Predicting Lipid-Rich Plaque Progression in Coronary Arteries Using Multimodal Imaging and Wall Shear Stress Signatures

BACKGROUND

Plaque composition and wall shear stress (WSS) magnitude act as well-established players in coronary plaque progression. However, WSS magnitude per se does not completely capture the mechanical stimulus to which the endothelium is subjected, since endothelial cells experience changes in the WSS spatiotemporal configuration on the luminal surface. This study explores WSS profile and lipid content signatures of plaque progression to identify novel biomarkers of coronary atherosclerosis.

METHODS

Thirty-seven patients with acute coronary syndrome underwent coronary computed tomography angiography, near-infrared spectroscopy intravascular ultrasound, and optical coherence tomography of at least 1 nonculprit vessel at baseline and 1-year follow-up. Baseline coronary artery geometries were reconstructed from intravascular ultrasound and coronary computed tomography angiography and combined with flow information to perform computational fluid dynamics simulations to assess the timeaveraged WSS magnitude (TAWSS) and the variability in the contraction/expansion action exerted by WSS on the endothelium, which can be assessed by the topological shear variation index (TSVI). Plaque progression was measured as intravascular ultrasound-derived percentage atheroma volume change at 1-year follow-up (Δplaque atheroma volume). Plaque composition information was extracted from near-infrared spectroscopy and optical coherence tomography.

RESULTS

Exposure to high TSVI and low TAWSS was associated with higher plaque progression (4.00±0.69% and 3.60±0.62%, respectively). Plaque composition acted synergistically with TSVI or TAWSS, resulting in the highest plaque progression (≥5.90%) at locations where lipid-rich content is exposed to high TSVI or low TAWSS.

CONCLUSIONS

Luminal exposure to high TSVI, solely or combined with a lipid-rich plaque phenotype, is associated with enhanced plaque progression at 1-year follow-up. Where plaque progression occurred, low TAWSS was also observed. These findings suggest TSVI, in addition to low TAWSS, as a potential biomechanical predictor for plaque progression, showing promise for clinical translation to improve patient prognosis.

The Role of Multiple Re-Entry Tears in Type B Aortic Dissection Progression: A Longitudinal Study Using a Controlled Swine Model

PURPOSE

False lumen (FL) expansion often occurs in type B aortic dissection (TBAD) and has been associated with the presence of re-entry tears. This longitudinal study aims to elucidate the role of re-entry tears in the progression of TBAD using a controlled swine model, by assessing aortic hemodynamics through combined imaging and computational modeling.

MATERIALS AND METHODS

A TBAD swine model with a primary entry tear at 7 cm distal to the left subclavian artery was created in a previous study. In the current study, reintervention was carried out in this swine model to induce 2 additional re-entry tears of approximately 5 mm in diameter. Computed tomography (CT) and 4-dimensional (4D) flow magnetic resonance imaging (MRI) scans were taken at multiple follow-ups before and after reintervention. Changes in aortic volume were measured on CT scans, and hemodynamic parameters were evaluated based on dynamic data acquired with 4D-flow MRI and computational fluid dynamics simulations incorporating all available in vivo data.

RESULTS

Morphological analysis showed FL growth of 20% following the initial TBAD-growth stabilized after the creation of additional tears and eventually FL volume reduced by 6%. Increasing the number of re-entry tears from 1 to 2 caused flow redistribution, with the percentage of true lumen (TL) flow increasing from 56% to 78%; altered local velocities; reduced wall shear stress surrounding the tears; and led to a reduction in FL pressure and pressure difference between the 2 lumina.

CONCLUSION

This study combined extensive in vivo imaging data with sophisticated computational methods to show that additional re-entry tears can alter dissection hemodynamics through redistribution of flow between the TL and FL. This helps to reduce FL pressure, which could potentially stabilize aortic growth and lead to reversal of FL expansion. This work provides a starting point for further study into the use of fenestration in controlling undesirable FL expansion.

CLINICAL IMPACT

Aortic growth and false lumen (FL) patency are associated with the presence of re-entry tears in type B aortic dissection (TBAD) patients. Guidelines on how to treat re-entry tears are lacking, especially with regards to the control and prevention of FL expansion. Through a combined imagining and computational hemodynamics study of a controlled swine model, we found that increasing the number of re-entry tears reduced FL pressure and cross lumen pressure difference, potentially stabilising aortic growth and leading to FL reduction. Our findings provide a starting point for further study into the use of fenestration in controlling undesirable FL expansion.

Longitudinal investigation of aortic dissection in mice with computational fluid dynamics

Predicting late adverse events in aortic dissections is challenging. One commonly observed risk factor is partial thrombosis of the false lumen. In this study we investigated false lumen thrombus progression over 7 days in four mice with angiotensin II-induced aortic dissection. We performed computational fluid dynamic simulations with subject-specific boundary conditions from velocity and pressure measurements. We investigated endothelial cell activation potential, mean velocity, thrombus formation potential, and other hemodynamic factors. Our findings support the hypothesis that flow stagnation is the predominant hemodynamic factor driving a large thrombus ratio in false lumina, particularly those with a single fenestration.

Deep-learning-based image segmentation for image-based computational hemodynamic analysis of abdominal aortic aneurysms: a comparison study

Computational hemodynamics is increasingly being used to quantify hemodynamic characteristics in and around abdominal aortic aneurysms (AAA) in a patient-specific fashion. However, the time-consuming manual annotation hinders the clinical translation of computational hemodynamic analysis. Thus, we investigate the feasibility of using deep-learning-based image segmentation methods to reduce the time required for manual segmentation. Two of the latest deep-learning-based image segmentation methods, ARU-Net and CACU-Net, were used to test the feasibility of automated computer model creation for computational hemodynamic analysis. Morphological features and hemodynamic metrics of 30 computed tomography angiography (CTA) scans were compared between pre-dictions and manual models. The DICE score for both networks was 0.916, and the correlation value was above 0.95, indicating their ability to generate models comparable to human segmentation. The Bland-Altman analysis shows a good agreement between deep learning and manual segmentation results. Compared with manual (computational hemodynamics) model recreation, the time for automated computer model generation was significantly reduced (from ∼2 h to ∼10 min). Automated image segmentation can significantly reduce time expenses on the recreation of patient-specific AAA models. Moreover, our study showed that both CACU-Net and ARU-Net could accomplish AAA segmentation, and CACU-Net outperformed ARU-Net in terms of accuracy and time-saving.

Impact of turbulence modeling on the simulation of blood flow in aortic coarctation

Numerical simulations of pulsatile blood flow in an aortic coarctation require the use of turbulence modeling. This paper considers three models from the class of large eddy simulation (LES) models (Smagorinsky, Vreman, σ -model) and one model from the class of variational multiscale models (residual-based) within a finite element framework. The influence of these models on the estimation of clinically relevant biomarkers used to assess the degree of severity of the pathological condition (pressure difference, secondary flow degree, normalized flow displacement, wall shear stress) is investigated in detail. The simulations show that most methods are consistent in terms of severity indicators such as pressure difference and stenotic velocity. Moreover, using second-order velocity finite elements, different turbulence models might lead to considerably different results concerning other clinically relevant quantities such as wall shear stresses. These differences may be attributed to differences in numerical dissipation introduced by the turbulence models.

Different Impact of Heart Rate Variability in the Deep Cerebral and Central Hemodynamics at Rest: An in silico Investigation

Background: Heart rate variability (HRV), defined as the variability between consecutive heartbeats, is a surrogate measure of cardiac vagal tone. It is widely accepted that a decreased HRV is associated to several risk factors and cardiovascular diseases. However, a possible association between HRV and altered cerebral hemodynamics is still debated, suffering from HRV short-term measures and the paucity of high-resolution deep cerebral data. We propose a computational approach to evaluate the deep cerebral and central hemodynamics subject to physiological alterations of HRV in an ideal young healthy patient at rest.

Methods: The cardiovascular-cerebral model is composed by electrical components able to reproduce the response of the different cardiovascular regions and their features. The model was validated over more than thirty studies and recently exploited to understand the hemodynamic mechanisms between cardiac arrythmia and cognitive deficit. Three configurations (baseline, increased HRV, and decreased HRV) are built based on the standard deviation (SDNN) of RR beats. For each configuration, 5,000 RR beats are simulated to investigate the occurrence of extreme values, alteration of the regular hemodynamics pattern, and variation of mean perfusion/pressure levels.

Results: In the cerebral circulation, our results show that HRV has overall a stronger impact on pressure than flow rate mean values but similarly alters pressure and flow rate in terms of extreme events. By comparing reduced and increased HRV, this latter induces a higher probability of altered mean and extreme values, and is therefore more detrimental at distal cerebral level. On the contrary, at central level a decreased HRV induces a higher cardiac effort without improving the mechano-contractile performance, thus overall reducing the heart efficiency.

Conclusions: Present results suggest that: (i) the increase of HRV per se does not seem to be sufficient to trigger a better cerebral hemodynamic response; (ii) by accounting for both central and cerebral circulations, the optimal HRV configuration is found at baseline. Given the relation inversely linking HRV and HR, the presence of this optimal condition can contribute to explain why the mean HR of the general population settles around the baseline value (70 bpm).

The variational multiscale formulation for the fully-implicit log-morphology equation as a tensor-based blood damage model

We derive a variational multiscale (VMS) finite element formulation for a viscoelastic, tensor-based blood damage model. The tensor equation is numerically stabilized by a logarithmic shape tensor description that prevents unphysical, negative eigenvalues. The resulting VMS stabilization terms for this so-called log-morph equation are presented together with their special numerical treatment. Results for a 2D rotating stirrer test case obtained from log-morph simulations with both SUPG and VMS stabilization show significantly improved numerical behavior if compared with Galerkin/least squares (GLS) stabilized untransformed morphology simulation results. The newly proposed method is also successfully applied to a state-of-the-art centrifugal ventricular assist device (VAD), and clear advantages of the VMS stabilization compared with the SUPG-stabilized formulation are presented.

Image-based modeling of blood flow in cerebral aneurysms treated with intrasaccular flow diverting devices

Modeling the flow dynamics in cerebral aneurysms after the implantation of intrasaccular devices is important for understanding the relationship between flow conditions created immediately posttreatment and the subsequent outcomes. This information, ideally available a priori based on computational modeling prior to implantation, is valuable to identify which aneurysms will occlude immediately and which aneurysms will likely remain patent and would benefit from a different procedure or device. In this report, a methodology for modeling the hemodynamics in intracranial aneurysms treated with intrasaccular flow diverting devices is described. This approach combines an image-guided, virtual device deployment within patient-specific vascular models with an immersed boundary method on adaptive unstructured grids. A partial mesh refinement strategy that reduces the number of mesh elements near the aneurysm dome where the flow conditions are largely stagnant was compared with the full refinement strategy that refines the mesh everywhere around the device wires. The results indicate that using the partial mesh refinement approach is adequate for analyzing the posttreatment hemodynamics, at a reduced computational cost. The results obtained on a series of four cerebral aneurysms treated with different intrasaccular devices were in good qualitative agreement with angiographic observations. Promising results were obtained relating posttreatment flow conditions and outcomes of treatments with intrasaccular devices, which need to be confirmed on larger series.

Wall shear stress estimation in the aorta: Impact of wall motion, spatiotemporal resolution, and phase noise

BACKGROUND

Wall shear stress (WSS) presents an important parameter for assessing blood flow characteristics and evaluating flow-mediated lesions in the aorta.

PURPOSE

To investigate the robustness of WSS and oscillatory shear index (OSI) estimation based on 4D flow MRI against vessel wall motion, spatiotemporal resolution, and velocity encoding (VENC).

STUDY TYPE

Simulated and prospective.

POPULATION

Synthetic 4D flow MRI data of the aorta, simulated using the Lattice-Boltzmann method; in vivo 4D flow MRI data of the aorta from healthy volunteers (n = 11) and patients with congenital heart defects (n = 17).

FIELD STRENGTH/SEQUENCE

1.5T; 4D flow MRI with PEAK-GRAPPA acceleration and prospective electrocardiogram triggering.

ASSESSMENT

Predicated upon 3D cubic B-splines interpolation of the image velocity field, WSS was estimated in mid-systole, early-diastole, and late-diastole and OSI was derived. We assessed the impact of spatiotemporal resolution and phase noise, and compared results based on tracked-using deformable registration-and static vessel wall location.

STATISTICAL TESTS

Bland-Altman analysis to assess WSS/OSI differences; Hausdorff distance (HD) to assess wall motion; and Pearson's correlation coefficient (PCC) to assess correlation of HD with WSS.

RESULTS

Synthetic data results show systematic over-/underestimation of WSS when different spatial resolution (mean ± 1.96 SD up to -0.24 ± 0.40 N/m2 and 0.5 ± 1.38 N/m2 for 8-fold and 27-fold voxel size, respectively) and VENC-depending phase noise (mean ± 1.96 SD up to 0.31 ± 0.12 N/m2 and 0.94 ± 0.28 N/m2 for 2-fold and 4-fold VENC increase, respectively) are given. Neglecting wall motion when defining the vessel wall perturbs WSS estimates to a considerable extent (1.96 SD up to 1.21 N/m2 ) without systematic over-/underestimation (Bland-Altman mean range -0.06 to 0.05).

DATA CONCLUSION

In addition to sufficient spatial resolution and velocity to noise ratio, accurate tracking of the vessel wall is essential for reliable image-based WSS estimation and should not be neglected if wall motion is present.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Numerical methods for polyline-to-point-cloud registration with applications to patient-specific stent reconstruction

We present novel numerical methods for polyline-to-point-cloud registration and their application to patient-specific modeling of deployed coronary artery stents from image data. Patient-specific coronary stent reconstruction is an important challenge in computational hemodynamics and relevant to the design and improvement of the prostheses. It is an invaluable tool in large-scale clinical trials that computationally investigate the effect of new generations of stents on hemodynamics and eventually tissue remodeling. Given a point cloud of strut positions, which can be extracted from images, our stent reconstruction method aims at finding a geometrical transformation that aligns a model of the undeployed stent to the point cloud. Mathematically, we describe the undeployed stent as a polyline, which is a piecewise linear object defined by its vertices and edges. We formulate the nonlinear registration as an optimization problem whose objective function consists of a similarity measure, quantifying the distance between the polyline and the point cloud, and a regularization functional, penalizing undesired transformations. Using projections of points onto the polyline structure, we derive novel distance measures. Our formulation supports most commonly used transformation models including very flexible nonlinear deformations. We also propose 2 regularization approaches ensuring the smoothness of the estimated nonlinear transformation. We demonstrate the potential of our methods using an academic 2D example and a real-life 3D bioabsorbable stent reconstruction problem. Our results show that the registration problem can be solved to sufficient accuracy within seconds using only a few number of Gauss-Newton iterations.

Comparison of reduced models for blood flow using Runge-Kutta discontinuous Galerkin methods

One-dimensional blood flow models take the general form of nonlinear hyperbolic systems but differ in their formulation. One class of models considers the physically conserved quantities of mass and momentum, while another class describes mass and velocity. Further, the averaging process employed in the model derivation requires the specification of the axial velocity profile; this choice differentiates models within each class. Discrepancies among differing models have yet to be investigated. In this paper, we comment on some theoretical differences among models and systematically compare them for physiologically relevant vessel parameters, network topology, and boundary data. In particular, the effect of the velocity profile is investigated in the cases of both smooth and discontinuous solutions, and a recommendation for a physiological model is provided. The models are discretized by a class of Runge-Kutta discontinuous Galerkin methods.

Reproducing Patient-Specific Hemodynamics in the Blalock-Taussig Circulation Using a Flexible Multi-Domain Simulation Framework: Applications for Optimal Shunt Design

For babies born with hypoplastic left heart syndrome, several open-heart surgeries are required. During Stage I, a Norwood procedure is performed to construct an appropriate circulation to both the systemic and the pulmonary arteries. The pulmonary arteries receive flow from the systemic circulation, often using a Blalock-Taussig (BT) shunt between the innominate artery and the right pulmonary artery. This procedure causes significantly disturbed flow in the pulmonary arteries. In this study, we use computational hemodynamic simulations to demonstrate its capacity for examining the properties of the flow through and near the BT shunt. Initially, we construct a computational model which produces blood flow and pressure measurements matching the clinical magnetic resonance imaging (MRI) and catheterization data. Achieving this required us to determine the level of BT shunt occlusion; because the occlusion is below the MRI resolution, this information is difficult to recover without the aid of computational simulations. We determined that the shunt had undergone an effective diameter reduction of 22% since the time of surgery. Using the resulting geometric model, we show that we can computationally reproduce the clinical data. We, then, replace the BT shunt with a hypothetical alternative shunt design with a flare at the distal end. Investigation of the impact of the shunt design reveals that the flare can increase pulmonary pressure by as much as 7% and flow by as much as 9% in the main pulmonary branches, which may be beneficial to the pulmonary circulation.

Evaluation of Hemodynamic Significance of Stenosis in Multiple Involvement of the Coronary Vessels by Mathematical Simulation

We use a mathematical model of one-dimensional blood flow in a network of blood vessels for in silico evaluation of hemodynamic significance of stenoses in multivessel coronary disease. Two cases were addressed: two stenosed vessels with different diameters and with the same degree of occlusion and two consecutive stenoses in the same vessel. We show that two criteria for the evaluation of hemodynamic significance based on the degree of stenosis and based on fractional flow reserve can give contradictory indications for surgical intervention. We also show that fractional flow reserve computation originally proposed for a single stenosis should be modified in the case of multivessel stenotic disease.

Numerical Method of Characteristics for One-Dimensional Blood Flow

Mathematical modeling at the level of the full cardiovascular system requires the numerical approximation of solutions to a one-dimensional nonlinear hyperbolic system describing flow in a single vessel. This model is often simulated by computationally intensive methods like finite elements and discontinuous Galerkin, while some recent applications require more efficient approaches (e.g. for real-time clinical decision support, phenomena occurring over multiple cardiac cycles, iterative solutions to optimization/inverse problems, and uncertainty quantification). Further, the high speed of pressure waves in blood vessels greatly restricts the time step needed for stability in explicit schemes. We address both cost and stability by presenting an efficient and unconditionally stable method for approximating solutions to diagonal nonlinear hyperbolic systems. Theoretical analysis of the algorithm is given along with a comparison of our method to a discontinuous Galerkin implementation. Lastly, we demonstrate the utility of the proposed method by implementing it on small and large arterial networks of vessels whose elastic and geometrical parameters are physiologically relevant.

Simulation of oxygen transfer in stented arteries and correlation with in-stent restenosis

Computational models are used to study the combined effect of biomechanical and biochemical factors on coronary in-stent restenosis, which is a postoperative remodeling and regrowth pathology of the stented arteries. More precisely, we address numerical simulations, on the basis of Navier-Stokes and mass transport equations, to study the role of perturbed wall shear stresses and reduced oxygen concentration in a geometrical model reconstructed from a real porcine artery treated with a stent. Joining in vivo and in silico tools of investigation has multiple benefits in this case. On one hand, the geometry of the arterial wall and of the stent closely correspond to a real implanted configuration. On the other hand, the inspection of histological tissue samples informs us on the location and intensity of in-stent restenosis. As a result, we are able to correlate geometrical factors, such as the axial variation of the artery diameter and its curvature; the numerical quantification of biochemical stimuli, such as wall shear stresses; and the availability of oxygen to the inner layers of the artery, with the appearance of in-stent restenosis. This study shows that the perturbation of the vessel curvature could induce hemodynamic conditions that stimulate undesired arterial remodeling.

Transient stress-based and strain-based hemolysis estimation in a simplified blood pump

We compare two approaches to numerical estimation of mechanical hemolysis in a simplified blood pump model. The stress-based model relies on the instantaneous shear stress in the blood flow, whereas the strain-based model uses an additional tensor equation to relate distortion of red blood cells to a shear stress measure. We use the newly proposed least-squares finite element method (LSFEM) to prevent negative concentration fields and show a stable and volume preserving LSFEM for the tensor equation. Application of both models to a simplified centrifugal blood pump at three different operating conditions shows that the stress-based model overestimates the rate of hemolysis. The strain-based model is found to deliver lower hemolysis rates because it incorporates a more detailed description of biophysical phenomena into the simulation process.