Impact of baseline coronary flow and its distribution on fractional flow reserve prediction

Müller, Lucas O.; Fossan, Fredrik Eikeland; Bråten, Anders Tjellaug; Jørgensen, Arve; Wiseth, Rune; Hellevik, Leif Rune

doi:10.1002/cnm.3246

Cited by 41 publications

(46 citation statements)

References 51 publications

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“…3 Hyde et al 21 used animal cryomicrotome data to connect epicardial arteries and microvessels, with a one-way coupling between a 1D coronary model and a multi-compartment porous model: inclusion of vascular data significantly improves the continuum perfusion results in comparison to a more simplistically parameterized model. Conversely, knowledge of perfusion 16 and coronary flow repartition 9,33 may improve coronary model boundary conditions. Finally, Lee et al 29 proposed a two-way coupling between a 1D coronary model and a single compartment poromechanical model, applied to a porcine geometry extracted from cryomicrotome.…”

Section: Introductionmentioning

confidence: 99%

Myocardial Perfusion Simulation for Coronary Artery Disease: A Coupled Patient-Specific Multiscale Model

et al. 2020

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Patient-specific models of blood flow are being used clinically to diagnose and plan treatment for coronary artery disease. A remaining challenge is bridging scales from flow in arteries to the micro-circulation supplying the myocardium. Previously proposed models are descriptive rather than predictive and have not been applied to human data. The goal here is to develop a multiscale patient-specific model enabling blood flow simulation from large coronary arteries to myocardial tissue. Patient vasculatures are segmented from coronary computed tomography angiography data and extended from the image-based model down to the arteriole level using a space-filling forest of synthetic trees. Blood flow is modeled by coupling a 1D model of the coronary arteries to a single-compartment Darcy myocardium model. Simulated results on five patients with non-obstructive coronary artery disease compare overall well to [$$^{15}$$ 15 O]$$\text {H}_{{2}}$$ H 2 O PET exam data for both resting and hyperemic conditions. Results on a patient with severe obstructive disease link coronary artery narrowing with impaired myocardial blood flow, demonstrating the model’s ability to predict myocardial regions with perfusion deficit. This is the first report of a computational model for simulating blood flow from the epicardial coronary arteries to the left ventricle myocardium applied to and validated on human data.

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Section: Introductionmentioning

confidence: 99%

Myocardial Perfusion Simulation for Coronary Artery Disease: A Coupled Patient-Specific Multiscale Model

et al. 2020

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“…This algorithm significantly reduces the model's sensitivity to the degree of details of a coronary tree and automatically considers coronary dominance type. In other works, this problem is partially solved by introducing additional coefficients [34], changing algorithm based on the coronary dominance type [11] or performing preliminary calculations [38]. All these approaches are valid and effective, but most of them can be further improved by implementing the recursive algorithm.…”

Section: Discussionmentioning

confidence: 99%

Computational Analysis of Haemodynamic Indices in Synthetic Atherosclerotic Coronary Netwroks

Simakov¹,

Gamilov²,

Kopylov³

et al. 2021

Preprint

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Haemodynamic indices are widely used in clinical practice for deciding on a particular type of treatment. Low quality of the CT data and tachycardia complicate interpretation of the measured or simulated values. In this work, we present a novel approach for evaluating resistances in terminal coronary arteries. Using 14 measurements from 10 patients, we show that this algorithm retains the accuracy of 1D haemodynamic simulations in less detailed (truncated) geometric models of coronary networks. We also apply the variable systole fraction model to study the effect of elevated heart rate on the values of FFR, CFR and iFR. We conclude that tachycardia may produce both overestimation or underestimation of coronary stenosis significance.

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“…Relatively, computational modeling provides a more convenient means of quantifying the impact of arrhythmia on myocardial perfusion and uncovering underlying mechanisms. Computational models of the coronary circulation have been widely applied to study the characteristics of coronary blood flow in the context of arrhythmia or coronary artery disease [10,12,13]. However, few studies have been dedicated to addressing the impact of arrhythmia on myocardial perfusion.…”

Section: Introductionmentioning

confidence: 99%

Impact of Arrhythmia on Myocardial Perfusion: A Computational Model-Based Study

Simakov

Liu

et al. 2021

Mathematics

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(1) Background: Arrhythmia, which is an umbrella term for various types of abnormal rhythms of heartbeat, has a high prevalence in both the general population and patients with coronary artery disease. So far, it remains unclear how different types of arrhythmia would affect myocardial perfusion and the risk/severity of myocardial ischemia. (2) Methods: A computational model of the coronary circulation coupled to the global cardiovascular system was employed to quantify the impacts of arrhythmia and its combination with coronary artery disease on myocardial perfusion. Furthermore, a myocardial supply–demand balance index (MSDBx) was proposed to quantitatively evaluate the severity of myocardial ischemia under various arrhythmic conditions. (3) Results: Tachycardia and severe irregularity of heart rates (HRs) depressed myocardial perfusion and increased the risk of subendocardial ischemia (evaluated by MSDBx), whereas lowering HR improved myocardial perfusion. The presence of a moderate to severe coronary artery stenosis considerably augmented the sensitivity of MSDBx to arrhythmia. Further data analyses revealed that arrhythmia induced myocardial ischemia mainly via reducing the amount of coronary artery blood flow in each individual cardiac cycle rather than increasing the metabolic demand of the myocardium (measured by the left ventricular pressure-volume area). (4) Conclusions: Both tachycardia and irregular heartbeat tend to increase the risk of myocardial ischemia, especially in the subendocardium, and the effects can be further enhanced by concomitant existence of coronary artery disease. In contrast, properly lowering HR using drugs like β-blockers may improve myocardial perfusion, thereby preventing or relieving myocardial ischemia in patients with coronary artery disease.

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Impact of baseline coronary flow and its distribution on fractional flow reserve prediction

Cited by 41 publications

References 51 publications

Myocardial Perfusion Simulation for Coronary Artery Disease: A Coupled Patient-Specific Multiscale Model

Myocardial Perfusion Simulation for Coronary Artery Disease: A Coupled Patient-Specific Multiscale Model

Computational Analysis of Haemodynamic Indices in Synthetic Atherosclerotic Coronary Netwroks

Impact of Arrhythmia on Myocardial Perfusion: A Computational Model-Based Study

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