Variability of computational fluid dynamics solutions for pressure and flow in a giant aneurysm: the ASME 2012 Summer Bioengineering Conference CFD Challenge

Influence of circle of Willis modeling on hemodynamic parameters in anterior communicating artery aneurysms and recommendations for model selection

Computational fluid dynamics (CFD) has been utilized to calculate hemodynamic parameters in anterior communicating artery aneurysm (AComA), which is located at a junction between left and right A1 and A2 segments. However, complete or half circle of Willis (CoW) models are used indiscriminately. This study aims to suggest recommendations for determining suitable CoW model. Five patient-specific CoW models with AComA were used, and each model was divided into complete, left-half, and right-half models. After validating the CFD using a flow experiment, the hemodynamic parameters and flow patterns in five AComAs were compared. In four out of five cases, inflow from one A1 side had a dominant influence on the AComA, while both left and right A1 sides affected the AComA in the remaining case. Also, the average difference in time-averaged wall shear stress between the complete and half models for four cases was 4.6%, but it was 62% in the other case. The differences in the vascular resistances of left and right A1 and A2 segments greatly influenced the flow patterns in the AComA. These results may help to enhance clinicians' understanding of blood flow in the brain, leading to improvements in diagnosis and treatment of cerebral aneurysms.

A time-consistent stabilized finite element method for fluids with applications to hemodynamics

Several finite element methods for simulating incompressible flows rely on the streamline upwind Petrov-Galerkin stabilization (SUPG) term, which is weighted by [Formula: see text]. The conventional formulation of [Formula: see text] includes a constant that depends on the time step size, producing an overall method that becomes exceedingly less accurate as the time step size approaches zero. In practice, such method inconsistency introduces significant error in the solution, especially in cardiovascular simulations, where small time step sizes may be required to resolve multiple scales of the blood flow. To overcome this issue, we propose a consistent method that is based on a new definition of [Formula: see text]. This method, which can be easily implemented on top of an existing streamline upwind Petrov-Galerkin and pressure stabilizing Petrov-Galerkin method, involves the replacement of the time step size in [Formula: see text] with a physical time scale. This time scale is calculated in a simple operation once every time step for the entire computational domain from the ratio of the L2-norm of the acceleration and the velocity. The proposed method is compared against the conventional method using four cases: a steady pipe flow, a blood flow through vascular anatomy, an external flow over a square obstacle, and a fluid-structure interaction case involving an oscillatory flexible beam. These numerical experiments, which are performed using linear interpolation functions, show that the proposed formulation eliminates the inconsistency issue associated with the conventional formulation in all cases. While the proposed method is slightly more costly than the conventional method, it significantly reduces the error, particularly at small time step sizes. For the pipe flow where an exact solution is available, we show the conventional method can over-predict the pressure drop by a factor of three. This large error is almost completely eliminated by the proposed formulation, dropping to approximately 1% for all time step sizes and Reynolds numbers considered.

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.

StrokeNet: An automated approach for segmentation and rupture risk prediction of intracranial aneurysm

Intracranial Aneurysms (IA) present a complex challenge for neurosurgeons as the risks associated with surgical intervention, such as Subarachnoid Hemorrhage (SAH) mortality and morbidity, may outweigh the benefits of aneurysmal occlusion in some cases. Hence, there is a critical need for developing techniques that assist physicians in assessing the risk of aneurysm rupture to determine which aneurysms require treatment. However, a reliable IA rupture risk prediction technique is currently unavailable. To address this issue, this study proposes a novel approach for aneurysm segmentation and multidisciplinary rupture prediction using 2D Digital Subtraction Angiography (DSA) images. The proposed method involves training a fully connected convolutional neural network (CNN) to segment aneurysm regions in DSA images, followed by extracting and fusing different features using a multidisciplinary approach, including deep features, geometrical features, Fourier descriptor, and shear pressure on the aneurysm wall. The proposed method also adopts a fast correlation-based filter approach to drop highly correlated features from the set of fused features. Finally, the selected fused features are passed through a Decision Tree classifier to predict the rupture severity of the associated aneurysm into four classes: Mild, Moderate, Severe, and Critical. The proposed method is evaluated on a newly developed DSA image dataset and on public datasets to assess its generalizability. The system's performance is also evaluated on DSA images annotated by expert neurosurgeons for the rupture risk assessment of the segmented aneurysm. The proposed system outperforms existing state-of-the-art segmentation methods, achieving an 85 % accuracy against annotated DSA images for the risk assessment of aneurysmal rupture.

A verified and validated moving domain computational fluid dynamics solver with applications to cardiovascular flows

Computational fluid dynamics (CFD) in combination with patient-specific medical images has been used to correlate flow phenotypes with disease initiation, progression and outcome, in search of a prospective clinical tool. A large number of CFD software packages are available, but are typically based on rigid domains and low-order finite volume methods, and are often implemented in massive low-level C++ libraries. Furthermore, only a handful of solvers have been appropriately verified and validated for their intended use. Our goal was to develop, verify and validate an open-source CFD solver for moving domains, with applications to cardiovascular flows. The solver is an extension of the CFD solver Oasis, which is based on the finite element method and implemented using the FEniCS open source framework. The new solver, named OasisMove, extends Oasis by expressing the Navier-Stokes equations in the arbitrary Lagrangian-Eulerian formulation, which is suitable for handling moving domains. For code verification we used the method of manufactured solutions for a moving 2D vortex problem, and for validation we compared our results against existing high-resolution simulations and laboratory experiments for two moving domain problems of varying complexity. Verification results showed that the L 2 error followed the theoretical convergence rates. The temporal accuracy was second-order, while the spatial accuracy was second- and third-order using ℙ 1 / ℙ 1 and ℙ 2 / ℙ 1 finite elements, respectively. Validation results showed good agreement with existing benchmark results, by reproducing lift and drag coefficients with less than 1% error, and demonstrating the solver's ability to capture vortex patterns in transitional and turbulent-like flow regimes. In conclusion, we have shown that OasisMove is an open-source, accurate and reliable solver for cardiovascular flows in moving domains.

Influence of blood viscosity models and boundary conditions on the computation of hemodynamic parameters in cerebral aneurysms using computational fluid dynamics

BACKGROUND

Computational fluid dynamics (CFD) is widely used to calculate hemodynamic parameters that are known to influence cerebral aneurysms. However, the boundary conditions for CFD are chosen without any specific criteria. Our objective is to establish the recommendations for setting the analysis conditions for CFD analysis of the cerebral aneurysm.

METHOD

The plug and the Womersley flow were the inlet boundary conditions, and zero and pulsatile pressures were the outlet boundary conditions. In addition, the difference in the assumption of viscosity was analyzed with respect to the flow rate. The CFD process used in our research was validated using particle image velocimetry experiment data from Tupin et al.'s work to ensure the accuracy of the simulations.

RESULTS

It was confirmed that if the entrance length was sufficiently secured, the inlet and outlet boundary conditions did not affect the CFD results. In addition, it was observed that the difference in the hemodynamic parameter between Newtonian and non-Newtonian fluid decreased as the flow rate increased. Furthermore, it was confirmed that similar tendencies were evaluated when these recommendations were utilized in the patient-specific cerebral aneurysm models.

CONCLUSIONS

These results may help conduct standardized CFD analyses regardless of the research group.

A SOX17-PDGFB signaling axis regulates aortic root development

Developmental etiologies causing complex congenital aortic root abnormalities are unknown. Here we show that deletion of Sox17 in aortic root endothelium in mice causes underdeveloped aortic root leading to a bicuspid aortic valve due to the absence of non-coronary leaflet and mispositioned left coronary ostium. The respective defects are associated with reduced proliferation of non-coronary leaflet mesenchyme and aortic root smooth muscle derived from the second heart field cardiomyocytes. Mechanistically, SOX17 occupies a Pdgfb transcriptional enhancer to promote its transcription and Sox17 deletion inhibits the endothelial Pdgfb transcription and PDGFB growth signaling to the non-coronary leaflet mesenchyme. Restoration of PDGFB in aortic root endothelium rescues the non-coronary leaflet and left coronary ostium defects in Sox17 nulls. These data support a SOX17-PDGFB axis underlying aortic root development that is critical for aortic valve and coronary ostium patterning, thereby informing a potential shared disease mechanism for concurrent anomalous aortic valve and coronary arteries.

Machine Learning for Cardiovascular Biomechanics Modeling: Challenges and Beyond

Recent progress in machine learning (ML), together with advanced computational power, have provided new research opportunities in cardiovascular modeling. While classifying patient outcomes and medical image segmentation with ML have already shown significant promising results, ML for the prediction of biomechanics such as blood flow or tissue dynamics is in its infancy. This perspective article discusses some of the challenges in using ML for replacing well-established physics-based models in cardiovascular biomechanics. Specifically, we discuss the large landscape of input features in 3D patient-specific modeling as well as the high-dimensional output space of field variables that vary in space and time. We argue that the end purpose of such ML models needs to be clearly defined and the tradeoff between the loss in accuracy and the gained speedup carefully interpreted in the context of translational modeling. We also discuss several exciting venues where ML could be strategically used to augment traditional physics-based modeling in cardiovascular biomechanics. In these applications, ML is not replacing physics-based modeling, but providing opportunities to solve ill-defined problems, improve measurement data quality, enable a solution to computationally expensive problems, and interpret complex spatiotemporal data by extracting hidden patterns. In summary, we suggest a strategic integration of ML in cardiovascular biomechanics modeling where the ML model is not the end goal but rather a tool to facilitate enhanced modeling.

On the numerical treatment of viscous and convective effects in relative pressure reconstruction methods

The mechanism of many cardiovascular diseases can be understood by studying the pressure distribution in blood vessels. Direct pressure measurements, however, require invasive probing and provide only single-point data. Alternatively, relative pressure fields can be reconstructed from imaging-based velocity measurements by considering viscous and inertial forces. Both contributions can be potential troublemakers in pressure reconstruction: the former due to its higher-order derivatives, and the latter because of the quadratic nonlinearity in the convective acceleration. Viscous and convective terms can be treated in various forms, which, although equivalent for ideal measurements, can perform differently in practice. In fact, multiple versions are often used in literature, with no apparent consensus on the more suitable variants. In this context, the present work investigates the performance of different versions of relative pressure estimators. For viscous effects, in particular, two new modified estimators are presented to circumvent second-order differentiation without requiring surface integrals. In-silico and in-vitro data in the typical regime of cerebrovascular flows are considered, allowing a systematic noise sensitivity study. Convective terms are shown to be the main source of error, even for flows with pronounced viscous component. Moreover, the conservation (often integrated) form of convection exhibits higher noise sensitivity than the standard convective description, in all three families of estimators considered here. For the classical pressure Poisson estimator, the present modified version of the viscous term tends to yield better accuracy than the (recently introduced) integrated form, although this effect is in most cases negligible when compared to convection-related errors.

Detection and analysis of cerebral aneurysms based on X-ray rotational angiography - the CADA 2020 challenge

The Cerebral Aneurysm Detection and Analysis (CADA) challenge was organized to support the development and benchmarking of algorithms for detecting, analyzing, and risk assessment of cerebral aneurysms in X-ray rotational angiography (3DRA) images. 109 anonymized 3DRA datasets were provided for training, and 22 additional datasets were used to test the algorithmic solutions. Cerebral aneurysm detection was assessed using the F2 score based on recall and precision, and the fit of the delivered bounding box was assessed using the distance to the aneurysm. The segmentation quality was measured using the Jaccard index and a combination of different surface distance measures. Systematic errors were analyzed using volume correlation and bias. Rupture risk assessment was evaluated using the F2 score. 158 participants from 22 countries registered for the CADA challenge. The U-Net-based detection solutions presented by the community show similar accuracy compared to experts (F2 score 0.92), with a small number of missed aneurysms with diameters smaller than 3.5 mm. In addition, the delineation of these structures, based on U-Net variations, is excellent, with a Jaccard score of 0.92. The rupture risk estimation methods achieved an F2 score of 0.71. The performance of the detection and segmentation solutions is equivalent to that of human experts. The best results are obtained in rupture risk estimation by combining different image-based, morphological, and computational fluid dynamic parameters using machine learning methods. Furthermore, we evaluated the best methods pipeline, from detecting and delineating the vessel dilations to estimating the risk of rupture. The chain of these methods achieves an F2-score of 0.70, which is comparable to applying the risk prediction to the ground-truth delineation (0.71).

Bedsores Management: Efficiency Simulation of a New Mattress Design

Bedsores, also known as pressure ulcers, are wounds caused by the applied external force (pressure) on body segments, thereby preventing blood supply from delivering the required elements to the skin tissue. Missing elements hinder the skin’s ability to maintain its health. It poses a significant threat to patients that have limited mobility. A new patented mattress design and alternative suggested designs aimed to reduce pressure are investigated in this paper for their performance in decreasing pressure. A simulation using Ansys finite element analysis (FEA) is carried out for comparison. Three-dimensional models are designed and tested in the simulation for a mattress and human anthropometric segments (Torso and Hip). All designs are carried out in solidworks. Results show that the original design can redistribute the pressure and decrease it up to 17% less than the normal mattress. The original design shows better ability to decrease the absolute amount of pressure on the body. However, increasing the surface area of the movable parts results in less pressure applied to the body parts. Thus, this work suggests changing the surface area of the cubes from 25 to 100 cm².

On the prevalence of flow instabilities from high-fidelity computational fluid dynamics of intracranial bifurcation aneurysms

High-fidelity computational fluid dynamics (HF-CFD) has revealed the potential for high-frequency flow instabilities (aka "turbulent-like" flow) in intracranial aneurysms, consistent with classic in vivo and in vitro reports of bruits and/or wall vibrations. However, HF-CFD has typically been performed on limited numbers of cases, often with unphysiological inflow conditions or focused on sidewall-type aneurysms where flow instabilities may be inherently less prevalent. Here we report HF-CFD of 50 bifurcation aneurysm cases from the open-source Aneurisk model repository. These were meshed using quadratic finite elements having an average effective spatial resolution of 0.065 mm, and solved under physiologically-pulsatile flow conditions using a well-validated, minimally-dissipative solver with 20,000 time-steps per cardiac cycle Flow instability was quantified using the recently introduced spectral power index (SPI), which quantifies, from 0 to 1, the power associated with velocity fluctuations above those of the driving inflow waveform. Of the 50 cases, nearly half showed regions within the sac having SPI up to 0.5, often with non-negligible power into the 100's of Hz, and roughly 1/3 had sac-averaged SPI > 0.1. High SPI did not significantly predict rupture status in this cohort. Proper orthogonal decomposition of cases with highest SPI_avg revealed time-varying energetics consistent with transient turbulence. Our reported prevalence of high-frequency flow instabilities in HF-CFD modelling of aneurysms suggests that care must be taken to avoid routinely overlooking them if we are to understand the highly dynamic mechanical forces to which some aneurysm walls may be exposed, and their prevalence in vivo.

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.

Use of patient specific 3D printed neurovascular phantoms to simulate mechanical thrombectomy

BACKGROUND

The ability of the patient specific 3D printed neurovascular phantoms to accurately replicate the anatomy and hemodynamics of the chronic neurovascular diseases has been demonstrated by many studies. Acute occurrences, however, may still require further development and investigation and therefore we studied acute ischemic stroke (AIS). The efficacy of endovascular procedures such as mechanical thrombectomy (MT) for the treatment of large vessel occlusion (LVO), can be improved by testing the performance of thrombectomy devices and techniques using patient specific 3D printed neurovascular models.

METHODS

3D printed phantoms were connected to a flow loop with physiologically relevant flow conditions, including input flow rate and fluid temperature. A simulated blood clot was introduced into the model and placed in the proximal Middle Cerebral Artery (MCA) region. Clot location, composition, length, and arterial angulation were varied and MTs were simulated using stent retrievers. Device placement relative to the clot and the outcome of the thrombectomy were recorded for each situation. Digital subtraction angiograms (DSA) were captured before and after LVO simulation. Recanalization outcome was evaluated using DSA as either 'no recanalization' or 'recanalization'. Forty-two 3DP neurovascular phantom benchtop experiments were performed.

RESULTS

Clot angulation within the MCA region had the most significant impact on the MT outcome, with a p-value of 0.016. Other factors such as clot location, clot composition, and clot length correlated weakly with the MT outcome.

CONCLUSIONS

This project allowed us to gain knowledge of how such characteristics influence thrombectomy success and can be used in making clinical decisions when planning the procedure and selecting specific thrombectomy tools and approaches.

Evaluation of challenges and limitations of mechanical thrombectomy using 3D printed neurovascular phantoms

The mechanical thrombectomy (MT) efficacy, for large vessel occlusion (LVO) treatment in patients with stroke, could be improved if better teaching and practicing surgical tools were available. We propose a novel approach that uses 3D printing (3DP) to generate patient anatomical vascular variants for simulation of diverse clinical scenarios of LVO treated with MT. 3DP phantoms were connected to a flow loop with physiologically relevant flow conditions, including input flow rate and fluid temperature. A simulated blood clot was introduced into the model and placed in the Middle Cerebral Artery region. Clot location, composition (hard or soft clot), length, and arterial angulation were varied and MTs were simulated using stent retrievers. Device placement relative to the clot and the outcome of the thrombectomy were recorded for each situation. Angiograms were captured before and after LVO simulation and after the MT. Recanalization outcome was evaluated using the Thrombolysis in Cerebral Infarction (TICI) scale. Forty-two 3DP neurovascular phantom benchtop experiments were performed. Clot mechanical properties, hard versus soft, had the highest impact on the MT outcome, with 18/42 proving to be successful with full or partial clot retrieval. Other factors such as device manufacturer and the tortuosity of the 3DP model correlated weakly with the MT outcome. We demonstrated that 3DP can become a comprehensive tool for teaching and practicing various surgical procedures for MT in LVO patients. This platform can help vascular surgeons understand the endovascular devices limitations and patient vascular geometry challenges, to allow surgical approach optimization.

Model Verification and Error Sensitivity of Turbulence-Related Tensor Characteristics in Pulsatile Blood Flow Simulations

Model verification, validation, and uncertainty quantification are essential procedures to estimate errors within cardiovascular flow modeling, where acceptable confidence levels are needed for clinical reliability. While more turbulent-like studies are frequently observed within the biofluid community, practical modeling guidelines are scarce. Verification procedures determine the agreement between the conceptual model and its numerical solution by comparing for example, discretization and phase-averaging-related errors of specific output parameters. This computational fluid dynamics (CFD) study presents a comprehensive and practical verification approach for pulsatile turbulent-like blood flow predictions by considering the amplitude and shape of the turbulence-related tensor field using anisotropic invariant mapping. These procedures were demonstrated by investigating the Reynolds stress tensor characteristics in a patient-specific aortic coarctation model, focusing on modeling-related errors associated with the spatiotemporal resolution and phase-averaging sampling size. Findings in this work suggest that attention should also be put on reducing phase-averaging related errors, as these could easily outweigh the errors associated with the spatiotemporal resolution when including too few cardiac cycles. Also, substantially more cycles are likely needed than typically reported for these flow regimes to sufficiently converge the phase-instant tensor characteristics. Here, higher degrees of active fluctuating directions, especially of lower amplitudes, appeared to be the most sensitive turbulence characteristics.

Prediction of internal carotid artery aneurysm recurrence by pressure difference at the coil mass surface

PURPOSE

A previous study on computational fluid dynamics reported that a high pressure difference (PD) at the surface of a coil mass is a strong predictor of aneurysm recurrence after coil embolization. PD was calculated using a virtual post-coiling model (VM), created by manually cutting the aneurysm by the flat plane from an anatomic model created with pre-coil embolization data; however, its credibility has not been fully evaluated. This study aims to clarify whether PD values calculated using the post-coiling model, which reflects the actual coil plane, are a strong predictor of aneurysm recurrence.

METHODS

Fifty internal carotid artery aneurysms treated with endovascular coil embolization were analyzed (7 recanalized, 43 stable). We created and subjected two post-coiling models, namely, VM and the real post-coiling model (RM), constructed from the post-coil embolization data. The relationship between PD and aneurysm recurrence was examined using these models. PD and its constituent three parameters were compared between VM and RM.

RESULTS

PD values calculated using RM showed significantly higher aneurysm recurrence in recurrence group than stable group (p < 0.001), and multivariate analysis showed that PD in RM (p = 0.02; odds ratio, 36.24) was significantly associated with aneurysm recurrence. The receiver operating characteristic analysis revealed that PD values accurately predicted aneurysm recurrence (area under the curve, 0.977; cutoff value, 3.08; sensitivity, 100%; specificity, 97.7%). All four parameters showed a significant correlation with VM and RM (p < 0.001).

CONCLUSION

Use of PD to predict recurrence after coil embolization can be clinically relevant.

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.

A review on the reliability of hemodynamic modeling in intracranial aneurysms: why computational fluid dynamics alone cannot solve the equation

Computational blood flow modeling in intracranial aneurysms (IAs) has enormous potential for the assessment of highly resolved hemodynamics and derived wall stresses. This results in an improved knowledge in important research fields, such as rupture risk assessment and treatment optimization. However, due to the requirement of assumptions and simplifications, its applicability in a clinical context remains limited.This review article focuses on the main aspects along the interdisciplinary modeling chain and highlights the circumstance that computational fluid dynamics (CFD) simulations are embedded in a multiprocess workflow. These aspects include imaging-related steps, the setup of realistic hemodynamic simulations, and the analysis of multidimensional computational results. To condense the broad knowledge, specific recommendations are provided at the end of each subsection.Overall, various individual substudies exist in the literature that have evaluated relevant technical aspects. In this regard, the importance of precise vessel segmentations for the simulation outcome is emphasized. Furthermore, the accuracy of the computational model strongly depends on the specific research question. Additionally, standardization in the context of flow analysis is required to enable an objective comparison of research findings and to avoid confusion within the medical community. Finally, uncertainty quantification and validation studies should always accompany numerical investigations.In conclusion, this review aims for an improved awareness among physicians regarding potential sources of error in hemodynamic modeling for IAs. Although CFD is a powerful methodology, it cannot provide reliable information, if pre- and postsimulation steps are inaccurately carried out. From this, future studies can be critically evaluated and real benefits can be differentiated from results that have been acquired based on technically inaccurate procedures.

Method to simulate distal flow resistance in coronary arteries in 3D printed patient specific coronary models

BACKGROUND

Three-dimensional printing (3DP) offers a unique opportunity to build flexible vascular patient-specific coronary models for device testing, treatment planning, and physiological simulations. By optimizing the 3DP design to replicate the geometrical and mechanical properties of healthy and diseased arteries, we may improve the relevance of using such models to simulate the hemodynamics of coronary disease. We developed a method to build 3DP patient specific coronary phantoms, which maintain a significant part of the coronary tree, while preserving geometrical accuracy of the atherosclerotic plaques and allows for an adjustable hydraulic resistance.

METHODS

Coronary computed tomography angiography (CCTA) data was used within Vitrea (Vital Images, Minnetonka, MN) cardiac analysis application for automatic segmentation of the aortic root, Left Anterior Descending (LAD), Left Circumflex (LCX), Right Coronary Artery (RCA), and calcifications. Stereolithographic (STL) files of the vasculature and calcium were imported into Autodesk Meshmixer for 3D model optimization. A base with three chambers was built and interfaced with the phantom to allow fluid collection and independent distal resistance adjustment of the RCA, LAD and LCX and branching arteries. For the 3DP we used Agilus for the arterial wall, VeroClear for the base and a Vero blend for the calcifications, respectively. Each chamber outlet allowed interface with catheters of varying lengths and diameters for simulation of hydraulic resistance of both normal and hyperemic coronary flow conditions. To demonstrate the manufacturing approach appropriateness, models were tested in flow experiments.

RESULTS

Models were used successfully in flow experiments to simulate normal and hyperemic flow conditions. The inherent mean resistance of the chamber for the LAD, LCX, and RCA, were 1671, 1820, and 591 (dynes ∙ sec/ cm5), respectively. This was negligible when compared with estimates in humans, with the chamber resistance equating to 0.65-5.86%, 1.23-6.86%, and 0.05-1.67% of the coronary resistance for the LAD, LCX, and RCA, respectively at varying flow rates and activity states. Therefore, the chamber served as a means to simulate the compliance of the distal coronary trees and to allow facile coupling with a set of known resistance catheters to simulate various physical activity levels.

CONCLUSIONS

We have developed a method to create complex 3D printed patient specific coronary models derived from CCTA, which allow adjustable distal capillary bed resistances. This manufacturing approach permits comprehensive coronary model development which may be used for physiologically relevant flow simulations.

An Automated Workflow for Hemodynamic Computations in Cerebral Aneurysms

In recent years, computational fluid dynamics (CFD) has become a valuable tool for investigating hemodynamics in cerebral aneurysms. CFD provides flow-related quantities, which have been shown to have a potential impact on aneurysm growth and risk of rupture. However, the adoption of CFD tools in clinical settings is currently limited by the high computational cost and the engineering expertise required for employing these tools, e.g., for mesh generation, appropriate choice of spatial and temporal resolution, and of boundary conditions. Herein, we address these challenges by introducing a practical and robust methodology, focusing on computational performance and minimizing user interaction through automated parameter selection. We propose a fully automated pipeline that covers the steps from a patient-specific anatomical model to results, based on a fast, graphics processing unit- (GPU-) accelerated CFD solver and a parameter selection methodology. We use a reduced order model to compute the initial estimates of the spatial and temporal resolutions and an iterative approach that further adjusts the resolution during the simulation without user interaction. The pipeline and the solver are validated based on previously published results, and by comparing the results obtained for 20 cerebral aneurysm cases with those generated by a state-of-the-art commercial solver (Ansys CFX, Canonsburg PA). The automatically selected spatial and temporal resolutions lead to results which closely agree with the state-of-the-art, with an average relative difference of only 2%. Due to the GPU-based parallelization, simulations are computationally efficient, with a median computation time of 40 minutes per simulation.

Computational Hemodynamic Modeling of Arterial Aneurysms: A Mini-Review

Arterial aneurysms are pathological dilations of blood vessels, which can be of clinical concern due to thrombosis, dissection, or rupture. Aneurysms can form throughout the arterial system, including intracranial, thoracic, abdominal, visceral, peripheral, or coronary arteries. Currently, aneurysm diameter and expansion rates are the most commonly used metrics to assess rupture risk. Surgical or endovascular interventions are clinical treatment options, but are invasive and associated with risk for the patient. For aneurysms in locations where thrombosis is the primary concern, diameter is also used to determine the level of therapeutic anticoagulation, a treatment that increases the possibility of internal bleeding. Since simple diameter is often insufficient to reliably determine rupture and thrombosis risk, computational hemodynamic simulations are being developed to help assess when an intervention is warranted. Created from subject-specific data, computational models have the potential to be used to predict growth, dissection, rupture, and thrombus-formation risk based on hemodynamic parameters, including wall shear stress, oscillatory shear index, residence time, and anomalous blood flow patterns. Generally, endothelial damage and flow stagnation within aneurysms can lead to coagulation, inflammation, and the release of proteases, which alter extracellular matrix composition, increasing risk of rupture. In this review, we highlight recent work that investigates aneurysm geometry, model parameter assumptions, and other specific considerations that influence computational aneurysm simulations. By highlighting modeling validation and verification approaches, we hope to inspire future computational efforts aimed at improving our understanding of aneurysm pathology and treatment risk stratification.

Hemodynamics of Cerebral Aneurysms: Connecting Medical Imaging and Biomechanical Analysis

In the last two decades, numerous studies have conducted patient-specific computations of blood flow dynamics in cerebral aneurysms and reported correlations between various hemodynamic metrics and aneurysmal disease progression or treatment outcomes. Nevertheless, intra-aneurysmal flow analysis has not been adopted in current clinical practice, and hemodynamic factors usually are not considered in clinical decision making. This review presents the state of the art in cerebral aneurysm imaging and image-based modeling, discussing the advantages and limitations of each approach and focusing on the translational value of hemodynamic analysis. Combining imaging and modeling data obtained from different flow modalities can improve the accuracy and fidelity of resulting velocity fields and flow-derived factors that are thought to affect aneurysmal disease progression. It is expected that predictive models utilizing hemodynamic factors in combination with patient medical history and morphological data will outperform current risk scores and treatment guidelines. Possible future directions include novel approaches enabling data assimilation and multimodality analysis of cerebral aneurysm hemodynamics.

Heterogeneous Computing (CPU–GPU) for Pollution Dispersion in an Urban Environment

The use of Computational Fluid Dynamics (CFD) to assist in air quality studies in urban environments can provide accurate results for the dispersion of pollutants. However, due to the computational resources needed, simulation domain sizes tend to be limited. This study aims to improve the computational efficiency of an emission and dispersion model implemented in a CPU-based solver by migrating it to a CPU–GPU-based one. The migration of the functions that handle boundary conditions and source terms for the pollutants is explained, as well as the main differences present in the solvers used. Once implemented, the model was used to run simulations with both engines on different platforms, enabling the comparison between them and reaching promising time improvements in favor of the use of GPUs.

Morphology and Hemodynamics in Isolated Common Iliac Artery Aneurysms Impacts Proximal Aortic Remodeling

Objective—

Isolated common iliac artery aneurysms (CIAA) are rare. Their prognosis and influence on aortoiliac blood flow and remodeling are unclear. We evaluated the hypotheses that morphology at and distal to the aortic bifurcation, together with the associated hemodynamic changes, influence both the natural history of CIAA and proximal aortic remodeling.

Approach and Results—

Twenty-five isolated CIAAs (15 intact, 10 ruptured), in 23 patients were reconstructed and analyzed with computational fluid dynamics: all showed abnormal flow. Then we studied a series of 24 hypothetical aortoiliac geometries in silico with varying abdominal aortic deflection and aortic bifurcation angles: key findings were assessed in an independent validation cohort of 162 patients. Wall shear stress in isolated unilateral CIAAs was lower than the contralateral common iliac artery, 0.38±0.33 Pa versus 0.61±0.24 Pa, inversely associated with CIAA diameter ( P <0.001) and morphology (high shear stress in variants distal to a sharp kink). Rupture usually occurred in regions of elevated low and oscillatory shear with a wide aortic bifurcation angle. Abdominal aortas deflected towards the CIAA for most unilateral isolated CIAAs (14/21). In silico, wider bifurcation angles created high focal regions of low and oscillatory shear in the common iliac artery. The associations of unilateral CIAA with aortic deflection and common iliac artery diameter with bifurcation angle were confirmed in the validation cohort.

Conclusions—

Decreasing wall shear stress is strongly associated with CIAA progression (larger aneurysms and rupture), whereas abnormal blood flow in the CIAA seems to promote proximal aortic remodeling, with adaptive lateral deflection of the abdominal aorta towards the aneurysmal side.

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.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH)-phase II: rupture risk assessment

PURPOSE

Assessing the rupture probability of intracranial aneurysms (IAs) remains challenging. Therefore, hemodynamic simulations are increasingly applied toward supporting physicians during treatment planning. However, due to several assumptions, the clinical acceptance of these methods remains limited.

METHODS

To provide an overview of state-of-the-art blood flow simulation capabilities, the Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH) was conducted. Seventeen research groups from all over the world performed segmentations and hemodynamic simulations to identify the ruptured aneurysm in a patient harboring five IAs. Although simulation setups revealed good similarity, clear differences exist with respect to the analysis of aneurysm shape and blood flow results. Most groups (12/71%) included morphological and hemodynamic parameters in their analysis, with aspect ratio and wall shear stress as the most popular candidates, respectively.

RESULTS

The majority of groups (7/41%) selected the largest aneurysm as being the ruptured one. Four (24%) of the participating groups were able to correctly select the ruptured aneurysm, while three groups (18%) ranked the ruptured aneurysm as the second most probable. Successful selections were based on the integration of clinically relevant information such as the aneurysm site, as well as advanced rupture probability models considering multiple parameters. Additionally, flow characteristics such as the quantification of inflow jets and the identification of multiple vortices led to correct predictions.

CONCLUSIONS

MATCH compares state-of-the-art image-based blood flow simulation approaches to assess the rupture risk of IAs. Furthermore, this challenge highlights the importance of multivariate analyses by combining clinically relevant metadata with advanced morphological and hemodynamic quantification.

A Hybrid Experimental-Computational Modeling Framework for Cardiovascular Device Testing

Significant advances in biomedical science often leverage powerful computational and experimental modeling platforms. We present a framework named physiology simulation coupled experiment ("PSCOPE") that can capitalize on the strengths of both types of platforms in a single hybrid model. PSCOPE uses an iterative method to couple an in vitro mock circuit to a lumped-parameter numerical simulation of physiology, obtaining closed-loop feedback between the two. We first compared the results of Fontan graft obstruction scenarios modeled using both PSCOPE and an established multiscale computational fluid dynamics method; the normalized root-mean-square error values of important physiologic parameters were between 0.1% and 2.1%, confirming the fidelity of the PSCOPE framework. Next, we demonstrate an example application of PSCOPE to model a scenario beyond the current capabilities of multiscale computational methods-the implantation of a Jarvik 2000 blood pump for cavopulmonary support in the single-ventricle circulation; we found that the commercial Jarvik 2000 controller can be modified to produce a suitable rotor speed for augmenting cardiac output by approximately 20% while maintaining blood pressures within safe ranges. The unified modeling framework enables a testing environment which simultaneously operates a medical device and performs computational simulations of the resulting physiology, providing a tool for physically testing medical devices with simulated physiologic feedback.

Morphological and hemodynamical alterations in brachial artery and cephalic vein. An image-based study for preoperative assessment for vascular access creation

The current study aims to computationally evaluate the effect of right upper arm position on the geometric and hemodynamic characteristics of the brachial artery (BA) and cephalic vein (CV) and, furthermore, to present in detail the methodology to characterise morphological and hemodynamical healthy vessels. Ten healthy volunteers were analysed in two configurations, the supine (S) and the prone (P) position. Lumen 3D surface models were constructed from images acquired from a non-contrast MRI sequence. Then, the models were used to numerically compute the physiological range of geometric (n = 10) and hemodynamic (n = 3) parameters in the BA and CV. Geometric parameters such as curvature and tortuosity, and hemodynamic parameters based on wall shear stress (WSS) metrics were calculated with the use of computational fluid dynamics. Our results highlight that changes in arm position had a greater impact on WSS metrics of the BA by altering the mean and maximum blood flow rate of the vessel. Whereas, curvature and tortuosity were found not to be significantly different between positions. Inter-variability was associated with antegrade and retrograde flow in BA, and antegrade flow in CV. Shear stress was low and oscillatory shear forces were negligible. This data suggests that deviations from this state may contribute to the risk of accelerated intimal hyperplasia of the vein in arteriovenous fistulas. Therefore, preoperative conditions coupled with post-operative longitudinal data will aid the identification of such relationships.

Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge

Purpose

Image-based computational fluid dynamics (CFD) is widely used to predict intracranial aneurysm wall shear stress (WSS), particularly with the goal of improving rupture risk assessment. Nevertheless, concern has been expressed over the variability of predicted WSS and inconsistent associations with rupture. Previous challenges, and studies from individual groups, have focused on individual aspects of the image-based CFD pipeline. The aim of this Challenge was to quantify the total variability of the whole pipeline.

Methods

3D rotational angiography image volumes of five middle cerebral artery aneurysms were provided to participants, who were free to choose their segmentation methods, boundary conditions, and CFD solver and settings. Participants were asked to fill out a questionnaire about their solution strategies and experience with aneurysm CFD, and provide surface distributions of WSS magnitude, from which we objectively derived a variety of hemodynamic parameters.

Results

A total of 28 datasets were submitted, from 26 teams with varying levels of self-assessed experience. Wide variability of segmentations, CFD model extents, and inflow rates resulted in interquartile ranges of sac average WSS up to 56%, which reduced to < 30% after normalizing by parent artery WSS. Sac-maximum WSS and low shear area were more variable, while rank-ordering of cases by low or high shear showed only modest consensus among teams. Experience was not a significant predictor of variability.

Conclusions

Wide variability exists in the prediction of intracranial aneurysm WSS. While segmentation and CFD solver techniques may be difficult to standardize across groups, our findings suggest that some of the variability in image-based CFD could be reduced by establishing guidelines for model extents, inflow rates, and blood properties, and by encouraging the reporting of normalized hemodynamic parameters.

Comparison of intracranial aneurysm flow quantification techniques: standard PIV vs stereoscopic PIV vs tomographic PIV vs phase-contrast MRI vs CFD

Image-based hemodynamic simulations to assess the rupture risk or improve the treatment planning of intracranial aneurysms have become popular recently. However, due to strong modeling assumptions and limitations, the acceptance of numerical approaches remains limited. Therefore, validation using experimental methods is mandatory.

In this study, a unique compilation of four in-vitro flow measurements (three particle image velocimetry approaches using a standard (PIV), stereoscopic (sPIV), and tomographic (tPIV) setup, as well as a phase-contrast magnetic resonance imaging (PC-MRI) measurement) were compared with a computational fluid dynamics (CFD) simulation. This was carried out in a patient-specific silicone phantom model of an internal carotid artery aneurysm under steady flow conditions. To evaluate differences between each technique, a similarity index (SI) with respect to the velocity vectors and the average velocity magnitude differences among all involved modalities were computed.

The qualitative comparison reveals that all techniques are able to provide a reasonable description of the global flow structures. High quantitative agreement in terms of SI and velocity magnitude differences was found between all PIV methods and CFD. However, quantitative differences were observed between PC-MRI and the other techniques. Deeper analysis revealed that the limited resolution of the PC-MRI technique is a major contributor to the experienced differences and leads to a systematic underestimation of overall velocity magnitude levels inside the vessel. This confirms the necessity of using highly resolving flow measurement techniques, such as PIV, in an in-vitro environment to individually verify the validity of the numerically obtained hemodynamic results.

The effect of inlet and outlet boundary conditions in image-based CFD modeling of aortic flow

Background

Computational modeling of cardiovascular flow is a growing and useful field, but such simulations usually require the researcher to guess the flow’s inlet and outlet conditions since they are difficult and expensive to measure. It is critical to determine the amount of uncertainty introduced by these assumptions in order to evaluate the degree to which cardiovascular flow simulations are accurate. Our work begins to address this question by examining the sensitivity of flow to several different assumed velocity inlet and outlet conditions in a patient-specific aorta model.

Methods

We examined the differences between plug flow, parabolic flow, linear shear flows, skewed cubic flow profiles, and Womersley flow at the inlet. Only the shape of the inlet velocity profile was varied—all other parameters were identical among these simulations. Secondary flow in the form of a counter-rotating pair of vortices was also added to parabolic axial flow to study its effect on the solution. In addition, we examined the differences between two-element Windkessel, three element Windkessel and the outflow boundary conditions. In these simulations, only the outlet boundary condition was varied.

Results

The results show axial and in-plane velocities are considerably different close to the inlet for the cases with different inlet velocity profile shapes. However, the solutions are qualitatively similar beyond 1.75D, where D is the inlet diameter. This trend is also observed in other quantities such as pressure and wall shear stress. Normalized root-mean-square deviation, a measure of axial velocity magnitude differences between the different cases, generally decreases along the streamwise coordinate. The linear shear inlet velocity boundary condition and plug velocity boundary condition solution exhibit the highest time-averaged wall shear stress, approximately \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$8\%$$\end{document}8% higher than the parabolic inlet velocity boundary condition. Upstream of 1D from the inlet, adding secondary flow has a significant impact on temporal wall shear stress distributions. This is especially observable during diastole, when integrated wall shear stress magnitude varies about \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$26\%$$\end{document}26% between simulations with and without secondary flow. The results from the outlet boundary condition study show the Windkessel models differ from the outflow boundary condition by as much as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$18\%$$\end{document}18% in terms of time-averaged wall shear stress. Furthermore, normalized root-mean-square deviation of axial velocity magnitude, a measure of deviation between Windkessel and the outflow boundary condition, increases along the streamwise coordinate indicating larger variations near outlets.

Conclusion

It was found that the selection of inlet velocity conditions significantly affects only the flow region close to the inlet of the aorta. Beyond two diameters distal to the inlet, differences in flow solution are small. Although additional studies must be performed to verify this result, the data suggest that it is important to use patient-specific inlet conditions primarily if the researcher is concerned with the details of the flow very close to the inlet. Similarly, the selection of outlet conditions significantly affects the flow in the vicinity of the outlets. Upstream of five diameters proximal to the outlet, deviations between the outlet boundary conditions examined are insignificant. Although the inlet and outlet conditions only affect the flow significantly in their respective neighborhoods, our study indicates that outlet conditions influence a larger percentage of the solution domain.

Hemodynamics in a giant intracranial aneurysm characterized by in vitro 4D flow MRI

Experimental and computational data suggest that hemodynamics play a critical role in the development, growth, and rupture of cerebral aneurysms. The flow structure, especially in aneurysms with a large sac, is highly complex and three-dimensional. Therefore, volumetric and time-resolved measurements of the flow properties are crucial to fully characterize the hemodynamics. In this study, phase-contrast Magnetic Resonance Imaging is used to assess the fluid dynamics inside a 3D-printed replica of a giant intracranial aneurysm, whose hemodynamics was previously simulated by multiple research groups. The physiological inflow waveform is imposed in a flow circuit with realistic cardiovascular impedance. Measurements are acquired with sub-millimeter spatial resolution for 16 time steps over a cardiac cycle, allowing for the detailed reconstruction of the flow evolution. Moreover, the three-dimensional and time-resolved pressure distribution is calculated from the velocity field by integrating the fluid dynamics equations, and is validated against differential pressure measurements using precision transducers. The flow structure is characterized by vortical motions that persist within the aneurysm sac for most of the cardiac cycle. All the main flow statistics including velocity, vorticity, pressure, and wall shear stress suggest that the flow pattern is dictated by the aneurysm morphology and is largely independent of the pulsatility of the inflow, at least for the flow regimes investigated here. Comparisons are carried out with previous computational simulations that used the same geometry and inflow conditions, both in terms of cycle-averaged and systolic quantities.

Initial Clinical Experience with AView-A Clinical Computational Platform for Intracranial Aneurysm Morphology, Hemodynamics, and Treatment Management

BACKGROUND

The management of intracranial aneurysm (IA) is challenging. Clinicians often rely on varied and intuitively disparate ways of evaluating rupture risk that may only partially take into account complex hemodynamic and morphologic factors. We developed a prototype of a clinically oriented, streamlined, computational platform, AView, for rapid assessment of hemodynamics and morphometrics in clinical settings. To show the potential clinical utility of AView, we report our initial multicenter experience highlighting the possible advantages of morphologic and hemodynamic analysis of IAs.

METHODS

AView software was deployed across 8 medical centers (6 in the United States, 2 in Japan). Eight clinicians were trained and used the AView software between September 2012 and January 2013.

RESULTS

We present 12 illustrative cases that show the potential clinical utility of AView. For all, morphology and hemodynamics, flow visualization, and rupture resemblance score (a surrogate for rupture risk) were provided. In 3 cases, AView could confirm the clinicians' decision to treat; in 3 cases, it could suggest which aneurysms may be at greater risk among multiple aneurysms; in 5 cases, AView could provide additional information for use during treatment decisions for ambiguous situations. In one stent-assisted coiling case, flow visualization predicted that the intuitive choice for stent placement could have resulted in sacrifice of an anterior cerebral artery due to blockage by coils and led clinicians to reconsider treatment plans.

CONCLUSIONS

AView has the potential to confirm decisions to treat IAs, suggest which among multiple aneurysms to treat, and guide treatment decisions. Furthermore, the flow visualization it affords can inform aneurysm treatment planning and potentially avoid poor outcomes.

Effect of different stent configurations using Lattice Boltzmann method and particles image velocimetry on artery bifurcation aneurysm problem

Proper design of stent for application at specific aneurysm effect arteries could help to reduce the issues with thrombosis and aneurysm. In this paper, four types of stent configuration namely half-Y (6 mm), half-Y (4 mm), cross-bar, and full-Y configuration will implanted on real 3D artery bifurcation aneurysm effected arteries. Comparisons were then conducted based on the flow patterns after stent placement using both LBM-based solver and PIV experimental findings. According to the data obtained from all 4 stent designs, the flow profiles and the computed velocity from both methods were in agreement with each other. Both methods found that half-Y (6 mm) stent configuration is by far the best configuration in reducing the blood velocity at the vicinity of the aneurysm sac. The analysis also show that the half-Y (6 mm) stent configuration recorded the highest percentage of velocity reduction and managed to substantially reduce the pressure at the bifurcation region. This high flow velocity reduction through the use of half-Y stent could consequently promote the formation of thrombus thereby reducing the risk of rupture in the aneurysm sac.

Cerebral Aneurysm Size and Distal Intracranial Hemodynamics: An Assessment of Flow and Pulsatility Index Using Quantitative Magnetic Resonance Angiography

BACKGROUND

The relationship between cerebral aneurysm size and risk of rupture is well documented, but the impact of aneurysms on distal intracranial hemodynamics is unknown.

OBJECTIVE

To examine the relationship between aneurysm size and distal intracranial hemodynamics prior to treatment.

METHODS

Patients seen at our institution between 2006 and 2015 with cerebral aneurysms within the internal carotid artery (ICA) segments (proximal to ICA terminus) were retrospectively reviewed. Patients were included if the aneurysm was unruptured, and were excluded if a contralateral aneurysm was present. Flows within bilateral ICAs and middle cerebral arteries (MCA) were measured prior to any treatment using quantitative magnetic resonance angiography. Pulsatility index (PI = [systolic − diastolic flow velocity]/mean flow velocity) within each vessel was then calculated. Hemodynamic parameters were analyzed with respect to aneurysm size.

RESULTS

Forty-two patients were included. Mean aneurysm size was 13.5 mm (range 2-40 mm). There was a significant correlation between aneurysm size and ipsilateral MCA PI (P = .006; r = 0.441), MCAipsilateral/ICAipsilateral PI ratio (P = .003; r = 0.57), and MCAipsilateral/MCAcontralateral PI ratio (P = .008; r = 0.43). Mean PI in the ipsilateral ICA was 0.38 (range 0.17-0.77) and ipsilateral MCA was 0.31 (range 0.08-0.83), and mean PI in contralateral ICA was 0.35 (range 0.19-0.57) and MCA was 0.30 (range 0.07-0.89).

CONCLUSION

Larger aneurysm size correlates with higher ipsilateral MCA PI, demonstrating that aneurysms affect distal intracranial hemodynamics.

Aneurysm size and the Windkessel effect: An analysis of contrast intensity in digital subtraction angiography

Large cerebral aneurysms are considered more dangerous than their smaller counterparts, with higher risk of subarachnoid hemorrhage. Understanding the hemodynamics of large aneurysms has potential to predict their response to treatment. Digital subtraction angiography images for patients with intracranial aneurysms over a seven-year period were reviewed. Unruptured solitary aneurysms of the internal carotid artery (ICA) proximal to the terminus and posterior communicating artery were included. Contrast intensity over time was analyzed at the center of the M1 segment of the middle cerebral artery distal to the aneurysm and compared to the contralateral side. Analysis included time to peak (TP)10%-100% (time needed for contrast to change from 10% intensity to 100%), washout time (WT)100%-10% (time for 100% intensity to 10%), and quartile time (QT)25%-25% (time for 25% intensity during vessel filling to 25% during emptying). Fifty patients met the inclusion criteria. Analysis over the ipsilateral M1 segment revealed a significant increase in QT25%-25% (8.5 vs 7.6 seconds, p = 0.006) compared to the contralateral side. There was a correlation between TP10%-100% and QT25%-25% with aneurysm size (Pearson's r = 0.37, p = 0.007 and r = 0.43, p = 0.001, respectively). Larger ICA aneurysms were associated with delayed contrast intensity times . A plausible mechanism is that large aneurysms act as a capacitance chamber (Windkessel effect) that slow the arrival of contrast distal to the aneurysm. This may be of significance for large aneurysms after treatment, where the loss of the Windkessel effect places the distal circulation at greater risk for hemorrhage, and warrants further study.

Non-Newtonian versus numerical rheology: Practical impact of shear-thinning on the prediction of stable and unstable flows in intracranial aneurysms

Computational fluid dynamics (CFD) shows promise for informing treatment planning and rupture risk assessment for intracranial aneurysms. Much attention has been paid to the impact on predicted hemodynamics of various modelling assumptions and uncertainties, including the need for modelling the non-Newtonian, shear-thinning rheology of blood, with equivocal results. Our study clarifies this issue by contextualizing the impact of rheology model against the recently demonstrated impact of CFD solution strategy on the prediction of aneurysm flow instabilities. Three aneurysm cases were considered, spanning a range of stable to unstable flows. Simulations were performed using a high-resolution/accuracy solution strategy with Newtonian and modified-Cross rheology models and compared against results from a so-called normal-resolution strategy. Time-averaged and instantaneous wall shear stress (WSS) distributions, as well as frequency content of flow instabilities and dome-averaged WSS metrics, were minimally affected by the rheology model, whereas numerical solution strategy had a demonstrably more marked impact when the rheology model was fixed. We show that point-wise normalization of non-Newtonian by Newtonian WSS values tended to artificially amplify small differences in WSS of questionable physiological relevance in already-low WSS regions, which might help to explain the disparity of opinions in the aneurysm CFD literature regarding the impact of non-Newtonian rheology. Toward the goal of more patient-specific aneurysm CFD, we conclude that attention seems better spent on solution strategy and other likely "first-order" effects (eg, lumen segmentation and choice of flow rates), as opposed to "second-order" effects such as rheology.

Robustness of common hemodynamic indicators with respect to numerical resolution in 38 middle cerebral artery aneurysms

Background

Using computational fluid dynamics (CFD) to compute the hemodynamics in cerebral aneurysms has received much attention in the last decade. The usability of these methods depends on the quality of the computations, highlighted in recent discussions. The purpose of this study is to investigate the convergence of common hemodynamic indicators with respect to numerical resolution.

Methods

38 middle cerebral artery bifurcation aneurysms were studied at two different resolutions (one comparable to most studies, and one finer). Relevant hemodynamic indicators were collected from two of the most cited studies, and were compared at the two refinements. In addition, correlation to rupture was investigated.

Results

Most of the hemodynamic indicators were very well resolved at the coarser resolutions, correlating with the finest resolution with a correlation coefficient >0.95. The oscillatory shear index (OSI) had the lowest correlation coefficient of 0.83. A logarithmic Bland-Altman plot revealed noticeable variations in the proportion of the aneurysm under low shear, as well as in spatial and temporal gradients not captured by the correlation alone.

Conclusion

Statistically, hemodynamic indicators agree well across the different resolutions studied here. However, there are clear outliers visible in several of the hemodynamic indicators, which suggests that special care should be taken when considering individual assessment.

Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations

A "credible" computational fluid dynamics (CFD) model has the potential to provide a meaningful evaluation of safety in medical devices. One major challenge in establishing "model credibility" is to determine the required degree of similarity between the model and experimental results for the model to be considered sufficiently validated. This study proposes a "threshold-based" validation approach that provides a well-defined acceptance criteria, which is a function of how close the simulation and experimental results are to the safety threshold, for establishing the model validity. The validation criteria developed following the threshold approach is not only a function of Comparison Error, E (which is the difference between experiments and simulations) but also takes in to account the risk to patient safety because of E. The method is applicable for scenarios in which a safety threshold can be clearly defined (e.g., the viscous shear-stress threshold for hemolysis in blood contacting devices). The applicability of the new validation approach was tested on the FDA nozzle geometry. The context of use (COU) was to evaluate if the instantaneous viscous shear stress in the nozzle geometry at Reynolds numbers (Re) of 3500 and 6500 was below the commonly accepted threshold for hemolysis. The CFD results ("S") of velocity and viscous shear stress were compared with inter-laboratory experimental measurements ("D"). The uncertainties in the CFD and experimental results due to input parameter uncertainties were quantified following the ASME V&V 20 standard. The CFD models for both Re = 3500 and 6500 could not be sufficiently validated by performing a direct comparison between CFD and experimental results using the Student's t-test. However, following the threshold-based approach, a Student's t-test comparing |S-D| and |Threshold-S| showed that relative to the threshold, the CFD and experimental datasets for Re = 3500 were statistically similar and the model could be considered sufficiently validated for the COU. However, for Re = 6500, at certain locations where the shear stress is close the hemolysis threshold, the CFD model could not be considered sufficiently validated for the COU. Our analysis showed that the model could be sufficiently validated either by reducing the uncertainties in experiments, simulations, and the threshold or by increasing the sample size for the experiments and simulations. The threshold approach can be applied to all types of computational models and provides an objective way of determining model credibility and for evaluating medical devices.

Virtual endovascular treatment of intracranial aneurysms: models and uncertainty

Virtual endovascular treatment models (VETMs) have been developed with the view to aid interventional neuroradiologists and neurosurgeons to pre-operatively analyze the comparative efficacy and safety of endovascular treatments for intracranial aneurysms. Based on the current state of VETMs in aneurysm rupture risk stratification and in patient-specific prediction of treatment outcomes, we argue there is a need to go beyond personalized biomechanical flow modeling assuming deterministic parameters and error-free measurements. The mechanobiological effects associated with blood clot formation are important factors in therapeutic decision making and models of post-treatment intra-aneurysmal biology and biochemistry should be linked to the purely hemodynamic models to improve the predictive power of current VETMs. The influence of model and parameter uncertainties associated to each component of a VETM is, where feasible, quantified via a random-effects meta-analysis of the literature. This allows estimating the pooled effect size of these uncertainties on aneurysmal wall shear stress. From such meta-analyses, two main sources of uncertainty emerge where research efforts have so far been limited: (1) vascular wall distensibility, and (2) intra/intersubject systemic flow variations. In the future, we suggest that current deterministic computational simulations need to be extended with strategies for uncertainty mitigation, uncertainty exploration, and sensitivity reduction techniques. WIREs Syst Biol Med 2017, 9:e1385. doi: 10.1002/wsbm.1385 For further resources related to this article, please visit the WIREs website.