CFD for Evaluation and Treatment Planning of Aneurysms: Review of Proposed Clinical Uses and Their Challenges

Role of physics-informed constraints in real-time estimation of 3D vascular fluid dynamics using multi-case neural network

Numerical simulations of fluid dynamics in tube-like structures are important to biomedical research to model flow in blood vessels and airways. It is further useful to some clinical applications, such as predicting arterial fractional flow reserves, and assessing vascular flow wall shear stresses to predict atherosclerosis disease progression. Traditionally, they are conducted via computational fluid dynamics (CFD) simulations, which, despite optimization, still take substantial time, limiting clinical adoption. To improve efficiency, we investigate the use of the multi-case Neural Network (NN) to enable real-time predictions of fluid dynamics (both steady and pulsatile flows) in a 3D curved tube (with a narrowing in the middle mimicking a stenosis) of any shape within a geometric range, using only geometric parameters and boundary conditions. We compare the unsupervised approach guided by physics governing equations (physics informed neural network or PINN) to the supervised approach of using mass CFD simulations to train the network (supervised network or SN). We find that multi-case PINN can generate accurate velocity, pressure and wall shear stress (WSS) results under steady flow (spatially maximum error < 2-5 %), but this requires a specific enhancement strategies: (1) estimating the curvilinear coordinate parameters via a secondary NN to use as inputs into PINN, (2) imposing no-slip wall boundary condition as a hard constraint, and (3) advanced strategy to better spatially propagate effects of boundary conditions. However, we cannot achieve reasonable accuracy for pulsatile flow with PINN. Conversely, SN provides very accurate velocity, pressure, and WSS predictions under both steady and pulsatile flow scenarios (spatially and/or temporally maximum error averaged over all geometries <1 %), and is much less computationally expensive to train. To achieve this, strategies (1) and (2) above and a spectral encoding strategy for pulsatile flow are necessary. Thus, interestingly, the use of physics constraints is not effective in our application.

Four-Dimensional Visualization of Topological Fixed Points in Pulsatile Cardiovascular Flows

Topological features of time-dependent, three-dimensional (3D) vector flow fields, such as wall shear stress (WSS) fixed points, are considered surrogates of pathological blood flow dynamics in cardiovascular diseases. Fixed-point visualizations are typically constrained to two-dimensional (2D) spaces, yet they aim to display complex spatiotemporal (four-dimensional (4D)) dynamics. There is a need for visualization strategies to reduce occlusion and reliance on animations to allow the detection of holistic flow patterns. Using intracranial aneurysms as a use case, we present the fixed-point carousel, a novel approach to visually depicting the "4D" nature of WSS fixed points via (1) topographic mapping of the 3D aneurysm sac to overcome occlusion while preserving fixed-point distances and sac morphological features; and (2) arranging these into a carousel model to present with temporal dimension holistically. Examples are presented for image-based computational fluid dynamic (CFD) models of intracranial aneurysms, illuminating the intricate and distinct fixed-point trajectories and interactions, a necessary step toward understanding the volumetric flow manifolds that drive them for this and other cardiovascular-and potentially nonbiomedical-fluid dynamics applications.

3D bioprinting technology for modeling vascular diseases and its application

In vitromodeling of vascular diseases provides a useful platform for drug screening and mechanistic studies, by recapitulating the essential structures and physiological characteristics of the native tissue. Bioprinting is an emerging technique that offers high-resolution 3D capabilities, which have recently been employed in the modeling of various tissues and associated diseases. Blood vessels are composed of multiple layers of distinct cell types, and experience different mechanical conditions depending on the vessel type. The intimal layer, in particular, is directly exposed to such hemodynamic conditions inducing shear stress, which in turn influence vascular physiology. 3D bioprinting techniques have addressed the structural limitations of the previous vascular models, by incorporating supporting cells such as smooth muscle cells, geometrical properties such as dilation, curvature, or branching, or mechanical stimulation such as shear stress and pulsatile pressure. This paper presents a review of the physiology of blood vessels along with the pathophysiology of the target diseases including atherosclerosis, thrombosis, aneurysms, and tumor angiogenesis. Additionally, it discusses recent advances in fabricatingin vitro3D vascular disease models utilizing bioprinting techniques, while addressing the current challenges and future perspectives for the potential clinical translation into therapeutic interventions.

Fast simulation of hemodynamics in intracranial aneurysms for clinical use

BACKGROUND

A widely accepted tool to assess hemodynamics, one of the most important factors in aneurysm pathophysiology, is Computational Fluid Dynamics (CFD). As current workflows are still time consuming and difficult to operate, CFD is not yet a standard tool in the clinical setting. There it could provide valuable information on aneurysm treatment, especially regarding local risks of rupture, which might help to optimize the individualized strategy of neurosurgical dissection during microsurgical aneurysm clipping.

METHOD

We established and validated a semi-automated workflow using 3D rotational angiographies of 24 intracranial aneurysms from patients having received aneurysm treatment at our centre. Reconstruction of vessel geometry and generation of volume meshes was performed using AMIRA 6.2.0 and ICEM 17.1. For solving ANSYS CFX was used. For validational checks, tests regarding the volumetric impact of smoothing operations, the impact of mesh sizes on the results (grid convergence), geometric mesh quality and time tests for the time needed to perform the workflow were conducted in subgroups.

RESULTS

Most of the steps of the workflow were performed directly on the 3D images requiring no programming experience. The workflow led to final CFD results in a mean time of 22 min 51.4 s (95%-CI 20 min 51.562 s-24 min 51.238 s, n = 5). Volume of the geometries after pre-processing was in mean 4.46% higher than before in the analysed subgroup (95%-CI 3.43-5.50%). Regarding mesh sizes, mean relative aberrations of 2.30% (95%-CI 1.51-3.09%) were found for surface meshes and between 1.40% (95%-CI 1.07-1.72%) and 2.61% (95%-CI 1.93-3.29%) for volume meshes. Acceptable geometric mesh quality of volume meshes was found.

CONCLUSIONS

We developed a semi-automated workflow for aneurysm CFD to benefit from hemodynamic data in the clinical setting. The ease of handling opens the workflow to clinicians untrained in programming. As previous studies have found that the distribution of hemodynamic parameters correlates with thin-walled aneurysm areas susceptible to rupture, these data might be beneficial for the operating neurosurgeon during aneurysm surgery, even in acute cases.

A Synergistic Overview between Microfluidics and Numerical Research for Vascular Flow and Pathological Investigations

Vascular diseases are widespread, and sometimes such life-threatening medical disorders cause abnormal blood flow, blood particle damage, changes to flow dynamics, restricted blood flow, and other adverse effects. The study of vascular flow is crucial in clinical practice because it can shed light on the causes of stenosis, aneurysm, blood cancer, and many other such diseases, and guide the development of novel treatments and interventions. Microfluidics and computational fluid dynamics (CFDs) are two of the most promising new tools for investigating these phenomena. When compared to conventional experimental methods, microfluidics offers many benefits, including lower costs, smaller sample quantities, and increased control over fluid flow and parameters. In this paper, we address the strengths and weaknesses of computational and experimental approaches utilizing microfluidic devices to investigate the rheological properties of blood, the forces of action causing diseases related to cardiology, provide an overview of the models and methodologies of experiments, and the fabrication of devices utilized in these types of research, and portray the results achieved and their applications. We also discuss how these results can inform clinical practice and where future research should go. Overall, it provides insights into why a combination of both CFDs, and experimental methods can give even more detailed information on disease mechanisms recreated on a microfluidic platform, replicating the original biological system and aiding in developing the device or chip itself.

On flow fluctuations in ruptured and unruptured intracranial aneurysms: resolved numerical study

Flow fluctuations have emerged as a promising hemodynamic metric for understanding of hemodynamics in intracranial aneurysms. Several investigations have reported flow instabilities using numerical tools. In this study, the occurrence of flow fluctuations is investigated using either Newtonian or non-Newtonian fluid models in five patient-specific intracranial aneurysms using high-resolution lattice Boltzmann simulation methods. Flow instabilities are quantified by computing power spectral density, proper orthogonal decomposition, and fluctuating kinetic energy of velocity fluctuations. Our simulations reveal substantial flow instabilities in two of the ruptured aneurysms, where the pulsatile inflow through the neck leads to hydrodynamic instability, particularly around the rupture position, throughout the entire cardiac cycle. In other monitoring points, the flow instability is primarily observed during the deceleration phase; typically, the fluctuations begin just after peak systole, gradually decay, and the flow returns to its original, laminar pulsatile state during diastole. Additionally, we assess the rheological impact on flow dynamics. The disparity between Newtonian and non-Newtonian outcomes remains minimal in unruptured aneurysms, with less than a 5% difference in key metrics. However, in ruptured cases, adopting a non-Newtonian model yields a substantial increase in the fluctuations within the aneurysm sac, with up to a 30% higher fluctuating kinetic energy compared to the Newtonian model. The study highlights the importance of using appropriate high-resolution simulations and non-Newtonian models to capture flow fluctuation characteristics that may be critical for assessing aneurysm rupture risk.

Mesh neural networks for SE(3)-equivariant hemodynamics estimation on the artery wall

Computational fluid dynamics (CFD) is a valuable asset for patient-specific cardiovascular-disease diagnosis and prognosis, but its high computational demands hamper its adoption in practice. Machine-learning methods that estimate blood flow in individual patients could accelerate or replace CFD simulation to overcome these limitations. In this work, we consider the estimation of vector-valued quantities on the wall of three-dimensional geometric artery models. We employ group-equivariant graph convolution in an end-to-end SE(3)-equivariant neural network that operates directly on triangular surface meshes and makes efficient use of training data. We run experiments on a large dataset of synthetic coronary arteries and find that our method estimates directional wall shear stress (WSS) with an approximation error of 7.6% and normalised mean absolute error (NMAE) of 0.4% while up to two orders of magnitude faster than CFD. Furthermore, we show that our method is powerful enough to accurately predict transient, vector-valued WSS over the cardiac cycle while conditioned on a range of different inflow boundary conditions. These results demonstrate the potential of our proposed method as a plugin replacement for CFD in the personalised prediction of hemodynamic vector and scalar fields.

Comapping Cellular Content and Extracellular Matrix with Hemodynamics in Intact Arterial Tissues Using Scanning Immunofluorescent Multiphoton Microscopy

Deviation of blood flow from an optimal range is known to be associated with the initiation and progression of vascular pathologies. Important open questions remain about how the abnormal flow drives specific wall changes in pathologies such as cerebral aneurysms where the flow is highly heterogeneous and complex. This knowledge gap precludes the clinical use of readily available flow data to predict outcomes and improve treatment of these diseases. As both flow and the pathological wall changes are spatially heterogeneous, a crucial requirement for progress in this area is a methodology for acquiring and comapping local vascular wall biology data with local hemodynamic data. Here, we developed an imaging pipeline to address this pressing need. A protocol that employs scanning multiphoton microscopy was developed to obtain three-dimensional (3D) datasets for smooth muscle actin, collagen, and elastin in intact vascular specimens. A cluster analysis was introduced to objectively categorize the smooth muscle cells (SMC) across the vascular specimen based on SMC actin density. Finally, direct quantitative comparison of local flow and wall biology in 3D intact specimens was achieved by comapping both heterogeneous SMC data and wall thickness to patient-specific hemodynamic results.

Stress Load and Ascending Aortic Aneurysms: An Observational, Longitudinal, Single-Center Study Using Computational Fluid Dynamics

Ascending aortic aneurysm (AAoA) is a silent disease with high mortality; however, the factors associated with a worse prognosis are not completely understood. The objective of this observational, longitudinal, single-center study was to identify the hemodynamic patterns and their influence on AAoA growth using computational fluid dynamics (CFD), focusing on the effects of geometrical variations on aortic hemodynamics. Personalized anatomic models were obtained from angiotomography scans of 30 patients in two different years (with intervals of one to three years between them), of which 16 (53%) showed aneurysm growth (defined as an increase in the ascending aorta volume by 5% or more). Numerically determined velocity and pressure fields were compared with the outcome of aneurysm growth. Through a statistical analysis, hemodynamic characteristics were found to be associated with aneurysm growth: average and maximum high pressure (superior to 100 Pa); average and maximum high wall shear stress (superior to 7 Pa) combined with high pressure (>100 Pa); and stress load over time (maximum pressure multiplied by the time interval between the exams). This study provides insights into a worse prognosis of this serious disease and may collaborate for the expansion of knowledge about mechanobiology in the progression of AAoA.

Accelerated simulation methodologies for computational vascular flow modelling

Vascular flow modelling can improve our understanding of vascular pathologies and aid in developing safe and effective medical devices. Vascular flow models typically involve solving the nonlinear Navier-Stokes equations in complex anatomies and using physiological boundary conditions, often presenting a multi-physics and multi-scale computational problem to be solved. This leads to highly complex and expensive models that require excessive computational time. This review explores accelerated simulation methodologies, specifically focusing on computational vascular flow modelling. We review reduced order modelling (ROM) techniques like zero-/one-dimensional and modal decomposition-based ROMs and machine learning (ML) methods including ML-augmented ROMs, ML-based ROMs and physics-informed ML models. We discuss the applicability of each method to vascular flow acceleration and the effectiveness of the method in addressing domain-specific challenges. When available, we provide statistics on accuracy and speed-up factors for various applications related to vascular flow simulation acceleration. Our findings indicate that each type of model has strengths and limitations depending on the context. To accelerate real-world vascular flow problems, we propose future research on developing multi-scale acceleration methods capable of handling the significant geometric variability inherent to such problems.

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.

Computational Fluid Dynamic Simulations of Cerebral Aneurysms

Computational fluid dynamics (CFD) simulations have been introduced to enable individualized risk prognosis for patients with unruptured cerebral aneurysms. The present contribution provides an overview of the biomechanical and physiological principles of aneurysm formation and rupture. It describes the computational steps of the CFD and the evaluated parameters. The clinical value of CFD is then discussed based on a recent literature review. Finally, we discuss current methodological limitations and possible future developments to overcome the actual drawbacks of CFD.

Multimodal exploration of the intracranial aneurysm wall

PURPOSE

Intracranial aneurysms (IAs) are pathological changes of the intracranial vessel wall, although clinical image data can only show the vessel lumen. Histology can provide wall information but is typically restricted to ex vivo 2D slices where the shape of the tissue is altered.

METHODS

We developed a visual exploration pipeline for a comprehensive view of an IA. We extract multimodal information (like stain classification and segmentation of histologic images) and combine them via 2D to 3D mapping and virtual inflation of deformed tissue. Histological data, including four stains, micro-CT data and segmented calcifications as well as hemodynamic information like wall shear stress (WSS), are combined with the 3D model of the resected aneurysm.

RESULTS

Calcifications were mostly present in the tissue part with increased WSS. In the 3D model, an area of increased wall thickness was identified and correlated to histology, where the Oil red O (ORO) stained images showed a lipid accumulation and the alpha-smooth muscle actin (aSMA) stained images showed a slight loss of muscle cells.

CONCLUSION

Our visual exploration pipeline combines multimodal information about the aneurysm wall to improve the understanding of wall changes and IA development. The user can identify regions and correlate how hemodynamic forces, e.g. WSS, are reflected by histological structures of the vessel wall, wall thickness and calcifications.

Hemodynamic characteristics in a cerebral aneurysm model using non-Newtonian blood analogues

This study aims to develop an experimentally validated computational fluid dynamics (CFD) model to estimate hemodynamic characteristics in cerebral aneurysms (CAs) using non-Newtonian blood analogues. Blood viscosities varying with shear rates were measured under four temperatures first, which serves as the reference for the generation of blood analogues. Using the blood analogue, particle image velocimetry (PIV) measurements were conducted to quantify flow characteristics in a CA model. Then, using the identical blood properties in the experiment, CFD simulations were executed to quantify the flow patterns, which were used to compare with the PIV counterpart. Additionally, hemodynamic characteristics in the simplified Newtonian and non-Newtonian models were quantified and compared using the experimentally validated CFD model. Results showed the proposed non-Newtonian viscosity model can predict blood shear-thinning properties accurately under varying temperatures and shear rates. Another developed viscosity model based on the blood analogue can well represent blood rheological properties. The comparisons in flow characteristics show good agreements between PIV and CFD, demonstrating the developed CFD model is qualified to investigate hemodynamic factors within CAs. Furthermore, results show the differences of absolute values were insignificant between Newtonian and non-Newtonian fluids in the distributions of wall shear stress (WSS) and oscillatory shear index (OSI) on arterial walls. However, not only does the simplified Newtonian model underestimate WSS and OSI in most regions of the aneurysmal sac, but it also makes mistakes in identifying the high OSI regions on the sac surface, which may mislead the hemodynamic assessment on the pathophysiology of CAs.

Computational fluid dynamic analysis of the initiation of cerebral aneurysms

OBJECTIVE

Relationships between aneurysm initiation and hemodynamic factors remain unclear since de novo aneurysms are rarely observed. Most previous computational fluid dynamics (CFD) studies have used artificially reproduced vessel geometries before aneurysm initiation for analysis. In this study, the authors investigated the hemodynamic factors related to aneurysm initiation by using angiographic images in patients with cerebral aneurysms taken before and after an aneurysm formation.

METHODS

The authors identified 10 cases of de novo aneurysms in patients who underwent follow-up examinations for existing cerebral aneurysms located at a different vessel. The authors then reconstructed the vessel geometry from the images that were taken before aneurysm initiation. In addition, 34 arterial locations without aneurysms were selected as control cases. Hemodynamic parameters acting on the arterial walls were calculated by CFD analysis.

RESULTS

In all de novo cases, the aneurysmal initiation area corresponded to the highest wall shear stress divergence (WSSD point), which indicated that there was a strong tensile force on the arterial wall at the initiation area. The other previously reported parameters did not show such correlations. Additionally, the pressure loss coefficient (PLc) was statistically significantly higher in the de novo cases (p < 0.01). The blood flow impact on the bifurcation apex, or the secondary flow accompanied by vortices, resulted in high tensile forces and high total pressure loss acting on the vessel wall.

CONCLUSIONS

Aneurysm initiation may be more likely in an area where both tensile forces acting on the vessel wall and total pressure loss are large.

Effects of different stent wire mesh densities on hemodynamics in aneurysms of different sizes

Background

Intracranial stents are used to treat aneurysms by diverting the blood flow from entering into the aneurysmal dome. Although delayed rupture is rare, clinical outcomes are extremely poor in such cases. Hemodynamics after stent deployment may be related to delayed rupture and a better understanding of the basic characteristics of pressure changes resulting from stent deployment is needed; therefore, this study investigated the relationships between hemodynamics in aneurysms of different sizes treated using stents of different wire mesh densities.

Methods

Using computational fluid dynamics analysis, parameters related to velocity, volume flow rate, pressure, and residual volume inside the aneurysm were evaluated in digital models of 5 basic aneurysms of differing sizes (Small, Medium, Medium-Large, Large, and Giant) and using 6 different types of stent (varying number of wires, stent pitch and wire mesh density) for each aneurysm.

Results

Regardless of the aneurysm size, the velocity inside the aneurysm and the volume flow rate into the aneurysm were observed to continuously decrease up to 89.2% and 78.1%, respectively, with increasing stent mesh density. In terms of pressure, for giant aneurysms, the pressure on the aneurysmal surface elevated to 10.3%, then decreased to 5.1% with increasing stent mesh density. However, in smaller aneurysms, this pressure continuously decreased with increasing stent mesh density. The flow-diverting effect of the stents was limited when a stent with low mesh density (under 20%) was used with a giant aneurysm.

Conclusions

The present results indicate that the selection of appropriate stents according to aneurysm size may contribute to reduced risks of hemodynamic alternations related to stent deployment, which could reduce the incidence of delayed rupture.

Review of the Development of Hemodynamic Modeling Techniques to Capture Flow Behavior in Arteries Affected by Aneurysm, Atherosclerosis, and Stenting

Cardiovascular diseases (CVDs) are the leading cause of death in the developed world. CVD can include atherosclerosis, aneurysm, dissection, or occlusion of the main arteries. Many CVDs are caused by unhealthy hemodynamics. Some CVDs can be treated with the implantation of stents and stent grafts. Investigations have been carried out to understand the effects of stents and stent grafts have on arteries and the hemodynamic changes post-treatment. Numerous studies on stent hemodynamics have been carried out using computational fluid dynamics (CFD) which has yielded significant insight into the effect of stent mesh design on near-wall blood flow and improving hemodynamics. Particle image velocimetry (PIV) has also been used to capture behavior of fluids that mimic physiological hemodynamics. However, PIV studies have largely been restricted to unstented models or intra-aneurysmal flow rather than peri or distal stent flow behaviors. PIV has been used both as a standalone measurement method and as a comparison to validate the CFD studies. This article reviews the successes and limitations of CFD and PIV-based modeling methods used to investigate the hemodynamic effects of stents. The review includes an overview of physiology and relevant mechanics of arteries as well as consideration of boundary conditions and the working fluids used to simulate blood for each modeling method along with the benefits and limitations introduced.

Present status and future directions - irrigants and irrigation methods

Irrigation is considered the primary means of cleaning and disinfection of the root canal system. The purpose of this review was to set the framework for the obstacles that irrigation needs to overcome, to critically appraise currently used irrigants and irrigation methods, to highlight knowledge gaps and methodological limitations in the available studies and to provide directions for future developments. Organization of bacteria in biofilms located in anatomic intricacies of the root canal system and the difficulty to eliminate them is the main challenge for irrigants. Sodium hypochlorite remains the primary irrigant of choice, but it needs to be supplemented by a chelator. Delivery of the irrigants using a syringe and needle and activation by an ultrasonic file are the most popular irrigation methods. There is no evidence that any adjunct irrigation method, including ultrasonic activation, can improve the long‐term outcome of root canal treatment beyond what can be achieved by instrumentation and syringe irrigation. It is necessary to redefine the research priorities in this field and investigate in greater depth the penetration of the irrigants, their effect on the biofilm and the long‐term treatment outcome. New studies must also focus on clinically relevant comparisons, avoid methodological flaws and have sufficiently large sample sizes to reach reliable conclusions. Future multidisciplinary efforts combining the knowledge from basic sciences such as Chemistry, Microbiology and Fluid Dynamics may lead to more effective antimicrobials and improved activation methods to bring them closer to the residual biofilm in the root canal system.

Virtual Flow-T Stenting for Two Patient-Specific Bifurcation Aneurysms

The effective treatment of wide necked cerebral aneurysms located at vessel bifurcations (WNBAs) remains a significant challenge. Such aneurysm geometries have typically been approached with Y or T stenting configurations of stents and/or flow diverters, often with the addition of endovascular coils. In this study, two WNBAs were virtually treated by a novel T-stenting technique (Flow-T) with a number of braided stents and flow-diverter devices. Multiple possible device deployment configurations with varying device compression levels were tested, using fast-deployment algorithms, before a steady state computational hemodynamic simulation was conducted to examine the efficacy and performance of each scenario. The virtual fast deployment algorithm based on a linear and torsional spring analogy is used to accurately deploy nine stents in two WNBAs geometries. The devices expand from the distal to proximal side of the devices with respect to aneurysm sac. In the WNBAs modelled, all configurations of Flow-T device placement were shown to reduce factors linked with increased aneurysm rupture risk including aneurysm inflow jets and high aneurysm velocity, along with areas of flow impingement and elevated wall shear stress (WSS). The relative position of the flow-diverting device in the secondary daughter vessel in the Flow-T approach was found to have a negligible effect on overall effectiveness of the procedure in the two geometries considered. The level of interventionalist-applied compression in the braised stent that forms the other arm of the Flow-T approach was shown to impact the aneurysm inflow reduction and aneurysm flow pattern more substantially. In the Flow-T approach the relative position of the secondary daughter vessel flow-diverter device (the SVB) was found to have a negligible effect on inflow reduction, aneurysm flow pattern, or WSS distribution in both aneurysm geometries. This suggests that the device placement in this vessel may be of secondary importance. By contrast, substantially more variation in inflow reduction and aneurysm flow pattern was seen due to variations in braided stent (LVIS EVO or Baby Leo) compression at the aneurysm neck. As such we conclude that the success of a Flow-T procedure is primarily dictated by the level of compression that the interventionalist applies to the braided stent. Similar computationally predicted outcomes for both aneurysm geometries studied suggest that adjunct coiling approach taken in the clinical intervention of the second geometry may have been unnecessary for successful aneurysm isolation. Finally, the computational modelling framework proposed offers an effective planning platform for complex endovascular techniques, such as Flow-T, where the scope of device choice and combination is large and selecting the best strategy and device combination from several candidates is vital.

A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics

We present a novel, cost-efficient methodology to simulate aortic haemodynamics in a patient-specific, compliant aorta using an MRI data fusion process. Based on a previously-developed Moving Boundary Method, this technique circumvents the high computational cost and numerous structural modelling assumptions required by traditional Fluid-Structure Interaction techniques. Without the need for Computed Tomography (CT) data, the MRI images required to construct the simulation can be obtained during a single imaging session. Black Blood MR Angiography and 2D Cine-MRI data were used to reconstruct the luminal geometry and calibrate wall movement specifically to each region of the aorta. 4D-Flow MRI and non-invasive pressure measurements informed patient-specific inlet and outlet boundary conditions. Luminal area closely matched 2D Cine-MRI measurements with a mean error of less than 4.6% across the cardiac cycle, while physiological pressure and flow distributions were simulated to within 3.3% of patient-specific targets. Moderate agreement with 4D-Flow MRI velocity data was observed. Despite lower peak velocity, an equivalent rigid-wall simulation predicted a mean Time-Averaged Wall Shear Stress (TAWSS) 13% higher than the compliant simulation. The agreement observed between compliant simulation results and MRI data is testament to the accuracy and efficiency of this MRI-based simulation technique.

Prediction of Cerebral Aneurysm Hemodynamics With Porous-Medium Models of Flow-Diverting Stents via Deep Learning

The interventional treatment of cerebral aneurysm requires hemodynamics to provide proper guidance. Computational fluid dynamics (CFD) is gradually used in calculating cerebral aneurysm hemodynamics before and after flow-diverting (FD) stent placement. However, the complex operation (such as the construction and placement simulation of fully resolved or porous-medium FD stent) and high computational cost of CFD hinder its application. To solve these problems, we applied aneurysm hemodynamics point cloud data sets and a deep learning network with double input and sampling channels. The flexible point cloud format can represent the geometry and flow distribution of different aneurysms before and after FD stent (represented by porous medium layer) placement with high resolution. The proposed network can directly analyze the relationship between aneurysm geometry and internal hemodynamics, to further realize the flow field prediction and avoid the complex operation of CFD. Statistical analysis shows that the prediction results of hemodynamics by our deep learning method are consistent with the CFD method (error function <13%), but the calculation time is significantly reduced 1,800 times. This study develops a novel deep learning method that can accurately predict the hemodynamics of different cerebral aneurysms before and after FD stent placement with low computational cost and simple operation processes.

In vitro pulsatile flow study in compliant and rigid ascending aorta phantoms by stereo particle image velocimetry

The aorta is a high risk region for cardiovascular disease (CVD). Haemodynamic patterns leading to CVD are not well established despite numerous experimental and numerical studies. Most overlook effects of arterial compliance and pulsatile flow. However, rigid wall assumptions can lead to overestimation of wall shear stress; a key CVD determinant. This work investigates the effect of compliance on aortic arch haemodynamics experiencing pulsatility. Rigid and compliant phantoms of the arch and brachiocephalic branch (BCA) were manufactured. Stereoscopic particle image velocimetry was used to observe velocity fields. Higher velocity magnitude was observed in the rigid BCA during acceleration. However, during deceleration, the compliant phantom experienced higher velocity. During deceleration, a low velocity region initiated and increased in size in the BCA of both phantoms with irregular shape in the compliant. At mid-deceleration, considerably larger recirculation was observed under compliance compared to rigid. Another recirculation region formed and increased in size on the inner wall of the arch in the compliant during late deceleration, but not rigid. The recirculation regions witnessed identify as high risk areas for atherosclerosis formation by a previous ex-vivo study. The results demonstrate necessity of compliance and pulsatility in haemodynamic studies to obtain highly relevant clinical outcomes.

Hemodynamic and Morphological Factors Related to Coil Compaction in Basilar Artery Tip Aneurysms

PURPOSE

Coil compaction is directly related to the degree of cerebral aneurysmal recanalization. The Degree of Recanalization (DoR) was quantified by measuring the volume vacated by coil deformation. The purpose of this study was to clarify the hemodynamic and morphological factors associated with coil compaction.

METHODS

Computational fluid dynamics (CFD) simulations were performed on 28 middle size (5-10 mm), unruptured basilar artery tip aneurysms. The DoR was measured by comparing the coil mass shape obtained from three-dimensional digital subtraction angiography data immediately after coil embolization and again within 1 to 2 years of follow-up. Deployed coils were modeled using a virtual coiling technique for CFD simulations. Hemodynamic and morphological factors to predict the DoR were derived using multiple linear regression.

RESULTS

Aneurysmal neck area, the maximum pressure generated on the neck surface after coil embolization, and the high-pressure position on the neck surface predicted DoR with statistical significance (p<0.001, p<0.001, p=0.004, respectively). DoR tended to increase when the neck area was large, the pressure generated on the coils was high, and the high-pressure position was close to the center of the neck surface. The volume embolization ratio was not statistically relevant for the DoR in the cases of this study.

CONCLUSIONS

Coil compaction occurs in cerebral aneurysms with a wide neck, high pressure generated on the coils, and high pressure in the center of the neck surface. Establishing the DoR can contribute to the prediction of recanalization after coil embolization.

Lagrangian Trajectory Simulation of Platelets and Synchrotron Microtomography Augment Hemodynamic Analysis of Intracranial Aneurysms Treated With Embolic Coils

As frequency of endovascular treatments for intracranial aneurysms increases, there is a growing need to understand the mechanisms for coil embolization failure. Computational fluid dynamics (CFD) modeling often simplifies modeling the endovascular coils as a homogeneous porous medium (PM), and focuses on the vascular wall endothelium, not considering the biomechanical environment of platelets. These assumptions limit the accuracy of computations for treatment predictions. We present a rigorous analysis using X-ray microtomographic imaging of the coils and a combination of Lagrangian (platelet) and Eulerian (endothelium) metrics. Four patient-specific, anatomically accurate in vitro flow phantoms of aneurysms are treated with the same patient-specific endovascular coils. Synchrotron tomography scans of the coil mass morphology are obtained. Aneurysmal hemodynamics are computationally simulated before and after coiling, using patient-specific velocity/pressure measurements. For each patient, we analyze the trajectories of thousands of platelets during several cardiac cycles, and calculate residence times (RTs) and shear exposure, relevant to thrombus formation. We quantify the inconsistencies of the PM approach, comparing them with coil-resolved (CR) simulations, showing the under- or overestimation of key hemodynamic metrics used to predict treatment outcomes. We fully characterize aneurysmal hemodynamics with converged statistics of platelet RT and shear stress history (SH), to augment the traditional wall shear stress (WSS) on the vascular endothelium. Incorporating microtomographic scans of coil morphology into hemodynamic analysis of coiled intracranial aneurysms, and augmenting traditional analysis with Lagrangian platelet metrics improves CFD predictions, and raises the potential for understanding and clinical translation of computational hemodynamics for intracranial aneurysm treatment outcomes.

Engineering Perspective on Cardiovascular Simulations of Fontan Hemodynamics: Where Do We Stand with a Look Towards Clinical Application

BACKGROUND

Cardiovascular simulations for patients with single ventricles undergoing the Fontan procedure can assess patient-specific hemodynamics, explore surgical advances, and develop personalized strategies for surgery and patient care. These simulations have not yet been broadly accepted as a routine clinical tool owing to a number of limitations. Numerous approaches have been explored to seek innovative solutions for improving methodologies and eliminating these limitations.

PURPOSE

This article first reviews the current state of cardiovascular simulations of Fontan hemodynamics. Then, it will discuss the technical progress of Fontan simulations with the emphasis of its clinical impact, noting that substantial improvements have been made in the considerations of patient-specific anatomy, flow, and blood rheology. The article concludes with insights into potential future directions involving clinical validation, uncertainty quantification, and computational efficiency. The advancements in these aspects could promote the clinical usage of Fontan simulations, facilitating its integration into routine clinical practice.

Association Between Aneurysmal Haemodynamics and Device Microstructural Characteristics After Flow-Diversion Treatments With Dual Stents of Different Sizes: A Numerical Study

Objectives

Treating intracranial aneurysms with flow-diverting stents sometimes requires deployment of a second device. Herein we quantify the sizing effects of devices in dual-stent treatments upon the final stent microstructure and the post-treatment aneurysmal haemodynamics.

Methods

Fifteen sidewall ICA aneurysm geometries were included. Using a virtual stenting technique, we implanted either one or two stents for each aneurysm treatment considered, with each stent specified as one of two different sizes, yielding a total of two single-stent and fouir dual-stent treatment scenarios for each aneurysm. Three stent microstructural parameters and nine aneurysmal haemodynamic parameters were quantified and systematically compared across the 90 treatment scenarios.

Results

Deployment of a second stent further reduced the aneurysmal inflow rate (IR) and energy loss (EL) by, respectively, 14 ± 11% (p = 0.001) and 9 ± 12% (p = 0.056), relative to the untreated condition. Sizing effects of the earlier-deployed stent led to largest differences of 6.9% for the final IR reduction and 11.1% for the EL, whereas sizing effects from the later-deployed stent were minor (≤2.1%). The change in stent pore size was the only microstructural parameter demonstrating a strong correlation with the reduction in the post-treatment aneurysmal haemodynamics, in terms of the IR (r = 0.50, p < 0.001) and pressure drop (r = 0.63, p < 0.001).

Conclusion

Size of the earlier-deployed stent has substantial effects on the final haemodynamic outcomes after dual-stent treatment. The average pore size of stent wires at the aneurysm orifice shows promise as a potential index for predicting the efficacy of flow-diversion treatments.

Thrombin-Fibrinogen In Vitro Flow Model of Thrombus Growth in Cerebral Aneurysms

Cerebral aneurysms are balloon-like structures that develop on weakened areas of cerebral artery walls, with a significant risk of rupture. Thrombi formation is closely associated with cerebral aneurysms and has been observed both before and after intervention, leading to a wide variability of outcomes in patients with the condition. The attempt to manage the outcomes has led to the development of various computational models of cerebral aneurysm thrombosis. In the current study, we developed a simplified thrombin–fibrinogen flow system, based on commercially available purified human-derived plasma proteins, which enables thrombus growth and tracking in an idealized cerebral aneurysm geometry. A three-dimensional printed geometry of an idealized cerebral aneurysm and parent vessel configuration was developed. An unexpected outcome was that this phantom-based flow model allowed us to track clot growth over a period of time, by using optical imaging to record the progression of the growing clot into the flow field. Image processing techniques were subsequently used to extract important quantitative metrics from the imaging dataset, such as end point intracranial thrombus volume. The model clearly demonstrates that clot formation, in cerebral aneurysms, is a complex interplay between mechanics and biochemistry. This system is beneficial for verifying computational models of cerebral aneurysm thrombosis, particularly those focusing on initial angiographic occlusion outcomes, and will also assist manufacturers in optimizing interventional device designs.

Numerical Simulation of Blood Flows in Patient-specific Abdominal Aorta with Primary Organs

The abdominal aorta is the largest artery in the abdominal cavity that supplies blood flows to vital organs through the complex visceral arterial branches, including the celiac trunk (the liver, stomach, spleen, etc.), the renal arteries (the kidneys) and the superior and inferior mesenteric arteries (the small and large intestine, pancreas, etc.). An accurate simulation of blood flows in this network of arteries is important for the understanding of the hemodynamics in various organs of healthy and diseased patients, but the computational cost is very high. As a result, most researchers choose to focus on a portion of the artery or use a low-dimensional approximation of the artery. In the present work, we introduce a parallel algorithm for the modeling of pulsatile flows in the abdominal aorta with branches to the primary organs, and an organ-based two-level method for calculating the resistances for the outflow boundary conditions. With this highly parallel approach, the simulation of the blood flow for a cardiac cycle of the anatomically detailed aorta can be obtained within a few hours, and the blood distribution to organs including liver, spleen and kidneys are also computed with certain accuracy. Moreover, we discuss the significant hemodynamic differences resulted from the influence of the peripheral branches. In addition, we examine the accuracy of the results with respect to the mesh size and time-step size and show the high parallel scalability of the proposed algorithm with up to 3000 processor cores.

How patient specific are patient-specific computational models of cerebral aneurysms? An overview of sources of error and variability

Computational modeling of cerebral aneurysms, derived from clinical 3D angiography, has become widespread over the past 15 years. While such "image-based" or "patient-specific" models have shown promise for the assessment of rupture risk, much debate remains about their reliability in light of necessary modeling assumptions and incomplete or uncertain model input parameters derived from the clinic. The aims of this review were to walk through the various steps of this so-called patient-specific modeling pipeline and to highlight evidence supporting those steps that we can or cannot rely on. The relative importance of the different sources of error and variability on hemodynamic predictions is summarized, with recommendations to standardize for those that can be avoided and to pay closer attention those to that cannot.

Inter-patient variations in flow boundary conditions at middle cerebral artery from 7T PC-MRI and influence on Computational Fluid Dynamics of intracranial aneurysms

BACKGROUND

Computational fluid dynamics(CFD) of intracranial aneurysms requires flow boundary conditions(BCs) as inputs. Patient-specific BCs are usually unavailable and substituted by literature-derived generic BCs. Therefore, we investigated inter-patient BC variations and their influence on middle cerebral artery aneurysmal hemodynamics.

METHOD

We retrospectively collected CT angiography and 7-T Phase-Contrast(PC)-MRI data from eight middle-cerebral-artery bifurcation aneurysms to reconstruct the geometry and measure the arterial flowrates, respectively. The coefficient of variation(CoV) was calculated for the inlet flowrate and the pulsatility index(PI). The outflow split estimated by Murray's law was compared with PC-MRI measurements. For each aneurysm, we performed seven simulations: "baseline" using PC-MRI-derived BCs and the other six with changing BCs to explore the influence of BC variations on hemodynamics.

RESULTS

From PC-MRI, the inlet flowrate was 1.94 ± 0.71 cm³/s(CoV = 36%) and PI was 0.37 ± 0.13(CoV = 34%). The outflow split estimated by Murray's law deviated by 15.3% compared to PC-MRI. Comparing to "baseline" models, ±36% variations in inlet flowrate caused -61% to +89% changes in time-averaged wall shear stress(WSS), -37% to +32% in normalized WSS(NWSS; by parent-artery), and -42% to +126% in oscillatory shear index(OSI). The ±34% variations in PI caused, -46% to +67% in OSI. Applying ±15% variations in outflow split led to inflow jet deflection and -41% to +52% changes in WSS, -41% to +47% in NWSS, and -44% to +144% in OSI.

CONCLUSION

Inflow rate and outflow split have a drastic impact on hemodynamics of intracranial aneurysms. Inlet waveform has a negligible impact on WSS and NWSS but major impact on OSI. CFD-based models need to consider such sensitivity.

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

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

Platelet Dynamics and Hemodynamics of Cerebral Aneurysms Treated with Flow-Diverting Stents

Flow-diverting stents (FDS) are used to treat cerebral aneurysms. They promote the formation of a stable thrombus within the aneurysmal sac and, if successful, isolate the aneurysmal dome from mechanical stresses to prevent rupture. Platelet activation, a mechanism necessary for thrombus formation, is known to respond to biomechanical stimuli, particularly to the platelets' residence time and shear stress exposure. Currently, there is no reliable method for predicting FDS treatment outcomes, either a priori or after the procedure. Eulerian computational fluid dynamic (CFD) studies of aneurysmal flow have searched for predictors of endovascular treatment outcome; however, the hemodynamics of thrombus formation cannot be fully understood without considering the platelets' trajectories and their mechanics-triggered activation. Lagrangian analysis of the fluid mechanics in the aneurysmal vasculature provides novel metrics by tracking the platelets' residence time (RT) and shear history (SH). Eulerian and Lagrangian parameters are compared for 19 patient-specific cases, both pre- and post-treatment, to assess the degree of change caused by the FDS and subsequent treatment efficacy.

Flow-splitting-based computation of outlet boundary conditions for improved cerebrovascular simulation in multiple intracranial aneurysms

PURPOSE

Image-based hemodynamic simulations have great potential for precise blood flow predictions in intracranial aneurysms. Due to model assumptions and simplifications with respect to boundary conditions, clinical acceptance remains limited.

METHODS

Within this study, we analyzed the influence of outflow-splitting approaches on multiple aneurysm studies and present a new outflow-splitting approach that takes the precise morphological vessel cross sections into account. We provide a detailed comparison of five outflow strategies considering eight intracranial aneurysms: zero-pressure configuration (1), a flow splitting inspired by Murray's law with a square (2) and a cubic (3) vessel diameter, a flow splitting incorporating vessel bifurcations based on circular vessel cross sections (4) and our novel flow splitting including vessel bifurcations and anatomical vessel cross sections (5). Other boundary conditions remain constant. For each simulation and each aneurysm, we conducted an evaluation based on common hemodynamic parameters, e.g., normalized wall shear stress and inflow concentration index.

RESULTS

The comparison of five outflow strategies for image-based simulations shows a large variability regarding the parameters of interest. Qualitatively, our strategy based on anatomical cross sections yields a more uniform flow rate distribution with increased aneurysm inflow rates. The commonly used zero-pressure approach shows the largest variations, especially for more distal aneurysms. A rank ordering of multiple aneurysms in one patient might still be possible, since the ordering appeared to be independent of the outflow strategy.

CONCLUSIONS

The results reveal that outlet boundary conditions have a crucial impact on image-based blood flow simulations, especially for multiple aneurysm studies. We could confirm the advantages of the more complex outflow-splitting model (4) including an incremental improvement (5) compared to strategies (1), (2) and (3) for this application scenario. Furthermore, we discourage from using zero-pressure configurations that lack a physiological basis.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH)-Phase Ib: Effect of morphology on hemodynamics

Background

Image-based blood flow simulations have been increasingly applied to investigate intracranial aneurysm (IA) hemodynamics. However, the acceptance among physicians remains limited due to the high variability in the underlying assumptions and quality of results.

Methods

To evaluate the vessel segmentation as one of the most important sources of error, the international Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH) was announced. 26 research groups from 13 different countries segmented three datasets, which contained five IAs in total. Based on these segmentations, 73 time-dependent blood flow simulations under consistent conditions were carried out. Afterwards, relevant flow and shear parameters (e.g., neck inflow rate, parent vessel flow rate, spatial mean velocity, and wall shear stress) were analyzed both qualitatively and quantitatively.

Results

Regarding the entire vasculature, the variability of the segmented vessel radius is 0.13 mm, consistent and independent of the local vessel radius. However, the centerline velocity shows increased variability in more distal vessels. Focusing on the aneurysms, clear differences in morphological and hemodynamic parameters were observed. The quantification of the segmentation-induced variability showed approximately a 14% difference among the groups for the parent vessel flow rate. Regarding the mean aneurysmal velocity and the neck inflow rate, a variation of 30% and 46% was observed, respectively. Finally, time-averaged wall shear stresses varied between 28% and 51%, depending on the aneurysm in question.

Conclusions

MATCH reveals the effect of state-of-the-art segmentation algorithms on subsequent hemodynamic simulations for IA research. The observed variations may lead to an inappropriate interpretation of the simulation results and thus, can lead to inappropriate conclusions by physicians. Therefore, accurate segmentation of the region of interest is necessary to obtain reliable and clinically helpful flow information.

Computational Fluid Dynamics Analysis of Carotid-Ophthalmic Aneurysms with Concomitant Ophthalmic Artery Infundibulum in a Patient-Specific Model

BACKGROUND

Although previous studies have reported cases of coexistence of carotid-ophthalmic aneurysm and ophthalmic artery (OA) infundibulum, the hemodynamic characteristics of this complicated structure and its damaging effects on vision remain to be elucidated. The aim of the present study was to analyze this artery structure using computational fluid dynamics (CFD) techniques.

METHODS

We have presented the case of a patient with a diagnosis of carotid-ophthalmic aneurysm, who had been experiencing blurred vision. A transient analysis was performed to investigate the blood flowing in the parent artery. Hemodynamic parameters such as streamline, wall shear stress (WSS), oscillatory shear index (OSI), and relative residence time were obtained.

RESULTS

When the inlet velocity of the parent artery was at the second peak, the flow rate and intensity of the vortex reached their maximum. In the aneurysm neck, a region of high time-averaged WSS (TAWSS) and a region of low TAWSS with a high OSI coexisted. In addition, a relaxation area was found. In the aneurysm dome, the minimum TAWSS was 2.5 Pa, the maximum OSI was 0.48, and the 2 regions did not overlap. In the OA infundibulum, the maximum OSI and relative residence time were 0.47 and 39.2, respectively; the minimum TAWSS was 0.59 Pa.

CONCLUSIONS

We detected aneurysm regions that were susceptible to further expansion and assessed the rupture risk of each region. The relaxation area could promote aneurysm progression. In addition, the location of the vortex shear force center varied with time. Finally, double vortex streamlines influenced the blood supply through the OA, impairing the vision. Infundibulum might promote thrombus formation and, hence, retard OA blood flow.

Computational study on hemodynamic changes in patient-specific proximal neck angulation of abdominal aortic aneurysm with time-varying velocity

Aneurysms are considered as a critical cardiovascular disease worldwide when they rupture. The clinical understanding of geometrical impact on the flow behaviour and biomechanics of abdominal aortic aneurysm (AAA) is progressively developing. Proximal neck angulations of AAAs are believed to influence the hemodynamic changes and wall shear stress (WSS) within AAAs. Our aim was to perform pulsatile simulations using computational fluid dynamics (CFD) for patient-specific geometry to investigate the influence of severe angular (≥ 60°) neck on AAA's hemodynamic and wall shear stress. The patient's geometrical characteristics were obtained from a computed tomography images database of AAA patients. The AAA geometry was reconstructed using Mimics software. In computational method, blood was assumed Newtonian fluid and an inlet varying velocity waveform in a cardiac cycle was assigned. The CFD study was performed with ANSYS software. The results of flow behaviours indicated that the blood flow through severe bending of angular neck leads to high turbulence and asymmetry of flows within the aneurysm sac resulting in blood recirculation. The high wall shear stress (WSS) occurred near the AAA neck and on surface of aneurysm sac. This study explained and showed flow behaviours and WSS progression within high angular neck AAA and risk prediction of abdominal aorta rupture. We expect that the visualization of blood flow and hemodynamic changes resulted from CFD simulation could be as an extra tool to assist clinicians during a decision making when estimation the risks of interventional procedures.

Reconstructing patient-specific cerebral aneurysm vasculature for in vitro investigations and treatment efficacy assessments

Perianeurysmal hemodynamics play a vital role in the initiation, growth and rupture of intracranial aneurysms. In vitro investigations of aneurysmal hemodynamics are helpful to visualize and measure blood flow, and aiding surgical planning approaches. Improving in vitro model creation can improve the feasibility and accuracy of hemodynamic investigations and surgical planning, improving clinical value. In this study, in vitro models were created from three-dimensional rotational angiography (3DRA) of six patients harboring intracranial aneurysms using a multi-step process involving 3D printing, index of refraction matching and silicone casting that renders the models transparent for flow visualization. Each model was treated with the same commercially-available, patient-specific, endovascular devices (coils and/or stents). All models were scanned by synchrotron X-ray microtomography to obtain high-resolution imaging of the vessel lumen, aneurysmal sac and endovascular devices. Dimensional accuracy was compared by quantifying the differences between the microtomographic reconstructions of the fabricated phantoms and the original 3DRA obtained during patient treatment. True-scale in vitro flow phantoms were successfully created for all six patients. Optical transparency was verified by using an index of refraction matched working fluid that replicated the mechanical behavior of blood. Synchrotron imaging of vessel lumen, aneurysmal sac and endovascular devices was successfully obtained, and dimensional errors were found to be O(100 μm). The creation of dimensionally-accurate, optically-transparent flow phantoms of patient-specific intracranial aneurysms is feasible using 3D printing technology. Such models may enable in vitro investigations of aneurysmal hemodynamics to aid in treatment planning and outcome prediction to devise optimal patient-specific neurointerventional strategies.

Credibility, Replicability, and Reproducibility in Simulation for Biomedicine and Clinical Applications in Neuroscience

Modeling and simulation in computational neuroscience is currently a research enterprise to better understand neural systems. It is not yet directly applicable to the problems of patients with brain disease. To be used for clinical applications, there must not only be considerable progress in the field but also a concerted effort to use best practices in order to demonstrate model credibility to regulatory bodies, to clinics and hospitals, to doctors, and to patients. In doing this for neuroscience, we can learn lessons from long-standing practices in other areas of simulation (aircraft, computer chips), from software engineering, and from other biomedical disciplines. In this manuscript, we introduce some basic concepts that will be important in the development of credible clinical neuroscience models: reproducibility and replicability; verification and validation; model configuration; and procedures and processes for credible mechanistic multiscale modeling. We also discuss how garnering strong community involvement can promote model credibility. Finally, in addition to direct usage with patients, we note the potential for simulation usage in the area of Simulation-Based Medical Education, an area which to date has been primarily reliant on physical models (mannequins) and scenario-based simulations rather than on numerical simulations.

Cognitive Imaging

This article, an extended version of ICCI*CC-2017 paper, co-authored by biomedical engineers specializing in brain blood circulation modeling and by experts in meaning-based NLP. This article suggests a cognitive computing technology for medical imaging analysis that removes image artifacts resulting in visual deviations from reality, such as discontinuous blood vessels or two vessels shown merged when they are not. It is implemented by supplying the pertinent knowledge that humans have to the computer and letting it initiate the corrective post-processing. The existing OST resource is centered on the ontology that is made to accommodate the domain with a minor adjustment effort; however, any ontology can be used, as demonstrated in this article. The examples from the ontology demonstrate the disparities between what the image shows and what the human knows. The computer detects them autonomously and can initiate the appropriate post-processing. If and when this cognitive imaging prevails, the post-processed images may replace the current ones as legitimate artifact-free MRIs.

Better Than Nothing: A Rational Approach for Minimizing the Impact of Outflow Strategy on Cerebrovascular Simulations

BACKGROUND AND PURPOSE

Computational fluid dynamics simulations of neurovascular diseases are impacted by various modeling assumptions and uncertainties, including outlet boundary conditions. Many studies of intracranial aneurysms, for example, assume zero pressure at all outlets, often the default ("do-nothing") strategy, with no physiological basis. Others divide outflow according to the outlet diameters cubed, nominally based on the more physiological Murray's law but still susceptible to subjective choices about the segmented model extent. Here we demonstrate the limitations and impact of these outflow strategies, against a novel "splitting" method introduced here.

MATERIALS AND METHODS

With our method, the segmented lumen is split into its constituent bifurcations, where flow divisions are estimated locally using a power law. Together these provide the global outflow rate boundary conditions. The impact of outflow strategy on flow rates was tested for 70 cases of MCA aneurysm with 0D simulations. The impact on hemodynamic indices used for rupture status assessment was tested for 10 cases with 3D simulations.

RESULTS

Differences in flow rates among the various strategies were up to 70%, with a non-negligible impact on average and oscillatory wall shear stresses in some cases. Murray-law and splitting methods gave flow rates closest to physiological values reported in the literature; however, only the splitting method was insensitive to arbitrary truncation of the model extent.

CONCLUSIONS

Cerebrovascular simulations can depend strongly on the outflow strategy. The default zero-pressure method should be avoided in favor of Murray-law or splitting methods, the latter being released as an open-source tool to encourage the standardization of outflow strategies.