Fluid-structure interaction simulations of patient-specific aortic dissection

Generation of personalized synthetic 3-dimensional inlet velocity profiles for computational fluid dynamics simulations of type B aortic dissection

BACKGROUND

Computational fluid dynamics (CFD) simulations have shown promise in assessing type B aortic dissection (TBAD) to predict disease progression, and inlet velocity profiles (IVPs) are essential for such simulations. To truly capture patient-specific hemodynamic features, 3D IVPs extracted from 4D-flow magnetic resonance imaging (4D MRI) should be used, but 4D MRI is not commonly available.

METHOD

A new workflow was devised to generate personalized synthetic 3D IVPs that can replace 4D MRI-derived IVPs in CFD simulations. Based on 3D IVPs extracted from 4D MRI of 33 TBAD patients, statistical shape modelling and principal component analysis were performed to generate 270 synthetic 3D IVPs accounting for specific flow features. The synthetic 3D IVPs were then scaled and fine-tuned to match patient-specific stroke volume and systole-to-diastole ratio. The performance of personalized synthetic IVPs in CFD simulations was evaluated against patient-specific IVPs and compared with parabolic and flat IVPs.

RESULTS

Our results showed that the synthetic 3D IVP was sufficient for faithful reproduction of hemodynamics throughout the aorta. In the ascending aorta (AAo), where non-patient-specific IVPs failed to replicate in vivo flow features in previous studies, the personalized synthetic IVP was able to match not only the flow pattern but also time-averaged wall shear stress (TAWSS), with a mean TAWSS difference of 5.9 %, which was up to 36.5 % by idealized IVPs. Additionally, the predicted retrograde flow index in both the AAo (8.36 %) and descending aorta (8.17 %) matched closely the results obtained with the 4D MRI-derived IVP (7.36 % and 6.55 %). The maximum false lumen pressure difference was reduced to 11.6 % from 68.8 % by the parabolic IVP and 72.6 % by the flat IVP.

CONCLUSION

This study demonstrates the superiority of personalized synthetic 3D IVPs over commonly adopted parabolic or flat IVPs and offers a viable alternative to 4D MRI-derived IVP for CFD simulations of TBAD.

Impact of Residual Intimal Flap Displacement Post-TEVAR on TBAD Haemodynamics in Compliant, Patient-specific CFD Simulations Informed by MRI

We propose a novel formulation of a moving boundary method to account for the motion of the intimal flap (IF) in a TBAD post-thoracic endovascular aortic repair using patient-specific compliant computational fluid dynamics simulations. The simulations were informed by non-invasive 4D flow MRI sequences. Predicted flow waveforms, aortic wall, and IF displacements were validated against in vivo 4D flow MRI and cine-MRI data. The patient-specific simulation showed that at peak systole, the dynamic interplay between high IF displacement and high transmural pressures promoted true lumen compression and false lumen expansion, whilst luminal patterns were reversed at the deceleration phase. High vorticity and swirling flow patterns were observed throughout the cardiac cycle at the primary entry tear, the descending aorta and proximal to the visceral aortic branches, correlating with high relative residence time, which could indicate an increased localised risk of aortic growth proximal to the IF. A rigid IF simulation revealed significant discrepancies in haemodynamic metrics, highlighting the potential mispredictions when using a rigid wall assumption to assess disease progression. Simulations assuming a more compliant IF highlighted potential increased risks of visceral branches malperfusion and localised aortic wall degeneration. The study underscores the necessity of patient-specific compliant IF simulations for accurate TBAD haemodynamic assessments. These insights can improve disease understanding and inform future treatment strategies.

Importance of Considering Temporal Variations in Pulse Wave Velocity for Accurate Blood Pressure Prediction

PURPOSE

Continuous, cuffless blood pressure (BP) monitoring devices based on measuring pulse wave velocity (PWV) or pulse transit time (PTT) are emerging but are often plagued by large prediction errors. A key issue is that these techniques typically rely on a single PWV value, assuming a linear response and small arterial wall deformations. However, arterial response to BP is inherently nonlinear, with PWV varying over time [PWV(t)] by up to 50% during a cardiac cycle. This study evaluates the impact of assuming a single PWV on BP prediction accuracy.

METHOD

Using a Fluid-structure Interaction (FSI) testbed, we simulate the radial and common carotid arteries with the Holzapfel-Gasser-Ogden (HGO) constitutive model to capture nonlinear arterial behavior under a pulsatile physiological blood flow. Pressure data from FSI simulation are used as the ground truth, while inner area A(t) and two PWV values, at diastole and systole, serve as inputs to BP prediction models. Two models are tested: one using a single PWV value, emulating existing PWV-based BP prediction methods; another using the two PWV values to account for PWV(t).

RESULTS

The single-PWV BP model produced prediction errors of 17.44 mmHg and 6.57 mmHg for the radial and carotid arteries, respectively. The model incorporating two PWV values reduced these errors by 90.6% and 96.8%, respectively.

CONCLUSION

Relying on a single PWV in BP prediction models can lead to significant errors. To improve BP accuracy, future efforts should focus on incorporating PWV(t), or at least both diastolic and systolic PWV values, into these models.

Geometric uncertainty of patient-specific blood vessels and its impact on aortic hemodynamics: A computational study

In the context of numerical simulations of the vascular system, local geometric uncertainties have not yet been examined in sufficient detail due to model complexity and the associated large numerical effort. Such uncertainties are related to geometric modeling errors resulting from computed tomography imaging, segmentation and meshing. This work presents a methodology to systematically induce local modifications and perform a sufficient number of blood flow simulations to draw statistically relevant conclusions on the most commonly employed quantities of interest, such as flow rates or wall shear stress. The surface of a structured hexahedral mesh of a patient-specific aorta is perturbed by displacement maps defined via Gaussian random fields to stochastically model the local uncertainty of the boundary. Three different cases are studied, with the perturbation magnitude of 0.25, 0.5 and 1.0mm. Valid, locally perturbed meshes are constructed via an elasticity operator that extends surface perturbations into the interior. Otherwise, identical incompressible flow problems are solved on these meshes, taking physiological boundary conditions and Carreau fluid parameters into account. Roughly 300000 three-dimensional non-stationary blood flow simulations are performed for the three different perturbation cases to estimate the probability distributions of the quantities of interest. Convergence studies justify the spatial resolution of the employed meshes. Overall, the results suggest that moderate geometric perturbations result in reasonable engineering accuracy (relative errors in single-digit percentage range) of the quantities of interest, with higher sensitivity for gradient-related measures, noting that the observed errors are not negligible.

Enhancing the predictive capability of magnetic resonance imaging using medical data-supervised cardiovascular flow simulations: A case study for analyzing patient-specific flow in the human aorta

BACKGROUND

Detailed hemodynamic parameters are essential for managing cardiovascular diseases, as they reveal blood flow dynamics that affect disease progression and treatment. However, even such advanced techniques as 4D Phase Contrast MRI face challenges in providing accurate, high-resolution data due to limitations in spatial and temporal resolution and image artifacts. Computational Fluid Dynamics (CFD) can estimate these parameters theoretically, but patient-specific accuracy may be compromised due to assumptions in boundary conditions and material properties.

METHOD

Here, we aim to circumvent current limitations in medical imaging and CFD simulations by creating a comprehensive cardiovascular analytics model informed by clinical data. We develop a patient-specific simulation framework by deriving critical geometric parameters, boundary conditions, and aortic wall material properties directly from medical investigation and imaging data. This detailed information is subsequently integrated into Fluid-Structure-Interaction simulations to predict such key hemodynamic indicators as pressure distribution, wall deformation, time-averaged wall shear stress and oscillatory shear index to better assess individual vascular health. This approach effectively links imaging technology with computational modeling, as evidenced from our findings based on the medical imaging data of a representative human subject.

RESULTS AND CONCLUSION

The results reveal that such amalgamation of patient-specific parameters enhances the simulation's accuracy, offering a more comprehensive and precise assessment of cardiovascular health than the traditional generic approaches. This comprehensive framework thus has potential to become an invaluable clinical tool, enhancing the accuracy of hemodynamic assessment, moving toward more personalized care and informing effective treatment decision-making.

Mechanisms of aortic dissection: From pathological changes to experimental and in silico models

Aortic dissection continues to be responsible for significant morbidity and mortality, although recent advances in medical data assimilation and in experimental and in silico models have improved our understanding of the initiation and progression of the accumulation of blood within the aortic wall. Hence, there remains a pressing necessity for innovative and enhanced models to more accurately characterize the associated pathological changes. Early on, experimental models were employed to uncover mechanisms in aortic dissection, such as hemodynamic changes and alterations in wall microstructure, and to assess the efficacy of medical implants. While experimental models were once the only option available, more recently they are also being used to validate in silico models. Based on an improved understanding of the deteriorated microstructure of the aortic wall, numerous multiscale material models have been proposed in recent decades to study the state of stress in dissected aortas, including the changes associated with damage and failure. Furthermore, when integrated with accessible patient-derived medical data, in silico models prove to be an invaluable tool for identifying correlations between hemodynamics, wall stresses, or thrombus formation in the deteriorated aortic wall. They are also advantageous for model-guided design of medical implants with the aim of evaluating the deployment and migration of implants in patients. Nonetheless, the utility of in silico models depends largely on patient-derived medical data, such as chosen boundary conditions or tissue properties. In this review article, our objective is to provide a thorough summary of medical data elucidating the pathological alterations associated with this disease. Concurrently, we aim to assess experimental models, as well as multiscale material and patient data-informed in silico models, that investigate various aspects of aortic dissection. In conclusion, we present a discourse on future perspectives, encompassing aspects of disease modeling, numerical challenges, and clinical applications, with a particular focus on aortic dissection. The aspiration is to inspire future studies, deepen our comprehension of the disease, and ultimately shape clinical care and treatment decisions.

Cardiac Pulsatile Helical Deformation of the Thoracic Aorta Before and After Thoracic Endovascular Aortic Repair of Type B Dissections

PURPOSE

Type B aortic dissections propagate with either achiral (nonspiraling) or right-handed chiral (spiraling) morphology, have mobile dissection flaps, and are often treated with thoracic endovascular aortic repair (TEVAR). We aim to quantify cardiac-induced helical deformation of the true lumen of type B aortic dissections before and after TEVAR.

MATERIAL AND METHODS

Retrospective cardiac-gated computed tomography (CT) images before and after TEVAR of type B aortic dissections were used to construct systolic and diastolic 3-dimensional (3D) surface models, including true lumen, whole lumen (true+false lumens), and branch vessels. This was followed by extraction of true lumen helicity (helical angle, twist, and radius) and cross-sectional (area, circumference, and minor/major diameter ratio) metrics. Deformations between systole and diastole were quantified, and deformations between pre- and post-TEVAR were compared.

RESULTS

Eleven TEVAR patients (59.9±4.6 years) were included in this study. Pre-TEVAR, there were no significant cardiac-induced deformations of helical metrics; however, post-TEVAR, significant deformation was observed for the true lumen proximal angular position. Pre-TEVAR, cardiac-induced deformations of all cross-sectional metrics were significant; however, only area and circumference deformations remained significant post-TEVAR. There were no significant differences of pulsatile deformation from pre- to post-TEVAR. Variance of proximal angular position and cross-sectional circumference deformation decreased after TEVAR.

CONCLUSION

Pre-TEVAR, type B aortic dissections did not exhibit significant helical cardiac-induced deformation, indicating that the true and false lumens move in unison (do not move with respect to each other). Post-TEVAR, true lumens exhibited significant cardiac-induced deformation of proximal angular position, suggesting that exclusion of the false lumen leads to greater rotational deformations of the true lumen and lack of true lumen major/minor deformation post-TEVAR means that the endograft promotes static circularity. Population variance of deformations is muted after TEVAR, and dissection acuity influences pulsatile deformation while pre-TEVAR chirality does not.Clinical ImpactDescription of thoracic aortic dissection helical morphology and dynamics, and understanding the impact of thoracic endovascular aortic repair (TEVAR) on dissection helicity, are important for improving endovascular treatment. These findings provide nuance to the complex shape and motion of the true and false lumens, enabling clinicians to better stratify dissection disease. The impact of TEVAR on dissection helicity provides a description of how treatment alters morphology and motion, and may provide clues for treatment durability. Finally, the helical component to endograft deformation is important to form comprehensive boundary conditions for testing and developing new endovascular devices.

Noninvasive estimation of central blood pressure through fluid-structure interaction modeling

Central blood pressure (cBP) is considered a superior indicator of cardiovascular fitness than brachial blood pressure (bBP). Even though bBP is easy to measure noninvasively, it is usually higher than cBP due to pulse wave amplification, characterized by the gradual increase in peak systolic pressure during pulse wave propagation. In this study, we aim to develop an individualized transfer function that can accurately estimate cBP from bBP. We first construct a three-dimensional, patient-specific model of the upper limb arterial system using fluid-structure interaction simulations, incorporating variable material properties and complex boundary conditions. Then, we develop an analytical brachial-aortic transfer function based on novel solutions for compliant vessels. The accuracy of this transfer function is successfully validated against numerical simulation results, which effectively reproduce pulse wave propagation and amplification, with key hemodynamic parameters falling within the range of clinical measurements. Further analysis of the transfer function reveals that cBP is a linear combination of bBP and aortic flow rate in the frequency domain, with the coefficients determined by vessel geometry, material properties, and boundary conditions. Additionally, bBP primarily contributes to the steady component of cBP, while the aortic flow rate is responsible for the pulsatile component. Furthermore, local sensitivity analysis indicates that the lumen radius is the most influential parameter in accurately estimating cBP. Although not directly applicable clinically, the proposed transfer function enhances understanding of the underlying physics-highlighting the importance of aortic flow and lumen radius-and can guide the development of more practical transfer functions.

Bayesian Windkessel calibration using optimized zero-dimensional surrogate models

Bayesian boundary condition (BC) calibration approaches from clinical measurements have successfully quantified inherent uncertainties in cardiovascular fluid dynamics simulations. However, estimating the posterior distribution for all BC parameters in three-dimensional (3D) simulations has been unattainable due to infeasible computational demand. We propose an efficient method to identify Windkessel parameter posteriors: We only evaluate the 3D model once for an initial choice of BCs and use the result to create a highly accurate zero-dimensional (0D) surrogate. We then perform Sequential Monte Carlo (SMC) using the optimized 0D model to derive the high-dimensional Windkessel BC posterior distribution. Optimizing 0D models to match 3D data a priori lowered their median approximation error by nearly one order of magnitude in 72 publicly available vascular models. The optimized 0D models generalized well to a wide range of BCs. Using SMC, we evaluated the high-dimensional Windkessel parameter posterior for different measured signal-to-noise ratios in a vascular model, which we validated against a 3D posterior. The minimal computational demand of our method using a single 3D simulation, combined with the open-source nature of all software and data used in this work, will increase access and efficiency of Bayesian Windkessel calibration in cardiovascular fluid dynamics simulations.This article is part of the theme issue 'Uncertainty quantification for healthcare and biological systems (Part 1)'.

Assessment of Aortic Dissection Remodeling With Patient-Specific Fluid-Structure Interaction Models

Aortic dissection leads to late complications due tochronic degeneration and dilatation of the false lumen. This study examines the interaction between hemodynamics and long-term remodeling of a patient's aortic dissection, tracked from pre-dissection to the chronic phase using CT angiography. Fluid-structure interaction models with tissue prestress, external support, and anisotropic properties were used to analyze hemodynamic markers. Each aortic wall layer had distinct thicknesses and material properties. The boundary conditions were guided by in vitro 4D-flow MRI and the patient's blood pressure. Aortic dilatation was most significant distal to the left subclavian artery, reaching 6 cm in the chronic phase. Simulations quantified the flow jet velocity through the entry tear, which peaked at 185 cm/s in the subacute phase and decreased to 123 to 133 cm/s in the chronic phase, corresponding to an increased entry tear size. Flow jet impingement on the false lumen resulted in a localized pressure increase of 11 and 2 mmHg in the subacute and chronic phases, with wall shear stress reaching 4 Pa. These hemodynamic changes appear to be the main drivers of aortic growth and morphological changes. Despite moderate overall flap movement, in-plane displacement increased from 0.6 to 1.8 mm as disease progressed, which was associated with an overall increase in aortic diameter. Simulations with a significant reduction in flap stiffness during the subacute phase resulted in increased flap motion up to 9.5 mm. Although these results are based on a single patient, they suggest a strong relationship between hemodynamics and aortic growth.

Predicting Late Adverse Events in Uncomplicated Stanford Type B Aortic Dissection: Results From the ROADMAP Validation Study

BACKGROUND

Risk stratification is highly desirable in patients with uncomplicated Stanford type B aortic dissection but inadequately supported by evidence. We sought to validate externally a published prediction model for late adverse events (LAEs), consisting of 1 clinical (connective tissue disease) and 4 imaging variables: maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and number of identifiable intercostal arteries.

METHODS

We assembled a retrospective multicenter cohort (ROADMAP [Registry of Aortic Diseases to Model Adverse Events and Progression]) of 401 patients with uncomplicated Stanford type B aortic dissection presenting to 1 of 8 aortic centers between 2001 and 2013, followed until 2020. LAEs were defined as fatal or nonfatal aortic rupture, new refractory hypertension or pain, organ or limb ischemia, aortic aneurysm formation (≥6 cm), or rapid growth (≥1 cm per year). We applied the original model parameters to the validation cohort and examined the effect on risk categorization using LAE end points.

RESULTS

One hundred and seventy-six patients (44%) with incomplete imaging or clinical data were excluded. Of 225 patients in the final cohort, 90 (40%) developed LAEs, predominantly driven by aneurysm formation. Baseline maximum aortic diameter was significantly larger in patients with (42.6 [95% CI, 39.1-45.8] mm) compared with patients without LAEs (39.9 [95% CI, 36.3-44.2] mm; P=0.001). A multivariable Cox regression model indicated that only maximum diameter was associated with LAEs (hazard ratio, 1.07 [95% CI, 1.03-1.11] per mm; P<0.001), while the other parameters were not (P>0.05). Applying the original prediction model to the validation cohort resulted in a poor 5-year sensitivity (38%) and specificity (69%).

CONCLUSIONS

A clinical and imaging-based prediction model performed poorly in the ROADMAP cohort. Maximum aortic diameter remains the strongest predictor of LAEs in uncomplicated Stanford type B aortic dissection.

Modeling Fibrous Tissue in Vascular Fluid-Structure Interaction: A Morphology-Based Pipeline and Biomechanical Significance

Modeling fibrous tissue for vascular fluid-structure interaction analysis poses significant challenges due to the lack of effective tools for preparing simulation data from medical images. This limitation hinders the physiologically realistic modeling of vasculature and its use in clinical settings. Leveraging an established lumen modeling strategy, we propose a comprehensive pipeline for generating thick-walled artery models. A specialized mesh generation procedure is developed to ensure mesh continuity across the lumen and wall interface. Exploiting the centerline information, a series of procedures are introduced for generating local basis vectors within the arterial wall. The procedures are tailored to handle thick-walled tissues where basis vectors may exhibit transmural variations. Additionally, we propose methods for accurately identifying the centerline in multi-branched vessels and bifurcating regions. These modeling approaches are algorithmically implementable, rendering them readily integrable into mainstream cardiovascular modeling software. The developed fiber generation method is evaluated against the strategy using linear elastostatics analysis, demonstrating that the proposed approach yields satisfactory fiber definitions in the considered benchmark. Finally, we examine the impact of anisotropic arterial wall models on the vascular fluid-structure interaction analysis through numerical examples, employing the neo-Hookean model for comparative purposes. The first case involves an idealized curved geometry, while the second studies an image-based abdominal aorta model. Our numerical results reveal that the deformation and stress distribution are critically related to the constitutive model of the wall, whereas hemodynamic factors are less sensitive to the wall model. This work paves the way for more accurate image-based vascular modeling and enhances the prediction of arterial behavior under physiologically realistic conditions.

Biomechanical stress analysis of Type-A aortic dissection at pre-dissection, post-dissection, and post-repair states

Acute type A aortic dissection remains a deadly and elusive condition, with risk factors such as hypertension, bicuspid aortic valves, and genetic predispositions. As existing guidelines for surgical intervention based solely on aneurysm diameter face scrutiny, there is a growing need to consider other predictors and parameters, including wall stress, in assessing dissection risk. Through our research, we aim to elucidate the biomechanical underpinnings of aortic dissection and provide valuable insights into its prediction and prevention. We applied finite element analysis (FEA) to assess stress distribution on a rare dataset comprising computed tomography (CT) images obtained from eight patients at three stages of aortic dissection: pre-dissection (preD), post-dissection (postD), and post-repair (postR). Our findings reveal significant increases in both mean and peak aortic wall stresses during the transition from the preD state to the postD state, reflecting the mechanical impact of dissection. Surgical repair effectively restores aortic wall diameter to pre-dissection levels, documenting its effectiveness in mitigating further complications. Furthermore, we identified stress concentration regions within the aortic wall that closely correlated with observed dissection borders, offering insights into high-risk areas. This study demonstrates the importance of considering biomechanical factors when assessing aortic dissection risk. Despite some limitations, such as uniform wall thickness assumptions and the absence of dynamic blood flow considerations, our patient-specific FEA approach provides valuable mechanistic insights into aortic dissection. These findings hold promise for improving predictive models and informing clinical decisions to enhance patient care.

Effective property method for efficient modeling of non-uniform tissue support in fluid-structure interaction simulation of blood flows

BACKGROUND AND OBJECTIVE

Incorporating tissue support in fluid-structure interaction analysis of cardiovascular flows is crucial for accurately representing physiological constraints, achieving realistic vessel wall motion, and minimizing artificial oscillations. The generalized Robin boundary condition, which models tissue support with a spring-damper-type force, uses elastic and damping parameters to represent the viscoelastic behavior of perivascular tissues. Using spatially distributed parameters for tissue support, rather than uniform ones, is more realistic and aligns with the varying properties of vessel walls. However, considering the spatial distribution of both can increase the complexity of preprocessing and numerical implementation. In this work, we develop an effective property method for efficient modeling of non-uniform tissue support and quantifying the contribution of tissue support to the mechanical behaviors of vessel walls.

METHODS

Based on the theory of linear viscoelasticity, we derive the mathematical formulas for the effective property method, integrating the parameters of generalized Robin boundary condition into vessel wall properties. The pulse wave velocity incorporating the influence of tissue support is also analyzed. Furthermore, we modify the coupled momentum method, originally formulated for elastic problems, to account for the viscoelastic properties of the vessel wall.

RESULTS

The method is verified with three-dimensional fluid-structure interaction simulations, achieving a maximum relative error of less than 2.2% for flow rate and less than 0.7% for pressure. This method shows that tissue support parameters can be integrated into vessel wall properties, resulting in increased apparent wall stiffness and viscosity, and further changing pressure, flow rate, and wave propagation.

CONCLUSION

In this study, we develop an effective property method for quantitatively assessing the impact of tissue support and for efficiently modeling non-uniform tissue support. Moreover, this method offers further insights into clinically measured pulse wave velocity, demonstrating that it reflects the combined influence of both vessel wall properties and tissue support.

Comparative analysis of Zero Pressure Geometry and prestress methods in cardiovascular Fluid-Structure Interaction

BACKGROUND AND OBJECTIVE

Modelling patient-specific aortic biomechanics with advanced computational techniques, such as Fluid-Structure Interaction (FSI), can be crucial to provide effective decision-making indices to enhance current clinical practices. To effectively simulate Ascending Thoracic Aortic Aneurysms (ATAA), the stress-free configuration must be defined. The Zero Pressure Geometry (ZPG) and the Prestress Tensor (PT) are two of the main approaches to tackle this issue. However, their impact on the numerical results is yet to be analysed. Computed Tomography Angiography (CTA) and Magnetic Resonance Imaging (MRI) data were used to develop patient-specific 2-way FSI frameworks.

METHODS

Three models were developed considering different tissue prestressing approaches to account for the reference configuration and their numerical results were compared. The selected approaches were: (i) ZPG, (ii) PT and (iii) a combination of the PT approach with a regional mapping of material properties (PTCAL).

RESULTS

The pressure fields estimated by all models were equivalent. The estimation of Wall Shear Stress (WSS) based metrics revealed good correspondence between all models except the Relative Residence Time (RRT). Regarding ATAA wall mechanics, the proposed extension to the PT approach presented a closer agreement with the ZPG model than its counterpart. Additionally, the PT and PTCAL approaches required around 60% fewer iterations to achieve cycle-to-cycle convergence than the ZPG algorithm.

CONCLUSION

Using a regional mapping of material properties in combination with the PT method presented a better correspondence with the ZPG approach. The outcomes of this study can pave the way for advancing the accuracy and convergence of ATAA numerical models using the PT methodology.

Investigating the role of thrombosis and false lumen orbital orientation in the hemodynamics of Type B aortic dissection

While much about the fundamental mechanisms behind the initiation and progression of Type B aortic dissection (TBAD) is still unknown, predictive models based on patient-specific fluid-structure interaction (FSI) simulations can help in risk stratification and optimal clinical decision-making. Aiming at the development of personalized treatment, FSI models can be leveraged to investigate the interplay between complex aortic flow patterns and anatomical features, while considering the deformation of the arterial wall and the dissection flap. In this study, the hemodynamics of false lumen thrombosis, a large fenestration, and the orbital orientation of the false lumen is studied through image-based FSI simulations on three TBAD patient-specific geometries. A new pipeline is developed leveraging the open-source software SimVascular and ParaView to analyze multiple patients simultaneously and to achieve large-scale parallelization in FSI results based on patients' computed tomography (CT) images. The results of this study suggest that the internal orbital orientation of the false lumen contributes to maintaining a positive luminal pressure difference Δ P T L - F L =P TL - P FL between the true lumen (TL) and the false lumen (FL), despite an impingement area in the false lumen near the entry tear. A positive and high luminal pressure difference is thought to promote TL expansion and FL compression. Moreover, it was also found that FL thrombosis at the entry tear region reduce the magnitude of the negative luminal pressure difference, which in turn may reduce FL expansion and the risk of unstable aortic growth. Finally, this FSI study suggests that the aortic wall and dissection flap stiffness determines the effects of a large fenestration in the descending thoracic aorta on the luminal pressure difference.

A semi-automatic method for block-structured hexahedral meshing of aortic dissections

The article presents a semi-automatic approach to generating structured hexahedral meshes of patient-specific aortas ailed by aortic dissection. The condition manifests itself as a formation of two blood flow channels in the aorta, as a result of a tear in the inner layers of the aortic wall. Subsequently, the morphology of the aorta is greatly impacted, making the task of domain discretization highly challenging. The meshing algorithm presented herein is automatic for the individual lumina, whereas the tears require user interaction. Starting from an input (triangle) surface mesh, we construct an implicit surface representation as well as a topological skeleton, which provides a basis for the generation of a block-structure. Thereafter, the mesh generation is performed via transfinite maps. The meshes are structured and fully hexahedral, exhibit good quality and reliably match the original surface. As they are generated with computational fluid dynamics in mind, a fluid flow simulation is performed to verify their usefulness. Moreover, since the approach is based on valid block-structures, the meshes can be made very coarse (around 1000 elements for an entire aortic dissection domain), and thus promote using solvers based on the geometric multigrid method, which is typically reliant on the presence of a hierarchy of coarser meshes.

Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins

Understanding the evolving nature of coronary hemodynamics is crucial for early disease detection and monitoring progression. We require digital twins that mimic a patient's circulatory system by integrating continuous physiological data and computing hemodynamic patterns over months. Current models match clinical flow measurements but are limited to single heartbeats. To this end, we introduced the longitudinal hemodynamic mapping framework (LHMF), designed to tackle critical challenges: (1) computational intractability of explicit methods; (2) boundary conditions reflecting varying activity states; and (3) accessible computing resources for clinical translation. We show negligible error (0.0002-0.004%) between LHMF and explicit data of 750 heartbeats. We deployed LHMF across traditional and cloud-based platforms, demonstrating high-throughput simulations on heterogeneous systems. Additionally, we established LHMFC, where hemodynamically similar heartbeats are clustered to avoid redundant simulations, accurately reconstructing longitudinal hemodynamic maps (LHMs). This study captured 3D hemodynamics over 4.5 million heartbeats, paving the way for cardiovascular digital twins.

An efficient procedure for the blood flow computer simulation of patient-specific aortic dissections

In this work we present a novel methodology for the numerical simulation of patient-specific aortic dissections. Our proposal, which targets the seamless virtual prototyping of customized scenarios, combines an innovative two-step segmentation procedure with a CutFEM technique capable of dealing with thin-walled bodies such as the intimal flap. First, we generate the fluid mesh from the outer aortic wall disregarding the intimal flap, similarly to what would be done in a healthy aorta. Second, we create a surface mesh from the approximate midline of the intimal flap. This approach allows us to decouple the segmentation of the fluid volume from that of the intimal flap, thereby bypassing the need to create a volumetric mesh around a thin-walled body, an operation widely known to be complex and error-prone. Once the two meshes are obtained, the original configuration of the dissection into true and false lumen is recovered by embedding the surface mesh into the volumetric one and calculating a level set function that implicitly represents the intimal flap in terms of the volumetric mesh entities. We then leverage the capabilities of unfitted mesh methods, specifically relying on a CutFEM technique tailored for thin-walled bodies, to impose the wall boundary conditions over the embedded intimal flap. We tested the method by simulating the flow in four patient-specific aortic dissections, all involving intricate geometrical patterns. In all cases, the preprocess is greatly simplified with no impact on the computational times. Additionally, the obtained results are consistent with clinical evidence and previous research.

Physics-informed neural networks for parameter estimation in blood flow models

BACKGROUND

Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving inverse problems, especially in cases where no complete information about the system is known and scatter measurements are available. This is especially useful in hemodynamics since the boundary information is often difficult to model, and high-quality blood flow measurements are generally hard to obtain.

METHODS

In this work, we use the PINNs methodology for estimating reduced-order model parameters and the full velocity field from scatter 2D noisy measurements in the aorta. Two different flow regimes, stationary and transient were studied.

RESULTS

We show robust and relatively accurate parameter estimations when using the method with simulated data, while the velocity reconstruction accuracy shows dependence on the measurement quality and the flow pattern complexity. Comparison with a Kalman filter approach shows similar results when the number of parameters to be estimated is low to medium. For a higher number of parameters, only PINNs were capable of achieving good results.

CONCLUSION

The method opens a door to deep-learning-driven methods in the simulations of complex coupled physical systems.

Critical role of arterial constitutive model in predicting blood pressure from pulse wave velocity

BACKGROUND

A promising approach to cuff-less, continuous blood pressure monitoring is to estimate blood pressure (BP) from Pulse Wave Velocity (PWV). However, most existing PWV-based methods rely on empirical BP-PWV relations and have large prediction errors, which may be caused by the implicit assumption of thin-walled, linear elastic arteries undergoing small deformations. Our objective is to understand the BP-PWV relationship in the absence of such limiting assumptions.

METHOD

We performed Fluid-Structure Interaction (FSI) simulations of the radial artery and the common carotid artery under physiological flow conditions. In these dynamic simulations, we employed two constitutive models for the arterial wall: the linear elastic model, implying a thin-walled linear elastic artery undergoing small deformations, and the Holzapfel-Gasser-Ogden (HGO) model, accounting for the nonlinear effects of collagen fibers and their orientations on the large arterial deformation.

RESULTS

Despite the changing BP, the linear elastic model predicts a constant PWV throughout a cardiac cycle, which is not physiological. The HGO model correctly predicts a positive BP-PWV correlation by capturing the nonlinear deformation of the artery, showing up to 50 % variations of PWV in a cardiac cycle.

CONCLUSION

Dynamic FSI simulations reveal that the BP-PWV relationship strongly depends on the arterial constitutive model, especially in the radial artery. To infer BP from PWV, one must account for the varying PWV, a consequence of the nonlinear arterial response due to collagen fibers. Future efforts should be directed towards robust measurement of time-varying PWV if it is to be used to predict BP.

A Monte Carlo Sensitivity Analysis for a Dimensionally Reduced-Order Model of the Aortic Dissection

PURPOSE

Aortic dissection is associated with a high mortality rate. Although computational approaches have shed light on many aspects of the disease, a sensitivity analysis is required to determine the significance of different factors. Because of its complex geometry and high computational expense, the three-dimensional (3D) fluid-structure interaction (FSI) simulation is not a suitable approach for sensitivity analysis.

METHODS

We performed a Monte Carlo simulation (MCS) to investigate the sensitivity of hemodynamic quantities to the lumped parameters of our zero-dimensional (0D) model with numerically calculated lumped parameters. We performed local and global analyses on the effect of the model parameters on important hemodynamic quantities.

RESULTS

The MCS showed that a larger lumped resistance value for the false lumen and the tears result in a higher retrograde flow rate in the false lumen (the coefficient of variation,c v , i = 0.0183 , the sensitivityS X i σ = 0.54 , Spearman's coefficient,ρ s = 0.464 ). For the intraluminal pressure, our results show a significant role in the resistance and inertance of the true lumen (the coefficient of variation,c v , i = 0.0640 , the sensitivityS X i σ = 0.85 , and Spearman's coefficient,ρ s = 0.855 for the inertance of the true lumen).

CONCLUSION

This study highlights the necessity of comparing the results of the local and global sensitivity analyses to understand the significance of multiple lumped parameters. Because of the efficiency of the method, our approach is potentially useful to investigate and analyze medical planning.

A Modular Framework for Implicit 3D-0D Coupling in Cardiac Mechanics

In numerical simulations of cardiac mechanics, coupling the heart to a model of the circulatory system is essential for capturing physiological cardiac behavior. A popular and efficient technique is to use an electrical circuit analogy, known as a lumped parameter network or zero-dimensional (0D) fluid model, to represent blood flow throughout the cardiovascular system. Due to the strong physical interaction between the heart and the blood circulation, developing accurate and efficient numerical coupling methods remains an active area of research. In this work, we present a modular framework for implicitly coupling three-dimensional (3D) finite element simulations of cardiac mechanics to 0D models of blood circulation. The framework is modular in that the circulation model can be modified independently of the 3D finite element solver, and vice versa. The numerical scheme builds upon a previous work that combines 3D blood flow models with 0D circulation models (3D fluid - 0D fluid). Here, we extend it to couple 3D cardiac tissue mechanics models with 0D circulation models (3D structure - 0D fluid), showing that both mathematical problems can be solved within a unified coupling scheme. The effectiveness, temporal convergence, and computational cost of the algorithm are assessed through multiple examples relevant to the cardiovascular modeling community. Importantly, in an idealized left ventricle example, we show that the coupled model yields physiological pressure-volume loops and naturally recapitulates the isovolumic contraction and relaxation phases of the cardiac cycle without any additional numerical techniques. Furthermore, we provide a new derivation of the scheme inspired by the Approximate Newton Method of Chan (1985), explaining how the proposed numerical scheme combines the stability of monolithic approaches with the modularity and flexibility of partitioned approaches.

Simulating impaired left ventricular-arterial coupling in aging and disease: a systematic review

Aortic stenosis, hypertension, and left ventricular hypertrophy often coexist in the elderly, causing a detrimental mismatch in coupling between the heart and vasculature known as ventricular-vascular (VA) coupling. Impaired left VA coupling, a critical aspect of cardiovascular dysfunction in aging and disease, poses significant challenges for optimal cardiovascular performance. This systematic review aims to assess the impact of simulating and studying this coupling through computational models. By conducting a comprehensive analysis of 34 relevant articles obtained from esteemed databases such as Web of Science, Scopus, and PubMed until July 14, 2022, we explore various modeling techniques and simulation approaches employed to unravel the complex mechanisms underlying this impairment. Our review highlights the essential role of computational models in providing detailed insights beyond clinical observations, enabling a deeper understanding of the cardiovascular system. By elucidating the existing models of the heart (3D, 2D, and 0D), cardiac valves, and blood vessels (3D, 1D, and 0D), as well as discussing mechanical boundary conditions, model parameterization and validation, coupling approaches, computer resources and diverse applications, we establish a comprehensive overview of the field. The descriptions as well as the pros and cons on the choices of different dimensionality in heart, valve, and circulation are provided. Crucially, we emphasize the significance of evaluating heart-vessel interaction in pathological conditions and propose future research directions, such as the development of fully coupled personalized multidimensional models, integration of deep learning techniques, and comprehensive assessment of confounding effects on biomarkers.

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.

Fluid-Structure Interaction Within Models of Patient-Specific Arteries: Computational Simulations and Experimental Validations

Cardiovascular disease (CVD) is the leading cause of mortality worldwide and its incidence is rising due to an aging population. The development and progression of CVD is directly linked to adverse vascular hemodynamics and biomechanics, whose in-vivo measurement remains challenging but can be simulated numerically and experimentally. The ability to evaluate these parameters in patient-specific CVD cases is crucial to better predict future disease progression, risk of adverse events, and treatment efficacy. While significant progress has been made toward patient-specific hemodynamic simulations, blood vessels are often assumed to be rigid, which does not consider the compliant mechanical properties of vessels whose malfunction is implicated in disease. In an effort to simulate the biomechanics of flexible vessels, fluid-structure interaction (FSI) simulations have emerged as promising tools for the characterization of hemodynamics within patient-specific cardiovascular anatomies. Since FSI simulations combine the blood's fluid domain with the arterial structural domain, they pose novel challenges for their experimental validation. This paper reviews the scientific work related to FSI simulations for patient-specific arterial geometries and the current standard of FSI model validation including the use of compliant arterial phantoms, which offer novel potential for the experimental validation of FSI results.

Hemodynamic effects of entry and exit tear size in aortic dissection evaluated with in vitro magnetic resonance imaging and fluid-structure interaction simulation

Understanding the complex interplay between morphologic and hemodynamic features in aortic dissection is critical for risk stratification and for the development of individualized therapy. This work evaluates the effects of entry and exit tear size on the hemodynamics in type B aortic dissection by comparing fluid-structure interaction (FSI) simulations with in vitro 4D-flow magnetic resonance imaging (MRI). A baseline patient-specific 3D-printed model and two variants with modified tear size (smaller entry tear, smaller exit tear) were embedded into a flow- and pressure-controlled setup to perform MRI as well as 12-point catheter-based pressure measurements. The same models defined the wall and fluid domains for FSI simulations, for which boundary conditions were matched with measured data. Results showed exceptionally well matched complex flow patterns between 4D-flow MRI and FSI simulations. Compared to the baseline model, false lumen flow volume decreased with either a smaller entry tear (- 17.8 and - 18.5%, for FSI simulation and 4D-flow MRI, respectively) or smaller exit tear (- 16.0 and - 17.3%). True to false lumen pressure difference (initially 11.0 and 7.9 mmHg, for FSI simulation and catheter-based pressure measurements, respectively) increased with a smaller entry tear (28.9 and 14.6 mmHg), and became negative with a smaller exit tear (- 20.6 and - 13.2 mmHg). This work establishes quantitative and qualitative effects of entry or exit tear size on hemodynamics in aortic dissection, with particularly notable impact observed on FL pressurization. FSI simulations demonstrate acceptable qualitative and quantitative agreement with flow imaging, supporting its deployment in clinical studies.

Calibration of the Mechanical Boundary Conditions for a Patient-Specific Thoracic Aorta Model Including the Heart Motion Effect

OBJECTIVE

We propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model derived from one patient with ascending aortic aneurysm. The BCs reproduce the visco-elastic structural support provided by the soft tissue and the spine and allow for the inclusion of the heart motion effect.

METHODS

We first segment the TA from magnetic resonance imaging (MRI) angiography and derive the heart motion by tracking the aortic annulus from cine-MRI. A rigid-wall fluid-dynamic simulation is performed to derive the time-varying wall pressure field. We build the finite element model considering patient-specific material properties and imposing the derived pressure field and the motion at the annulus boundary. The calibration, which involves the zero-pressure state computation, is based on purely structural simulations. After obtaining the vessel boundaries from the cine-MRI sequences, an iterative procedure is performed to minimize the distance between them and the corresponding boundaries derived from the deformed structural model. A strongly-coupled fluid-structure interaction (FSI) analysis is finally performed with the tuned parameters and compared to the purely structural simulation.

RESULTS AND CONCLUSION

The calibration with structural simulations allows to reduce maximum and mean distances between image-derived and simulation-derived boundaries from 8.64 mm to 6.37 mm and from 2.24 mm to 1.83 mm, respectively. The maximum root mean square error between the deformed structural and FSI surface meshes is 0.19 mm. This procedure may prove crucial for increasing the model fidelity in replicating the real aortic root kinematics.

Sizing the Frozen Elephant Trunk Based on Aortic Pathology and the Importance of Pre-Operative Imaging

The frozen elephant trunk is a formidable tool for the aortovascular surgeon. An appreciation of how to size the graft in different pathologies is key in achieving optimal results. Herein, we demonstrate worked examples of how imaging can be used to plan for a frozen elephant trunk and discuss the nuisances and uncertainties of sizing using three index cases: Type A aortic dissection, distal thoracic aortic aneurysm and chronic dissection.

Fluid-structure interactions of peripheral arteries using a coupled in silico and in vitro approach

Vascular compliance is considered both a cause and a consequence of cardiovascular disease and a significant factor in the mid- and long-term patency of vascular grafts. However, the biomechanical effects of localised changes in compliance cannot be satisfactorily studied with the available medical imaging technologies or surgical simulation materials. To address this unmet need, we developed a coupled silico-vitro platform which allows for the validation of numerical fluid-structure interaction results as a numerical model and physical prototype. This numerical one-way and two-way fluid-structure interaction study is based on a three-dimensional computer model of an idealised femoral artery which is validated against patient measurements derived from the literature. The numerical results are then compared with experimental values collected from compliant arterial phantoms via direct pressurisation and ring tensile testing. Phantoms within a compliance range of 1.4-68.0%/100 mmHg were fabricated via additive manufacturing and silicone casting, then mechanically characterised via ring tensile testing and optical analysis under direct pressurisation with moderately statistically significant differences in measured compliance ranging between 10 and 20% for the two methods. One-way fluid-structure interaction coupling underestimated arterial wall compliance by up to 14.7% compared with two-way coupled models. Overall, Solaris™ (Smooth-On) matched the compliance range of the numerical and in vivo patient models most closely out of the tested silicone materials. Our approach is promising for vascular applications where mechanical compliance is especially important, such as the study of diseases which commonly affect arterial wall stiffness, such as atherosclerosis, and the model-based design, surgical training, and optimisation of vascular prostheses.

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.

Aneurysmal growth in type-B aortic dissection: assessing the impact of patient-specific inlet conditions on key haemodynamic indices

Type-B aortic dissection is a cardiovascular disease in which a tear develops in the intimal layer of the descending aorta, allowing pressurized blood to delaminate the layers of the vessel wall. In medically managed patients, long-term aneurysmal dilatation of the false lumen (FL) is considered virtually inevitable and is associated with poorer disease outcomes. While the pathophysiological mechanisms driving FL dilatation are not yet understood, haemodynamic factors are believed to play a key role. Computational fluid dynamics (CFD) and 4D-flow MRI (4DMR) analyses have revealed correlations between flow helicity, oscillatory wall shear stress and aneurysmal dilatation of the FL. In this study, we compare CFD simulations using a patient-specific, three-dimensional, three-component inlet velocity profile (4D IVP) extracted from 4DMR data against simulations with flow rate-matched uniform and axial velocity profiles that remain widely used in the absence of 4DMR. We also evaluate the influence of measurement errors in 4DMR data by scaling the 4D IVP to the degree of imaging error detected in prior studies. We observe that oscillatory shear and helicity are highly sensitive to inlet velocity distribution and flow volume throughout the FL and conclude that the choice of IVP may greatly affect the future clinical value of simulations.

Hemodynamic parameters impact the stability of distal stent graft-induced new entry

Stent graft-induced new entry tear (SINE) is a serious complication in aortic dissection patients caused by the stent-graft itself after thoracic endovascular aortic repair (TEVAR). The stability of SINE is a key indicator for the need and timing of reinterventions. This study aimed to understand the role of hemodynamics in SINE stability by means of computational fluid dynamics (CFD) analysis based on patient-specific anatomical information. Four patients treated with TEVAR who developed a distal SINE (dSINE) were included; two patients had a stable dSINE and two patients experienced expansion of the dSINE upon follow-up examinations. CFD simulations were performed on geometries reconstructed from computed tomography scans acquired upon early detection of dSINE in these patients. Computational results showed that stable dSINEs presented larger regions with low time-averaged wall shear stress (TAWSS) and high relative residence time (RRT), and partial thrombosis was observed at subsequent follow-ups. Furthermore, significant systolic antegrade flow was observed in the unstable dSINE which also had a larger retrograde flow fraction (RFF) on the SINE plane. In conclusion, this pilot study suggested that high RRT and low TAWSS may indicate stable dSINE by promoting thrombosis, whereas larger RFF and antegrade flows inside dSINE might be associated with its expansion.

Modeling Dynamics of the Cardiovascular System Using Fluid-Structure Interaction Methods

Using fluid-structure interaction algorithms to simulate the human circulatory system is an innovative approach that can provide valuable insights into cardiovascular dynamics. Fluid-structure interaction algorithms enable us to couple simulations of blood flow and mechanical responses of the blood vessels while taking into account interactions between fluid dynamics and structural behaviors of vessel walls, heart walls, or valves. In the context of the human circulatory system, these algorithms offer a more comprehensive representation by considering the complex interplay between blood flow and the elasticity of blood vessels. Algorithms that simulate fluid flow dynamics and the resulting forces exerted on vessel walls can capture phenomena such as wall deformation, arterial compliance, and the propagation of pressure waves throughout the cardiovascular system. These models enhance the understanding of vasculature properties in human anatomy. The utilization of fluid-structure interaction methods in combination with medical imaging can generate patient-specific models for individual patients to facilitate the process of devising treatment plans. This review evaluates current applications and implications of fluid-structure interaction algorithms with respect to the vasculature, while considering their potential role as a guidance tool for intervention procedures.

The Influence of Minor Aortic Branches in Patient-Specific Flow Simulations of Type-B Aortic Dissection

Type-B aortic dissection (TBAD) is a disease in which a tear develops in the intimal layer of the descending aorta forming a true lumen and false lumen (FL). Because disease outcomes are thought to be influenced by haemodynamic quantities such as pressure and wall shear stress (WSS), their analysis via numerical simulations may provide valuable clinical insights. Major aortic branches are routinely included in simulations but minor branches are virtually always neglected, despite being implicated in TBAD progression and the development of complications. As minor branches are estimated to carry about 7-21% of cardiac output, neglecting them may affect simulation accuracy. We present the first simulation of TBAD with all pairs of intercostal, subcostal and lumbar arteries, using 4D-flow MRI (4DMR) to inform patient-specific boundary conditions. Compared to an equivalent case without minor branches, their inclusion improved agreement with 4DMR velocities, reduced time-averaged WSS (TAWSS) and transmural pressure and elevated oscillatory shear in regions where FL dilatation and calcification were observed in vivo. Minor branch inclusion resulted in differences of 60-75% in these metrics of potential clinical relevance, indicating a need to account for minor branch flow loss if simulation accuracy is sought.

A computational study of the effects of size, location, and number of tears on haemodynamics in surgically repaired type A aortic dissection

Objective

This study aimed to comprehensively examine the roles of size, location, and number of tears in the progression of surgically repaired type A aortic dissection (TAAD) by assessing haemodynamic changes through patient-specific computational fluid dynamic (CFD) simulations.

Methods

Two patient-specific TAAD geometries with replaced ascending aorta were reconstructed based upon computed 15 tomography (CT) scans, after which 10 hypothetical models (5 per patient) with different tear configurations were artificially created. CFD simulations were performed on all the models under physiologically realistic boundary conditions.

Results

Our simulation results showed that increasing either the size or number of the re-entry tears reduced the luminal pressure difference (LPD) and maximum time-averaged wall shear stress (TAWSS), as well as areas exposed to abnormally high or low TAWSS values. Models with a large re-entry tear outperformed the others by reducing the maximum LPD by 1.88 mmHg and 7.39 mmHg, for patients 1 and 2, respectively. Moreover, proximally located re-entry tears in the descending aorta were more effective at reducing LPD than distal re-entry tears.

Discussion

These computational results indicate that the presence of a relatively large re-entry tear in the proximal descending aorta might help stabilize post-surgery aortic growth. This finding has important implications for the management and risk stratification of surgically repaired TAAD patients. Nevertheless, further validation in a large patient cohort is needed.

Analytical solution to Windkessel models using piecewise linear aortic flow waveform

Objective.Deriving time-domain analytical solutions to two- three- and four-element Windkessel models, which are commonly used in teaching and research to analyse the behaviour of the arterial pressure-flow relationship.Approach.The governing (first-order, non-homogeneous, linear) differential equations are solved analytically, based on a piecewise linear function that can accurately approximate typical aortic flow waveforms.Main results.Closed-form expressions for arterial pressure are obtained both in transient conditions and in steady-state periodic regime.Significance.In most cases Windkessel models are studied in the frequency domain and when studied in the time domain, numerical methods are used. The main advantage of the proposed expressions is that they are an explicit, exact, and easily understood mathematical description of the model behaviour. Moreover, they avoid the use of Fourier analysis or numerical solvers to integrate the differential equations.

Aortic haemodynamics and wall stress analysis following arch aneurysm repair using a single-branched endograft

Introduction

Thoracic endovascular aortic repair (TEVAR) of the arch is challenging given its complex geometry and the involvement of supra-aortic arteries. Different branched endografts have been designed for use in this region, but their haemodynamic performance and the risk for post-intervention complications are not yet clear. This study aims to examine aortic haemodynamics and biomechanical conditions following TVAR treatment of an aortic arch aneurysm with a two-component single-branched endograft.

Methods

Computational fluid dynamics and finite element analysis were applied to a patient-specific case at different stages: pre-intervention, post-intervention and follow-up. Physiologically accurate boundary conditions were used based on available clinical information.

Results

Computational results obtained from the post-intervention model confirmed technical success of the procedure in restoring normal flow to the arch. Simulations of the follow-up model, where boundary conditions were modified to reflect change in supra-aortic vessel perfusion observed on the follow-up scan, predicted normal flow patterns but high levels of wall stress (up to 1.3M MPa) and increased displacement forces in regions at risk of compromising device stability. This might have contributed to the suspected endoleaks or device migration identified at the final follow up.

Discussion

Our study demonstrated that detailed haemodynamic and biomechanical analysis can help identify possible causes for post-TEVAR complications in a patient-specific setting. Further refinement and validation of the computational workflow will allow personalised assessment to aid in surgical planning and clinical decision making.

Advanced risk prediction for aortic dissection patients using imaging-based computational flow analysis

Patients with either a repaired or medically managed aortic dissection have varying degrees of risk of developing late complications. High-risk patients would benefit from earlier intervention to improve their long-term survival. Currently serial imaging is used for risk stratification, which is not always reliable. On the other hand, understanding aortic haemodynamics within a dissection is essential to fully evaluate the disease and predict how it may progress. In recent decades, computational fluid dynamics (CFD) has been extensively applied to simulate complex haemodynamics within aortic diseases, and more recently, four-dimensional (4D)-flow magnetic resonance imaging (MRI) techniques have been developed for in vivo haemodynamic measurement. This paper presents a comprehensive review on the application of image-based CFD simulations and 4D-flow MRI analysis for risk prediction in aortic dissection. The key steps involved in patient-specific CFD analyses are demonstrated. Finally, we propose a workflow incorporating computational modelling for personalised assessment to aid in risk stratification and treatment decision-making.

A Computational Study of Dynamic Obstruction in Type B Aortic Dissection

A serious complication in aortic dissection is dynamic obstruction of the true lumen (TL). Dynamic obstruction results in malperfusion, a blockage of blood flow to a vital organ. Clinical data reveal that increases in central blood pressure promote dynamic obstruction. However, the mechanisms by which high pressures result in TL collapse are underexplored and poorly understood. Here, we developed a computational model to investigate biomechanical and hemodynamical factors involved in Dynamic obstruction. We hypothesize that relatively small pressure gradient between TL and false lumen (FL) are sufficient to displace the flap and induce obstruction. An idealized fluid-structure interaction model of type B aortic dissection was created. Simulations were performed under mean cardiac output while inducing dynamic changes in blood pressure by altering FL outflow resistance. As FL resistance increased, central aortic pressure increased from 95.7 to 115.3 mmHg. Concurrent with blood pressure increase, flap motion was observed, resulting in TL collapse, consistent with clinical findings. The maximum pressure gradient between TL and FL over the course of the dynamic obstruction was 4.5 mmHg, consistent with our hypothesis. Furthermore, the final stage of dynamic obstruction was very sudden in nature, occurring over a short time (<1 s) in our simulation, consistent with the clinical understanding of this dramatic event. Simulations also revealed sudden drops in flow and pressure in the TL in response to the flap motion, consistent with first stages of malperfusion. To our knowledge, this study represents the first computational analysis of potential mechanisms driving dynamic obstruction in aortic dissection.

Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease

Physics-based computational models of the cardiovascular system are increasingly used to simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and diseased states. While predictive models using computational fluid dynamics (CFD) originated primarily for use in surgical planning, their application now extends well beyond this purpose. In this review, we describe an increasingly wide range of modeling applications aimed at uncovering fundamental mechanisms of disease progression and development, performing model-guided design, and generating testable hypotheses to drive targeted experiments. Increasingly, models are incorporating multiple physical processes spanning a wide range of time and length scales in the heart and vasculature. With these expanded capabilities, clinical adoption of patient-specific modeling in congenital and acquired cardiovascular disease is also increasing, impacting clinical care and treatment decisions in complex congenital heart disease, coronary artery disease, vascular surgery, pulmonary artery disease, and medical device design. In support of these efforts, we discuss recent advances in modeling methodology, which are most impactful when driven by clinical needs. We describe pivotal recent developments in image processing, fluid-structure interaction, modeling under uncertainty, and reduced order modeling to enable simulations in clinically relevant timeframes. In all these areas, we argue that traditional CFD alone is insufficient to tackle increasingly complex clinical and biological problems across scales and systems. Rather, CFD should be coupled with appropriate multiscale biological, physical, and physiological models needed to produce comprehensive, impactful models of mechanobiological systems and complex clinical scenarios. With this perspective, we finally outline open problems and future challenges in the field.

Post-stroke rehabilitation optimization & recommendation framework using tele-robotic ecosystem: Industry 4.0 readiness approach

Technological development in biomedical procedures has given an upper understanding of the ease of evaluating and handling critical scenarios and diseases. A sustainable model design is required for the post-medical procedures to maintain the consistency of medical treatment. In this article, a telerobotic-based stroke rehabilitation optimization and recommendation technique cum framework is proposed and evaluated. Selecting optimal features for training deep neural networks can help in optimizing the training time and also improve the performance of the model. To achieve this, we have used Whale Optimization Algorithm (WOA) due to its higher convergence accuracy, better stability, stronger global search ability, and faster convergence speed to streamline the dependency matrix of each attribute associated with post-stroke rehabilitation. Deep Neural Networking assures the selection of datasets from training and testing validation. The proposed framework is developed on providing decision support with a recommendation of activities and task flow, these recommendations are independent and have higher feasibility with the scenario of evaluation. The proposed model achieved a precision of 99.6%, recall of 99.5 %, F1-score of 99.7%, and accuracy of 99.9%, which outperform the other considered optimization algorithms such as antlion and gravitational search algorithms. The proposed technique has provided an efficient recommendation model compared to the trivial SVM-based models and techniques.

A computational study of aortic reconstruction in single ventricle patients

Patients with hypoplastic left heart syndrome (HLHS) are born with an underdeveloped left heart. They typically receive a sequence of surgeries that result in a single ventricle physiology called the Fontan circulation. While these patients usually survive into early adulthood, they are at risk for medical complications, partially due to their lower than normal cardiac output, which leads to insufficient cerebral and gut perfusion. While clinical imaging data can provide detailed insight into cardiovascular function within the imaged region, it is difficult to use these data for assessing deficiencies in the rest of the body and for deriving blood pressure dynamics. Data from patients used in this paper include three-dimensional, magnetic resonance angiograms (MRA), time-resolved phase contrast cardiac magnetic resonance images (4D-MRI) and sphygmomanometer blood pressure measurements. The 4D-MRI images provide detailed insight into velocity and flow in vessels within the imaged region, but they cannot predict flow in the rest of the body, nor do they provide values of blood pressure. To remedy these limitations, this study combines the MRA, 4D-MRI, and pressure data with 1D fluid dynamics models to predict hemodynamics in the major systemic arteries, including the cerebral and gut vasculature. A specific focus is placed on studying the impact of aortic reconstruction occurring during the first surgery that results in abnormal vessel morphology. To study these effects, we compare simulations for an HLHS patient with simulations for a matched control patient that has double outlet right ventricle (DORV) physiology with a native aorta. Our results show that the HLHS patient has hypertensive pressures in the brain as well as reduced flow to the gut. Wave intensity analysis suggests that the HLHS patient has irregular circulatory function during light upright exercise conditions and that predicted wall shear stresses are lower than normal, suggesting the HLHS patient may have hypertension.

Fluid-structure interaction simulation of visceral perfusion and impact of different cannulation methods on aortic dissection

Hemodynamics in aortic dissection (AD) is closely associated with the risk of aortic aneurysm, rupture, and malperfusion. Altered blood flow in patients with AD can lead to severe complications such as visceral malperfusion. In this study, we aimed to investigate the effect of cannulation flow on hemodynamics in AD using a fluid-structure interaction simulation. We developed a specific-idealized AD model that included an intimal tear in the descending thoracic aorta, a re-entry tear in the left iliac artery, and nine branches. Two different cannulation methods were tested: (1) axillary cannulation (AC) only through the brachiocephalic trunk and (2) combined axillary and femoral cannulation (AFC) through the brachiocephalic trunk and the right common iliac artery. AC was found to result in the development of a pressure difference between the true lumen and false lumen, owing to the difference in the flow rate through each lumen. This pressure difference collapsed the true lumen, disturbing blood flow to the celiac and superior mesenteric arteries. However, in AFC, the pressure levels between the two lumens were similar, and no collapse occurred. Moreover, the visceral flow was higher than that in AC. Lastly, the stiffness of the intimal flap affected the true lumen's collapse.

High-fidelity fluid structure interaction simulations of turbulent-like aneurysm flows reveals high-frequency narrowband wall vibrations: A stimulus of mechanobiological relevance?

Recent high-fidelity/resolution computational fluid dynamics simulations of intracranial aneurysm hemodynamics have revealed turbulent-like flows. We hypothesized that the associated high-frequency pressure fluctuations could promote aneurysm wall vibrations. We performed fully coupled high-fidelity transient fluid structure interaction simulations between the blood flow and compliant aneurysm sac wall taking 5,000 time steps per second using a 3D patient-specific model previously shown to harbour turbulent-like flow. Our results show that the flow velocity contained fluctuations with a smooth and continuously decaying energy up to ∼160Hz, and fluctuating pressures with characteristic frequency peaks at approximately 30, 130 and 210Hz. There was a strong two-way coupling between the pressure and the wall deformation, for which the frequency spectrum showed similar characteristics, but with a narrow band peak at ∼120Hz with large regional differences in amplitude up to 80μm. The physics of the flow is broadly consistent with clinical reports of turbulent-like flows, while the physics of the wall is consistent with reports of spectral peaks in aneurysm patients. As many aneurysms are known to harbour turbulent-like flows, wall vibrations could be a widespread phenomenon. Finally, since aneurysms are vascular pathologies by definition and many/most aneurysms do not have endothelial cells but still display a focal remodeling, we hypothesize that vibrations and stresses within the wall itself might play a role in the mechanobiological processes of vessel wall pathology.

Cerebral hemodynamics during atrial fibrillation: Computational fluid dynamics analysis of lenticulostriate arteries using 7 T high-resolution magnetic resonance imaging

Atrial fibrillation (AF) is the most common cardiac arrhythmia, inducing irregular and faster heart beating. Aside from disabling symptoms-such as palpitations, chest discomfort, and reduced exercise capacity-there is growing evidence that AF increases the risk of dementia and cognitive decline, even in the absence of clinical strokes. Among the possible mechanisms, the alteration of deep cerebral hemodynamics during AF is one of the most fascinating and least investigated hypotheses. Lenticulostriate arteries (LSAs)-small perforating arteries perpendicularly departing from the anterior and middle cerebral arteries and supplying blood flow to basal ganglia-are especially involved in silent strokes and cerebral small vessel diseases, which are considered among the main vascular drivers of dementia. We propose for the first time a computational fluid dynamics analysis to investigate the AF effects on the LSAs hemodynamics by using 7 T high-resolution magnetic resonance imaging (MRI). We explored different heart rates (HRs)-from 50 to 130 bpm-in sinus rhythm and AF, exploiting MRI data from a healthy young male and internal carotid artery data from validated 0D cardiovascular-cerebral modeling as inflow condition. Our results reveal that AF induces a marked reduction of wall shear stress and flow velocity fields. This study suggests that AF at higher HR leads to a more hazardous hemodynamic scenario by increasing the atheromatosis and thrombogenesis risks in the LSAs region.

Feasibility of Vascular Parameter Estimation for Assessing Hypertensive Pregnancy Disorders

Hypertensive pregnancy disorders (HPDs), such as pre-eclampsia, are leading sources of both maternal and fetal morbidity in pregnancy. Noninvasive imaging, such as ultrasound (US) and magnetic resonance imaging (MRI), is an important tool for predicting and monitoring these high risk pregnancies. While imaging can measure hemodynamic parameters, such as uterine artery pulsatility and resistivity indices (PI and RI), the interpretation of such metrics for disease assessment relies on ad hoc standards, which provide limited insight to the physical mechanisms underlying the emergence of hypertensive pregnancy disorders. To provide meaningful interpretation of measured hemodynamic data in patients, advances in computational fluid dynamics can be brought to bear. In this work, we develop a patient-specific computational framework that combines Bayesian inference with a reduced-order fluid dynamics model to infer parameters, such as vascular resistance, compliance, and vessel cross-sectional area, known to be related to the development of hypertension. The proposed framework enables the prediction of hemodynamic quantities of interest, such as pressure and velocity, directly from sparse and noisy MRI measurements. We illustrate the effectiveness of this approach in two systemic arterial network geometries: an aorta with branching carotid artery and a maternal pelvic arterial network. For both cases, the model can reconstruct the provided measurements and infer parameters of interest. In the case of the maternal pelvic arteries, the model can make a distinction between the pregnancies destined to develop hypertension and those that remain normotensive, expressed through the value range of the predicted absolute pressure.

MRI in CFD for chronic type B aortic dissection: Ready for prime time?

OBJECTIVES

Better tools are needed for risk assessment of Type B aortic dissection (TBAD) to determine optimal treatment for patients with uncomplicated disease. Magnetic resonance imaging (MRI) has the potential to inform computational fluid dynamics (CFD) simulations for TBAD by providing individualised quantification of haemodynamic parameters, for assessment of complication risks. This systematic review aims to present an overview of MRI applications for CFD studies of TBAD.

METHODS

Following PRISMA guidelines, a search in Medline, Embase, and the Scopus Library identified 136 potentially relevant articles. Studies were included if they used MRI to inform CFD simulation in TBAD.

RESULTS

There were 20 articles meeting the inclusion criteria. 19 studies used phase contrast MRI (PC-MRI) to provide data for CFD flow boundary conditions. In 12 studies, CFD haemodynamic parameter results were validated against PC-MRI. In eight studies, geometric models were developed from MR angiography. In three studies, aortic wall or intimal flap motion data were derived from PC/cine MRI.

CONCLUSIONS

MRI provides complementary patient-specific information in CFD haemodynamic studies for TBAD that can be used for personalised care. MRI provides structural, dynamic and flow data to inform CFD for pre-treatment planning, potentially advancing its integration into clinical decision-making. The use of MRI to inform CFD in TBAD surgical planning is promising, however further validation and larger cohort studies are required.

Colocalization of Coronary Plaque with Wall Shear Stress in Myocardial Bridge Patients

PURPOSE

Patients with myocardial bridges (MBs) have a higher prevalence of atherosclerosis. Wall shear stress (WSS) has previously been correlated with plaque in coronary artery disease patients, but such correlations have not been investigated in symptomatic MB patients. The aim of this paper was to use a multi-scale computational fluid dynamics (CFD) framework to simulate hemodynamics in MB patient, and investigate the co-localization of WSS and plaque.

METHODS

We identified N = 10 patients from a previously reported cohort of 50 symptomatic MB patients, all of whom had plaque in the proximal vessel. Dynamic 3D models were reconstructed from coronary computed tomography angiography (CCTA), intravascular ultrasound (IVUS) and catheter angiograms. CFD simulations were performed to compute WSS proximal to, within and distal to the MB. Plaque was quantified from IVUS images in 2 mm segments and registered to CFD model. Plaque area was compared to absolute and patient-normalized WSS.

RESULTS

WSS was lower in the proximal segment compared to the bridge segment (6.1 ± 2.9 vs. 16.0 ± 7.1 dynes/cm², p value < 0.01). Plaque area and plaque burden measured from IVUS peaked at 1-3 cm proximal to the MB entrance, coinciding with the first diagonal branch. Normalized WSS showed a statistically significant moderate correlation with plaque area (r = 0.41, p < 0.01).

CONCLUSION

WSS may be obtained non-invasively in MB patients and provides a surrogate marker of plaque area. Using CFD, it may be possible to non-invasively assess the extent of plaque area, and identify patients who could benefit from frequent monitoring or medical management.