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Anatomy of the heart and major coronary vessels in anterior (left) and posterior (right) orientations. Coronary arteries: left coronary artery (LCA), left circumflex (LCX), left anterior descending (LAD), right coronary artery (RCA). Coronary veins: coronary sinus (CS), great cardiac vein (GCV), middle cardiac vein (MCV), small cardiac vein (SCV), left ventricular posterior vein (LVPV). Pulmonary vessels: left and right pulmonary arteries (LPA/RPA), left and right pulmonary veins (LPV/RPV). Vena cava: superior vena cava (SVC), inferior vena cava (IVC)
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Coronary flow is governed by a number of determinants including network anatomy, systemic afterload and the mechanical interaction with the myocardium throughout the cardiac cycle. The range of spatial scales and multi-physics nature of coronary perfusion highlights a need for a multiscale framework that captures the relevant details at each level...
Context in source publication
Context 1
... summary of selected past and recent state of the art in coronary modelling, extending over full and reduced-dimensional approaches relevant for con- structing a multiscale model and where appropriate, link these developments to clinical applications. For the benefit of the general audience, readers may refer to the basic coronary anatomy ( Fig. 1) and hemody- namic characteristics (Table 1, Fig. 2) as background to this ...Similar publications
Background: Concerns exist about reliability of pressure-wire-guided coronary revascularization of non-infarct-related arteries (non-IRA). We investigated whether physiological assessment of non-IRA during the subacute phase of myocardial infarction might be flawed by microcirculatory dysfunction.
Methods and Results: We analyzed non-IRA that under...
Citations
... CFD can help predict intra-aneurysmal flow, jet impingement, stasis, and WSS using CT and MRI data in the case of cerebral aneurysm, but these obtained results need to be validated for rupture predictions (Radaelli et al. 2008;Peach et al. 2014;Schneiders et al. 2015). Stent design and stent-induced hemodynamic disturbance post percutaneous coronary intervention can be analyzed in terms of WSS using CFD models that may require time-resolved pulsatility and finer mesh thus, requiring longer run times (Wentzel et al. 2001;Jin et al. 2004;LaDisa et al. 2005;Chien 2007;Jiménez and Davies 2009;Seshadhri et al. 2011;Lee and Smith 2012;Morlacchi and Migliavacca 2013). CFD models complemented with FSI can help monitor transvalvular hemodynamics by estimating transvalvular pressure drop and regurgitant fraction without the need for invasive procedures (De Hart et al. 2003;Astorino et al. 2012). ...
This study delves into the most recent advancements in computational fluid dynamics (CFD) and fluid–structure interaction (FSI) modeling applied to cardiovascular engineering. The application of FSI methods serves to overcome the constraints inherent in individual finite element analysis (FEA) and CFD techniques by simultaneously considering both fluidic and structural domains. The present review also explores One-Way and Two-Way FSI implementations across diverse cardiovascular systems, including scenarios involving aortic aneurysms and coronary arteries. A wide spectrum of cardiovascular applications is addressed, encompassing subjects such as hemodynamics in both healthy and diseased vessels, optimization of stent designs, evaluation of the effects of device interventions during stent deployment, modeling thrombosis and conducting risk assessments, analysis of heart valve dynamics, and assessment of cardiovascular devices such as ventricular assist devices. Furthermore, the study delves into assessing computational resource requirements, strategic implementation approaches, and potential directions for solving FSI-related issues within the context of cardiovascular systems. The integration of CFD modeling within cardiovascular medicine has profoundly transformed the landscape of biomedical device research and development. However, the challenges pertaining to regulatory aspects must be effectively addressed to ensure the widespread integration of CFD modeling within cardiovascular medicine. Successfully overcoming these challenges and adeptly addressing limitations will facilitate the seamless amalgamation of these pioneering techniques, ushering in a new era of precision medicine within cardiovascular healthcare.
... Based on the preceding, computational approaches have lately been regarded as the preferred method by several studies [36][37][38][39][40] and have developed into a useful instrument for assessing and forecasting disease development and testing the effectiveness of new devices for its treatment. Some limitations of experimental hemodynamic techniques can be overcome by computational models [39][40][41][42][43][44][45] by having the ability to create more realistic virtual models, getting quick and accurate results, and thoroughly testing different physiological conditions; however, it is crucial to note that the computational models are unable to entirely substitute the experimental tests because they still have difficulty accurately simulating natural blood flow [46]. Numerical simulations in computational atherosclerosis investigations have grown in favor recently [47] because of their many benefits. ...
Carotid atherosclerosis is one of the main cardiovascular diseases, widely considered as the main reason for death. Atherosclerosis forms a plaque that impedes blood vessels, and if ruptured, it causes a stroke or heart attack. The treatment protocol for atherosclerosis depends heavily on plaque type, structure, and composition, affecting plaque behavior (stable/unstable) or vulnerability. The fluid–structure interaction between the blood vessels and the blood flow must be examined to study the plaque's behavior. Consequently, this paper aims to reconstruct patient-specific three-dimensional models of the blood vessels for simulation and three-dimensional (3D) Printing, particularly for the carotid artery. In addition, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) datasets of atherosclerotic vessels are used to reconstruct the 3D model fed into a simulation program to measure the stress, strain, pressure, and velocity to assess the plaque. Five analyses studies were conducted on the constructed blood vessels; Non-pathological Flow in a cylindrical artery, Pathological Flow in a cylindrical artery, Non-pathological Flow in a 2D bifurcating carotid artery, Blood flow analysis in a normal carotid artery, and Blood flow analysis in a stenosed carotid artery. Two validation studies were performed for normal and atherosclerotic arteries. The results agreed with previous well-published work, considering that a 3D realistic model was printed for the vessel. Based on the above, our work provides a simulation environment for predicting atherosclerotic plaque behavior that helps medical specialists choose the proper treatment and preventive medical plans.
... However, the development of a comprehensive model of myocardial perfusion requires accounting for the complex interactions among multiple physical processes, including the coexistence of multiple spatial scales in the coronary circulation. The coronary arterial tree can be subdivided into epicardial coronary arteries (large coronaries) and intramural vessels (arterioles, venules and microvasculature) 7 . From a modeling point of view, the blood flow in the large epicardial vessels can be described using full 3D fluid dynamics or fluid-structure-interaction equations [7][8][9][10][11][12] , or geometrically reduced hemodynamics model, as 1D models [13][14][15] . ...
... The coronary arterial tree can be subdivided into epicardial coronary arteries (large coronaries) and intramural vessels (arterioles, venules and microvasculature) 7 . From a modeling point of view, the blood flow in the large epicardial vessels can be described using full 3D fluid dynamics or fluid-structure-interaction equations [7][8][9][10][11][12] , or geometrically reduced hemodynamics model, as 1D models [13][14][15] . Differently, below a threshold length scale, the blood flow in the myocardium can be represented as in a porous medium 16 , thanks to Darcy or multicompartment Darcy models 4,13,[17][18][19][20] . ...
... However, the development of a comprehensive model of myocardial perfusion requires accounting for the complex interactions among multiple physical processes, including the coexistence of multiple spatial scales in the coronary circulation. The coronary arterial tree can be subdivided into epicardial coronary arteries (large coronaries) and intramural vessels (arterioles, venules and microvasculature) 7 . From a modeling point of view, the blood flow in the large epicardial vessels can be described using full 3D fluid dynamics or fluid-structure-interaction equations [7][8][9][10][11][12] , or geometrically reduced hemodynamics model, as 1D models [13][14][15] . ...
... The coronary arterial tree can be subdivided into epicardial coronary arteries (large coronaries) and intramural vessels (arterioles, venules and microvasculature) 7 . From a modeling point of view, the blood flow in the large epicardial vessels can be described using full 3D fluid dynamics or fluid-structure-interaction equations [7][8][9][10][11][12] , or geometrically reduced hemodynamics model, as 1D models [13][14][15] . Differently, below a threshold length scale, the blood flow in the myocardium can be represented as in a porous medium 16 , thanks to Darcy or multicompartment Darcy models 4,13,[17][18][19][20] . ...
The aim of this paper is to introduce a new mathematical model that simulates myocardial blood perfusion that accounts for multiscale and multiphysics features. Our model incorporates cardiac electrophysiology, active and passive mechanics, hemodynamics, valve modeling, and a multicompartment Darcy model of perfusion. We consider a fully coupled electromechanical model of the left heart that provides input for a fully coupled Navier–Stokes–Darcy Model for myocardial perfusion. The fluid dynamics problem is modeled in a left heart geometry that includes large epicardial coronaries, while the multicompartment Darcy model is set in a biventricular myocardium. Using a realistic and detailed cardiac geometry, our simulations demonstrate the biophysical fidelity of our model in describing cardiac perfusion. Specifically, we successfully validate the model reliability by comparing in-silico coronary flow rates and average myocardial blood flow with clinically established values ranges reported in relevant literature. Additionally, we investigate the impact of a regurgitant aortic valve on myocardial perfusion, and our results indicate a reduction in myocardial perfusion due to blood flow taken away by the left ventricle during diastole. To the best of our knowledge, our work represents the first instance where electromechanics, hemodynamics, and perfusion are integrated into a single computational framework.
... Использование 3D и 2D моделей требует постанов-ки точных граничных условий на границах, через которые происходит течение крови, задания реологических свойств крови, учета подвижности стенки сосудов, упругих свойств стенки, давления окружающих тканей. Все это делает использование моделей данного класса весьма сложным, трудоемким процессом, требующим достаточно большого количества вычислительных ресурсов [20,23]. В настоящее время существует большое количество исследований, посвященных моделированию кровотока с использованием различных модальностей визуализации, что говорит об актуальности и развитии данного направления [7,24]. ...
X-ray computed tomography coronary angiography (CTCA) is a current method for diagnosing ischemic heart disease. Although this method has a high specificity and a negative predictive value in diagnosing coronary obstructions, there are limitations in determining the hemodynamic significance of the stenosis. Extensive use of noninvasive methods for evaluation of coronary hemodynamics, specifically evaluation of the fractional flow reserve (FFR) is limited due to its high cost and risks of complications. Mathematical modeling of coronary circulation and its reserve based on CTCA data is an up-to-date method that has been experimentally confirmed and clinically validated. This method showed a high diagnostic efficacy in several large studies that used the invasive determination of FFR as a "gold standard". This review addresses the current state of studies on mathematical modeling for fractional coronary reserve in patients with ischemic heart disease, as well as the limitations and prospects of this method.
... To this end, further evaluation of the maintenance of regional contractile function relative to respective regional (transmural) perfusion in response to changes in CPP, arterial oxygen content, and/or MVO 2 would serve to strengthen the present observations. Additional incorporation of phenomena observed here using multi-scale computational modeling [29,36,43] may also yield deeper insights than are immediately apparent from the data. ...
The coronary circulation has an innate ability to maintain constant blood flow over a wide range of perfusion pressures. However, the mechanisms responsible for coronary autoregulation remain a fundamental and highly contested question. This study interrogated the local metabolic hypothesis of autoregulation by testing the hypothesis that hypoxemia-induced exaggeration of the metabolic error signal improves the autoregulatory response. Experiments were performed on open-chest anesthetized swine during stepwise changes in coronary perfusion pressure (CPP) from 140 to 40 mmHg under normoxic (n = 15) and hypoxemic (n = 8) conditions, in the absence and presence of dobutamine-induced increases in myocardial oxygen consumption (MVO2) (n = 5–7). Hypoxemia (PaO2 < 40 mmHg) decreased coronary venous PO2 (CvPO2) ~ 30% (P < 0.001) and increased coronary blood flow ~ 100% (P < 0.001), sufficient to maintain myocardial oxygen delivery (P = 0.14) over a wide range of CPPs. Autoregulatory responsiveness during hypoxemia-induced reductions in CvPO2 were associated with increases of autoregulatory gain (Gc; P = 0.033) but not slope (P = 0.585) over a CPP range of 120 to 60 mmHg. Preservation of autoregulatory Gc (P = 0.069) and slope (P = 0.264) was observed during dobutamine administration ± hypoxemia. Reductions in coronary resistance in response to decreases in CPP predominantly occurred below CvPO2 values of ~ 25 mmHg, irrespective of underlying vasomotor reserve. These findings support the presence of an autoregulatory threshold under which oxygen-sensing pathway(s) act to preserve sufficient myocardial oxygen delivery as CPP is reduced during increases in MVO2 and/or reductions in arterial oxygen content.
... Since coronary arteries are attached to the cardiac epicardial surface, any abnormal motion of cardiac muscle can potentially affect the vascular hemodynamics including blood emptying and filling. Studies on the mechanical interaction between the myocardium and coronary arteries are well-documented [2][3][4]. Large torsional motion, wall thickening and contraction dynamics of the ventricles are expected to alter the hemodynamic environment within the coronary arteries. ...
... Arterial motion has been shown to function as a pump that drives blood into the artery [4]. These works studied the effect of myocardial motion on coronary blood flow [5,6] and revealed that the impact of cardiac motion on time-averaged wall shear stress (WSS) was insignificant compared to oscillatory hemodynamic parameters such as temporal variation of WSS and oscillatory shear index. ...
... Previous models had focused on the isolated processes in the myocardial demand-supply feedback system, namely, coronary blood flow [60,61] and LV mechanics [62], but they do not consider their bi-directional interactions and the integrated system response. On the other hand, a model simulating coronary flow regulation in an open-loop circulatory system also did not consider the coupling between blood flow and contractility [21,63]. ...
Background and Objective
The myocardial demand-supply feedback system plays an important role in augmenting blood supply in response to exercise-induced increased myocardial demand. During this feedback process, the myocardium and coronary blood flow interact bidirectionally at many different levels.
Methods
To investigate these interactions, a novel computational framework that considers the closed myocardial demand-supply feedback system was developed. In the framework coupling the systemic circulation of the left ventricle and coronary perfusion with regulation, myocardial work affects coronary perfusion via flow regulation mechanisms (e.g., metabolic regulation) and myocardial-vessel interactions, whereas coronary perfusion affects myocardial contractility in a closed feedback system. The framework was calibrated based on the measurements from healthy subjects under graded exercise conditions, and then applied to simulate the effects of graded exercise on myocardial demand-supply under different physiological and pathological conditions.
Results
We found the framework can recapitulate key features found during exercise in clinical and animal studies. We showed that myocardial blood flow is increased but maximum hyperemia is reduced during exercise, which led to a reduction in coronary flow reserve. For coronary stenosis and myocardial inefficiency, the model predicts that an increase in heart rate is necessary to maintain the baseline cardiac output. Correspondingly, the resting coronary flow reserve is exhausted and the range of heart rate before exhaustion of coronary flow reserve is reduced. In the presence of metabolic regulation dysfunction, the model predicts that the metabolic vasodilator signal is higher at rest, saturates faster during exercise, and as a result, causes quicker exhaustion of coronary flow reserve.
Conclusions
Model predictions showed that the coronary flow reserve deteriorates faster during graded exercise, which in turn, suggests a decrease in exercise tolerance for patients with stenosis, myocardial inefficiency and metabolic flow regulation dysfunction. The findings in this study may have clinical implications in diagnosing cardiovascular diseases.
... The third component is the systemic circulation, which carries blood to the rest of the organs. The myocardial coronary vessels present large variations of spatial scales in the range of 10--500 \mu m [DJBBD92,FAC16] with very different mechanical properties [AKL10a] and a complex network structure [HBRS08,LMR+10,LS12]. As a result, the pressure that drives perfusion in the coronary microvasculature is given by the combined effects of the intravessel and intramyocardial pressures [AKL10b]. ...
... There have been few clinical studies on the linear relationship between IMR and microcirculatory resistance evaluated in vivo (Fearon et al., 2003;Aarnoudse et al., 2004b). Hemodynamic parameters such as flow rate (Lee and Smith, 2012), distal coronary pressure, and aortic pressure (Morris et al., 2016) are closely associated with IMR, and the quantitative relationship between IMR and these parameters requires further investigation. Finally, as summarized in Table 1, the computational estimation of IMR has not been directly applied in clinical practice, because of inconsistency in the IMR range and the difficulty of distinguishing normal from pathological cases. ...
The dysfunction of coronary microcirculation is an important cause of coronary artery disease (CAD). The index of microcirculatory resistance (IMR) is a quantitative evaluation of coronary microcirculatory function, which provides a significant reference for the prediction, diagnosis, treatment, and prognosis of CAD. IMR also plays a key role in investigating the interaction between epicardial and microcirculatory dysfunctions, and is closely associated with coronary hemodynamic parameters such as flow rate, distal coronary pressure, and aortic pressure, which have been widely applied in computational studies of CAD. However, there is currently a lack of consensus across studies on the normal and pathological ranges of IMR. The relationships between IMR and coronary hemodynamic parameters have not been accurately quantified, which limits the application of IMR in computational CAD studies. In this paper, we discuss the research gaps between IMR and its potential applications in the computational simulation of CAD. Computational simulation based on the combination of IMR and other hemodynamic parameters is a promising technology to improve the diagnosis and guide clinical trials of CAD.
