.

Computational Study of Hemodynamic Field of an Occluded Artery Model with Anastomosis

In this research work, the hemodynamic field of an occluded artery with anastomosis by means of computational simulation has been studied. The main objective of the current study is the investigation of 3D flow field phenomena in the by-pass region and the effect of the bypass graft to stenosis volume flow ratio on their formation. The anastomosis type was end-to-side with a 45° angle, while stenosis imposed a 75% area blockage of the aorta vessel and the total volume flow was 220 lt/h. The computational study of the flow field was utilized via a laminar flow model and three turbulence models (k-ε RNG, standard k-ω, and k-ω SST). Numerical results were compared qualitatively with experimental visualizations carried out under four different flow conditions, varying according to the flow ratio between the stenosis and the anastomotic graft. Comparison between computational results and experimental visualization findings exhibited a good agreement. Results showed that SST k-ω turbulence models reproduce better visually obtained flow patterns. Furthermore, cross-sectional velocity distributions demonstrated two distinct flow patterns down the bypass graft, depending on the flow ratio. Low values of flow ratio are characterized by fluid rolling up, whereas for high values fluid volume twisting was observed. Finally, areas with low wall shear stresses were mapped, as these are more prone to postoperative degradation of the bypass graft due to the development of subendothelial hyperplasia.

Mechanisms of the ascites volume differences between patients receiving a left or right hemi-liver graft liver transplantation: From biofluidic analysis

BACKGROUND AND OBJECTIVE

Post-transplant refractory ascites (RA) is common in patients receiving living donor liver transplantation (LDLT) using a left hemi-liver graft than in those using a right hemi-liver graft. However, there is currently no clear mechanism explaining the effect of grafts on ascites drainage. The purpose of this study is to analyze the values of blood flow parameters in the portal vein under different grafts using computational fluid dynamics (CFD) to interpret the relationship between portal pressure values with ascites drainage.

METHODS

In this work, ascites drainage was counted in 30 patients who underwent left-sided liver transplantation and 26 patients who underwent right-sided liver transplantation. The portal vein flow models of the transplanted liver under different flow rates were established based on computed tomography (CT) images and finite element theory. Ascites drainage and blood flow parameters were qualitatively compared.

RESULTS

The results show that the ascites drained from patients who received LDLT with a left hemi-liver is three times as that with a right hemi-liver. The simulation results show that the coefficient of the pressure-velocity curve of the left-liver is 1.7 times of the right-liver under the same hydrodynamic conditions, which qualitatively agrees with the clinical data. Moreover, the streamline of the transplanted left liver shows more vortexes compared with the right liver, which is a major reason for the left liver's higher pressure value.

CONCLUSION

This clinical phenomenon is reproduced and comprehensively explained by the hemodynamic parameters of the portal vein. This work establishes the relationship between portal pressure values and floating water drainage, and offers a new way for physicians to predict postoperative risks intuitively.

Non-invasive diagnostics of blockage growth in the descending aorta-computational approach

Atherosclerosis causes blockages to the main arteries such as the aorta preventing blood flow from delivering oxygen to the organs. Non-invasive diagnosis of these blockages is difficult, particularly in primary healthcare. In this paper, the effect of arterial blockage development and growth is investigated at the descending aorta on some possible non-invasive assessment parameters including the blood pressure waveform, wall shear stress (WSS), time-average WSS (TAWSS) and the oscillation shear index (OSI). Blockage severity growth is introduced in a simulation model as 25%, 35%, 50% and 65% stenosis at the descending aorta based on specific healthy control aorta data clinically obtained. A 3D aorta model with invasive pulsatile waveforms (blood flow and pressure) is used in the CFD simulation. Blockage severity is assessed by using blood pressure measurements at the left subclavian artery. An arterial blockage growth more than 35% of the lumen diameter significantly affects the pressure. A strong correlation is also observed between the ascending aorta pressure values, pressure at the left subclavian artery and the relative residence time (RRT). An increase of RRT downstream from the stenosis indicates a 35% stenosis at the descending aorta which results in high systolic and diastolic pressure readings. The findings of this study could be further extended by transferring the waveform reading from the left subclavian artery to the brachial artery.

Graphical abstract

A proof-of-concept study for the simulation of blood flow in a post arterial segment for different blood rheology models

Cardiovascular disease (CVD) and especially atherosclerosis are chronic inflammatory diseases which cause the atherosclerotic plaque growth in the arterial vessels and the blood flow reduction. Stents have revolutionized the treatment of this disease to a great extent by restoring the blood flow in the vessel. The present study investigates the performance of the blood flow after stent implantation in patient-specific coronary artery and demonstrates the effect of using Newtonian vs. non-Newtonian blood fluid models in the distribution of endothelial shear stress. In particular, the Navier-Stokes and continuity equations were employed, and three non-Newtonian fluid models were investigated (Carreau, Carreau-Yasuda and the Casson model). Computational finite elements models were used for the simulation of blood flow. The comparison of the results demonstrates that the Newtonian fluid model underestimates the calculation of Endothelial Shear Stress, while the three non-Newtonian fluids present similar distribution of shear stress. Keywords: Blood flow dynamics, stented artery, non-Newtonian fluid. Clinical Relevance- This work demonstrates that when blood flow modeling is performed at stented arteries and predictive models are developed, the non-Newtonian nature of blood must be considered.

A Study of the Fluid–Structure Interaction of the Plaque Circumferential Distribution in the Left Coronary Artery

Atherosclerotic plaques within the coronary arteries can prevent blood from flowing to downstream tissues, causing coronary heart disease and a myocardial infarction over time. The degree of stenosis is an important reference point during percutaneous coronary intervention (PCI). However, clinically, patients with the same degree of stenosis exhibit different degrees of disease severity. To investigate the connection between this phenomenon and the plaque circumferential distribution, in this paper, four models with different plaque circumferential locations were made based on the CT data. The blood in the coronary arteries was simulated using the fluid–structure interaction method in ANSYS Workbench software. The results showed that the risk of plaque rupture was less affected by the circumferential distribution of plaque, and the distribution of blood in each branch was affected by the circumferential distribution of plaque. Low TAWSS areas were found posterior to the plaque, and the TAWSS < 0.4 Pa area was ranked from highest to lowest in each model species: plaque on the side away from the left circumflex branch, plaque on the side away from the heart; plaque on the side close to the heart; and plaque on the side close to the left circumflex branch. The same trend was also found in the OSI. It was concluded that the circumferential distribution of plaques affects their further development. This finding will be useful for clinical treatment.

A modified method of noninvasive computed tomography derived fractional flow reserve based on the microvascular growth space

OBJECTIVE

To establish a modified method for optimizing outlet boundary conditions (BC) of computed tomography-derived fractional flow reserve (CT-FFR), considering the myocardium as a growth space for microcirculation. The feasibility and diagnostic performance of the modified method in stable coronary artery disease (CAD) were compared with invasive fractional flow reserve (FFR).

METHODS

Nineteen patients (19 lesions) underwent coronary computed tomography angiography (CCTA) and following invasive FFR were included. The microcirculation resistance model generated based on patient-specific anatomical structures and physiological principles was used as the outlet BC, considering the myocardium as a growth space. Brachial artery pressure (BAP) plus or minus 10 mmHg was used as the inlet pressure BC to investigate the effect of the circadian rhythm. After simulation, CT-FFR was compared with invasive FFR with a threshold of 0.80.

RESULTS

Compared with invasive FFR, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of CT-FFR with an optimal threshold of 0.80 were 100%, 100%, 100%, 100%, 100%, respectively. There were a good correlation and consistency between CT-FFR and invasive FFR. Little effect of the circadian fluctuation of BAP was found on the simulation.

CONCLUSIONS

A modified method for CT-FFR with high diagnostic accuracy compared with invasive FFR was established, considering the whole myocardial as the growth space for microcirculation. Circadian fluctuations in BAP could be ignored when it was used as the inlet BC.

Modelling coronary flows: impact of differently measured inflow boundary conditions on vessel-specific computational hemodynamic profiles

BACKGROUND AND OBJECTIVES

The translation of hemodynamic quantities based on wall shear stress (WSS) or intravascular helical flow into clinical biomarkers of coronary atherosclerotic disease is still hampered by the assumptions/idealizations required by the computational fluid dynamics (CFD) simulations of the coronary hemodynamics. In the resulting budget of uncertainty, inflow boundary conditions (BCs) play a primary role. Accordingly, in this study we investigated the impact of the approach adopted for in vivo coronary artery blood flow rate assessment on personalized CFD simulations where blood flow rate is used as inflow BC.

METHODS

CFD simulations were carried out on coronary angiograms by applying personalized inflow BCs derived from four different techniques assessing in vivo surrogates of flow rate: continuous thermodilution, intravascular Doppler, frame count-based 3D contrast velocity, and diameter-based scaling law. The impact of inflow BCs on coronary hemodynamics was evaluated in terms of WSS- and helicity-based quantities.

RESULTS

As main findings, we report that: (i) coronary flow rate values may differ based on the applied flow derivation technique, as continuous thermodilution provided higher flow rate values than intravascular Doppler and diameter-based scaling law (p = 0.0014 and p = 0.0023, respectively); (ii) such intrasubject differences in flow rate values lead to different surface-averaged values of WSS magnitude and helical blood flow intensity (p<0.0020); (iii) luminal surface areas exposed to low WSS and helical flow topological features showed robustness to the flow rate values.

CONCLUSIONS

Although the absence of a clinically applicable gold standard approach prevents a general recommendation for one coronary blood flow rate derivation technique, our findings indicate that the inflow BC may impact computational hemodynamic results, suggesting that a standardization would be desirable to provide comparable results among personalized CFD simulations of the coronary hemodynamics.

INVESTIGATION OF FLOW IN AN IDEALIZED CURVED ARTERY: COMPARATIVE STUDY USING CFD AND FSI WITH NEWTONIAN AND NON-NEWTONIAN FLUIDS

Artery curvatures, where disturbed flow patterns are expected, are preferred sites of formation of atherosclerosis. Experimental studies have shown that low and oscillating wall shear stress (WSS) plays an important role in the development and progression of atherosclerosis. Accurate estimation of these biomechanical parameters is important to assess the risk of atherosclerosis formation. The coupled effects of non-Newtonian behavior of blood and artery wall flexibility for the transient blood flow through an idealized curved coronary artery are investigated using computational fluid dynamics (CFD) as well as fluid–structure interaction (FSI) simulations. The choice of fluid model, Carreau and Newtonian, was found to impact the time averaged and minimum WSS values. The effects of wall deformation on time averaged wall shear tress were negligible. However, a comparison of temporal minima of WSS along the curvature showed significant variations between CFD and FSI simulations. Since low WSS values are crucial in the prediction of atherosclerosis development, it is concluded that both the non-Newtonian behavior of blood and the wall flexibility should be considered for computational studies.

A Comparative Study on the Hemodynamic Performance Within Cross and Non-cross Stent-Grafts for Abdominal Aortic Aneurysms With an Angulated Neck

Objectives: Cross-limb stent grafts for endovascular aneurysm repair (EVAR) are often employed for abdominal aortic aneurysms (AAAs) with significant aortic neck angulation. Neck angulation may be coronal or sagittal; however, previous hemodynamic studies of cross-limb EVAR stent grafts (SGs) primarily utilized simplified planar neck geometries. This study examined the differences in flow patterns and hemodynamic parameters between crossed and non-crossed limb SGs at different spatial neck angulations.

Methods: Ideal models consisting of 13 cross and 13 non-cross limbs were established, with coronal and sagittal angles ranging from 0 to 90°. Computational fluid dynamics (CFD) was used to capture the hemodynamic information, and the differences were compared.

Results: With regards to the pressure drop index, the maximum difference caused by the configuration and angular direction was 4.6 and 8.0%, respectively, but the difference resulting from the change in aneurysm neck angle can reach 27.1%. With regards to the SAR-TAWSS index, the maximum difference caused by the configuration and angular direction was 7.8 and 9.8%, respectively, but the difference resulting from the change in aneurysm neck angle can reach 26.7%. In addition, when the aneurysm neck angle is lower than 45°, the configuration and angular direction significantly influence the OSI and helical flow intensity index. However, when the aneurysm neck angle is greater than 45°, the hemodynamic differences of each model at the same aneurysm neck angle are reduced.

Conclusion: The main factor affecting the hemodynamic index was the angle of the aneurysm neck, while the configuration and angular direction had little effect on the hemodynamics. Furthermore, when the aneurysm neck was greatly angulated, the cross-limb technique did not increase the risk of thrombosis.

Mathematical modeling of plaque progression and associated microenvironment: How far from predicting the fate of atherosclerosis?

Mathematical modeling contributes to pathophysiological research of atherosclerosis by helping to elucidate mechanisms and by providing quantitative predictions that can be validated. In turn, the complexity of atherosclerosis is well suited to quantitative approaches as it provides challenges and opportunities for new developments of modeling. In this review, we summarize the current 'state of the art' on the mathematical modeling of the effects of biomechanical factors and microenvironmental factors on the plaque progression, and its potential help in prediction of plaque development. We begin with models that describe the biomechanical environment inside and outside the plaque and its influence on its growth and rupture. We then discuss mathematical models that describe the dynamic evolution of plaque microenvironmental factors, such as lipid deposition, inflammation, smooth muscle cells migration and intraplaque hemorrhage, followed by studies on plaque growth and progression using these modelling approaches. Moreover, we present several key questions for future research. Mathematical models can complement experimental and clinical studies, but also challenge current paradigms, redefine our understanding of mechanisms driving plaque vulnerability and propose future potential direction in therapy for cardiovascular disease.

Atheroprone sites of coronary artery bifurcation: Effect of heart motion on hemodynamics-dependent monocytes deposition

Atherosclerosis as a common cardiovascular disease is a result of both adverse hemodynamics conditions and monocyte deposition within coronary arteries. It is known that the adhesion of monocytes on the arterial wall and their interaction with the vascular surface are one of the main parameters in the initiation and progression of atherosclerosis. In this work, hemodynamic parameters and monocyte deposition have been investigated in a 3D computational model of the Left Anterior Descending coronary artery (LAD) and its first diagonal branch (D1) under the heart motion. A one-way Lagrangian approach is performed to trace the monocyte particles under different blood flow regimes and heart motion conditions. The hemodynamic results show that the myocardial wall, and also the flow divider wall can be candidates for atheroprone sites. The dynamic movement and pulsatile inlet changed the flow rate between branches about 21% compared to the static case and steady inlet. On the other hand, the calculation of monocytes' depositional behavior illustrates that they settle down downstream the LAD-D1 bifurcation and on the myocardial wall. The deposition rate is closely associated with the inlet type and changing the steady inlet to the sinusoidal and real physiologic profile showed a 150% increase in the deposition rate. These results ensure that the myocardial wall and LAD-D1 bifurcation are the desirable locations for atherosclerosis. These results are in good agreement with the clinical observations.

Application of physics-based flow models in cardiovascular medicine: Current practices and challenges

Personalized physics-based flow models are becoming increasingly important in cardiovascular medicine. They are a powerful complement to traditional methods of clinical decision-making and offer a wealth of physiological information beyond conventional anatomic viewing using medical imaging data. These models have been used to identify key hemodynamic biomarkers, such as pressure gradient and wall shear stress, which are associated with determining the functional severity of cardiovascular diseases. Importantly, simulation-driven diagnostics can help researchers understand the complex interplay between geometric and fluid dynamic parameters, which can ultimately improve patient outcomes and treatment planning. The possibility to compute and predict diagnostic variables and hemodynamics biomarkers can therefore play a pivotal role in reducing adverse treatment outcomes and accelerate development of novel strategies for cardiovascular disease management.

Effect of transport parameters on atherosclerotic lesion growth: A parameter sensitivity analysis

BACKGROUND

Atherosclerosis is a degenerative disease of the arterial wall. It results in the formation of progressively growing plaque lesions that can harden and narrow their host arteries. Current computational models of the inflammatory process that govern atherosclerosis growth are reliant on a number of parameters that can freely vary and whose precise values are not well known.

METHODS

To identify the significance of variation in such parameters, a parametric sensitivity study had been conducted on the blood density, blood viscosity, plasma viscosity and bulk flow low density lipoprotein (LDL) concentration. Using computational modeling, the significance of variation in these parameters was assessed on the transport of LDL. The simulation was performed via the 2^k factorial experimental design, which was conducted to identify the significance of the select parameters on the intima LDL concentration and endothelial LDL coverage area.

RESULTS

Results identified the blood viscosity and bulk flow LDL concentration are the dominant parameters for the atherosclerotic lesion growth. The coverage of LDL on the arterial wall surface was strongly dependent on the blood viscosity. The significance of these findings was discussed.

CONCLUSION

This statistical study identifies two dominating blood factors, LDL concentration and blood viscosity, and how they influence atherosclerosis which will serves as a guideline for further investigation on the atherosclerosis topic.

Blood Flow Modeling in Coronary Arteries: A Review

Atherosclerosis is one of the main causes of cardiovascular events, namely, myocardium infarction and cerebral stroke, responsible for a great number of deaths every year worldwide. This pathology is caused by the progressive accumulation of low-density lipoproteins, cholesterol, and other substances on the arterial wall, narrowing its lumen. To date, many hemodynamic studies have been conducted experimentally and/or numerically; however, this disease is not yet fully understood. For this reason, the research of this pathology is still ongoing, mainly, resorting to computational methods. These have been increasingly used in biomedical research of atherosclerosis because of their high-performance hardware and software. Taking into account the attempts that have been made in computational techniques to simulate realistic conditions of blood flow in both diseased and healthy arteries, the present review aims to give an overview of the most recent numerical studies focused on coronary arteries, by addressing the blood viscosity models, and applied physiological flow conditions. In general, regardless of the boundary conditions, numerical studies have been contributed to a better understanding of the development of this disease, its diagnosis, and its treatment.

Residual time of sinusoidal metachronal ciliary flow of non-Newtonian fluid through ciliated walls: fertilization and implantation

The monitoring of the ciliated walls in the uterine tube has supreme importance in enhancing the sperm to reach the egg (capacitation processes), and at peristaltic ciliary flow has a more favorable residual time along the canal when compared to the peristaltic flow. Based on the importance of this study, a mathematical simulation of this process has been carried out by studying the behavior of a non-Newtonian magnetized fluid with a Darcy flow model with an oscillating wall having an internal ciliated surface. The governing equation is formed with Eyring-Powell fluid (tubal fallopian fluid) without using any approximations and solved using the Adomian analysis method. Using the vorticity formula, the components of the velocity function, pressure gradient, and stream function are obtained. The influence of relevant parameters is explained through diagramming and discussion. We also analyzed the residue time effects on the flow parameters. The results indicate that peristaltic ciliary flow has a more favorable residual time along the canal when compared to peristaltic flow.

The Effect of Hematocrit and Nanoparticles Diameter on Hemodynamic Parameters and Drug Delivery in Abdominal Aortic Aneurysm with Consideration of Blood Pulsatile Flow

BACKGROUND AND OBJECTIVE

The present article has simulated to investigate the efficient hemodynamic parameters, the drug persistence, and drug distribution on an abdominal aortic aneurysm.

METHODS

Blood as a non-Newtonian fluid enters the artery acting as a real pulse waveform; its behavior is dependent on hematocrit and strain rate. In this simulation of computational fluid dynamic, magnetic nanoparticles of iron oxide which were in advance coated with the drug, are injected into the artery during a cardiac cycle. A two-phase model was applied to investigate the distribution of these carriers.

RESULTS

The results are presented for different hematocrits and the nanoparticle diameter. It is observed that hematocrit significantly affects drug persistence, so that lower hematocrit incites more accumulation of the drug in the dilatation part of the artery. The better drug accumulation is noticed, at the higher wall shear stress. Although no considerable impact on the flow pattern and wall shear stress was found with various nanoparticle diameters, the smaller size of the nanoparticles results in a greater amount of drug augmentation in the aneurysm wall output.

CONCLUSIONS

At the higher hematocrit levels, the blood resistance to drug delivery increases throughout the artery. Also, the drug accumulates less on the aneurysm wall and stays longer on the aneurysm wall. On the contrary, the drug accumulates more by decreasing hematocrit level and stays shorter on the aneurysm wall. Moreover, the maximum drug concentration is observed at the lowest hematocrit level and nanoparticle diameter; also, the diameter of nanoparticles imposes no significant effect on the vorticity and wall shear stress. It is seen that the increment of the hematocrit level reduces the strength of vorticity and increases the amount of wall shear stress in the dilatation segment of the artery. The shear stress at three points of the dilatation wall is extreme, where the maximum density of nanoparticles occurs.

HEARTBEAT CLASSIFICATION ALGORITHM BASED ON ONE-DIMENSIONAL CONVOLUTION NEURAL NETWORK

The morbidity of cardiovascular disease increasingly rises, which makes great impact upon people’s health and life. Electrocardiogram (ECG) beat classification is of great significance to clinical diagnosis of cardiovascular diseases. Traditional ECG signal classification algorithm relies heavily on the accuracy of feature extraction or increases the complexity of the calculation process by means of the correlation characteristic coefficient transformation, which results in that the ECG beat classification effect is still not satisfactory. Aimed at this problem, a novel method based on convolution neural network (CNN) is presented in this paper. First, ECG signal is preprocessed to suppress the noise and to locate the R peaks, and five kinds of ECG beat waveform data are obtained. Then taking ECG beat sampling points as input, four layers of one-dimensional CNN are constructed for feature extraction and classification. Finally, experimental verification is carried out on the data from MIT-BIH database, and the accuracy of recognition and classification of the presented method reaches 99.10%. Comparison with the methods based on artificial features, this method shows better performance, which avoids serious dependence on the accuracy of feature extraction, skips the steps of feature extraction and selection, and reduces the complexity of computational process.

PPG-BASED AUTOMATED ESTIMATION OF BLOOD PRESSURE USING PATIENT-SPECIFIC NEURAL NETWORK MODELING

Recently, photoplethysmography (PPG)-based techniques have been extensively used for cuff-less, automated estimation of blood pressure because of their inexpensive and effortless acquisition technology compared to other conventional approaches. However, most of the reported PPG-based, generalized BP estimation methods often lack the desired accuracy due to pathophysiological diversity. Moreover, some methods rely on several correction factors, which are not globalized yet and require further investigation. In this paper, a simple and automated systolic (SBP) and diastolic (DBP) blood pressure estimation method is proposed based on patient-specific neural network (NN) modeling. Initially, 15 time-plane PPG features are extracted and after feature selection, only four selected features are used in the NN model for beat-to-beat estimation of SBP and DBP, respectively. The proposed technique also presents reasonable accuracy while used for generalized estimation of BP. Performance of the algorithm is evaluated on 670 records of 50 intensive care unit (ICU) patients taken from MIMIC, MIMIC II and MIMIC Challenge databases. The proposed algorithm exhibits high average accuracy with (mean[Formula: see text][Formula: see text][Formula: see text]SD) of the estimated SBP as ([Formula: see text]) mmHg and DBP as ([Formula: see text]) mmHg. Compared to the other generalized models, the use of patient-specific approach eliminates the necessity of individual correction factors, thus increasing the robustness, accuracy and potential of the method to be implemented in personal healthcare applications.