Counterpoint: realizing the clinical utility of computational fluid dynamics--closing the gap

Using DFT on ultrasound measurements to determine patient-specific blood flow boundary conditions for computational hemodynamics of intracranial aneurysms

Boundary conditions (BCs) is one pivotal factor influencing the accuracy of hemodynamic predictions on intracranial aneurysms (IAs) using computational fluid dynamics (CFD) modeling. Unfortunately, a standard procedure to secure accurate BCs for hemodynamic modeling does not exist. To bridge such a knowledge gap, two representative patient-specific IA models (Case-I and Case-II) were reconstructed and their blood flow velocity waveforms in the internal carotid artery (ICA) were measured by ultrasonic techniques and modeled by discrete Fourier transform (DFT). Then, numerical investigations were conducted to explore the appropriate number of samples (N) for DFT modeling to secure the accurate BC by comparing a series of hemodynamic parameters using in-vitro validated CFD modeling. Subsequently, a comprehensive comparison in hemodynamic characteristics under patient-specific BCs and a generalized BC based on a one-dimensional (1D) model was conducted to reinforce the understanding that a patient-specific BC is pivotal for accurate hemodynamic risk evaluations on IA pathophysiology. In addition, the influence of the variance of heart rate/cardiac pulsatile period on hemodynamic characteristics in IA models was studied preliminarily. The results showed that N ≥ 16 for DFT model is a decent choice to secure the proper BC profile to calculate time-averaged hemodynamic parameters, while more data points such as N ≥ 36 can ensure the accuracy of instantaneous hemodynamic predictions. In addition, results revealed the generalized BC could overestimate or underestimate the hemodynamic risks on IAs significantly; thus, patient-specific BCs are highly recommended for hemodynamic modeling for IA risk evaluation. Furthermore, this study discovered the variance of heart rate has rare influences on hemodynamic characteristics in both instantaneous and time-averaged parameters under the assumption of an identical blood flow rate.

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.

Reinforcement learning for patient-specific optimal stenting of intracranial aneurysms

Developing new capabilities to predict the risk of intracranial aneurysm rupture and to improve treatment outcomes in the follow-up of endovascular repair is of tremendous medical and societal interest, both to support decision-making and assessment of treatment options by medical doctors, and to improve the life quality and expectancy of patients. This study aims at identifying and characterizing novel flow-deviator stent devices through a high-fidelity computational framework that combines state-of-the-art numerical methods to accurately describe the mechanical exchanges between the blood flow, the aneurysm, and the flow-deviator and deep reinforcement learning algorithms to identify a new stent concepts enabling patient-specific treatment via accurate adjustment of the functional parameters in the implanted state.

Near-wall hemodynamic parameters quantification in in vitro intracranial aneurysms with 7 T PC-MRI

OBJECTIVE

Wall shear stress (WSS) and its derived spatiotemporal parameters have proven to play a major role on intracranial aneurysms (IAs) growth and rupture. This study aims to demonstrate how ultra-high field (UHF) 7 T phase contrast magnetic resonance imaging (PC-MRI) coupled with advanced image acceleration techniques allows a highly resolved visualization of near-wall hemodynamic parameters patterns in in vitro IAs, paving the way for more robust risk assessment of their growth and rupture.

MATERIALS AND METHODS

We performed pulsatile flow measurements inside three in vitro models of patient-specific IAs using 7 T PC-MRI. To this end, we built an MRI-compatible test bench, which faithfully reproduced a typical physiological intracranial flow rate in the models.

RESULTS

The ultra-high field 7 T images revealed WSS patterns with high spatiotemporal resolution. Interestingly, the high oscillatory shear index values were found in the core of low WSS vortical structures and in flow stream intersecting regions. In contrast, maxima of WSS occurred around the impinging jet sites.

CONCLUSIONS

We showed that the elevated signal-to-noise ratio arising from 7 T PC-MRI enabled to resolve high and low WSS patterns with a high degree of detail.

Rupture risk prediction of cerebral aneurysms using a novel convolutional neural network-based deep learning model

BACKGROUND

Cerebral aneurysms should be treated before rupture because ruptured aneurysms result in serious disability. Therefore, accurate prediction of rupture risk is important and has been estimated using various hemodynamic factors.

OBJECTIVE

To suggest a new way to predict rupture risk in cerebral aneurysms using a novel deep learning model based on hemodynamic parameters for better decision-making about treatment.

METHODS

A novel convolutional neural network (CNN) model was used for rupture risk prediction retrospectively of 123 aneurysm cases. To include the effect of hemodynamic parameters into the CNN, the hemodynamic parameters were first calculated using computational fluid dynamics and fluid-structure interaction. Then, they were converted into images for training the CNN using a novel approach. In addition, new data augmentation methods were devised to obtain sufficient training data. A total of 53,136 images generated by data augmentation were used to train and test the CNN.

RESULTS

The CNNs trained with wall shear stress (WSS), strain, and combination images had area under the receiver operating characteristics curve values of 0.716, 0.741, and 0.883, respectively. Based on the cut-off values, the CNN trained with WSS (sensitivity: 0.5, specificity: 0.79) or strain (sensitivity: 0.74, specificity: 0.71) images alone was not highly predictive. However, the CNN trained with combination images of WSS and strain showed a sensitivity and specificity of 0.81 and 0.82, respectively.

CONCLUSION

CNN-based deep learning algorithm using hemodynamic factors, including WSS and strain, could be an effective tool for predicting rupture risk in cerebral aneurysms with good predictive accuracy.

Numerical simulation flow dynamics of an intracranial aneurysm

BACKGROUND

Computational fluid dynamics provides a new method for the study of the blood flow characteristics of the formation and development of intracranial aneurysms.

OBJECTIVE

To compare blood flow characteristics between the healthy internal carotid artery and normal intracranial aneurysms.

METHODS

The internal carotid arteries were simulated to obtain hemodynamic parameters in one patient.

RESULTS

The internal carotid artery associated with aneurysm presents low wall shear stress, high oscillatory shear index, and high particle retention time compared with the normal internal carotid artery.

CONCLUSIONS

There are differences in blood flow between the normal internal carotid artery and intracranial aneurysm. The vortex of the aneurysm will produce turbulence, indicating that it is unstable, which results in the growth and rupture of the aneurysm.

Wall shear stress gradient is independently associated with middle cerebral artery aneurysm development: a case-control CFD patient-specific study based on 77 patients

Background

Previously published computational fluid dynamics (CFD) studies regarding intracranial aneurysm (IA) formation present conflicting results. Our study analysed the involvement of the combination of high wall shear stress (WSS) and a positive WSS gradient (WSSG) in IA formation.

Methods

We designed a case-control study with a selection of 38 patients with an unruptured middle cerebral artery (MCA) aneurysm and 39 non-aneurysmal controls to determine the involvement of WSS, oscillatory shear index (OSI), the WSSG and its absolute value (absWSSG) in aneurysm formation based on patient-specific CFD simulations using velocity profiles obtained from transcranial colour-coded sonography.

Results

Among the analysed parameters, only the WSSG had significantly higher values compared to the controls (11.05 vs − 14.76 [Pa/mm], P = 0.020). The WSS, absWSSG and OSI values were not significantly different between the analysed groups. Logistic regression analysis identified WSS and WSSG as significant co-predictors for MCA aneurysm formation, but only the WSSG turned out to be a significant independent prognosticator (OR: 1.009; 95% CI: 1.001–1.017; P = 0.025). Significantly more patients (23/38) in the case group had haemodynamic regions of high WSS combined with a positive WSSG near the bifurcation apex, while in the control group, high WSS was usually accompanied by a negative WSSG (14/39). From the analysis of the ROC curve for WSSG, the area under the curve (AUC) was 0.654, with the optimal cut-off value −0.37 Pa/mm. The largest AUC was recognised for combined WSS and WSSG (AUC = 0.671). Our data confirmed that aneurysms tend to form near the bifurcation apices in regions of high WSS values accompanied by positive WSSG.

Conclusions

The development of IAs is determined by an independent effect of haemodynamic factors. High WSS impacts MCA aneurysm formation, while a positive WSSG mainly promotes this process.

SDF-1α/CXCR4 Pathway Mediates Hemodynamics-Induced Formation of Intracranial Aneurysm by Modulating the Phenotypic Transformation of Vascular Smooth Muscle Cells

The objective of this study is to explore the role of the SDF-1α/CXCR4 pathway in the development of intracranial aneurysm (IA) induced by hemodynamic forces. We collected 12 IA and six superficial temporal artery samples for high-throughput sequencing, hematoxylin and eosin staining, and immunohistochemistry to examine vascular remodeling and determine the expression of the components of the SDF-1α/CXCR4 pathway, structural proteins (α-SMA and calponin) of vascular smooth muscle cells (VSMCs), and inflammatory factors (MMP-2 and TNF-α). Computational fluid dynamics (CFD) was used for hemodynamic analysis. Mouse IA model and dynamic co-culture model were established to explore the mechanism through which the SDF-1α/CXCR4 pathway regulates the phenotypic transformation of VSMCs in vivo and in vitro. We detected a significant elevation of SDF-1α and CXCR4 in IA, which was accompanied by vascular remodeling in the aneurysm wall (i.e., the upregulation of inflammatory factors, MMP-2 and TNF-α, and the downregulation of contractile markers, α-SMA and calponin). In addition, hemodynamic analysis revealed that compared with unruptured aneurysms, ruptured aneurysms were associated with lower wall shear stress and higher MMP-2 expression. In vivo and in vitro experiments showed that abnormal hemodynamics could activate the SDF-1α/CXCR4, P38, and JNK signaling pathways to induce the phenotypic transformation of VSMCs, leading to IA formation. Hemodynamics can induce the phenotypic transformation of VSMCs and cause IA by activating the SDF-1α/CXCR4 signaling pathway.

A Simple Flow Classification Parameter Can Discriminate Rupture Status in Intracranial Aneurysms

BACKGROUND

A simple dimensionless aneurysm number ($An$), which depends on geometry and flow pulsatility, was previously shown to distinguish the flow mode in intracranial aneurysms (IA): vortex mode with a dynamic vortex formation/evolution if $An > 1$, and cavity mode with a steady shear layer if $An < 1$.

OBJECTIVE

To hypothesize that $An\ > \ 1$ can distinguish rupture status because vortex mode is associated with high oscillatory shear index, which, in turn, is statistically associated with rupture.

METHODS

The above hypothesis is tested on a retrospective, consecutively collected database of 204 patient-specific IAs. The first 119 cases are assigned to training and the remainder to testing dataset. $An$ is calculated based on the pulsatility index (PI) approximated either from the literature or solving an optimization problem (denoted as$\ \widehat {PI}$). Student's t-test and logistic regression (LR) are used for hypothesis testing and data fitting, respectively.

RESULTS

$An$ can significantly discriminate ruptured and unruptured status with 95% confidence level (P < .0001). $An$ (using PI) and $\widehat {An}$ (using $\widehat {PI}$) significantly predict the ruptured IAs (for training dataset $An\!:\ $AUC = 0.85, $\widehat {An}\!:\ $AUC = 0.90, and for testing dataset $An\!:\ $sensitivity = 94%, specificity = 33%, $\widehat {An}\!:\ $sensitivity = 93.1%, specificity = 52.85%).

CONCLUSION

$An > 1$ predicts ruptured status. Unlike traditional hemodynamic parameters such as wall shear stress and oscillatory shear index, $An$ has a physical threshold of one (does not depend on statistical analysis) and does not require time-consuming flow simulations. Therefore, $An$ is a simple, practical discriminator of IA rupture status.

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.

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.

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.

Size-Dependent Distribution of Patient-Specific Hemodynamic Factors in Unruptured Cerebral Aneurysms Using Computational Fluid Dynamics

PURPOSE

To analyze size-dependent hemodynamic factors [velocity, shear rate, blood viscosity, wall shear stress (WSS)] in unruptured cerebral aneurysms using computational fluid dynamics (CFD) based on the measured non-Newtonian model of viscosity.

METHODS

Twenty-one patients with unruptured aneurysms formed the study cohort. Patient-specific geometric models were reconstructed for CFD analyses. Aneurysms were divided into small and large groups based on a cutoff size of 5 mm. For comparison between small and large aneurysms, 5 morphologic variables were measured. Patient-specific non-Newtonian blood viscosity was applied for more detailed CFD simulation. Quantitative and qualitative analyses of velocity, shear rate, blood viscosity, and WSS were conducted to compare small and large aneurysms.

RESULTS

Complex flow patterns were found in large aneurysms. Large aneurysms had a significantly lower shear rate (235 ± 341 s^-1)) than small aneurysms (915 ± 432 s^-1) at peak-systole. Two times higher blood viscosity was observed in large aneurysms compared with small aneurysms. Lower WSS was found in large aneurysms (1.38 ± 1.36 Pa) than in small aneurysms (3.53 ± 1.22 Pa). All the differences in hemodynamic factors between small and large aneurysms were statistically significant.

CONCLUSIONS

Large aneurysms tended to have complex flow patterns, low shear rate, high blood viscosity, and low WSS. The hemodynamic factors that we analyzed might be useful for decision making before surgical treatment of aneurysms.

Mechanism of Action and Biology of Flow Diverters in the Treatment of Intracranial Aneurysms

Flow diverters have drastically changed the landscape of intracranial aneurysm treatment and are now considered first-line therapy for select lesions. Their mechanism of action relies on intrinsic alteration in hemodynamic parameters, both at the parent artery and within the aneurysm sac. Moreover, the device struts act as a nidus for endothelial cell growth across the aneurysm neck ultimately leading to aneurysm exclusion from the circulation. In silico computational analyses and investigations in preclinical animal models have provided valuable insights into the underlying biological basis for flow diverter therapy. Here, we review the present understanding pertaining to flow diverter biology and mechanisms of action, focusing on stent design, induction of intra-aneurysmal thrombosis, endothelialization, and alterations in hemodynamics.

Intercorrelations of morphology with hemodynamics in intracranial aneurysms in computational fluid dynamics

Objective:

To measure morphological indices and wall shear stress (WSS) of aneurysms and parent artery surface in order to explore the relationship of morphological characteristics and WSS.

Methods:

Data from 47 events of consecutive cerebral saccular aneurysms from 39 patients which were referred to the interventional Neuroradiology service of the Shaoxing People’s Hospital, Shaoxing, China between 2014 April and 2015 August. Wall shear stress and wall pressure (WP) of the pre-aneurysm, aneurysm and near vessel (<1.0 cm) surface were obtained. Correlation analysis was carried between morphological parameters and WSS and its ratio. WSS, WP, intra-aneurysmal flow pattern, and location of aneurysms were analyzed.

Results:

Impaction zone from inflow jet was located in the distal neck part of aneurysm with high WSS in 36 aneurysms (76.6%). There were significant differences in WSS between pre-aneurysm surface and near vessel (p<0.001), aneurysm (p<0.001), aneurysm and near vessel (p<0.001). Significant correlations were found between aneurysm WSS and aspect ratio (r=-0.296), aneurysm-artery WSS ratio and size ratio (r=-0.322), aspect ratio (r=-0.416).

Conclusion:

Uneven WSS distributes in the various part of the pre-aneurysm vessel. The impaction zone from inflow jet is located in the distal neck of aneurysm. Aspect and size ratios can effect aneurysm WSS

Impact of predictive medicine on therapeutic decision making: a randomized controlled trial in congenital heart disease

Computational modelling has made significant progress towards clinical application in recent years. In addition to providing detailed diagnostic data, these methods have the potential to simulate patient-specific interventions and to predict their outcome. Our objective was to evaluate to which extent patient-specific modelling influences treatment decisions in coarctation of the aorta (CoA), a common congenital heart disease. We selected three cases with CoA, two of which had borderline indications for intervention according to current clinical guidelines. The third case was not indicated for intervention according to guidelines. For each case, we generated two separate datasets. First dataset included conventional diagnostic parameters (echocardiography and magnetic resonance imaging). In the second, we added modelled parameters (pressure fields). For the two cases with borderline indications for intervention, the second dataset also included pressure fields after virtual stenting simulations. All parameters were computed by modelling methods that were previously validated. In an online-administered, invitation-only survey, we randomized 178 paediatric cardiologists to view either conventional (control) or add-on modelling (experimental) datasets. Primary endpoint was the proportion of participants recommending different therapeutic options: (1) surgery or catheter lab (collectively, "intervention") or (2) no intervention (follow-up with or without medication). Availability of data from computational predictive modelling influenced therapeutic decision making in two of three cases. There was a statistically significant association between group assignment and the recommendation of an intervention for one borderline case and one non-borderline case: 94.3% vs. 72.2% (RR: 1.31, 95% CI: 1.14-1.50, p = 0.00) and 18.8% vs. 5.1% (RR: 3.09, 95% CI: 1.17-8.18, p = 0.01) of participants in the experimental and control groups respectively recommended an intervention. For the remaining case, there was no difference between the experimental and control group and the majority of participants recommended intervention. In sub-group analyses, findings were not affected by the experience level of participating cardiologists. Despite existing clinical guidelines, the therapy recommendations of the participating physicians were heterogeneous. Validated patient-specific computational modelling has the potential to influence treatment decisions. Future studies in broader areas are needed to evaluate whether differences in decisions result in improved outcomes (Trial Registration: NCT02700737).

Identification of Hostile Hemodynamics and Geometries of Cerebral Aneurysms: A Case-Control Study

BACKGROUND AND PURPOSE

Hostile hemodynamic conditions and geometries are thought to predispose aneurysms for instability and rupture. This study compares stable, unstable, and ruptured aneurysms while controlling for location and patient characteristics.

MATERIALS AND METHODS

The hemodynamics and geometries of 165 stable, 65 unstable, and 554 ruptured aneurysms were compared. Hemodynamics was modeled using image-based computational fluid dynamics. Case-control pairs were selected matching aneurysm location, patient age, and sex. Paired Wilcoxon tests were used to compare hemodynamic and geometric variables among different aneurysm groups. The pairing was repeated 100 times, and the combined P values were calculated and adjusted for multiple testing.

RESULTS

Ruptured aneurysms had lower minimum wall shear stress (P = .03), higher maximum wall shear stress (P = .03), more concentrated (P = .03) and mean oscillatory shear stress (P = .03), higher maximum velocity (P = .03), and more complex flows (vortex core-line length, P = .03) than stable aneurysms. Similarly, unstable aneurysms had more concentrated shear stress (P = .04) and more complex flows (vortex core-line length, P = .04) than stable aneurysms. Compared with stable aneurysms, ruptured aneurysms were larger (size ratio, aneurysm size/vessel size, P = .03), more elongated (aspect ratio, P = .03), and irregular (nonsphericity index, P = .03). Similarly, unstable aneurysms were larger (size ratio, P = .04), more elongated (aspect ratio, P = .04), and irregular (bulge location, P = .04; area-weighted Gaussian curvature; P = .04) than stable aneurysms. No significant differences were found between unstable and ruptured aneurysms.

CONCLUSIONS

Unstable and ruptured aneurysms have more complex flows with concentrated wall shear stress and are larger, more elongated, and irregular than stable aneurysms, independent of aneurysm location and patient sex and age.

A comparison of 4D flow MRI-derived wall shear stress with computational fluid dynamics methods for intracranial aneurysms and carotid bifurcations - A review

BACKGROUND

4D flow MRI is a relatively quick method for obtaining wall shear stress (WSS) in vivo, a hemodynamic parameter which has shown promise in risk stratification for rupture of cerebrovascular diseases such as intracranial aneurysms and atherosclerotic plaques. The accuracy of such measurements is still largely unknown.

OBJECTIVE

To quantify the accuracy of 4D flow MRI-derived wall shear stress values for intracranial aneurysms and carotid bifurcations.

METHOD

We performed a review of all original research articles which compared the magnitudes of WSS derived from 4D flow MRI with corresponding values derived from computational fluid dynamics (CFD) within both intracranial aneurysms and carotid bifurcations.

RESULT

For intracranial aneurysms and carotid bifurcations, 4D flow MRI-derived WSS estimations are generally lower in magnitude compared to WSS derived by CFD methods. These differences are more pronounced in regions of higher WSS. However, the relative distributions of WSS derived from both methods are reasonably similar.

CONCLUSION

Pooled analysis suggests that WSS magnitudes obtained by 4D flow MRI are underestimated, while the relative distribution is reasonably accurate, the latter being an important factor for determining the natural history of intracranial aneurysms and other cerebrovascular diseases. 4D flow MRI shows enormous potential in providing new risk stratification parameters which could have significant impact on individualized treatment decisions and improved patient outcomes.

Multiple intracranial aneurysms: a direct hemodynamic comparison between ruptured and unruptured vessel malformations

PURPOSE

Despite numerous studies addressing the rupture risk of intracranial aneurysms that have been published, the assessment thereof still remains challenging. Image-based simulations enable a precise prediction of patient-specific blood flow information. However, those approaches normally consider only small segments of the complete cerebral vasculature.

METHODS

To test the validity of the consideration of single aneurysms in one computational setup, domains of the complete anterior and posterior circulations with multiple intracranial aneurysms (MIA) were simulated. Six patients with MIA were investigated, while 3D surfaces of eleven unruptured and six ruptured aneurysms were segmented. The segmentations were used for the determination of morphological parameters and also for image-based blood flow simulations used to characterize the hemodynamic properties of each aneurysm.

RESULTS

In the geometric comparison, neck aspect ratios of unruptured and ruptured aneurysms did not differ significantly. In contrast, size ratios, aspect ratios, surface areas, volumes, and non-sphericity indices were significantly higher in the ruptured cases. The analysis of hemodynamic parameters demonstrated that in each patient, the ruptured aneurysm exhibited the lowest averaged wall shear stresses and highest oscillatory shears. Unstable flow was also detected in ruptured aneurysms based on increased oscillatory velocity.

CONCLUSION

In this small study involving patients with MIA, different morphologies and flow patterns were observed between ruptured and unruptured aneurysms. The analysis of the hemodynamics in such patients revealed a good agreement with studies that only considered single malformations. Additionally, complex flow patterns are detected in ruptured cases, which require deeper investigation.

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.

Association between hemodynamics, morphology, and rupture risk of intracranial aneurysms: a computational fluid modeling study

The objective of the study was to examine the correlations between intracranial aneurysm morphology and wall shear stress (WSS) to identify reliable predictors of rupture risk. Seventy-two intracranial aneurysms (41 ruptured and 31 unruptured) from 63 patients were studied retrospectively. All aneurysms were divided into two categories: narrow (aspect ratio ≥1.4) and wide-necked (aspect ratio <1.4 or neck width ≥4 mm). Computational fluid dynamics was used to determine the distribution of WSS, which was analyzed between different morphological groups and between ruptured and unruptured aneurysms. Sections of the walls of clipped aneurysms were stained with hematoxylin–eosin, observed under a microscope, and photographed. Ruptured aneurysms were statistically more likely to have a greater low WSS area ratio (LSAR) (P = 0.001) and higher aneurysms parent WSS ratio (P = 0.026) than unruptured aneurysms. Narrow-necked aneurysms were statistically more likely to have a larger LSAR (P < 0.001) and lower values of MWSS (P < 0.001), mean aneurysm-parent WSS ratio (P < 0.001), HWSS (P = 0.012), and the highest aneurysm-parent WSS ratio (P < 0.001) than wide-necked aneurysms. The aneurysm wall showed two different pathological changes associated with high or low WSS in wide-necked aneurysms. Aneurysm morphology could affect the distribution and magnitude of WSS on the basis of differences in blood flow. Both high and low WSS could contribute to focal wall damage and rupture through different mechanisms associated with each morphological type.

Flow Conditions in the Intracranial Aneurysm Lumen Are Associated with Inflammation and Degenerative Changes of the Aneurysm Wall

BACKGROUND AND PURPOSE

Saccular intracranial aneurysm is a common disease that may cause devastating intracranial hemorrhage. Hemodynamics, wall remodeling, and wall inflammation have been associated with saccular intracranial aneurysm rupture. We investigated how saccular intracranial aneurysm hemodynamics is associated with wall remodeling and inflammation of the saccular intracranial aneurysm wall.

MATERIALS AND METHODS

Tissue samples resected during a saccular intracranial aneurysm operation (11 unruptured, 9 ruptured) were studied with histology and immunohistochemistry. Patient-specific computational models of hemodynamics were created from preoperative CT angiographies.

RESULTS

More stable and less complex flows were associated with thick, hyperplastic saccular intracranial aneurysm walls, while slower flows with more diffuse inflow were associated with degenerated and decellularized saccular intracranial aneurysm walls. Wall degeneration (P = .041) and rupture were associated with increased inflammation (CD45+, P = .031). High wall shear stress (P = .018), higher vorticity (P = .046), higher viscous dissipation (P = .046), and high shear rate (P = .046) were associated with increased inflammation. Inflammation was also associated with lack of an intact endothelium (P = .034) and the presence of organized luminal thrombosis (P = .018), though overall organized thrombosis was associated with low minimum wall shear stress (P = .034) and not with the flow conditions associated with inflammation.

CONCLUSIONS

Flow conditions in the saccular intracranial aneurysm are associated with wall remodeling. Inflammation, which is associated with degenerative wall remodeling and rupture, is related to high flow activity, including elevated wall shear stress. Endothelial injury may be a mechanism by which flow induces inflammation in the saccular intracranial aneurysm wall. Hemodynamic simulations might prove useful in identifying saccular intracranial aneurysms at risk of developing inflammation, a potential biomarker for rupture.

Porcine In Vivo Validation of a Virtual Contrast Model: The Influence of Contrast Agent Properties and Vessel Flow Rates

BACKGROUND AND PURPOSE

Accurately and efficiently modeling the transport of angiographic contrast currently offers the best method of verifying computational fluid dynamics simulations and, with it, progress toward the lofty goal of prediction of aneurysm treatment outcome a priori. This study specifically examines the influence of estimated flow rate and contrast properties on such in silico predictions of aneurysm contrast residence and decay.

MATERIALS AND METHODS

Four experimental sidewall aneurysms were created in swine, with aneurysm contrast flow patterns and decay rates observed under angiography. A simplified computational fluid dynamics model of the experimental aneurysm was constructed from 3D angiography and contrast residence predicted a priori. The relative influence of a number of estimated model parameters (contrast viscosity, contrast density, and blood flow rate) on contrast residence was then investigated with further simulations.

RESULTS

Contrast infiltration and washout pattern were accurately predicted by the a priori computational fluid dynamics model; however, the contrast decay rate was underestimated by ∼25%. This error was attributed to the estimated parent vessel flow rate alone, and the effects of contrast viscosity and density on the decay rate were found to be inconsequential. A linear correlation between the parent vessel flow rate and the corresponding contrast decay rate was observed.

CONCLUSIONS

In experimental sidewall aneurysms, contrast fluid properties (viscosity and density) were shown to have a negligible effect on variation in the modeled contrast decay rate. A strong linear correlation was observed between parent vessel flow rate and contrast decay over a physiologically reasonable range of flow rates.

Effects of Reynolds and Womersley Numbers on the Hemodynamics of Intracranial Aneurysms

The effects of Reynolds and Womersley numbers on the hemodynamics of two simplified intracranial aneurysms (IAs), that is, sidewall and bifurcation IAs, and a patient-specific IA are investigated using computational fluid dynamics. For this purpose, we carried out three numerical experiments for each IA with various Reynolds (Re = 145.45 to 378.79) and Womersley (Wo = 7.4 to 9.96) numbers. Although the dominant flow feature, which is the vortex ring formation, is similar for all test cases here, the propagation of the vortex ring is controlled by both Re and Wo in both simplified IAs (bifurcation and sidewall) and the patient-specific IA. The location of the vortex ring in all tested IAs is shown to be proportional to Re/Wo² which is in agreement with empirical formulations for the location of a vortex ring in a tank. In sidewall IAs, the oscillatory shear index is shown to increase with Wo and 1/Re because the vortex reached the distal wall later in the cycle (higher resident time). However, this trend was not observed in the bifurcation IA because the stresses were dominated by particle trapping structures, which were absent at low Re = 151.51 in contrast to higher Re = 378.79.

Uncertainty quantification of wall shear stress in intracranial aneurysms using a data-driven statistical model of systemic blood flow variability

Adverse wall shear stress (WSS) patterns are known to play a key role in the localisation, formation, and progression of intracranial aneurysms (IAs). Complex region-specific and time-varying aneurysmal WSS patterns depend both on vascular morphology as well as on variable systemic flow conditions. Computational fluid dynamics (CFD) has been proposed for characterising WSS patterns in IAs; however, CFD simulations often rely on deterministic boundary conditions that are not representative of the actual variations in blood flow. We develop a data-driven statistical model of internal carotid artery (ICA) flow, which is used to generate a virtual population of waveforms used as inlet boundary conditions in CFD simulations. This allows the statistics of the resulting aneurysmal WSS distributions to be computed. It is observed that ICA waveform variations have limited influence on the time-averaged WSS (TAWSS) on the IA surface. In contrast, in regions where the flow is locally highly multidirectional, WSS directionality and harmonic content are strongly affected by the ICA flow waveform. As a consequence, we argue that the effect of blood flow variability should be explicitly considered in CFD-based IA rupture assessment to prevent confounding the conclusions.

Quantification of velocity reduction after flow diverter placement in intracranial aneurysm: An ex vivo study with 3D printed replicas

Phase contrast MRI (pcMRI) was used to measure flow before and after placement of a flow diverter (n = 3). Decreases from 18% to 31% in flow velocity were seen in the inflow jet of the aneurysms. Flow patterns were also compared. It was observed that the gross aneurysmal flow patterns were maintained after flow diverter placement despite decreased fluid velocities. All measurements were carried out in 3D printed aneurysm replicas.

Heart blood flow simulation: a perspective review

Cardiovascular disease (CVD), the leading cause of death today, incorporates a wide range of cardiovascular system malfunctions that affect heart functionality. It is believed that the hemodynamic loads exerted on the cardiovascular system, the left ventricle (LV) in particular, are the leading cause of CVD initiation and propagation. Moreover, it is believed that the diagnosis and prognosis of CVD at an early stage could reduce its high mortality and morbidity rate. Therefore, a set of robust clinical cardiovascular assessment tools has been introduced to compute the cardiovascular hemodynamics in order to provide useful insights to physicians to recognize indicators leading to CVD and also to aid the diagnosis of CVD. Recently, a combination of computational fluid dynamics (CFD) and different medical imaging tools, image-based CFD (IB-CFD), has been widely employed for cardiovascular functional assessment by providing reliable hemodynamic parameters. Even though the capability of CFD to provide reliable flow dynamics in general fluid mechanics problems has been widely demonstrated for many years, up to now, the clinical implications of the IB-CFD patient-specific LVs have not been applicable due to its limitations and complications. In this paper, we review investigations conducted to numerically simulate patient-specific human LV over the past 15 years using IB-CFD methods. Firstly, we divide different studies according to the different LV types (physiological and different pathological conditions) that have been chosen to reconstruct the geometry, and then discuss their contributions, methodologies, limitations, and findings. In this regard, we have studied CFD simulations of intraventricular flows and related cardiology insights, for (i) Physiological patient-specific LV models, (ii) Pathological heart patient-specific models, including myocardial infarction, dilated cardiomyopathy, hypertrophic cardiomyopathy and hypoplastic left heart syndrome. Finally, we discuss the current stage of the IB-CFD LV simulations in order to mimic realistic hemodynamics of patient-specific LVs. We can conclude that heart flow simulation is on the right track for developing into a useful clinical tool for heart function assessment, by (i) incorporating most of heart structures' (such as heart valves) operations, and (ii) providing useful diagnostic indices based hemodynamic parameters, for routine adoption in clinical usage.

Characterization of Hemodynamics in Great Arteries of Wild-Type Mouse Using Computational Fluid Dynamics Based on Ultrasound Images

Hemodynamic factors in cardiovascular system are hypothesized to play a significant role in causing structural heart development. It is thus important to improve our understanding of velocity characteristics and parameters. We present such a study on wild-type mouse to characterize the vessel geometry, flow pattern, and wall shear stress in great arteries. Microultrasound imaging for small animals was used to measure blood boundary and velocity of the great arteries. Subsequently, specimens' flow boundary conditions were used for 3-dimensional reconstructions of the great artery and aortic arch dimensions, and blood flow velocity data were input into subject-specific computational fluid dynamics for modeling hemodynamics. Measurement by microultrasound imaging showed that blood velocities in the great artery and aortic arch had strong correlations with vascular sizes, whereas blood pressure had a weak trend in relation to vascular size. Wall shear stress magnitude increased when closer to arterial branches and reduced proximally in the aortic root and distally in the descending aorta, and the parameters were related to the fluid mechanics in branches in some degree. We developed a method to investigate fluid mechanics in mouse arteries, using a combination of microultrasound and computational fluid dynamics, and demonstrated its ability to reveal detailed geometric, kinematic, and fluid mechanics parameters.

The Computational Fluid Dynamics Rupture Challenge 2013—Phase II: Variability of Hemodynamic Simulations in Two Intracranial Aneurysms

With the increased availability of computational resources, the past decade has seen a rise in the use of computational fluid dynamics (CFD) for medical applications. There has been an increase in the application of CFD to attempt to predict the rupture of intracranial aneurysms, however, while many hemodynamic parameters can be obtained from these computations, to date, no consistent methodology for the prediction of the rupture has been identified. One particular challenge to CFD is that many factors contribute to its accuracy; the mesh resolution and spatial/temporal discretization can alone contribute to a variation in accuracy. This failure to identify the importance of these factors and identify a methodology for the prediction of ruptures has limited the acceptance of CFD among physicians for rupture prediction. The International CFD Rupture Challenge 2013 seeks to comment on the sensitivity of these various CFD assumptions to predict the rupture by undertaking a comparison of the rupture and blood-flow predictions from a wide range of independent participants utilizing a range of CFD approaches. Twenty-six groups from 15 countries took part in the challenge. Participants were provided with surface models of two intracranial aneurysms and asked to carry out the corresponding hemodynamics simulations, free to choose their own mesh, solver, and temporal discretization. They were requested to submit velocity and pressure predictions along the centerline and on specified planes. The first phase of the challenge, described in a separate paper, was aimed at predicting which of the two aneurysms had previously ruptured and where the rupture site was located. The second phase, described in this paper, aims to assess the variability of the solutions and the sensitivity to the modeling assumptions. Participants were free to choose boundary conditions in the first phase, whereas they were prescribed in the second phase but all other CFD modeling parameters were not prescribed. In order to compare the computational results of one representative group with experimental results, steady-flow measurements using particle image velocimetry (PIV) were carried out in a silicone model of one of the provided aneurysms. Approximately 80% of the participating groups generated similar results. Both velocity and pressure computations were in good agreement with each other for cycle-averaged and peak-systolic predictions. Most apparent “outliers” (results that stand out of the collective) were observed to have underestimated velocity levels compared to the majority of solutions, but nevertheless identified comparable flow structures. In only two cases, the results deviate by over 35% from the mean solution of all the participants. Results of steady CFD simulations of the representative group and PIV experiments were in good agreement. The study demonstrated that while a range of numerical schemes, mesh resolution, and solvers was used, similar flow predictions were observed in the majority of cases. To further validate the computational results, it is suggested that time-dependent measurements should be conducted in the future. However, it is recognized that this study does not include the biological aspects of the aneurysm, which needs to be considered to be able to more precisely identify the specific rupture risk of an intracranial aneurysm.

Diversity in the Strength and Structure of Unruptured Cerebral Aneurysms

Intracranial aneurysms are pathological enlargements of brain arteries that are believed to arise from progressive wall degeneration and remodeling. Earlier work using classical histological approaches identified variability in cerebral aneurysm mural content, ranging from layered walls with intact endothelium and aligned smooth muscle cells, to thin, hypocellular walls. Here, we take advantage of recent advances in multiphoton microscopy, to provide novel results for collagen fiber architecture in 15 human aneurysm domes without staining or fixation as well as in 12 control cerebral arteries. For all aneurysm samples, the elastic lamina was absent and the abluminal collagen fibers had similar diameters to control arteries. In contrast, the collagen fibers on the luminal side showed great variability in both diameter and architecture ranging from dense fiber layers to sparse fiber constructs suggestive of ineffective remodeling efforts. The mechanical integrity of eight aneurysm samples was assessed using uniaxial experiments, revealing two sub-classes (i) vulnerable unruptured aneurysms (low failure stress and failure pressure), and (ii) strong unruptured aneurysms (high failure stress and failure pressure). These results suggest a need to refine the end-point of risk assessment studies that currently do not distinguish risk levels among unruptured aneurysms. We propose that a measure of wall integrity that identifies this vulnerable wall subpopulation will be useful for interpreting future biological and structural data.

AView: An Image-based Clinical Computational Tool for Intracranial Aneurysm Flow Visualization and Clinical Management

Intracranial aneurysms (IAs) occur in around 3% of the entire population. IA rupture is responsible for the most devastating type of hemorrhagic strokes, with high fatality and disability rates as well as healthcare costs. With increasing detection of unruptured aneurysms, clinicians are routinely faced with the dilemma whether to treat IA patients and how to best treat them. Hemodynamic and morphological characteristics are increasingly considered in aneurysm rupture risk assessment and treatment planning, but currently no computational tools allow routine integration of flow visualization and quantitation of these parameters in clinical workflow. In this paper, we introduce AView, a prototype of a clinician-oriented, integrated computation tool for aneurysm hemodynamics, morphology, and risk and data management to aid in treatment decisions and treatment planning in or near the procedure room. Specifically, we describe how we have designed the AView structure from the end-user's point of view, performed a pilot study and gathered clinical feedback. The positive results demonstrate AView's potential clinical value on enhancing aneurysm treatment decision and treatment planning.

Hemodynamic-morphological discriminant models for intracranial aneurysm rupture remain stable with increasing sample size

BACKGROUND

We previously established three logistic regression models for discriminating intracranial aneurysm rupture status based on morphological and hemodynamic analysis of 119 aneurysms. In this study, we tested if these models would remain stable with increasing sample size, and investigated sample sizes required for various confidence levels (CIs).

METHODS

We augmented our previous dataset of 119 aneurysms into a new dataset of 204 samples by collecting an additional 85 consecutive aneurysms, on which we performed flow simulation and calculated morphological and hemodynamic parameters, as done previously. We performed univariate significance tests on these parameters, and multivariate logistic regression on significant parameters. The new regression models were compared against the original models. Receiver operating characteristics analysis was applied to compare the performance of regression models. Furthermore, we performed regression analysis based on bootstrapping resampling statistical simulations to explore how many aneurysm cases were required to generate stable models.

RESULTS

Univariate tests of the 204 aneurysms generated an identical list of significant morphological and hemodynamic parameters as previously (from the analysis of 119 cases). Furthermore, multivariate regression analysis produced three parsimonious predictive models that were almost identical to the previous ones, with model coefficients that had narrower CIs than the original ones. Bootstrapping showed that 10%, 5%, 2%, and 1% convergence levels of CI required 120, 200, 500, and 900 aneurysms, respectively.

CONCLUSIONS

Our original hemodynamic-morphological rupture prediction models are stable and improve with increasing sample size. Results from resampling statistical simulations provide guidance for designing future large multi-population studies.

The effect of inlet waveforms on computational hemodynamics of patient-specific intracranial aneurysms

Due to the lack of patient-specific inlet flow waveform measurements, most computational fluid dynamics (CFD) simulations of intracranial aneurysms usually employ waveforms that are not patient-specific as inlet boundary conditions for the computational model. The current study examined how this assumption affects the predicted hemodynamics in patient-specific aneurysm geometries. We examined wall shear stress (WSS) and oscillatory shear index (OSI), the two most widely studied hemodynamic quantities that have been shown to predict aneurysm rupture, as well as maximal WSS (MWSS), energy loss (EL) and pressure loss coefficient (PLc). Sixteen pulsatile CFD simulations were carried out on four typical saccular aneurysms using 4 different waveforms and an identical inflow rate as inlet boundary conditions. Our results demonstrated that under the same mean inflow rate, different waveforms produced almost identical WSS distributions and WSS magnitudes, similar OSI distributions but drastically different OSI magnitudes. The OSI magnitude is correlated with the pulsatility index of the waveform. Furthermore, there is a linear relationship between aneurysm-averaged OSI values calculated from one waveform and those calculated from another waveform. In addition, different waveforms produced similar MWSS, EL and PLc in each aneurysm. In conclusion, inlet waveform has minimal effects on WSS, OSI distribution, MWSS, EL and PLc and a strong effect on OSI magnitude, but aneurysm-averaged OSI from different waveforms has a strong linear correlation with each other across different aneurysms, indicating that for the same aneurysm cohort, different waveforms can consistently stratify (rank) OSI of aneurysms.

Modeling of the acute effects of primary hypertension and hypotension on the hemodynamics of intracranial aneurysms

Hemodynamics is a risk factor in intracranial aneurysms (IA). Hypertension and pharmacologically induced hypotension are common in IA patients. This study investigates how hypertension and hypotension may influence aneurysmal hemodynamics. Images of 23 IAs at typical locations were used to build patient-specific Computational Fluid Dynamics models. The effects of hypotension and hypertension were simulated through boundary conditions by modulating the normotensive flow and pressure waveforms, in turn produced by a 1D systemic vascular model. Aneurysm location and flow pattern types were used to categorize the influence of hypotension and hypertension on relevant flow variables (velocity, pressure and wall shear stress). Results indicate that, compared to other locations, vertebrobasilar aneurysms (VBA) are more sensitive to flow changes. In VBAs, space-averaged velocity at peak systole increased by 30% in hypertension (16-21% in other locations). Flow in VBAs in hypotension decreased by 20% (10-13% in other locations). Momentum-driven hemodynamic types were also more affected by hypotension and hypertension, than shear-driven types. This study shows how patient-specific modeling can be effectively used to identify location-specific flow patterns in a clinically-relevant study, thus reinforcing the role played by modeling technologies in furthering our understanding of cardiovascular disease, and their potential in future healthcare.

Rupture Resemblance Score (RRS): toward risk stratification of unruptured intracranial aneurysms using hemodynamic-morphological discriminants

OBJECTIVE

We have previously developed three logistic regression models for discriminating intracranial aneurysm rupture status from 119 aneurysms based on hemodynamic-morphological parameters. In this study we exploit their use as a tool for predicting the risk of rupture of aneurysms with a defined Rupture Resemblance Score (RRS).

METHODS

We collected three-dimensional images of 85 consecutive aneurysms, applied the three regression models and compared model performance at predicting rupture status against anecdotal metrics (aneurysm size and aspect ratio). We then reinterpreted the model-predicted probability as RRS, where the higher the score the closer the resemblance to previously known rupture components, and applied the RRS prospectively to four unruptured aneurysms with borderline treatment decisions.

RESULTS

All three models yielded excellent sensitivity (0.78-0.83) and specificity (0.78-0.84) at a cutoff score of 50%, whereas aneurysm size and aspect ratio showed poor sensitivities (0.28 and 0.33, respectively). Lowering the cutoff score to 30% improved sensitivity to 0.90. The RRS identified most of the ruptured aneurysms and also some unruptured ones that closely resembled ruptured aneurysms hemodynamically and/or morphologically. The prospective application of the RRS to unruptured aneurysms shows that it could provide additional insights for treatment decisions.

CONCLUSIONS

Previous regression models based on hemodynamic-morphological parameters are able to discriminate rupture in a new cohort in the same population. A higher probability of rupture is associated with larger size ratio, lower normalized wall shear stress and higher oscillatory shear index. The RRS could potentially stratify rupture risk and assist in treatment decision-making for unruptured aneurysms.

An approach to the symbolic representation of brain arteriovenous malformations for management and treatment planning

INTRODUCTION

There is currently no standardised approach to arteriovenous malformation (AVM) reporting. Existing AVM classification systems focuses on angioarchitectural features and omit haemodynamic, anatomical and topological parameters intuitively used by therapists.

METHODS

We introduce a symbolic vocabulary to represent the state of an AVM of the brain at different stages of treatment. The vocabulary encompasses the main anatomic and haemodynamic features of interest in treatment planning and provides shorthand symbols to represent the interventions themselves in a schematic representation.

RESULTS

The method was presented to 50 neuroradiologists from 14 countries during a workshop and graded 7.34 ± 1.92 out of ten for its usefulness as means of standardising and facilitating communication between clinicians and allowing comparisons between AVM cases. Feedback from the survey was used to revise the method and improve its completeness. For an AVM test case, participants were asked to produce a conventional written report and subsequently a diagrammatic report. The two required, on average, 6.19 ± 2.05 and 5.09 ± 3.01 min, respectively. Eighteen participants said that producing the diagram changed the way they thought about the AVM test case.

CONCLUSION

Introduced into routine practice, the diagrams would represent a step towards a standardised approach to AVM reporting with consequent benefits for comparative analysis and communication as well as for identifying best treatment strategies.

Validation of computational fluid dynamics methods with anatomically exact, 3D printed MRI phantoms and 4D pcMRI

A new concept of rapid 3D prototyping was implemented using cost-effective 3D printing for creating anatomically correct replica of cerebral aneurysms. With a dedicated flow loop set-up in a full body human MRI scanner, flow measurements were performed using 4D phase contrast magnetic resonance imaging to visualize and quantify intra-aneurysmal flow patterns. Ultrashort TE sequences were employed to obtain high-resolution 3D image data to visualize the lumen inside the plastic replica. In-vitro results were compared with retrospectively obtained in-vivo data and results from computational fluid dynamics simulations (CFD). Rapid prototyping of anatomically realistic 3D models may have future impact in treatment planning, design of image acquisition methods for MRI and angiographic systems and for the design and testing of advanced image post-processing technologies.

Mind the gap: impact of computational fluid dynamics solution strategy on prediction of intracranial aneurysm hemodynamics and rupture status indicators

BACKGROUND AND PURPOSE

Computational fluid dynamics has become a popular tool for studying intracranial aneurysm hemodynamics, demonstrating success for retrospectively discriminating rupture status; however, recent highly refined simulations suggest potential deficiencies in solution strategies normally used in the aneurysm computational fluid dynamics literature. The purpose of the present study was to determine the impact of this gap.

MATERIALS AND METHODS

Pulsatile flow in 12 realistic MCA aneurysms was simulated by using both high-resolution and normal-resolution strategies. Velocity fields were compared at selected instants via domain-averaged error. We also compared wall shear stress fields and various reduced hemodynamic indices: cycle-averaged mean and maximum wall shear stress, oscillatory shear index, low shear area, viscous dissipation ratio, and kinetic energy ratio.

RESULTS

Instantaneous differences in flow and wall shear stress patterns were appreciable, especially for bifurcation aneurysms. Linear regressions revealed strong correlations (R(2) > 0.9) between high-resolution and normal-resolution solutions for all indices except kinetic energy ratio (R(2) = 0.25) and oscillatory shear index (R(2) = 0.23); however, for most indices, the slopes were significantly <1, reflecting a pronounced underestimation by the normal-resolution simulations. Some high-resolution simulations were highly unstable, with fluctuating wall shear stresses reflected by the poor oscillatory shear index correlation.

CONCLUSIONS

Typical computational fluid dynamics solution strategies may ultimately be adequate for augmenting rupture risk assessment on the basis of certain highly reduced indices; however, they cannot be relied on for predicting the magnitude and character of the complex biomechanical stimuli to which the aneurysm wall may be exposed. This impact of the computational fluid dynamics solution strategy is likely greater than that for other modeling assumptions or uncertainties.