Association Between Automated 3D Measurement of Coronary Luminal Narrowing and Risk of Future Myocardial Infarction.

This study focuses on identifying anatomical markers with predictive capacity for long-term myocardial infarction (MI) in focal coronary artery disease (CAD). Eighty future culprit lesions (FCL) and 108 non-culprit lesions (NCL) from 80 patients underwent 3D quantitative coronary angiography. The minimum lumen area (MLA), minimum lumen ratio (MLR), and vessel fractional flow reserve (vFFR) were evaluated. MLR was defined as the ratio between MLA and the cross-sectional area at the proximal lesion edge, with lower values indicating more abrupt luminal narrowing. Significant differences were observed between FCL and NCL in MLR (0.41 vs. 0.53, p < 0.001). MLR correlated inversely with translesional vFFR (r = - 0.26, p = 0.0004) and was the strongest predictor of MI at 5 years (AUC = 0.75). Lesions with MLR < 0.40 had a fourfold increased MI incidence at 5 years. MLR is a robust predictor of future adverse coronary events.

Impact of wall displacements on the large-scale flow coherence in ascending aorta.

In the context of aortic hemodynamics, uncertainties affecting blood flow simulations hamper their translational potential as supportive technology in clinics. Computational fluid dynamics (CFD) simulations under rigid-walls assumption are largely adopted, even though the aorta contributes markedly to the systemic compliance and is characterized by a complex motion. To account for personalized wall displacements in aortic hemodynamics simulations, the moving-boundary method (MBM) has been recently proposed as a computationally convenient strategy, although its implementation requires dynamic imaging acquisitions not always available in clinics. In this study we aim to clarify the real need for introducing aortic wall displacements in CFD simulations to accurately capture the large-scale flow structures in the healthy human ascending aorta (AAo). To do that, the impact of wall displacements is analyzed using subject-specific models where two CFD simulations are performed imposing (1) rigid walls, and (2) personalized wall displacements adopting a MBM, integrating dynamic CT imaging and a mesh morphing technique based on radial basis functions. The impact of wall displacements on AAo hemodynamics is analyzed in terms of large-scale flow patterns of physiological significance, namely axial blood flow coherence (quantified applying the Complex Networks theory), secondary flows, helical flow and wall shear stress (WSS). From the comparison with rigid-wall simulations, it emerges that wall displacements have a minor impact on the AAo large-scale axial flow, but they can affect secondary flows and WSS directional changes. Overall, helical flow topology is moderately affected by aortic wall displacements, whereas helicity intensity remains almost unchanged. We conclude that CFD simulations with rigid-wall assumption can be a valid approach to study large-scale aortic flows of physiological significance.

Network-Based Characterization of Blood Large-Scale Coherent Motion in the Healthy Human Aorta With 4D Flow MRI.

OBJECTIVE: The need for distilling the hemodynamic complexity of aortic flows into clinically relevant quantities resulted in a loss of the information hidden in 4D aortic fluid structures. To reduce information loss, this study proposes a network-based approach to identify and characterize in vivo the large-scale coherent motion of blood in the healthy human aorta. METHODS: The quantitative paradigm of the aortic flow as a "social network" was applied on 4D flow MRI acquisitions performed on forty-one healthy volunteers. Correlations between the aortic blood flow rate waveform at the proximal ascending aorta (AAo), assumed as one of the drivers of aortic hemodynamics, and the waveforms of the axial velocity in the whole aorta were used to build "one-to-all" networks. The impact of the driving flow rate waveform and of aortic geometric attributes on the transport of large-scale coherent fluid structures was investigated. RESULTS: The anatomical length of persistence of large-scale coherent motion was the 29.6% of the healthy thoracic aorta length (median value, IQR 23.1%-33.9%). Such length is significantly influenced by the average and peak-to-peak AAo blood flow rate values, suggesting a remarkable inertial effect of the AAo flow rate on the transport of large-scale fluid structures in the distal aorta. Aortic geometric attributes such as curvature, torsion and arch shape did not influence the anatomical length of persistence. CONCLUSION: The proposed in vivo approach allowed to quantitatively characterize the transport of large-scale fluid structures in the healthy aorta, strengthening the definition of coherent hemodynamic structures and identifying flow inertia rather than geometry as one of its main determinants. SIGNIFICANCE: The findings on healthy aortas may be used as reference values to investigate the impact of aortic disease or implanted devices in disrupting/restoring the physiological spatiotemporal coherence of large-scale aortic flow.

Divergence of the normalized wall shear stress as an effective computational template of low-density lipoprotein polarization at the arterial blood-vessel wall interface.

BACKGROUND AND OBJECTIVE: Near-wall transport of low-density lipoproteins (LDL) in arteries plays a relevant role in the initiation of atherosclerosis. Although it can be modelled in silico by coupling the Navier-Stokes equations with the 3D advection-diffusion (AD) equation, the associated computational cost is high. As wall shear stress (WSS) represents a first-order approximation of the near-wall velocity in arteries, we aimed at identifying computationally convenient WSS-based quantities to infer LDL near-wall transport based on the underlying near-wall hemodynamics in five models of three human arterial districts (aorta, carotid bifurcations, coronary arteries). The simulated LDL transport and its WSS-based surrogates were qualitatively compared with in vivo longitudinal measurements of wall thickness growth on the coronary artery models. METHODS: Numerical simulations of blood flow coupled with AD equations for LDL transport and blood-wall transfer were performed. The co-localization of the simulated LDL concentration polarization patterns with luminal surface areas characterized by low cycle-average WSS, near-wall flow stagnation and WSS attracting patterns was quantitatively assessed by the similarity index (SI). In detail, the latter two represent features of the WSS topological skeleton, obtained respectively through the Lagrangian tracking of surface-born particles, and the Eulerian analysis of the divergence of the normalized cycle-average WSS vector field. RESULTS: Convergence of the solution of the AD problem required the simulation of 3 (coronary artery) to 10 (aorta) additional cardiac cycles with respect to the Navier-Stokes problem. Co-localization results underlined that WSS topological skeleton features indicating near-wall flow stagnation and WSS attracting patterns identified LDL concentration polarization profiles more effectively than low WSS, as indicated by higher SI values (SI range: 0.17-0.50 for low WSS; 0.24-0.57 for WSS topological skeleton features). Moreover, the correspondence between the simulated LDL uptake and WSS-based quantities profiles with the in vivo measured wall thickness growth in coronary arteries appears promising. CONCLUSIONS: The recently introduced Eulerian approach for identifying WSS attracting patterns from the divergence of normalized WSS provides a computationally affordable template of the LDL polarization at the arterial blood-wall interface without simulating the AD problem. It thus candidates as an effective biomechanical tool for elucidating the mechanistic link amongst LDL transfer at the arterial blood-wall interface, WSS and atherogenesis.

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.

Coronary Artery Stenting Affects Wall Shear Stress Topological Skeleton.

Despite the important advancements in the stent technology for the treatment of diseased coronary arteries, major complications still affect the postoperative long-term outcome. The stent-induced flow disturbances, and especially the altered wall shear stress (WSS) profile at the strut level, play an important role in the pathophysiological mechanisms leading to stent thrombosis (ST) and in-stent restenosis (ISR). In this context, the analysis of the WSS topological skeleton is gaining more and more interest by extending the current understanding of the association between local hemodynamics and vascular diseases. This study aims to analyze the impact that a deployed coronary stent has on the WSS topological skeleton. Computational fluid dynamics (CFD) simulations were performed in three stented human coronary artery geometries reconstructed from clinical images. The selected cases presented stents with different designs (i.e., two contemporary drug-eluting stents and one bioresorbable scaffold) and included regions with stent malapposition or overlapping. A recently proposed Eulerian-based approach was applied to analyze the WSS topological skeleton features. The results highlighted that the presence of single or multiple stents within a coronary artery markedly impacts the WSS topological skeleton. In particular, repetitive patterns of WSS divergence were observed at the luminal surface, highlighting a WSS contraction action exerted proximal to the stent struts and a WSS expansion action distal to the stent struts. This WSS action pattern was independent from the stent design. In conclusion, these findings could contribute to a deeper understanding of the hemodynamics-driven processes underlying ST and ISR.

Comparison of Swine and Human Computational Hemodynamics Models for the Study of Coronary Atherosclerosis.

Coronary atherosclerosis is a leading cause of illness and death in Western World and its mechanisms are still non completely understood. Several animal models have been used to 1) study coronary atherosclerosis natural history and 2) propose predictive tools for this disease, that is asymptomatic for a long time, aiming for a direct translation of their findings to human coronary arteries. Among them, swine models are largely used due to the observed anatomical and pathophysiological similarities to humans. However, a direct comparison between swine and human models in terms of coronary hemodynamics, known to influence atherosclerotic onset/development, is still lacking. In this context, we performed a detailed comparative analysis between swine- and human-specific computational hemodynamic models of coronary arteries. The analysis involved several near-wall and intravascular flow descriptors, previously emerged as markers of coronary atherosclerosis initiation/progression, as well as anatomical features. To do that, non-culprit coronary arteries (18 right-RCA, 18 left anterior descending-LAD, 13 left circumflex-LCX coronary artery) from patients presenting with acute coronary syndrome were imaged by intravascular ultrasound and coronary computed tomography angiography. Similarly, the three main coronary arteries of ten adult mini-pigs were also imaged (10 RCA, 10 LAD, 10 LCX). The geometries of the imaged coronary arteries were reconstructed (49 human, 30 swine), and computational fluid dynamic simulations were performed by imposing individualized boundary conditions. Overall, no relevant differences in 1) wall shear stress-based quantities, 2) intravascular hemodynamics (in terms of helical flow features), and 3) anatomical features emerged between human- and swine-specific models. The findings of this study strongly support the use of swine-specific computational models to study and characterize the hemodynamic features linked to coronary atherosclerosis, sustaining the reliability of their translation to human vascular disease.

Early Atherosclerotic Changes in Coronary Arteries are Associated with Endothelium Shear Stress Contraction/Expansion Variability.

Although unphysiological wall shear stress (WSS) has become the consensus hemodynamic mechanism for coronary atherosclerosis, the complex biomechanical stimulus affecting atherosclerosis evolution is still undetermined. This has motivated the interest on the contraction/expansion action exerted by WSS on the endothelium, obtained through the WSS topological skeleton analysis. This study tests the ability of this WSS feature, alone or combined with WSS magnitude, to predict coronary wall thickness (WT) longitudinal changes. Nine coronary arteries of hypercholesterolemic minipigs underwent imaging with local WT measurement at three time points: baseline (T1), after 5.6 ± 0.9 (T2), and 7.6 ± 2.5 (T3) months. Individualized computational hemodynamic simulations were performed at T1 and T2. The variability of the WSS contraction/expansion action along the cardiac cycle was quantified using the WSS topological shear variation index (TSVI). Alone or combined, high TSVI and low WSS significantly co-localized with high WT at the same time points and were significant predictors of thickening at later time points. TSVI and WSS magnitude values in a physiological range appeared to play an atheroprotective role. Both the variability of the WSS contraction/expansion action and WSS magnitude, accounting for different hemodynamic effects on the endothelium, (1) are linked to WT changes and (2) concur to identify WSS features leading to coronary atherosclerosis.

Combining 4D Flow MRI and Complex Networks Theory to Characterize the Hemodynamic Heterogeneity in Dilated and Non-dilated Human Ascending Aortas.

Motivated by the evidence that the onset and progression of the aneurysm of the ascending aorta (AAo) is intertwined with an adverse hemodynamic environment, the present study characterized in vivo the hemodynamic spatiotemporal complexity and organization in human aortas, with and without dilated AAo, exploring the relations with clinically relevant hemodynamic and geometric parameters. The Complex Networks (CNs) theory was applied for the first time to 4D flow magnetic resonance imaging (MRI) velocity data of ten patients, five of them presenting with AAo dilation. The time-histories along the cardiac cycle of velocity-based quantities were used to build correlation-based CNs. The CNs approach succeeded in capturing large-scale coherent flow features, delimiting flow separation and recirculation regions. CNs metrics highlighted that an increasing AAo dilation (expressed in terms of the ratio between the maximum AAo and aortic root diameter) disrupts the correlation in forward flow reducing the correlation persistence length, while preserving the spatiotemporal homogeneity of secondary flows. The application of CNs to in vivo 4D MRI data holds promise for a mechanistic understanding of the spatiotemporal complexity and organization of aortic flows, opening possibilities for the integration of in vivo quantitative hemodynamic information into risk stratification and classification criteria.

Deciphering ascending thoracic aortic aneurysm hemodynamics in relation to biomechanical properties.

The degeneration of the arterial wall at the basis of the ascending thoracic aortic aneurysm (ATAA) is a complex multifactorial process, which may lead to clinical complications and, ultimately, death. Individual genetic, biological or hemodynamic factors are inadequate to explain the heterogeneity of ATAA development/progression mechanisms, thus stimulating the analysis of their complex interplay. Here the disruption of the hemodynamic environment in the ATAA is investigated integrating patient-specific computational hemodynamics, CT-based in vivo estimation of local aortic stiffness and advanced fluid mechanics methods of analysis. The final aims are (1) deciphering the ATAA spatiotemporal hemodynamic complexity and its link to near-wall topological features, and (2) identifying the existing links between arterial wall degeneration and hemodynamic insult. Technically, two methodologies are applied to computational hemodynamics data, the wall shear stress (WSS) topological skeleton analysis, and the Complex Networks theory. The same analysis was extended to the healthy aorta. As main findings of the study, we report that: (1) different spatiotemporal heterogeneity characterizes the ATAA and healthy hemodynamics, that markedly reflect on their WSS topological skeleton features; (2) a link (stronger than canonical WSS-based descriptors) emerges between the variation of contraction/expansion action exerted by WSS on the endothelium along the cardiac cycle, and ATAA wall stiffness. The findings of the study suggest the use of advanced methods for a deeper understanding of the hemodynamics disruption in ATAA, and candidate WSS topological skeleton features as promising indicators of local wall degeneration.

Exploring wall shear stress spatiotemporal heterogeneity in coronary arteries combining correlation-based analysis and complex networks with computational hemodynamics.

Atherosclerosis at the early stage in coronary arteries has been associated with low cycle-average wall shear stress magnitude. However, parallel to the identification of an established active role for low wall shear stress in the onset/progression of the atherosclerotic disease, a weak association between lesions localization and low/oscillatory wall shear stress has been observed. In the attempt to fully identify the wall shear stress phenotype triggering early atherosclerosis in coronary arteries, this exploratory study aims at enriching the characterization of wall shear stress emerging features combining correlation-based analysis and complex networks theory with computational hemodynamics. The final goal is the characterization of the spatiotemporal and topological heterogeneity of wall shear stress waveforms along the cardiac cycle. In detail, here time-histories of wall shear stress magnitude and wall shear stress projection along the main flow direction and orthogonal to it (a measure of wall shear stress multidirectionality) are analyzed in a representative dataset of 10 left anterior descending pig coronary artery computational hemodynamics models. Among the main findings, we report that the proposed analysis quantitatively demonstrates that the model-specific inlet flow-rate shapes wall shear stress time-histories. Moreover, it emerges that a combined effect of low wall shear stress magnitude and of the shape of the wall shear stress-based descriptors time-histories could trigger atherosclerosis at its earliest stage. The findings of this work suggest for new experiments to provide a clearer determination of the wall shear stress phenotype which is at the basis of the so-called arterial hemodynamic risk hypothesis in coronary arteries.

Hemodialysis arterio-venous graft design reducing the hemodynamic risk of vascular access dysfunction.

Although arterio-venous grafts (AVGs) represent the second choice as permanent vascular access for hemodialysis, this solution is still affected by a relevant failure rate due to graft thrombosis, and development of neointimal hyperplasia (IH) at the distal vein. As a key role in these processes has been attributed to the abnormal hemodynamics establishing in the distal vein, the optimization of AVGs design aimed at minimizing flow disturbances would reduce AVG hemodynamic-related risks. In this study we used computational fluid dynamics to investigate the impact of alternative AVG designs on the reduction of IH and thrombosis risk at the distal venous anastomosis. The performance of the newly designed AVGs was compared to that of commercially available devices. In detail, a total of eight AVG models in closed-loop configuration were constructed: two models resemble the commercially available straight conventional and helical-shaped AVGs; six models are characterized by the insertion of a flow divider (FD), straight or helical shaped, differently positioned inside the graft. Unfavorable hemodynamic conditions were analyzed by assessing the exposure to disturbed shear at the distal vein. Bulk flow was investigated in terms of helical blood flow features, potential thrombosis risk, and pressure drop over the graft. Findings from this study clearly show that using a helically-shaped FD located at the venous side of the graft could induce beneficial helical flow patterns that, minimizing flow disturbances, reduce the IH-related risk of failure at the distal vein, with a clinically irrelevant increase in thrombosis risk and pressure drop over the graft.

Spatiotemporal Hemodynamic Complexity in Carotid Arteries: An Integrated Computational Hemodynamics and Complex Networks-Based Approach.

OBJECTIVE: The study of the arterial hemodynamics is essential for a better understanding of the risks associated with the onset/progression of vascular disease. However, conventional quantification and visualization paradigms are not sufficient to fully capture the spatiotemporal evolution of correlated blood flow patterns and their "sphere of influence" in complex vascular geometries. In the attempt to bridge this knowledge gap, an integrated computational hemodynamics and complex networks-based approach is proposed to unveil organization principles of cardiovascular flows. METHODS: The approach is applied to ten patient-specific hemodynamic models of carotid bifurcation, a vascular bed characterized by a complex hemodynamics and clinically-relevant disease. Correlation-based networks are built starting from time-histories of two fluid mechanics quantities of physiological significance, respectively (1) the blood velocity vector axial component locally aligned with the main flow direction, and (2) the kinetic helicity density. RESULTS: Unlike conventional hemodynamic analyses, here the spatiotemporal similarity of dynamic intravascular flow structures is encoded in a distance function. In the case of the carotid bifurcation, this study measures for the first time to what extent flow similarity is disrupted by vascular geometric features. CONCLUSION: It emerges that a larger bifurcation expansion, a hallmark of vascular disease, significantly disrupts the network topological connections between axial flow structures, reducing also their anatomical persistence length. On the contrary, connections in helical flow patterns are overall less geometry-sensitive. SIGNIFICANCE: The integrated approach proposed here, by exploiting the connections of hemodynamic patterns undergoing similar dynamical evolution, opens avenues for further comprehension of vascular physiopathology.

A Eulerian method to analyze wall shear stress fixed points and manifolds in cardiovascular flows.

Based upon dynamical systems theory, a fixed point of a vector field such as the wall shear stress (WSS) at the luminal surface of a vessel is a point where the vector field vanishes. Unstable/stable manifolds identify contraction/expansion regions linking fixed points. The significance of such WSS topological features lies in their strong link with "disturbed" flow features like flow stagnation, separation and reversal, deemed responsible for vascular dysfunction initiation and progression. Here, we present a Eulerian method to analyze WSS topological skeleton through the identification and classification of WSS fixed points and manifolds in complex vascular geometries. The method rests on the volume contraction theory and analyzes the WSS topological skeleton through the WSS vector field divergence and Poincar[Formula: see text] index. The method is here applied to computational hemodynamics models of carotid bifurcation and intracranial aneurysm. An in-depth analysis of the time dependence of the WSS topological skeleton along the cardiac cycle is provided, enriching the information obtained from cycle-average WSS. Among the main findings, it emerges that on the carotid bifurcation, instantaneous WSS fixed points co-localize with cycle-average WSS fixed points for a fraction of the cardiac cycle ranging from 0 to [Formula: see text]; a persistent instantaneous WSS fixed point confined on the aneurysm dome does not co-localize with the cycle-average low-WSS region. In conclusion, the here presented approach shows the potential to speed up studies on the physiological significance of WSS topological skeleton in cardiovascular flows, ultimately increasing the chance of finding mechanistic explanations to clinical observations.

What is needed to make low-density lipoprotein transport in human aorta computational models suitable to explore links to atherosclerosis? Impact of initial and inflow boundary conditions.

Personalized computational hemodynamics (CH) is a promising tool to clarify/predict the link between low density lipoproteins (LDL) transport in aorta, disturbed shear and atherogenesis. However, CH uses simplifying assumptions that represent sources of uncertainty. In particular, modelling blood-side to wall LDL transfer is challenged by the cumbersomeness of protocols needed to obtain reliable LDL concentration profile estimations. This paucity of data is limiting the establishment of rigorous CH protocols able to balance the trade-offs among the variety of in vivo data to be acquired, and the accuracy required by biological/clinical applications. In this study, we analyze the impact of LDL concentration initialization (initial conditions, ICs) and inflow boundary conditions (BCs) on CH models of LDL blood-to-wall transfer in aorta. Technically, in an image-based model of human aorta, two different inflow BCs are generated imposing subject-specific inflow 3D PC-MRI measured or idealized (flat) velocity profiles. For each simulated BC, four different ICs for LDL concentration are applied, imposing as IC the LDL distribution resulting from steady-state simulations with average conditions, or constant LDL concentration values. Based on CH results, we conclude that: (1) the imposition of realistic 3D velocity profiles as inflow BC reduces the uncertainty affecting the representation of LDL transfer; (2) different LDL concentration ICs lead to markedly different patterns of LDL transfer. Given that it is not possible to verify in vivo the proper LDL concentration initialization to be applied, we suggest to carefully set and unambiguously declare the imposed BCs and LDL concentration IC when modelling LDL transfer in aorta, in order to obtain reproducible and ultimately comparable results among different laboratories.