Hemodynamic effects on atherosclerosis-prone coronary artery: wall shear stress/rate distribution and impedance phase angle in coronary and aortic circulation

The Stress Phase Angle Measurement Using Spectral Domain Optical Coherence Tomography

The stress phase angle (SPA), defined as the temporal phase angle between circumferential stress (CS) in the arterial wall and wall shear stress (WSS), is utilized to investigate the interactions between CS and WSS. SPA serves as an important parameter for the early diagnosis of cardiovascular disease. In this study, we proposed a novel method for measuring SPA using spectral domain optical coherence tomography (SD-OCT). The multi-M-mode scan strategy is adopted for interference spectrum acquisition. The phases of CS and WSS are extracted from the corresponding structural and flow velocity images of SD-OCT. The method is validated by measuring SPA in the outflow tract (OFT) of chick embryonic hearts and the common carotid artery of mice. To the best of our knowledge, this is the first time that OCT has been used for SPA measurement.

Machine Learning for Aiding Blood Flow Velocity Estimation Based on Angiography

Computational fluid dynamics (CFD) is widely employed to predict hemodynamic characteristics in arterial models, while not friendly to clinical applications due to the complexity of numerical simulations. Alternatively, this work proposed a framework to estimate hemodynamics in vessels based on angiography images using machine learning (ML) algorithms. First, the iodine contrast perfusion in blood was mimicked by a flow of dye diffusing into water in the experimentally validated CFD modeling. The generated projective images from simulations imitated the counterpart of light passing through the flow field as an analogy of X-ray imaging. Thus, the CFD simulation provides both the ground truth velocity field and projective images of dye flow patterns. The rough velocity field was estimated using the optical flow method (OFM) based on 53 projective images. ML training with least absolute shrinkage, selection operator and convolutional neural network was conducted with CFD velocity data as the ground truth and OFM velocity estimation as the input. The performance of each model was evaluated based on mean absolute error and mean squared error, where all models achieved or surpassed the criteria of 3 × 10-3 and 5 × 10-7 m/s, respectively, with a standard deviation less than 1 × 10-6 m/s. Finally, the interpretable regression and ML models were validated with over 613 image sets. The validation results showed that the employed ML model significantly reduced the error rate from 53.5% to 2.5% on average for the v-velocity estimation in comparison with CFD. The ML framework provided an alternative pathway to support clinical diagnosis by predicting hemodynamic information with high efficiency and accuracy.

An unexpected paradox: wall shear stress in the aorta is less in patients with severe atherosclerosis regardless of obesity

BACKGROUND

Obesity is a widespread condition that is more prevalent in Western countries compared to others. Aortic atherosclerosis (AA) is a condition that frequently has been associated with obesity. An obesity paradox, where morbidly obese decedents had either no or minimal AA compared to nonobese decedents, recently has been described by some of us. The explanation for this almost counterintuitive paradox has yet to be determined, but a number of hypotheses were advanced, including hemodynamic factors producing aortic wall shear stress (WSS). The purpose of the present study was to determine if there was a relationship between AA and WSS, as determined by postmortem measurement of aortic wall diameters.

METHODS

Circumferences of the aorta at the levels of the ascending, thoracic and abdominal aorta were measured in 274 consecutive autopsies over 2-year period of time. AA was assessed using a previously described grading scale as either mild or severe. Circumferences were mathematically converted to diameters and WSS was calculated using the Hagen-Poiseuille formula. Two different methods to estimate cardiac output were used, both based on literature methods, one of which was body mass index (BMI) dependent, and the other BMI independent. Univariate and multivariable analyses of the relationship between WSS, age, BMI, gender, race and severity of AA were performed.

RESULTS

Of the 274 decedents, 140 had mild and 134 had moderate to severe AA. BMI <35 was associated with moderate to severe AA. WSS was inversely correlated with AA in all these segments of the aorta in each BMI subgroup with the exception of the ascending aorta for decedents with BMI ≤35 kg/m². Contrary to what we had hypothesized, WSS was not a determinant of the obesity paradox. However, among all the variables analyzed, a history of hypertension, diabetes mellitus and age were significant factors for developing AA (relative risk [RR] 0.35, P = .039; RR 1.51, P = .0006, RR 1.19, P = .0001, respectively).

CONCLUSIONS

Our data demonstrate that WSS was unexpectedly lower in decedents with moderate and severe AA as compared to those with mild AA. This observation, which requires further investigations, was seen in all BMI ranges and was confirmed by 2 methods to calculate WSS.

An Obesity Paradox: Increased Body Mass Index Is Associated with Decreased Aortic Atherosclerosis

Brodsky et al. (Cardiovasc Pathol 25(6), 515-520, 2016) recently have reported that there was an unexpected and highly significant inverse correlation between body mass index (BMI) and atherosclerosis of the aortas of morbidly obese decedents (BMI >40 kg/m²). In a series of 304 decedents, 65 of whom were morbidly obese, minimal or no atherosclerosis was seen in 46 of them (70%) versus 20 (30%) who had severe atherosclerosis (P = 0.008). This obesity paradox was unexpected and raises important questions about the etiology and pathogenesis of atherosclerosis, which will be the subject of this commentary. The concept of healthy versus unhealthy adiposity may in part provide an explanation for the "obesity paradox." Another factor that will be considered is the possible role of adipokines and their genetic determinants that may significantly reduce the risk of developing aortic atherosclerosis in morbidly obese individuals. Considering the marked variability in the pattern and extent of atherosclerosis of the aorta, hemodynamic factors and endothelial cell shear stress may be the most important determinants that might explain the obesity paradox that we have observed. Finally, the possible role of gut microbiota and inflammation as factors in the etiopathogenesis of atherosclerosis will be considered, but their importance is less clear than that of hemodynamic factors. We conclude with the remarkable finding that a 5300-year-old, well-preserved mummy of the "Iceman," Ötzi had atherosclerotic disease of a number of major arteries and the interesting questions that this raises.

Computational fluid dynamics in coronary artery disease

Computational fluid dynamics (CFD) is a widely used method in mechanical engineering to solve complex problems by analysing fluid flow, heat transfer, and associated phenomena by using computer simulations. In recent years, CFD has been increasingly used in biomedical research of coronary artery disease because of its high performance hardware and software. CFD techniques have been applied to study cardiovascular haemodynamics through simulation tools to predict the behaviour of circulatory blood flow in the human body. CFD simulation based on 3D luminal reconstructions can be used to analyse the local flow fields and flow profiling due to changes of coronary artery geometry, thus, identifying risk factors for development and progression of coronary artery disease. This review aims to provide an overview of the CFD applications in coronary artery disease, including biomechanics of atherosclerotic plaques, plaque progression and rupture; regional haemodynamics relative to plaque location and composition. A critical appraisal is given to a more recently developed application, fractional flow reserve based on CFD computation with regard to its diagnostic accuracy in the detection of haemodynamically significant coronary artery disease.

Computational fluid dynamics in cardiovascular disease

Computational fluid dynamics (CFD) is a mechanical engineering field for analyzing fluid flow, heat transfer, and associated phenomena, using computer-based simulation. CFD is a widely adopted methodology for solving complex problems in many modern engineering fields. The merit of CFD is developing new and improved devices and system designs, and optimization is conducted on existing equipment through computational simulations, resulting in enhanced efficiency and lower operating costs. However, in the biomedical field, CFD is still emerging. The main reason why CFD in the biomedical field has lagged behind is the tremendous complexity of human body fluid behavior. Recently, CFD biomedical research is more accessible, because high performance hardware and software are easily available with advances in computer science. All CFD processes contain three main components to provide useful information, such as pre-processing, solving mathematical equations, and post-processing. Initial accurate geometric modeling and boundary conditions are essential to achieve adequate results. Medical imaging, such as ultrasound imaging, computed tomography, and magnetic resonance imaging can be used for modeling, and Doppler ultrasound, pressure wire, and non-invasive pressure measurements are used for flow velocity and pressure as a boundary condition. Many simulations and clinical results have been used to study congenital heart disease, heart failure, ventricle function, aortic disease, and carotid and intra-cranial cerebrovascular diseases. With decreasing hardware costs and rapid computing times, researchers and medical scientists may increasingly use this reliable CFD tool to deliver accurate results. A realistic, multidisciplinary approach is essential to accomplish these tasks. Indefinite collaborations between mechanical engineers and clinical and medical scientists are essential. CFD may be an important methodology to understand the pathophysiology of the development and progression of disease and for establishing and creating treatment modalities in the cardiovascular field.

Novel non-dimensional approach to comparison of wall shear stress distributions in coronary arteries of different groups of patients

BACKGROUND

Local wall shear stress (WSS) has an impact on local remodelling of the vessel wall. WSS in turn strongly depends on local geometry. Our aim was to characterize patterns of local wall shear stress associated with distinct types of remodelling in coronary arteries. Vessel size and flow rates are different between patients, however. To compare distribution patterns of WSS in analogy to fluid-dynamic modelling, non-dimensional WSS/area functions are calculated.

METHODS

Right coronary arteries from seven controls, five patients with coronary artery disease (CAD) and five patients with aneurysmatic CAD (AnCAD) were analyzed. Flow simulations were performed in three-dimensionally reconstructed coronary vessels from biplane angiographic projections. Local WSS was normalized as percentage of maximum value in a histogram (100 classes) and corresponding area was expressed as percentage of total area.

RESULTS

The normalized WSS distribution was characterized by a single peak with a large lower tie in controls, a loss of the single peak and a stochastic distribution in AnCAD and a narrowing of the lower tie in CAD. Correct classification of 16/17 coronary arteries was feasible by Fisher's discriminant functions based on median WSS, mean diameter, percentage of area with WSS <or=0.4 Pa and with WSS >or=15 Pa.

CONCLUSION

Normalized WSS distribution might be an efficient tool in comparing wall shear stress between different patient groups. Whether normalized WSS distribution curves are apt to grade severity of disease remains to be investigated.

Effects of the shape of coronary arteries on the presence, extent, and severity of their disease

It is now known that a C-shaped right coronary artery (RCA) (C-RCA) is associated with more atherosclerotic disease than a sigma-shaped RCA (S-RCA). This study was designed to investigate the relationship between the shape of the RCA and the presence, extent, and severity of coronary artery disease (CAD) in all coronary arteries. Two hundred and forty-five patients were divided into C-RCA (group 1, n = 161) and S-RCA (group 2, n = 84) groups. The vessel score, extent score, and Gensini score were higher in group 1 than in group 2 (P < 0.001 for all comparisons). In multivariate analyses, age (P = 0.001), male sex (P < 0.001), smoking (P = 0.002), and C-RCA (P < 0.001) were independent predictors of significant CAD (presence of at least one lesion causing at least >50% stenosis). Multiple linear regression analysis to predict vessel score identified C-RCA (P < 0.001), age (P = 0.004), and male sex (P = 0.020), to predict extent score identified C-RCA (P < 0.001), age (P = 0.005), and male sex (P = 0.003), and to predict Gensini score identified C-RCA (P < 0.001), male sex (P = 0.009), and dyslipidemia (P = 0.049) as independently associated variables. Sensitivity and specificity of C-RCA for detecting significant CAD were 79% and 46%, respectively. This study showed that C-RCA was an independent predictor of significant CAD, which was independently associated with vessel score, extent score, and Gensini score. However, it was not clinically useful, because it was not specific or sensitive enough to identify patients with significant CAD.

Effects of aggregation of red cells and linear velocity gradients on the correlation-based method for quantitative IVUS blood flow at 20 MHz

Recent computer simulations suggest that the presence of aggregates of red blood cells (RBCs), at random angles and lengths, does not affect the measurements of blood flow transverse to the ultrasound (US) beam direction using a correlation-based method and an intravascular (IV) US array catheter. However, in case of aggregates of RBCs aligned with the flow, measurements of simulated blood velocity are affected. Blood velocity gradients were also shown not to influence the correlation-based method for blood velocity estimation. The objective of this study was to quantify the influence of aggregates of RBCs and blood velocity gradients on the correlation-based method during in vitro experiments. For this purpose, measurements were performed on washed RBCs (no aggregation), normal human blood, and two types of diseased blood in which a lower or a higher level of aggregation was present. The decorrelation pattern of a circular US transducer as a function of transverse blood flow was studied using a Couette system. Changing the shear rate of the Couette system modified the aggregation level of RBCs and the velocity gradient. With the exception of the results at low shear rates and abnormally high aggregation levels, agreements were found between the autoconvolution of the acoustical beam (reference curve) and the radiofrequency (RF) decorrelation patterns. For the high shear rate present in coronary arteries, the correlation-based method for blood flow estimation should not be influenced by these phenomena.