Computational Hemodynamic Modeling of Arterial Aneurysms: A Mini-Review

In Vivo Deformation of the Human Basilar Artery

An estimated 6.8 million people in the United States have an unruptured intracranial aneurysms, with approximately 30,000 people suffering from intracranial aneurysms rupture each year. Despite the development of population-based scores to evaluate the risk of rupture, retrospective analyses have suggested the limited usage of these scores in guiding clinical decision-making. With recent advancements in imaging technologies, artery wall motion has emerged as a promising biomarker for the general study of neurovascular mechanics and in assessing the risk of intracranial aneurysms. However, measuring arterial wall deformations in vivo itself poses several challenges, including how to image local wall motion and deriving the anisotropic wall strains over the cardiac cycle. To overcome these difficulties, we first developed a novel in vivo MRI-based imaging method to acquire cardiac gated images of the human basilar artery (BA) over the cardiac cycle. Next, complete BA endoluminal surfaces from each frame were segmented, producing high-resolution point clouds of the endoluminal surfaces. From these point clouds we developed a novel B-spline-based surface representation, then exploited the local support nature of B-splines to determine the local endoluminal surface strains. Results indicated distinct regional and temporal variations in BA wall deformation, highlighting the heterogeneous nature BA function. These included large circumferential strains (up to ∼ 20 % ), and small longitudinal strains, which were often contractile and out of phase with the circumferential strains patterns. Of particular interest was the temporal phase lag in the maximum circumferential perimeter length, which indicated that the BA deforms asynchronously over the cardiac cycle. In summary, the proposed method enabled local deformation analysis, allowing for the successful reproduction of local features of the BA, such as regional principal stretches, areal changes, and pulsatile motion. Integrating the proposed method into existing population-based scores has the potential to improve our understanding of mechanical properties of human BA and enhance clinical decision-making.

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.

Comparative study between 1-way and 2-way coupled fluid-structure interaction in numerical simulation of aortic arch aneurysms

Hemodynamic forces are related to pathological variations of the cardiovascular system, and numerical simulations for fluid-structure interaction have been systematically used to analyze the behavior of blood flow and the arterial wall in aortic aneurysms. This paper proposes a comparative analysis of 1-way and 2-way coupled fluid-structure interaction for aortic arch aneurysm. The coupling models of fluid-structure interaction were conducted using 3D geometry of the thoracic aorta from computed tomography. Hyperelastic anisotropic properties were estimated for the Holzapfel arterial wall model. The rheological behavior of the blood was modeled by the Carreau-Yasuda model. The results showed that the 1-way approach tends to underestimate von Mises stress, displacement, and strain over the entire cardiac cycle, compared to the 2-way approach. In contrast, the behavior of the variables of flow field, velocity, wall shear stress, and Reynolds number when coupled by the 1-way model was overestimated at the systolic moment and tends to be equal at the diastolic moment. The quantitative differences found, especially during the systole, suggest the use of 2-way coupling in numerical simulations of aortic arch aneurysms due to the hyperelastic nature of the arterial wall, which leads to a strong iteration between the fluid and the arterial wall.

Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows

Quantifying the flow of cerebrospinal fluid (CSF) is crucial for understanding brain waste clearance and nutrient delivery, as well as edema in pathological conditions such as stroke. However, existing in vivo techniques are limited to sparse velocity measurements in pial perivascular spaces (PVSs) or low-resolution measurements from brain-wide imaging. Additionally, volume flow rate, pressure, and shear stress variation in PVSs are essentially impossible to measure in vivo. Here, we show that artificial intelligence velocimetry (AIV) can integrate sparse velocity measurements with physics-informed neural networks to quantify CSF flow in PVSs. With AIV, we infer three-dimensional (3D), high-resolution velocity, pressure, and shear stress. Validation comes from training with 70% of PTV measurements and demonstrating close agreement with the remaining 30%. A sensitivity analysis on the AIV inputs shows that the uncertainty in AIV inferred quantities due to uncertainties in the PVS boundary locations inherent to in vivo imaging is less than 30%, and the uncertainty from the neural net initialization is less than 1%. In PVSs of N = 4 wild-type mice we find mean flow speed 16.33 ± 11.09 µm/s, volume flow rate 2.22 ± 1.983 × 103 µm3/s, axial pressure gradient ( - 2.75 ± 2.01)×10-4 Pa/µm (-2.07 ± 1.51 mmHg/m), and wall shear stress (3.00 ± 1.45)×10-3 Pa (all mean ± SE). Pressure gradients, flow rates, and resistances agree with prior predictions. AIV infers in vivo PVS flows in remarkable detail, which will improve fluid dynamic models and potentially clarify how CSF flow changes with aging, Alzheimer's disease, and small vessel disease.

How does hemodynamics affect rupture tissue mechanics in abdominal aortic aneurysm: Focus on wall shear stress derived parameters, time-averaged wall shear stress, oscillatory shear index, endothelial cell activation potential, and relative residence time

An abdominal aortic aneurysm (AAA) is a critical health condition with a risk of rupture, where the diameter of the aorta enlarges more than 50% of its normal diameter. The incidence rate of AAA has increased worldwide. Currently, about three out of every 100,000 people have aortic diseases. The diameter and geometry of AAAs influence the hemodynamic forces exerted on the arterial wall. Therefore, a reliable assessment of hemodynamics is crucial for predicting the rupture risk. Wall shear stress (WSS) is an important metric to define the level of the frictional force on the AAA wall. Excessive levels of WSS deteriorate the remodeling mechanism of the arteries and lead to abnormal conditions. At this point, WSS-related hemodynamic parameters, such as time-averaged WSS (TAWSS), oscillatory shear index (OSI), endothelial cell activation potential (ECAP), and relative residence time (RRT) provide important information to evaluate the shear environment on the AAA wall in detail. Calculation of these parameters is not straightforward and requires a physical understanding of what they represent. In addition, computational fluid dynamics (CFD) solvers do not readily calculate these parameters when hemodynamics is simulated. This review aims to explain the WSS-derived parameters focusing on how these represent different characteristics of disturbed hemodynamics. A representative case is presented for spatial and temporal formulation that would be useful for interested researchers for practical calculations. Finally, recent hemodynamics investigations relating WSS-related parameters with AAA rupture risk assessment are presented. This review will be useful to understand the physical representation of WSS-related parameters in cardiovascular flows and how they can be calculated practically for AAA investigations.

Impact of spatial and temporal stability of flow vortices on vascular endothelial cells

PURPOSE

Intracranial aneurysms (IAs) are pathological dilations of cerebrovascular vessels due to degeneration of the mechanical strength of the arterial wall, precluded by altered cellular functionality. The presence of swirling hemodynamic flow (vortices) is known to alter vascular endothelial cell (EC) morphology and protein expression indicative of IAs. Unfortunately, less is known if vortices with varied spatial and temporal stability lead to differing levels of EC change. The aim of this work is to investigate vortices of varying spatial and temporal stability impact on ECs.

METHODS

Vortex and EC interplay was investigated by a novel combination of parallel plate flow chamber (PPFC) design and computational analysis. ECs were exposed to laminar (7.5 dynes/[Formula: see text] wall shear stress) or low (<1 dynes/[Formula: see text]) stress vortical flow using PPFCs. Immunofluorescent imaging analyzed EC morphology, while ELISA tests quantified VE-cadherin (cell-cell adhesion), VCAM-1 (macrophage-EC adhesion), and cleaved caspase-3 (apoptotic signal) expression. PPFC flow was simulated, and vortex stability was calculated via the temporally averaged degree of (volume) overlap (TA-DVO) of vortices within a given area.

RESULTS

EC morphological changes were independent of vortex stability. Increased stability promoted VE-cadherin degradation (correlation coefficient r = [Formula: see text]0.84) and 5-fold increased cleaved caspase-3 post 24 h in stable (TA-DVO 0.736 ± 0.05) vs unstable (TA-DVO 0.606 [Formula: see text]0.2) vortices. ECs in stable vortices displayed a 4.5-fold VCAM-1 increase than unstable counterparts after 12 h.

CONCLUSION

This work demonstrates highly stable disturbed flow imparts increased inflammatory signaling, degraded cell-cell adhesion, and increased cellular apoptosis than unstable vortices. Such knowledge offers novel insight toward understanding IA development and rupture.

Animal models and animal-free innovations for cardiovascular research: current status and routes to be explored. Consensus document of the ESC Working Group on Myocardial Function and the ESC Working Group on Cellular Biology of the Heart

Cardiovascular diseases represent a major cause of morbidity and mortality, necessitating research to improve diagnostics, and to discover and test novel preventive and curative therapies, all of which warrant experimental models that recapitulate human disease. The translation of basic science results to clinical practice is a challenging task, in particular for complex conditions such as cardiovascular diseases, which often result from multiple risk factors and comorbidities. This difficulty might lead some individuals to question the value of animal research, citing the translational 'valley of death', which largely reflects the fact that studies in rodents are difficult to translate to humans. This is also influenced by the fact that new, human-derived in vitro models can recapitulate aspects of disease processes. However, it would be a mistake to think that animal models do not represent a vital step in the translational pathway as they do provide important pathophysiological insights into disease mechanisms particularly on an organ and systemic level. While stem cell-derived human models have the potential to become key in testing toxicity and effectiveness of new drugs, we need to be realistic, and carefully validate all new human-like disease models. In this position paper, we highlight recent advances in trying to reduce the number of animals for cardiovascular research ranging from stem cell-derived models to in situ modelling of heart properties, bioinformatic models based on large datasets, and state-of-the-art animal models, which show clinically relevant characteristics observed in patients with a cardiovascular disease. We aim to provide a guide to help researchers in their experimental design to translate bench findings to clinical routine taking the replacement, reduction, and refinement (3R) as a guiding concept.

Differential hemodynamics between arteriovenous fistulas with or without intervention before successful use

A significant number of arteriovenous fistulas (AVFs) fail to maturate for dialysis. Although interventions promote maturation, functional primary patency loss is higher for AVFs with interventions (assisted maturation) than AVFs without interventions (un-assisted maturation). Although blood flow-associated hemodynamics have long been proposed to affect AVF remodeling, the optimal hemodynamic parameters for un-assisted maturation are unclear. Additionally, AVF maturation progress is generally not investigated until 6 weeks after AVF creation, and the examination is focused on the AVF's venous limb. In this exploratory study, patients (n = 6) underwent magnetic resonance imaging (MRI) at 1 day, 6 weeks, and 6 months after AVF creation surgery. Before successful use for hemodialysis, three AVFs required intervention and three did not. MRI of the AVFs were used to calculate lumen cross-sectional area (CSA) and perform computational fluid dynamics (CFD) to analyze hemodynamics, including velocity, wall shear stress (WSS), and vorticity. For the venous limb, the no-intervention group and intervention group had similar pre-surgery vein diameter and 1-day post-surgery venous CSA. However, the no-intervention group had statistically larger 1-day venous velocity (0.97 ± 0.67 m/s; mean ± SD), WSS (333 ± 336 dyne/cm2) and vorticity (1709 ± 1290 1/s) than the intervention group (velocity = 0.23 ± 0.10 m/s; WSS = 49 ± 40 dyne/cm2; vorticity = 493.1 ± 227 1/s) (P < 0.05). At 6 months, the no-intervention group had statistically larger venous CSA (43.5 ± 27.4 mm2) than the intervention group (15.1 ± 6.2 mm2) (P < 0.05). Regarding the arterial limb, no-intervention AVF arteries also had statistically larger 1-day velocity (1.17 ± 1.0 m/s), WSS (340 ± 423 dyne/cm2), vorticity (1787 ± 1694 1/s), and 6-month CSA (22.6 ± 22.7 mm2) than the intervention group (velocity = 0.64 ± 0.36 m/s; WSS = 104 ± 116 dyne/cm2, P < 0.05; vorticity = 867 ± 4551/s; CSA = 10.7 ± 6.0 mm2, P < 0.05). Larger venous velocity, WSS, and vorticity immediately after AVF creation surgery may be important for later lumen enlargement and AVF maturation, with the potential to be used as a tool to help diagnose poor AVF maturation earlier. However, future studies using a larger cohort are needed to validate this finding and determine cut off values, if any.

Natural history and clinical significance of aortic focal intimal flaps

Objective

Focal intimal flaps (FIF) are a variety of defects of the aorta that result in a short, flap-like projection into the lumen, and are often encountered in asymptomatic patients undergoing computed tomography angiography (CTA) surveillance for aortic aneurysm, but the natural history and clinical significance of such lesions has not yet been studied.

Methods

We retrospectively identified patients with an asymptomatic FIF and available imaging follow-up (>1 year). FIF was defined as flap-like intimal irregularity < 4 cm in length involving the thoracic aorta (TA), abdominal aorta (AA) or common iliac arteries (CIA). FIF characteristics included length and circumferential extent as well as the presence and size (width and depth) of associated penetrating aortic ulcers (PAUs). Patient characteristics, adverse events and history of surgical repair was determined by chart review. FIFs and associated PAUs were assessed for progression by comparing baseline and follow-up CTA studies.

Results

A total of 84 FIFs were identified in 77 patients. Average age was 69.2 ± 10.1 years, and 81% were male (81%). Common co-morbidities included: hypertension (78%), hyperlipidemia (68%), smoking (60%), coronary artery disease (41%), aortic aneurysm (34%), type II diabetes mellitus (27%) and prior cardiovascular surgery (25%). FIFs were most commonly located in the abdominal aorta (n = 50, 60%). Nearly all FIFs were associated with local atherosclerotic plaque (93%). Mean follow-up interval was 3.5 ± 2.6 years (259 cumulative follow-up years). Change in FIF length and local aortic diameter over follow-up were 0.7 ± 2.3 mm and 0.8 ± 1.1 mm, respectively. Nearly half (47%) of FIFs were associated with penetrating aortic ulcers (PAU) with baseline depth of 7.3 mm (IQR: 6.1–10.2) and change in depth of 0.5 ± 1.4 mm. Only 12% of FIFs and 0% of associated PAUs demonstrated growth (≥3 mm) at follow-up. No acute pathology developed in the location of FIFs and no aortic interventions were performed specifically to treat FIFs.

Conclusion

Focal intimal flaps identified in asymptomatic patients with aortic disease were co-localized with atherosclerotic plaque and PAUs, and demonstrated indolent behavior, not leading to significant growth or acute aortic events, supporting a conservative management approach.

A fluid-structure interaction model accounting arterial vessels as a key part of the blood-flow engine for the analysis of cardiovascular diseases

According to the classical Windkessel model, the heart is the only power source for blood flow, while the arterial system is assumed to be an elastic chamber that acts as a channel and buffer for blood circulation. In this paper we show that in addition to the power provided by the heart for blood circulation, strain energy stored in deformed arterial vessels in vivo can be transformed into mechanical work to propel blood flow. A quantitative relationship between the strain energy increment and functional (systolic, diastolic, mean and pulse blood pressure) and structural (stiffness, diameter and wall thickness) parameters of the aorta is described. In addition, details of blood flow across the aorta remain unclear due to changes in functional and other physiological parameters. Based on the arterial strain energy and fluid-structure interaction theory, the relationship between physiological parameters and blood supply to organs was studied, and a corresponding mathematical model was developed. The findings provided a new understanding about blood-flow circulation, that is, cardiac output allows blood to enter the aorta at an initial rate, and then strain energy stored in the elastic arteries pushes blood toward distal organs and tissues. Organ blood supply is a key factor in cardio-cerebrovascular diseases (CCVD), which are caused by changes in blood supply in combination with multiple physiological parameters. Also, some physiological parameters are affected by changes in blood supply, and vice versa. The model can explain the pathophysiological mechanisms of chronic diseases such as CCVD and hypertension among others, and the results are in good agreement with epidemiological studies of CCVD.

Medical Image-Based Computational Fluid Dynamics and Fluid-Structure Interaction Analysis in Vascular Diseases

Hemodynamic factors, induced by pulsatile blood flow, play a crucial role in vascular health and diseases, such as the initiation and progression of atherosclerosis. Computational fluid dynamics, finite element analysis, and fluid-structure interaction simulations have been widely used to quantify detailed hemodynamic forces based on vascular images commonly obtained from computed tomography angiography, magnetic resonance imaging, ultrasound, and optical coherence tomography. In this review, we focus on methods for obtaining accurate hemodynamic factors that regulate the structure and function of vascular endothelial and smooth muscle cells. We describe the multiple steps and recent advances in a typical patient-specific simulation pipeline, including medical imaging, image processing, spatial discretization to generate computational mesh, setting up boundary conditions and solver parameters, visualization and extraction of hemodynamic factors, and statistical analysis. These steps have not been standardized and thus have unavoidable uncertainties that should be thoroughly evaluated. We also discuss the recent development of combining patient-specific models with machine-learning methods to obtain hemodynamic factors faster and cheaper than conventional methods. These critical advances widen the use of biomechanical simulation tools in the research and potential personalized care of vascular diseases.

On the Potential Self-Amplification of Aneurysms Due to Tissue Degradation and Blood Flow Revealed From FSI Simulations

Tissue degradation plays a crucial role in the formation and rupture of aneurysms. Using numerical computer simulations, we study the combined effects of blood flow and tissue degradation on intra-aneurysm hemodynamics. Our computational analysis reveals that the degradation-induced changes of the time-averaged wall shear stress (TAWSS) and oscillatory shear index (OSI) within the aneurysm dome are inversely correlated. Importantly, their correlation is enhanced in the process of tissue degradation. Regions with a low TAWSS and a high OSI experience still lower TAWSS and higher OSI during degradation. Furthermore, we observed that degradation leads to an increase of the endothelial cell activation potential index, in particular, at places experiencing low wall shear stress. These findings are robust and occur for different geometries, degradation intensities, heart rates and pressures. We interpret these findings in the context of recent literature and argue that the degradation-induced hemodynamic changes may lead to a self-amplification of the flow-induced progressive damage of the aneurysmal wall.

Underlying mechanism of hemodynamics and intracranial aneurysm

In modern society, subarachnoid hemorrhage, mostly caused by intracranial aneurysm rupture, is accompanied by high disability and mortality rate, which has become a major threat to human health. Till now, the etiology of intracranial aneurysm has not been entirely clarified. In recent years, more and more studies focus on the relationship between hemodynamics and intracranial aneurysm. Under the physiological condition, the mechanical force produced by the stable blood flow in the blood vessels keeps balance with the structure of the blood vessels. When the blood vessels are stimulated by the continuous abnormal blood flow, the functional structure of the blood vessels changes, which becomes the pathophysiological basis of the inflammation and atherosclerosis of the blood vessels and further promotes the occurrence and development of the intracranial aneurysm. This review will focus on the relationship between hemodynamics and intracranial aneurysms, will discuss the mechanism of occurrence and development of intracranial aneurysms, and will provide a new perspective for the research and treatment of intracranial aneurysms.