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

Verifying the Accuracy of Hemodynamic Analysis Using High Spatial Resolution 3D Phase-contrast MR Imaging on a 7T MR System: Comparison with a 3T System

PURPOSE

Hemodynamics is important in the initiation, growth, and rupture of intracranial aneurysms. Since intracranial aneurysms are small, a high-field MR system with high spatial resolution and high SNR is desirable for this hemodynamic analysis. The purpose of this study was to investigate whether the accuracy of MR fluid dynamic (MRFD) results based on 3D phase-contrast MR (3D PC MR, non-electrocardiogram[ECG]-gated 4D Flow MRI) data from a human cerebrovascular phantom and human healthy subjects obtained by a 7T MR system was superior to those by a 3T MR system.

METHODS

3D PC MR and 3D time of flight MR angiography (3D TOF MRA) imaging were performed on a 3T MR system and a 7T MR system for a human cerebrovascular phantom and 10 healthy human subjects, and MRFD analysis was performed using these data. The MRFD results from each MR system were then compared with the following items based on the computational fluid dynamics (CFD) results: 3D velocity vector field; correlation coefficient (R), angular similarity index (ASI), and magnitude similarity index (MSI) of blood flow velocity vectors.

RESULTS

In the MRFD results of 3D velocity vectors of the cerebrovascular phantom, noise-like vectors were observed near the vascular wall on the 3T MR system, but no noise was observed on the 7T MR system, showing results similar to those of CFD. In the MRFD results of the cerebrovascular phantom and healthy subjects, the correlation coefficients R, ASI, and MSI of the 7T MR system were higher than those of the 3T MR system, and ASI and MSI of healthy human subjects were significantly different between the two systems.

CONCLUSIONS

The accuracy of high spatial resolution MRFD using the 7T MR system exceeded that of the 3T MR system.

Histopathology-based near-realistic arterial wall reconstruction of a patient-specific cerebral aneurysm for fluid-structure interaction studies

BACKGROUND AND OBJECTIVE

Cerebral aneurysms occur as balloon-like outpouchings in an artery, which commonly develop at the weak curved regions and bifurcations. When aneurysms are detected, understanding the risk of rupture is of immense clinical value for better patient management. Towards this, Fluid-Structure Interaction (FSI) studies can improve our understanding of the mechanics behind aneurysm initiation, progression, and rupture. Performing retrospective hemodynamic analysis using an accurate computational model that is closer to the actual biological milieu could yield clinically useful rupture risk predictions. Currently, the geometric model for the FSI studies rely on imaging the flow-domain using Computed Tomographic Angiography (CTA) or Digital Subtraction angiography (DSA), which limits accurate discerning of the vessel wall thickness. Histopathological information has always been ignored in accurately reconstructing the geometric model for the aneurysm. The present study combines both the shape information of the 3D lumen model (as it existed in vivo), which is accurately rendered through the CTA, in conjunction with the wall thickness information extracted from histo-pathological 2D images of the aneurysm. Furthermore, fluid-structure interaction (FSI) simulations are performed to understand the influence of patient-specific wall contribution towards rupture.

METHODS

A 3D geometric model of the blood-flow domain of an anterior communicating artery (ACoA) aneurysm is extracted from the CTA of a patient that was surgically clipped. After safely clipping the aneurysm, the fundus of the aneurysm beyond the clip was cut and extracted. This was carefully preserved and sliced to obtain the wall thickness variation of the hoop at various axial sections. This study proposes a novel methodology of combining multi-modal image data to geometrically render the 3D model of the Cerebral aneurysm. The wall thickness extracted from the histological 2D cross-sectional images of the aneurysm is encapsulated around the 3D lumen model obtained from CT Angiographic data. To this end, a wall thickness transfer algorithm is developed to accurately reconstruct the patient-specific aneurysm wall thickness variation for the FSI simulations.

RESULTS

The wall thickness transfer algorithm accurately combines both the blood flow domain from the CT angiography and the histopathological images involving the wall thickness heterogeneity for the aneurysm. The patient-specific wall thickness variation, as it existed in vivo, has a mean wall thickness of 0.553 mm with a standard deviation of 0.256 mm. Detailed FSI simulations were performed to study the role of the patient-specific wall thickness (PWT) model vis-a-vis the uniform wall thickness (UWT) model. It was observed that the maximum wall stress for the UWT model was 13.6 kPa, while it was substantially higher for the PWT model (48.4 kPa). The maximum wall displacement for the UWT model was 58.5μm, while it was 162μm for the PWT model. Similarly, the mean wall stress for the UWT model was 2.13 kPa, while for the PWT model, it was 8.43 kPa. The mean wall displacement for the PWT model was substantially higher than the UWT model (52.58μm against 16.47μm).

CONCLUSION

The rendered patient-specific aneurysm wall model with its thickness variation, as it existed in vivo was obtained. Comparing fluid-structure interaction (FSI) simulation results, between the patient-specific wall-lumen combined model against the uniform wall thickness model have clearly shown that there were significant differences (p< 0.05) in the distribution of the hemodynamic parameters. The percentage difference in mean wall displacement and associated wall stress was 69% and 75%, respectively. Corresponding numbers for maximum wall displacement and maximum wall stress are 64% and 72%, respectively. Patient-specific fluid-structure interaction simulations show that, the present approach is highly valuable, as it improves our understanding towards rupture potential analysis for the cerebral aneurysms.

CFD investigations of a shape-memory polymer foam-based endovascular embolization device for the treatment of intracranial aneurysms

The hemodynamic and convective heat transfer effects of a patient-specific endovascular therapeutic agent based on shape-memory polymer foam (SMPf) are evaluated using computational fluid dynamics studies for six patient-specific aneurysm geometries. The SMPf device is modeled as a continuous porous medium with full expansion for the flow studies and with various degrees of expansion for the heat transfer studies. The flow simulation parameters were qualitatively validated based on the existing literature. Further, a mesh independence study was conducted to verify an optimal cell size and reduce the computational costs. For convective heat transfer, a worst-case scenario is evaluated where the minimum volumetric flow rate is applied alongside the zero-flux boundary conditions. In the flow simulations, we found a reduction of the average intra-aneurysmal flow of > 85% and a reduction of the maximum intra-aneurysmal flow of > 45% for all presented geometries. These findings were compared with the literature on numerical simulations of hemodynamic and heat transfer of SMPf devices. The results obtained from this study provide a novel and practical framework for optimizing the design of patient-specific SMPf devices, integrating advanced computational models of hemodynamics and heat transfer. This framework could guide the future development of personalized endovascular embolization solutions for intracranial aneurysms with improved therapeutic outcome.

Advancements in Brain Aneurysm Management: Integrating Neuroanatomy, Physiopathology, and Neurosurgical Techniques

Brain aneurysms, characterized by abnormal bulging in blood vessels, pose significant risks if ruptured, necessitating precise neuroanatomical knowledge and advanced neurosurgical techniques for effective management. This article delves into the intricate neuroanatomy relevant to brain aneurysms, including the vascular structures and critical regions involved. It provides a comprehensive overview of the pathophysiology of aneurysm formation and progression. The discussion extends to modern neurosurgical approaches for treating brain aneurysms, such as microsurgical clipping, endovascular coiling, and flow diversion techniques. Emphasis is placed on preoperative planning, intraoperative navigation, and postoperative care, highlighting the importance of a multidisciplinary approach. By integrating neuroanatomical insights with cutting-edge surgical practices, this article aims to enhance the understanding and treatment outcomes of brain aneurysms.

CFD investigations of a shape-memory polymer foam-based endovascular embolization device for the treatment of intracranial aneurysms

The hemodynamic and convective heat transfer effects of a patient-specific endovascular therapeutic agent based on shape memory polymer foam (SMPf) are evaluated using computational fluid dynamics studies for six patient-specific aneurysm geometries. The SMPf device is modeled as a continuous porous medium with full expansion for the flow studies and with various degrees of expansion for the heat transfer studies. The flow simulation parameters were qualitatively validated based on the existing literature. Further, a mesh independence study was conducted to verify an optimal cell size and reduce the computational costs. For convective heat transfer, a worst-case scenario is evaluated where the minimum volumetric flow rate is applied alongside the zero-flux boundary conditions. In the flow simulations, we found a reduction of the average intra-aneurysmal flow of > 85% and a reduction of the maximum intra-aneurysmal flow of > 45% for all presented geometries. These findings were compared with the literature on numerical simulations of hemodynamic and heat transfer of SMPf devices. The results obtained from this study can serve as a guide for optimizing the design and development of patient-specific SMPf devices aimed at personalized endovascular embolization of intracranial aneurysms.

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

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

Comparison of computational fluid dynamics with transcranial Doppler ultrasound in response to physiological stimuli

Cerebrovascular haemodynamics are sensitive to multiple physiological stimuli that require synergistic response to maintain adequate perfusion. Understanding haemodynamic changes within cerebral arteries is important to inform how the brain regulates perfusion; however, methods for direct measurement of cerebral haemodynamics in these environments are challenging. The aim of this study was to assess velocity waveform metrics obtained using transcranial Doppler (TCD) with flow-conserving subject-specific three-dimensional (3D) simulations using computational fluid dynamics (CFD). Twelve healthy participants underwent head and neck imaging with 3 T magnetic resonance angiography. Velocity waveforms in the middle cerebral artery were measured with TCD ultrasound, while diameter and velocity were measured using duplex ultrasound in the internal carotid and vertebral arteries to calculate incoming cerebral flow at rest, during hypercapnia and exercise. CFD simulations were developed for each condition, with velocity waveform metrics extracted in the same insonation region as TCD. Exposure to stimuli induced significant changes in cardiorespiratory measures across all participants. Measured absolute TCD velocities were significantly higher than those calculated from CFD (P range < 0.001-0.004), and these data were not correlated across conditions (r range 0.030-0.377, P range 0.227-0.925). However, relative changes in systolic and time-averaged velocity from resting levels exhibited significant positive correlations when the distinct techniques were compared (r range 0.577-0.770, P range 0.003-0.049). Our data indicate that while absolute measures of cerebral velocity differ between TCD and 3D CFD simulation, physiological changes from resting levels in systolic and time-averaged velocity are significantly correlated between techniques.

Image-based hemodynamic simulations for intracranial aneurysms: the impact of complex vasculature

PURPOSE

Hemodynamics play an important role in the assessment of intracranial aneurysm (IA) development and rupture risk. The purpose of this study was to examine the impact of complex vasculatures onto the intra-vessel and intra-aneurysmal blood flow.

METHODS

Complex segmentation of a subject-specific, 60-outlet and 3-inlet circle of Willis model captured with 7T magnetic resonance imaging was performed. This model was trimmed to a 10-outlet model version. Two patient-specific IAs were added onto both models yielding two pathological versions, and image-based blood flow simulations of the four resulting cases were carried out. To capture the differences between complex and trimmed model, time-averaged and centerline velocities were compared. The assessment of intra-saccular blood flow within the IAs involved the evaluation of wall shear stresses (WSS) at the IA wall and neck inflow rates (NIR).

RESULTS

Lower flow values are observed in the majority of the complex model. However, at specific locations (left middle cerebral artery 0.5 m/s, left posterior cerebral artery 0.25 m/s), higher flow rates were visible when compared to the trimmed counterpart. Furthermore, at the centerlines the total velocity values reveal differences up to 0.15 m/s. In the IAs, the reduction in the neck inflow rate and WSS in the complex model was observed for the first IA (IA-A δNIRmean =  - 0.07ml/s, PCA.l δWSSmean =  - 0.05 Pa). The second IA featured an increase in the neck inflow rate and WSS (IA-B δNIRmean = 0.04 ml/s, PCA.l δWSSmean = 0.07 Pa).

CONCLUSION

Both the magnitude and shape of the flow distribution vary depending on the model's complexity. The magnitude is primarily influenced by the global vessel model, while the shape is determined by the local structure. Furthermore, intra-aneurysmal flow strongly depends on the location in the vessel tree, emphasizing the need for complex model geometries for realistic hemodynamic assessment and rupture risk analysis.

Multi-Dimensional Modeling of Cerebral Hemodynamics: A Systematic Review

The Circle of Willis (CoW) describes the arterial system in the human brain enabling the neurovascular blood supply. Neurovascular diseases like intracranial aneurysms (IAs) can occur within the CoW and carry the risk of rupture, which can lead to subarachnoid hemorrhage. The assessment of hemodynamic information in these pathologies is crucial for their understanding regarding detection, diagnosis and treatment. Multi-dimensional in silico approaches exist to evaluate these hemodynamics based on patient-specific input data. The approaches comprise low-scale (zero-dimensional, one-dimensional) and high-scale (three-dimensional) models as well as multi-scale coupled models. The input data can be derived from medical imaging, numerical models, literature-based assumptions or from measurements within healthy subjects. Thus, the most realistic description of neurovascular hemodynamics is still controversial. Within this systematic review, first, the models of the three scales (0D, 1D, 3D) and second, the multi-scale models, which are coupled versions of the three scales, were discussed. Current best practices in describing neurovascular hemodynamics most realistically and their clinical applicablility were elucidated. The performance of 3D simulation entails high computational expenses, which could be reduced by analyzing solely the region of interest in detail. Medical imaging to establish patient-specific boundary conditions is usually rare, and thus, lower dimensional models provide a realistic mimicking of the surrounding hemodynamics. Multi-scale coupling, however, is computationally expensive as well, especially when taking all dimensions into account. In conclusion, the 0D-1D-3D multi-scale approach provides the most realistic outcome; nevertheless, it is least applicable. A 1D-3D multi-scale model can be considered regarding a beneficial trade-off between realistic results and applicable performance.

Prediction of cerebral aneurysm rupture risk by machine learning algorithms: a systematic review and meta-analysis of 18,670 participants

It is possible to identify unruptured intracranial aneurysms (UIA) using machine learning (ML) algorithms, which can be a life-saving strategy, especially in high-risk populations. To better understand the importance and effectiveness of ML algorithms in practice, a systematic review and meta-analysis were conducted to predict cerebral aneurysm rupture risk. PubMed, Scopus, Web of Science, and Embase were searched without restrictions until March 20, 2023. Eligibility criteria included studies that used ML approaches in patients with cerebral aneurysms confirmed by DSA, CTA, or MRI. Out of 35 studies included, 33 were cohort, and 11 used digital subtraction angiography (DSA) as their reference imaging modality. Middle cerebral artery (MCA) and anterior cerebral artery (ACA) were the commonest locations of aneurysmal vascular involvement-51% and 40%, respectively. The aneurysm morphology was saccular in 48% of studies. Ten of 37 studies (27%) used deep learning techniques such as CNNs and ANNs. Meta-analysis was performed on 17 studies: sensitivity of 0.83 (95% confidence interval (CI), 0.77-0.88); specificity of 0.83 (95% CI, 0.75-0.88); positive DLR of 4.81 (95% CI, 3.29-7.02) and the negative DLR of 0.20 (95% CI, 0.14-0.29); a diagnostic score of 3.17 (95% CI, 2.55-3.78); odds ratio of 23.69 (95% CI, 12.75-44.01). ML algorithms can effectively predict the risk of rupture in cerebral aneurysms with good levels of accuracy, sensitivity, and specificity. However, further research is needed to enhance their diagnostic performance in predicting the rupture status of IA.

Computational Fluid Dynamic Simulations of Cerebral Aneurysms

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

Multimodal exploration of the intracranial aneurysm wall

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Global tendencies and frontier topics in hemodynamics research of intracranial aneurysms: a bibliometric analysis from 1999 to 2022

Background: Hemodynamics plays a crucial role in the initiation, enlargement, and rupture of intracranial aneurysms (IAs). This bibliometric analysis aimed to map the knowledge network of IA hemodynamic research. Methods: Studies on hemodynamics in IAs published from 1999 to 2022 were retrieved from the Web of Science Core Collection (WoSCC). The contributions of countries, institutions, authors, and journals were identified using VOSviewer, Scimago Graphica, and Microsoft Excel. Tendencies, frontier topics, and knowledge networks were analyzed and visualized using VOSviewer and CiteSpace. Results: We identified 2,319 publications on hemodynamics in IAs. The annual number of publications exhibited an overall increasing trend. Among these, the United States, Japan, and China were the three major contributing countries. Capital Medical University, State University of New York (SUNY) Buffalo University, and George Mason University were the three most productive institutions. Meng H ranked first among authors regarding the number of articles and citations, while Cebral JR was first among co-cited authors. The American Journal of Neuroradiology was the top journal in terms of the number of publications, citations, and co-citations. In addition, the research topics can be divided into three clusters: hemodynamics itself, the relationship of hemodynamics with IA rupture, and the relationship of hemodynamics with IA treatment. The frontier directions included flow diverters, complications, morphology, prediction, recanalization, and four-dimensional flow magnetic resonance imaging (4D flow MRI). Conclusion: This study drew a knowledge map of the top countries, institutions, authors, publications, and journals on IA hemodynamics over the past 2 decades. The current and future hotspots of IA hemodynamics mainly include hemodynamics itself (4D flow MRI), its relationship with IA rupture (morphology and prediction), and its relationship with IA treatment (flow diverters, complications, and recanalization).

Design of a virtual data shelf to effectively explore a large database of 3D medical surface models in VR

PURPOSE

Medical researchers deal with a large amount of patient data to improve future treatment decisions and come up with new hypotheses. To facilitate working with a large database containing many patients and parameters, we propose a virtual data shelf, displaying the 3D anatomical surface models in an immersive VR environment.

METHODS

Thereby, different functionalities such as sorting, filtering and finding similar cases are included. To provide an appropriate layout and arrangement of 3D models that optimally supports working with the database, three layouts (flat, curved and spherical) and two distances are evaluated. A broad audience study with 61 participants was conducted to compare the different layouts based on their ease of interaction, to get an overview and to explore single cases. Medical experts additionally evaluated medical use cases.

RESULTS

The study revealed that the flat layout with small distance is significantly faster in providing an overview. Applying the virtual data shelf to the medical use case intracranial aneurysms, qualitative expert feedback with two neuroradiologists and two neurosurgeons was gathered. Most of the surgeons preferred the curved and spherical layouts.

CONCLUSION

Our tool combines benefits of two data management metaphors, resulting in an efficient way to work with a large database of 3D models in VR. The evaluation gives insight into benefits of layouts as well as possible use cases in medical research.

Sensitivity of hostile hemodynamics to aneurysm geometry via unsupervised shape interpolation

BACKGROUND AND OBJECTIVE

Vessel geometry and hemodynamics are intrinsically linked, whereby geometry determines hemodynamics, and hemodynamics influence vascular remodeling. Both have been used for testing clinical outcomes, but geometry/morphology generally has less uncertainty than hemodynamics derived from medical image-based computational fluid dynamics (CFD). To provide clinical utility, CFD-based hemodynamic parameters must be robust to modeling errors and/or uncertainties, but must also provide useful information not more-easily extracted from shape alone. The objective of this study was to methodically assess the response of hemodynamic parameters to gradual changes in shape created using an unsupervised 3D shape interpolation method.

METHODS

We trained the neural network NeuroMorph on 3 patient-derived intracranial aneurysm surfaces (labelled A, B, C), and then generated 3 distinct morph sequences (A→B, B→C, C→A) each containing 10 interpolated surfaces. From high-fidelity CFD simulation of these, we calculated a variety of common reduced hemodynamic parameters, including many previously associated with aneurysm rupture, and analyzed their responses to changes in shape, and their correlations.

RESULTS

The interpolated surfaces demonstrate complex, gradual changes in branch angles, vessel diameters, and aneurysm morphology. CFD simulation showed gradual changes in aneurysm jetting characteristics and wall-shear stress (WSS) patterns, but demonstrated a range of responses from the reduced hemodynamic parameters. Spatially and temporally averaged parameters including time-averaged WSS, time-averaged velocity, and low-shear area (LSA) showed low variation across all morph sequences, while parameters of flow complexity such as oscillatory shear, spectral broadening, and spectral bandedness indices showed high variation between slightly-altered neighboring surfaces. Correlation analysis revealed a great deal of mutual information with easier-to-measure shape-based parameters.

CONCLUSIONS

In the absence of large clinical datasets, unsupervised shape interpolation provides an ideal laboratory for exploring the delicate balance between robustness and sensitivity of nominal hemodynamic predictors of aneurysm rupture. Parameters like time-averaged WSS and LSA that are highly "robust" may, as a result, be effectively redundant to morphological predictors, whereas more sensitive parameters may be too uncertain for practical clinical use. Understanding these sensitivities may help identify parameters that are capable of providing added value to rupture risk assessment.

Is Accurate Lumen Segmentation More Important than Outlet Boundary Condition in Image-Based Blood Flow Simulations for Intracranial Aneurysms?

PURPOSE

Image-based blood flow simulations are increasingly used to investigate the hemodynamics in intracranial aneurysms (IAs). However, a strong variability in segmentation approaches as well as the absence of individualized boundary conditions (BCs) influence the quality of these simulation results leading to imprecision and decreased reliability. This study aims to analyze these influences on relevant hemodynamic parameters within IAs.

METHODS

As a follow-up study of an international multiple aneurysms challenge, the segmentation results of five IAs differing in size and location were investigated. Specifically, five possible outlet BCs were considered in each of the IAs. These are comprised of the zero-pressure condition (BC1), a flow distribution based on Murray's law with the exponents n = 2 (BC2) and n = 3 (BC3) as well as two advanced flow-splitting models considering the real vessels by including circular cross sections (BC4) or anatomical cross sections (BC5), respectively. In total, 120 time-dependent blood flow simulations were analyzed qualitatively and quantitatively, focusing on five representative intra-aneurysmal flow and five shear parameters such as vorticity and wall shear stress.

RESULTS

The outlet BC variation revealed substantial differences. Higher shear stresses (up to Δ9.69 Pa), intrasaccular velocities (up to Δ0.15 m/s) and vorticities (up to Δ629.22 1/s) were detected when advanced flow-splitting was applied compared to the widely used zero-pressure BC. The tendency of outlets BCs to over- or underestimate hemodynamic parameters is consistent across different segmentations of a single aneurysm model. Segmentation-induced variability reaches Δ19.58 Pa, Δ0.42 m/s and Δ957.27 1/s, respectively. Excluding low fidelity segmentations, however, (a) reduces the deviation drastically (>43%) and (b) leads to a lower impact of the outlet BC on hemodynamic predictions.

CONCLUSION

With a more realistic lumen segmentation, the influence of the BC on the resulting hemodynamics is decreased. A realistic lumen segmentation can be ensured, e.g., by using high-resolved 2D images. Furthermore, the selection of an advanced outflow-splitting model is advised and the use of a zero-pressure BC and BC based on Murray's law with exponent n = 3 should be avoided.

The influence of contralateral circulation on computational fluid dynamics of intracranial arteries: simulated versus measured flow velocities

BACKGROUND

This study aimed to retrospectively evaluate the influence of contralateral anterior circulation on computational fluid dynamics (CFD) of intracranial arteries, by comparing the CFD values of flow velocities in unilateral anterior circulation with the measured values from phase-contrast magnetic resonance angiography (PC-MRA).

METHODS

We analyzed 21 unilateral anterior circulation models without proximal stenosis from 15 patients who performed both time-of-flight MRA (TOF-MRA) and PC-MRA. CFD was performed with the inflow boundary condition of a pulsatile flow of the internal carotid artery (ICA) obtained from PC-MRA. The outflow boundary condition was given as atmospheric pressure. Simulated flow velocities of the middle cerebral artery (MCA) and anterior cerebral artery (ACA) from CFD were compared with the measured values from PC-MRA.

RESULTS

The velocities of MCA were shown to be more accurately simulated on CFD than those of ACA (Spearman correlation coefficient 0.773 and 0.282, respectively). In four models with severe stenosis or occlusion of the contralateral ICA, the CFD values of ACA velocities were significantly lower (< 50%) than those measured with PC-MRA. ACA velocities were relatively accurately simulated in the models including similar diameters of both ACAs.

CONCLUSION

It may be necessary to consider the flow condition of the contralateral anterior circulation in CFD of intracranial arteries, especially in the ACA.

RELEVANCE STATEMENT

Incorporating the flow conditions of the contralateral circulation is of clinical importance for an accurate prediction of a rupture risk in Acom aneurysms as the bidirectional flow and accurate velocity of both ACAs can significantly impact the CFD results.

KEY POINTS

• CFD simulations using unilateral vascular models were relatively accurate for MCA. • Contralateral ICA steno-occlusion resulted in an underestimation of CFD velocity in ACA. • Contralateral flow may need to be considered in CFD simulations of ACA.

Personalised simulation of hemodynamics in cerebrovascular disease: lessons learned from a study of diagnostic accuracy

Intracranial atherosclerotic disease (ICAD) poses a significant risk of subsequent stroke but current prevention strategies are limited. Mechanistic simulations of brain hemodynamics offer an alternative precision medicine approach by utilising individual patient characteristics. For clinical use, however, current simulation frameworks have insufficient validation. In this study, we performed the first quantitative validation of a simulation-based precision medicine framework to assess cerebral hemodynamics in patients with ICAD against clinical standard perfusion imaging. In a retrospective analysis, we used a 0-dimensional simulation model to detect brain areas that are hemodynamically vulnerable to subsequent stroke. The main outcome measures were sensitivity, specificity, and area under the receiver operating characteristics curve (ROC AUC) of the simulation to identify brain areas vulnerable to subsequent stroke as defined by quantitative measurements of relative mean transit time (relMTT) from dynamic susceptibility contrast MRI (DSC-MRI). In 68 subjects with unilateral stenosis >70% of the internal carotid artery (ICA) or middle cerebral artery (MCA), the sensitivity and specificity of the simulation were 0.65 and 0.67, respectively. The ROC AUC was 0.68. The low-to-moderate accuracy of the simulation may be attributed to assumptions of Newtonian blood flow, rigid vessel walls, and the use of time-of-flight MRI for geometric representation of subject vasculature. Future simulation approaches should focus on integrating additional patient data, increasing accessibility of precision medicine tools to clinicians, addressing disease burden disparities amongst different populations, and quantifying patient benefit. Our results underscore the need for further improvement of mechanistic simulations of brain hemodynamics to foster the translation of the technology to clinical practice.

Study of Typical Ruptured and Unruptured Intracranial Aneurysms Based on Fluid-Structure Interaction

BACKGROUND

Most intracranial aneurysms (IAs) will be abnormal bulges on the walls of intracranial arteries that result from the dynamic interaction of geometric morphology, hemodynamics, and pathophysiology. Hemodynamics plays a key role in the origin, development, and rupture of IAs. In the past, hemodynamic studies of IAs were mostly based on the rigid wall hypothesis of computational fluid dynamics, and the influence of arterial wall deformation was ignored. We used fluid-structure interaction (FSI) to study the features of ruptured aneurysms, because it can solve this problem very well and the simulation will be more realistic.

METHODS

A total of 12 IAs, 8 ruptured and 4 unruptured, at the middle cerebral artery bifurcation were studied using FSI to better identify the characteristics of ruptured IAs. We studied the differences in the hemodynamic parameters, including the flow pattern, wall shear stress (WSS), oscillatory shear index (OSI), and displacement and deformation of the arterial wall.

RESULTS

Ruptured IAs had a larger low WSS area and more complex, concentrated, and unstable flow. Also, the OSI was higher. In addition, the displacement deformation area at the ruptured IA was more concentrated and larger.

CONCLUSIONS

A large aspect ratio; a large height/width ratio; complex, unstable, and concentrated flow patterns with small impact areas; a large low WSS region; large WSS fluctuation, high OSI; and large displacement of the aneurysm dome could be risk factors associated with aneurysm rupture. If similar cases are encountered when simulation is used in the clinic, priority should be given to diagnosis and treatment.

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.

Assessment of the flow-diverter efficacy for intracranial aneurysm treatment considering pre- and post-interventional hemodynamics

Endovascular treatment of intracranial aneurysms with flow diverters (FD) has become one of the most promising interventions. Due to its woven high-density structure they are particularly applicable for challenging lesions. Although several studies have already conducted realistic hemodynamic quantification of the FD efficacy, a comparison with morphologic post-interventional data is still missing. This study analyses the hemodynamics of ten intracranial aneurysm patients treated with a novel FD device. Based on pre- and post-interventional 3D digital subtraction angiography image data, patient-specific 3D models of both treatment states are generated applying open source threshold-based segmentation methods. Using a fast virtual stenting approach, the real stent positions available in the post-interventional data are virtually replicated and both treatment scenarios were characterized using image-based blood flow simulations. The results show FD-induced flow reductions at the ostium by a decrease in mean neck flow rate (51%), inflow concentration index (56%) and mean inflow velocity (53%). Intraluminal reductions in flow activity for time-averaged wall shear stress (47%) and kinetic energy (71%) are present as well. However, an intra-aneurysmal increase in flow pulsatility (16%) for the post-interventional cases can be observed. Patient-specific FD simulations demonstrate the desired flow redirection and activity reduction inside the aneurysm beneficial for thrombosis formation. Differences in the magnitude of hemodynamic reduction exist over the cardiac cycle which may be addressed in a clinical setting by anti-hypertensive treatment in selected cases.

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.

Hemodynamics of anterior circulation intracranial aneurysms with daughter blebs: investigating the multidirectionality of blood flow fields

Recent advances in diagnostic neuroradiological imaging, allowed the detection of unruptured intracranial aneurysms (IAs). The shape - irregular or multilobular - of the aneurysmal dome, is considered as a possible rupture risk factor, independently of the size, the location and patient medical background. Disturbed blood flow fields in particular is thought to play a key role in IAs progression. However, there is an absence of widely-used hemodynamic indices to quantify the extent of a multi-directional disturbed flow. We simulated blood flow in twelve patient-specific anterior circulation unruptured intracranial aneurysms with daughter blebs utilizing the spectral/hp element framework Nektar++. We simulated three cardiac cycles using a volumetric flow rate waveform while we considered blood as a Newtonian fluid. To investigate the multidirectionality of the blood flow fields, besides the time-averaged wall shear stress (TAWSS), we calculated the oscillatory shear index (OSI), the relative residence time (RRT) and the time-averaged cross flow index (TACFI). Our CFD simulations suggest that in the majority of our vascular models there is a formation of complex intrasaccular flow patterns, resulting to low and highly oscillating WSS, especially in the area of the daughter blebs. The existence of disturbed multi-directional blood flow fields is also evident by the distributions of the RRT and the TACFI. These findings further support the theory that IAs with daughter blebs are linked to a potentially increased rupture risk.

Deep learning-based recognition and segmentation of intracranial aneurysms under small sample size

The manual identification and segmentation of intracranial aneurysms (IAs) involved in the 3D reconstruction procedure are labor-intensive and prone to human errors. To meet the demands for routine clinical management and large cohort studies of IAs, fast and accurate patient-specific IA reconstruction becomes a research Frontier. In this study, a deep-learning-based framework for IA identification and segmentation was developed, and the impacts of image pre-processing and convolutional neural network (CNN) architectures on the framework's performance were investigated. Three-dimensional (3D) segmentation-dedicated architectures, including 3D UNet, VNet, and 3D Res-UNet were evaluated. The dataset used in this study included 101 sets of anonymized cranial computed tomography angiography (CTA) images with 140 IA cases. After the labeling and image pre-processing, a training set and test set containing 112 and 28 IA lesions were used to train and evaluate the convolutional neural network mentioned above. The performances of three convolutional neural networks were compared in terms of training performance, segmentation performance, and segmentation efficiency using multiple quantitative metrics. All the convolutional neural networks showed a non-zero voxel-wise recall (V-Recall) at the case level. Among them, 3D UNet exhibited a better overall segmentation performance under the relatively small sample size. The automatic segmentation results based on 3D UNet reached an average V-Recall of 0.797 ± 0.140 (3.5% and 17.3% higher than that of VNet and 3D Res-UNet), as well as an average dice similarity coefficient (DSC) of 0.818 ± 0.100, which was 4.1%, and 11.7% higher than VNet and 3D Res-UNet. Moreover, the average Hausdorff distance (HD) of the 3D UNet was 3.323 ± 3.212 voxels, which was 8.3% and 17.3% lower than that of VNet and 3D Res-UNet. The three-dimensional deviation analysis results also showed that the segmentations of 3D UNet had the smallest deviation with a max distance of +1.4760/-2.3854 mm, an average distance of 0.3480 mm, a standard deviation (STD) of 0.5978 mm, a root mean square (RMS) of 0.7269 mm. In addition, the average segmentation time (AST) of the 3D UNet was 0.053s, equal to that of 3D Res-UNet and 8.62% shorter than VNet. The results from this study suggested that the proposed deep learning framework integrated with 3D UNet can provide fast and accurate IA identification and segmentation.

Aneurysm Neck Overestimation has a Relatively Modest Impact on Simulated Hemodynamics

INTRODUCTION

Overestimation of intracranial aneurysm neck width by 3D angiography is a recognized clinical problem, and has long been a concern for image-based computational fluid dynamics (CFD). Recently, it was demonstrated that neck overestimation in 3D rotational angiography (3DRA) could be corrected via segmentation with upsampled resolution and gradient enhancement (SURGE). Our aim was to leverage this approach to determine whether and how neck overestimation actually impacts CFD-derived hemodynamics.

MATERIALS AND METHODS

A subset of 17 cases having the largest neck errors from a consecutive clinical sample of 60 was segmented from 3DRA using both standard watershed and SURGE methods. High-fidelity, pulsatile CFD was performed, and a variety of scalar hemodynamic parameters that have been associated with aneurysm growth and/or rupture status were derived.

RESULTS

With a few exceptions, flow and wall shear stress (WSS) patterns were qualitatively similar between neck-overestimated and corrected models. Sac-averaged WSS values were significantly lower after neck correction (p = 0.0005) but were highly correlated with their neck-overestimated counterparts (R² = 0.98). Jet impingement was significantly more concentrated in the neck-corrected vs. -uncorrected models (p = 0.0011), and only moderately correlated (R² = 0.61). Parameters quantifying velocity or WSS fluctuations were not significantly different after neck correction, but this reflected their poorer correlations (R² < 0.4). Nevertheless, for all hemodynamic parameters, median absolute differences were < 26%, and no parameter had more than 5/17 cases with absolute differences > 50%.

CONCLUSION

Differences in hemodynamics due to neck width overestimation were found to be at most equal to, and often less than, those reported for other sources of error/uncertainty in intracranial aneurysm CFD, such as solver settings or assumed inflow rates.

Reducing Geometric Uncertainty in Computational Hemodynamics by Deep Learning-Assisted Parallel-Chain MCMC

Computational hemodynamic modeling has been widely used in cardiovascular research and healthcare. However, the reliability of model predictions is largely dependent on the uncertainties of modeling parameters and boundary conditions, which should be carefully quantified and further reduced with available measurements. In this work, we focus on propagating and reducing the uncertainty of vascular geometries within a Bayesian framework. A novel deep learning (DL)-assisted parallel Markov chain Monte Carlo (MCMC) method is presented to enable efficient Bayesian posterior sampling and geometric uncertainty reduction. A DL model is built to approximate the geometry-to-hemodynamic map, which is trained actively using online data collected from parallel MCMC chains and utilized for early rejection of unlikely proposals to facilitate convergence with less expensive full-order model evaluations. Numerical studies on two-dimensional aortic flows are conducted to demonstrate the effectiveness and merit of the proposed method.

A web-based dynamic nomogram for rupture risk of posterior communicating artery aneurysms utilizing clinical, morphological, and hemodynamic characteristics

Background

Predicting rupture risk is important for aneurysm management. This research aimed to develop and validate a nomogram model to forecast the rupture risk of posterior communicating artery (PcomA) aneurysms.

Methods

Clinical, morphological, and hemodynamic parameters of 107 unruptured PcomA aneurysms and 225 ruptured PcomA aneurysms were retrospectively analyzed. The least absolute shrinkage and selection operator (LASSO) analysis was applied to identify the optimal rupture risk factors, and a web-based dynamic nomogram was developed accordingly. The nomogram model was internally validated and externally validated independently. The receiver operating characteristic (ROC) curve was used to assess the discrimination of nomogram, and simultaneously the Hosmer–Lemeshow test and calibration plots were used to assess the calibration. Decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the clinical utility of nomogram additionally.

Results

Four optimal rupture predictors of PcomA aneurysms were selected by LASSO and identified by multivariate logistic analysis, including hypertension, aspect ratio (AR), oscillatory shear index (OSI), and wall shear stress (WSS). A web-based dynamic nomogram was then developed. The area under the curve (AUC) in the training and external validation cohorts was 0.872 and 0.867, respectively. The Hosmer–Lemeshow p > 0.05 and calibration curves showed an appropriate fit. The results of DCA and CIC indicated that the net benefit rate of the nomogram model is higher than other models.

Conclusion

Hypertension, high AR, high OSI, and low WSS were the most relevant risk factors for rupture of PcomA aneurysms. A web-based dynamic nomogram thus established demonstrated adequate discrimination and calibration after internal and external validation. We hope that this tool will provide guidance for the management of PcomA aneurysms.

A predictive hemodynamic model based on risk factors for ruptured mirror aneurysms

Objectives

To identify hemodynamic risk factors for intracranial aneurysm rupture and establish a predictive model to aid evaluation.

Methods

We analyzed the hemodynamic parameters of 91 pairs of ruptured mirror aneurysms. A conditional univariate analysis was used for the continuous variables. A conditional multivariate logistic regression analysis was performed to identify the independent risk factors. Differences where p < 0.05 were statistically significant. A predictive model was established based on independent risk factors. Odds ratios (ORs) were used to score points. The validation cohort consisted of 189 aneurysms. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs) of the predictive model and independent risk factors.

Results

The conditional multivariate logistic analysis showed that the low shear area (LSA) (OR = 70.322, p = 0.044, CI = 1.112–4,445.256), mean combined hemodynamic parameter (CHP) (>0.087) (OR = 3.171, p = 0.034, CI = 1.089–9.236), and wall shear stress gradient (WSSG) ratio (>893.180) (OR = 5.740, p = 0.003, CI = 1.950–16.898) were independent risk factors. A prediction model was established: 23^*LSA + 1^*CHP mean (>0.087: yes = 1, no = 0) + 2 ^* WSSG ratio (>893.180: yes = 1, no = 0). The AUC values of the predictive model, LSA, mean CHP (>0.087), and WSSG ratio (>893.180) were 0.748, 0.700, 0.654, and 0.703, respectively. The predictive model and LSA cutoff values were 1.283 and 0.016, respectively. In the validation cohort, the predictive model, LSA, CHP (>0.087), and WSSG ratio (>893.180) were 0.736, 0.702, 0.689, and 0.706, respectively.

Conclusions

LSA, CHP (>0.087), and WSSG ratio (>893.180) were independent risk factors for aneurysm rupture. Our predictive model could aid practical evaluation.

The Role of Hemodynamics through the Circle of Willis in the Development of Intracranial Aneurysm: A Systematic Review of Numerical Models

Background: The role of regional hemodynamics in the intracranial aneurysmal formation, growth, and rupture has been widely discussed based on numerical models over the past decades. Variation of the circle of Willis (CoW), which results in hemodynamic changes, is associated with the aneurysmal formation and rupture. However, such correlation has not been further clarified yet. The aim of this systematic review is to investigate whether simulated hemodynamic indices of the CoW are relevant to the formation, growth, or rupture of intracranial aneurysm. Methods: We conducted a review of MEDLINE, Web of Science, and EMBASE for studies on the correlation between hemodynamics indices of the CoW derived from numerical models and intracranial aneurysm up to December 2020 in compliance with PRISMA guidelines. Results: Three case reports out of 1046 publications met our inclusion and exclusion criteria, reporting 13 aneurysms in six patients. Eleven aneurysms were unruptured, and the state of the other two aneurysms was unknown. Wall shear stress, oscillatory shear index, von-Mises tension, flow velocity, and flow rate were reported as hemodynamic indices. Due to limited cases and significant heterogeneity between study settings, meta-analysis could not be performed. Conclusion: Numerical models can provide comprehensive information on the cerebral blood flow as well as local flow characteristics in the intracranial aneurysm. Based on only three case reports, no firm conclusion can be drawn regarding the correlation between hemodynamic parameters in the CoW derived from numerical models and aneurysmal formation or rupture. Due to the inherent nature of numerical models, more sensitive analysis and rigorous validations are required to determine its measurement error and thus extend their application into clinical practice for personalized management. Prospero registration number: CRD42021125169.

Patient-Specific Cerebral Blood Flow Simulation Based on Commonly Available Clinical Datasets

Cerebral hemodynamics play an important role in the development of cerebrovascular diseases. In this work, we propose a numerical framework for modeling patient-specific cerebral blood flow, using commonly available clinical datasets. Our hemodynamic model was developed using Simscape Fluids library in Simulink, based on a block diagram language. Medical imaging data obtained from computerized tomography angiography (CTA) in 59 patients with aneurysmal subarachnoid hemorrhage was used to extract arterial geometry parameters. Flow information obtained from transcranial Doppler (TCD) measurement was employed to calibrate input parameters of the hemodynamic model. The results show that the proposed numerical model can reproduce blood flow in the circle of Willis (CoW) per patient per measurement set. The resistance at the distal end of each terminal branch was the predominant parameter for the flow distribution in the CoW. The proposed model may be a promising tool for assessing cerebral hemodynamics in patients with cerebrovascular disease.

Imaging Modalities for Intracranial Aneurysm: More Than Meets the Eye

Intracranial aneurysms (IA) are often asymptomatic and have a prevalence of 3 to 5% in the adult population. The risk of IA rupture is low, however when it occurs half of the patients dies from subarachnoid hemorrhage (SAH). To avoid this fatal evolution, the main treatment is an invasive surgical procedure, which is considered to be at high risk of rupture. This risk score of IA rupture is evaluated mainly according to its size and location. Therefore, angiography and anatomic imaging of the intracranial aneurysm are crucial for its diagnosis. Moreover, it has become obvious in recent years that several other factors are implied in this complication, such as the blood flow complexity or inflammation. These recent findings lead to the development of new IA imaging tools such as vessel wall imaging, 4D-MRI, or molecular MRI to visualize inflammation at the site of IA in human and animal models. In this review, we will summarize IA imaging techniques used for the patients and those currently in development.

Can Endovascular Treatment of Fusiform Intracranial Aneurysms Restore the Healthy Hemodynamic Environment?–A Virtual Pilot Study

Numerous studies assess intracranial aneurysm rupture risk based on morphological and hemodynamic parameter analysis in addition to clinical information such as aneurysm localization, age, and sex. However, intracranial aneurysms mostly occur with a saccular shape located either lateral to the parent artery or at a bifurcation. In contrast, fusiform intracranial aneurysms (FIAs), i.e., aneurysms with a non-saccular, dilated form, occur in approximately 3–13% of all cases and therefore have not yet been as thoroughly studied. To improve the understanding of FIA hemodynamics, this pilot study contains morphological analyses and image-based blood flow simulations in three patient-specific cases. For a precise and realistic comparison to the pre-pathological state, each dilation was manually removed and the time-dependent blood flow simulations were repeated. Additionally, a validated fast virtual stenting approach was applied to evaluate the effect of virtual endovascular flow-diverter deployment focusing on relevant hemodynamic quantities. For two of the three patients, post-interventional information was available and included in the analysis. The results of this numerical pilot study indicate that complex flow structures, i.e., helical flow phenomena and the presence of high oscillating flow features, predominantly occur in FIAs with morphologically differing appearances. Due to the investigation of the individual healthy states, the original flow environment could be restored which serves as a reference for the virtual treatment target. It was shown that the realistic deployment led to a considerable stabilization of the individual hemodynamics in all cases. Furthermore, a quantification of the stent-induced therapy effect became feasible for the treating physician. The results of the morphological and hemodynamic analyses in this pilot study show that virtual stenting can be used in FIAs to quantify the effect of the planned endovascular treatment.

Virtual embolization for treatment support of intracranial AVMs using an interactive desktop and VR application

PURPOSE

The treatment of intracranial arteriovenous malformations (AVM) is challenging due to their complex anatomy. For this vessel pathology, arteries are directly linked to veins without a capillary bed in between. For endovascular treatment, embolization is carried out, where the arteries that supply the AVM are consecutively blocked. A virtual embolization could support the medical expert in treatment planning.

METHOD

We designed and implemented an immersive VR application that allows the visualization of the simulated blood flow by displaying millions of particles. Furthermore, the user can interactively block or unblock arteries that supply the AVM and analyze the altered blood flow based on pre-computed simulations.

RESULTS

In a pilot study, the application was successfully adapted to three patient-specific cases. We performed a qualitative evaluation with two experienced neuroradiologist who regularly conduct AVM embolizations. The feature of virtually blocking or unblocking feeders was rated highly beneficial, and a desire for the inclusion of quantitative information was formulated.

CONCLUSION

The presented application allows for virtual embolization and interactive blood flow visualization in an immersive virtual reality environment. It could serve as useful addition for treatment planning and education in clinical practice, supporting the understanding of AVM topology as well as understanding the influence of the AVM's feeding arteries.

Aneurysm Wall Enhancement Is Associated With Decreased Intrasaccular IL-10 and Morphological Features of Instability

BACKGROUND

High-resolution vessel wall imaging plays an increasingly important role in assessing the risk of aneurysm rupture.

OBJECTIVE

To introduce an approach toward the validation of the wall enhancement as a direct surrogate parameter for aneurysm stability.

METHODS

A total of 19 patients harboring 22 incidental intracranial aneurysms were enrolled in this study. The aneurysms were dichotomized according to their aneurysm-to-pituitary stalk contrast ratio using a cutoff value of 0.5 (nonenhancing < 0.5; enhancing ≥ 0.5). We evaluated the association of aneurysm wall enhancement with morphological characteristics, hemodynamic features, and inflammatory chemokines directly measured inside the aneurysm.

RESULTS

Differences in plasma concentration of chemokines and inflammatory molecules, morphological, and hemodynamic parameters were analyzed using the Welch test or Mann-Whitney U test. The concentration ΔIL-10 in the lumen of intracranial aneurysms with low wall enhancement was significantly increased compared to aneurysms with strong aneurysm wall enhancement (P = .014). The analysis of morphological and hemodynamic parameters showed significantly increased values for aneurysm volume (P = .03), aneurysm area (P = .044), maximal diameter (P = .049), and nonsphericity index (P = .021) for intracranial aneurysms with strong aneurysm wall enhancement. None of the hemodynamic parameters reached statistical significance; however, the total viscous shear force computed over the region of low wall shear stress showed a strong tendency toward significance (P = .053).

CONCLUSION

Aneurysmal wall enhancement shows strong associations with decreased intrasaccular IL-10 and established morphological indicators of aneurysm instability.

Luminal enhancement in intracranial aneurysms: fact or feature?-A quantitative multimodal flow analysis

Purpose

Intracranial aneurysm (IA) wall enhancement on post-contrast vessel wall magnetic resonance imaging (VW-MRI) is assumed to be a biomarker for vessel wall inflammation and aneurysm instability. However, the exact factors contributing to enhancement are not yet clarified. This study investigates the relationship between luminal enhancement and intra-aneurysmal flow behaviour to assess the suitability of VW-MRI as a surrogate method for determining quantitative and qualitative flow behaviour in the aneurysm sac.

Methods

VW-MRI signal is measured in the lumen of three patient-specific IA flow models and compared with the intra-aneurysmal flow fields obtained using phase-contrast magnetic resonance imaging (PC-MRI) and computational fluid dynamics (CFD). The IA flow models were supplied with two different time-varying flow regimes.

Results

Overall, the velocity fields acquired using PC-MRI or CFD were in good agreement with the VW-MRI enhancement patterns. Generally, the regions with slow-flowing blood show higher VW-MRI signal intensities, whereas high flow leads to a suppression of the signal. For all aneurysm models, a signal value above three was associated with velocity values below three cm/s.

Conclusion

Regions with lower enhancements have been correlated with the slow and high flow at the same time. Thus, further factors like flow complexity and stability can contribute to flow suppression in addition to the flow magnitude. Nevertheless, VW-MRI can qualitatively assess intra-aneurysmal flow phenomena and estimate the velocity range present in the corresponding region.

Pseudo-Enhancement in Intracranial Aneurysms on Black-Blood MRI: Effects of Flow Rate, Spatial Resolution, and Additional Flow Suppression

BACKGROUND

Vessel-wall enhancement (VWE) on black-blood MRI (BB MRI) has been proposed as an imaging marker for a higher risk of rupture and associated with wall inflammation. Whether VWE is causally linked to inflammation or rather induced by flow phenomena has been a subject of debate.

PURPOSE

To study the effects of slow flow, spatial resolution, and motion-sensitized driven equilibrium (MSDE) preparation on signal intensities in BB MRI of patient-specific aneurysm flow models.

STUDY TYPE

Prospective.

SUBJECTS/FLOW ANEURYSM MODEL/VIRTUAL VESSELS

Aneurysm flow models based on 3D rotational angiography datasets of three patients with intracranial aneurysms were 3D printed and perfused at two different flow rates, with and without Gd-containing contrast agent.

FIELD STRENGTH/SEQUENCE

Variable refocusing flip angle 3D fast-spin echo sequence at 3 T with and without MSDE with three voxel sizes ((0.5 mm)³ , (0.7 mm)³ , and (0.9 mm)³ ); time-resolved with phase-contrast velocity-encoding 3D spoiled gradient echo sequence (4D flow MRI).

ASSESSMENT

Three independent observers performed a qualitative visual assessment of flow patterns and signal enhancement. Quantitative analysis included voxel-wise evaluation of signal intensities and magnitude velocity distributions in the aneurysm.

STATISTICAL TESTS

Kruskal-Wallis test, potential regressions.

RESULTS

A hyperintense signal in the lumen and adjacent to the aneurysm walls on BB MRI was colocalized with slow flow. Signal intensities increased by a factor of 2.56 ± 0.68 (P < 0.01) after administering Gd contrast. After Gd contrast administration, the signal was suppressed most in conjunction with high flows and with MSDE (2.41 ± 2.07 for slow flow without MSDE, and 0.87 ± 0.99 for high flow with MSDE). A clear result was not achieved by modifying the spatial resolution .

DATA CONCLUSIONS

Slow-flow phenomena contribute substantially to aneurysm enhancement and vary with MRI parameters. This should be considered in the clinical setting when assessing VWE in patients with an unruptured aneurysm.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

VICTORIA: VIrtual neck Curve and True Ostium Reconstruction of Intracranial Aneurysms

Purpose

For the status evaluation of intracranial aneurysms (IAs), morphological and hemodynamic parameters can provide valuable information. For their extraction, a separation of the aneurysm sac from its parent vessel is required that yields the neck curve and the ostium. However, manual and subjective neck curve and ostium definitions might lead to inaccurate IA assessments.

Methods

The research project VICTORIA was initiated, allowing users to interactively define the neck curve of five segmented IA models using a web application. The submitted results were qualitatively and quantitatively compared to identify the minimum, median and maximum aneurysm surface area. Finally, image-based blood flow simulations were carried out to assess the effect of variable neck curve definitions on relevant flow- and shear-related parameters.

Results

In total, 55 participants (20 physicians) from 18 countries participated in VICTORIA. For relatively simple aneurysms, a good agreement with respect to the neck curve definition was found. However, differences among the participants increased with increasing complexity of the aneurysm. Furthermore, it was observed that the majority of participants excluded any small arteries occurring in the vicinity of an aneurysm. This can lead to non-negligible deviations among the flow- and shear-related parameters, which need to be carefully evaluated, if quantitative analysis is desired. Finally, no differences between participants with medical and non-medical background could be observed.

Conclusions

VICTORIAs findings reveal the complexity of aneurysm neck curve definition, especially for bifurcation aneurysms. Standardization appears to be mandatory for future sac-vessel-separations. For hemodynamic simulations a careful neck curve definition is crucial to avoid inaccuracies during the quantitative flow analysis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13239-021-00535-w.

Correlation of Inflow Velocity Ratio Detected by Phase Contrast Magnetic Resonance Angiography with the Bleb Color of Unruptured Intracranial Aneurysms

BACKGROUND

Intraoperative rupture is the most fatal and catastrophic complication of surgery for unruptured intracranial aneurysms (UIAs); thus, it is extremely useful to predict reddish and thin-walled regions of the UIA before surgery. Although several studies have reported a relationship between the hemodynamic characteristics and intracranial aneurysm wall thickness, a consistent opinion is lacking. We aimed to investigate the relationship between objectively and quantitatively evaluated bleb wall color and hemodynamic characteristics using phase-contrast magnetic resonance angiography (PC-MRA).

METHODS

Ten patients diagnosed with UIA who underwent surgical clipping and preoperative magnetic resonance imaging along with PC-MRA were included in this study. Bleb wall color was evaluated from an intraoperative video. Based on the Red (R), Green, and Blue values, bleb wall redness (modified R value; mR) was calculated and compared with the hemodynamic characteristics obtained from PC-MRA.

RESULTS

The wall redness distribution of 18 blebs in 11 UIAs in 10 patients was analyzed. Bleb/neck inflow velocity ratio (Vb/Va: r = 0.66, P = 0.003) strongly correlated with mR, whereas bleb/neck inflow rate ratio (r = 0.58, P = 0.012) correlated moderately. Multivariate regression analysis revealed that only Vb/Va (P = 0.017) significantly correlated with mR. There was no correlation between wall shear stress and mR.

CONCLUSIONS

The bleb redness of UIAs and Vb/Va, calculated using PC-MRA, showed a significantly greater correlation. Thus, it is possible to predict bleb thickness noninvasively before surgery. This will facilitate more detailed pre- and intraoperative strategies for clipping and coiling for safe surgery.

Possible Association Between Rupture and Intranidal Microhemodynamics in Arteriovenous Malformations: Phase-Contrast Magnetic Resonance Angiography-Based Flow Quantification

OBJECTIVE

To examine a potential association between intranidal microhemodynamics and rupture using a phase-contrast magnetic resonance angiography (PCMRA)-based flow quantification technique in arteriovenous malformations (AVMs).

METHODS

We retrospectively collected data on 30 consecutive patients with AVMs (23 unruptured and 7 ruptured). Based on PCMRA data, maximal (V_max) and mean (V_mean) intranidal velocities were calculated. Logistic regression analysis was performed to assess factors associated with previous AVM rupture.

RESULTS

All ruptures occurred within 6 months before PCMRA. The mean nidus volume was 4.7 mL. Eleven patients (37%) had deep draining vein(s), and 6 patients (20%) had a deep-seated nidus. The mean ± standard deviation V_mean and V_max were 9.6 ± 2.8 cm/second and 66.7 ± 26.2 cm/second, respectively. The logistic regression analyses revealed that higher V_max (P = 0.075, unit odds ratio [OR] = 1.05, 95% confidence interval [95% CI] = 1.00-1.10) was significantly associated with prior hemorrhage. The receiver-operating curve analyses demonstrated that a V_mean of 10.8 cm/second (area under the curve = 0.671) and V_max of 90.2 cm/second (area under the curve = 0.764) maximized the Youden Index. A V_max > 90 cm/second was significantly associated with AVM rupture both in the univariate (P = 0.025, OR = 9.0, 95% CI = 1.3-61.1) and multivariate (P = 0.008, OR = 51.7, 95% CI = 2.8-968.3) analyses.

CONCLUSIONS

Presence of faster velocities in intranidal vessels may suggest aberrant microhemodynamics and thus be associated with AVM rupture. PCMRA-based velocimetry seems to be a promising tool to predict future AVM rupture.

Complex wall modeling for hemodynamic simulations of intracranial aneurysms based on histologic images

Purpose

For the evaluation and rupture risk assessment of intracranial aneurysms, clinical, morphological and hemodynamic parameters are analyzed. The reliability of intracranial hemodynamic simulations strongly depends on the underlying models. Due to the missing information about the intracranial vessel wall, the patient-specific wall thickness is often neglected as well as the specific physiological and pathological properties of the vessel wall.

Methods

In this work, we present a model for structural simulations with patient-specific wall thickness including different tissue types based on postmortem histologic image data. Images of histologic 2D slices from intracranial aneurysms were manually segmented in nine tissue classes. After virtual inflation, they were combined into 3D models. This approach yields multiple 3D models of the inner and outer wall and different tissue parts as a prerequisite for subsequent simulations.

Result

We presented a pipeline to generate 3D models of aneurysms with respect to the different tissue textures occurring in the wall. First experiments show that including the variance of the tissue in the structural simulation affect the simulation result. Especially at the interfaces between neighboring tissue classes, the larger influence of stiffer components on the stability equilibrium became obvious.

Conclusion

The presented approach enables the creation of a geometric model with differentiated wall tissue. This information can be used for different applications, like hemodynamic simulations, to increase the modeling accuracy.

Digital Twins for Tissue Culture Techniques—Concepts, Expectations, and State of the Art

Techniques to provide in vitro tissue culture have undergone significant changes during the last decades, and current applications involve interactions of cells and organoids, three-dimensional cell co-cultures, and organ/body-on-chip tools. Efficient computer-aided and mathematical model-based methods are required for efficient and knowledge-driven characterization, optimization, and routine manufacturing of tissue culture systems. As an alternative to purely experimental-driven research, the usage of comprehensive mathematical models as a virtual in silico representation of the tissue culture, namely a digital twin, can be advantageous. Digital twins include the mechanistic of the biological system in the form of diverse mathematical models, which describe the interaction between tissue culture techniques and cell growth, metabolism, and the quality of the tissue. In this review, current concepts, expectations, and the state of the art of digital twins for tissue culture concepts will be highlighted. In general, DT’s can be applied along the full process chain and along the product life cycle. Due to the complexity, the focus of this review will be especially on the design, characterization, and operation of the tissue culture techniques.

Stent-Induced Vascular Remodeling in Two-Step Stent-Assisted Coiling Treatment of Brain Aneurysms: A Closer Look Into the Hemodynamic Changes During the Stent Healing Period

Stenting has become an important adjunctive tool for assisting coil embolization in complex-shaped intracranial aneurysms. However, as a secondary effect, stent deployment has been related to both immediate and delayed remodeling of the local vasculature. Recent studies have demonstrated that this phenomenon may assume different roles depending on the treatment stage. However, the extent of such event on the intra-aneurysmal hemodynamics is still unclear; especially when performing two-step stent-assisted coiling (SAC). Therefore, we performed computational fluid dynamics (CFD) analysis of the blood flow in four bifurcation aneurysms focusing on the stent healing period found in SAC as a two-step maneuver. Our results show that by changing the local vasculature, the intra-aneurysmal hemodynamics changes considerably. However, even though changes do occur, they were not consistent among the cases. Furthermore, by changing the local vasculature not only the shear levels change but also the shear distribution on the aneurysm surface. Additionally, a geometric analysis alone can mislead the estimation of the novel hemodynamic environment after vascular remodeling, especially in the presence of mixing streams. Therefore, although the novel local vasculature might induce an improved hemodynamic environment, it is also plausible to expect that adverse hemodynamic conditions might occur. This could pose a particularly delicate condition since the aneurysm surface remains completely exposed to the novel hemodynamic environment during the stent healing period. Finally, our study emphasizes that vascular remodeling should be considered when assessing the hemodynamics in aneurysms treated with stents, especially when evaluating the earlier stages of the treatment process.

Central moments multiple relaxation time LBM for hemodynamic simulations in intracranial aneurysms: An in-vitro validation study using PIV and PC-MRI

The lattice Boltzmann method (LBM) has recently emerged as an efficient alternative to classical Navier-Stokes solvers. This is particularly true for hemodynamics in complex geometries. However, in its most basic formulation, i.e. with the so-called single relaxation time (SRT) collision operator, it has been observed to have a limited stability domain in the Courant/Fourier space, strongly constraining the minimum time-step and grid size. The development of improved collision models such as the multiple relaxation time (MRT) operator in central moments space has tremendously widened the stability domain, while allowing to overcome a number of other well-documented artifacts, therefore opening the door for simulations over a wider range of grid and time-step sizes. The present work focuses on implementing and validating a specific collision operator, the central Hermite moments multiple relaxation time model with the full expansion of the equilibrium distribution function, to simulate blood flows in intracranial aneurysms. The study further proceeds with a validation of the numerical model through different test-cases and against experimental measurements obtained via stereoscopic particle image velocimetry (PIV) and phase-contrast magnetic resonance imaging (PC-MRI). For a patient-specific aneurysm both PIV and PC-MRI agree fairly well with the simulation. Finally, low-resolution simulations were shown to be able to capture blood flow information with sufficient accuracy, as demonstrated through both qualitative and quantitative analysis of the flow field while leading to strongly reduced computation times. For instance in the case of the patient-specific configuration, increasing the grid-size by a factor of two led to a reduction of computation time by a factor of 14 with very good similarity indices still ranging from 0.83 to 0.88.

Middle cerebral artery pressure laterality in patients with symptomatic ICA stenosis

An internal carotid artery (ICA) stenosis can potentially decrease the perfusion pressure to the brain. In this study, computational fluid dynamics (CFD) was used to study if there was a hemispheric pressure laterality between the contra- and ipsilateral middle cerebral artery (MCA) in patients with a symptomatic ICA stenosis. We further investigated if this MCA pressure laterality (ΔPMCA) was related to the hemispheric flow laterality (ΔQ) in the anterior circulation, i.e., ICA, proximal MCA and the proximal anterior cerebral artery (ACA). Twenty-eight patients (73±6 years, range 59-80 years, 21 men) with symptomatic ICA stenosis were included. Flow rates were measured using 4D flow MRI data (PC-VIPR) and vessel geometries were obtained from computed tomography angiography. The ΔPMCA was calculated from CFD, where patient-specific flow rates were applied at all input- and output boundaries. The ΔPMCA between the contra- and ipsilateral side was 6.4±8.3 mmHg (p<0.001) (median 3.9 mmHg, range -1.3 to 31.9 mmHg). There was a linear correlation between the ΔPMCA and ΔQICA (r = 0.85, p<0.001) and ΔQACA (r = 0.71, p<0.001), respectively. The correlation to ΔQMCA was weaker (r = 0.47, p = 0.011). In conclusion, the MCA pressure laterality obtained with CFD, is a promising physiological biomarker that can grade the hemodynamic disturbance in patients with a symptomatic ICA stenosis.

Modeling and Reducing the Effect of Geometric Uncertainties in Intracranial Aneurysms with Polynomial Chaos Expansion, Data Decomposition, and 4D-Flow MRI

PURPOSE

Variations in the vessel radius of segmented surfaces of intracranial aneurysms significantly influence the fluid velocities given by computer simulations. It is important to generate models that capture the effect of these variations in order to have a better interpretation of the numerically predicted hemodynamics. Also, it is highly relevant to develop methods that combine experimental observations with uncertainty modeling to get a closer approximation to the blood flow behavior.

METHODS

This work applies polynomial chaos expansion to model the effect of geometric uncertainties on the simulated fluid velocities of intracranial aneurysms. The radius of the vessel is defined as the uncertainty variable. Proper orthogonal decomposition is applied to characterize the solution space of fluid velocities. Next, a process of projecting the 4D-Flow MRI velocities on the basis vectors followed by coefficient mapping using generalized dynamic mode decomposition enables the merging of 4D-Flow MRI with the uncertainty propagated fluid velocities.

RESULTS

Polynomial chaos expansion propagates the fluid velocities with an error of 2% in velocity magnitude relative to computer simulations. Also, the bifurcation region (or impingement location) shows a standard deviation of 0.17 m/s (since an available reported variance in the vessel radius is adopted to model the uncertainty, the expected standard deviation may be different). Numerical phantom experiments indicate that the proposed approach reconstructs the fluid velocities with 0.3% relative error in presence of geometric uncertainties.

CONCLUSION

Polynomial chaos expansion is an effective approach to propagate the effect of the uncertainty variable in the blood flow velocities of intracranial aneurysms. Merging 4D-Flow MRI and uncertainty propagated fluid velocities leads to more realistic flow trends relative to ignoring the uncertainty in the vessel radius.

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.

Rupture risk assessment for multiple intracranial aneurysms: why there is no need for dozens of clinical, morphological and hemodynamic parameters

Introduction:

A multitude of approaches have been postulated for assessing the risk of intracranial aneurysm rupture. However, the amount of potential predictive factors is not applicable in clinical practice and they are rejected in favor of the more practical PHASES score. For the subgroup of multiple intracranial aneurysms (MIAs), the PHASES score might severely underestimate the rupture risk, as only the aneurysm with the largest diameter is considered for risk evaluation.

Methods:

In this study, we investigated 38 patients harboring a total number of 87 MIAs with respect to their morphological and hemodynamical characteristics. For the determination of the best suited parameters regarding their predictive power for aneurysm rupture, we conducted three phases of statistical evaluation. The statistical analysis aimed to identify parameters that differ significantly between ruptured and unruptured aneurysms, show smallest possible correlations among each other and have a high impact on rupture risk prediction.

Results:

Significant differences between ruptured and unruptured aneurysms were found in 16 out of 49 parameters. The lowest correlation were found for gamma, aspect ratio (AR1), aneurysm maximal relative residence time (Aneurysm_RRT_max) and aneurysm mean relative residence time. The data-driven parameter selection yielded a significant correlation of only two parameters (AR1 and the Aneurysm_RRT_max) with rupture state (area under curve = 0.75).

Conclusion:

A high number of established morphological and hemodynamical parameters seem to have no or only low effect on prediction of aneurysm rupture in patients with MIAs. For best possible rupture risk assessment of patients with MIAs, only the morphological parameter AR1 and the hemodynamical parameter Aneurysm_RRT_max need to be included in the prediction model.

Super-resolution and denoising of 4D-Flow MRI using physics-Informed deep neural nets

BACKGROUND AND OBJECTIVE

Time resolved three-dimensional phase contrast magnetic resonance imaging (4D-Flow MRI) has been used to non-invasively measure blood velocities in the human vascular system. However, issues such as low spatio-temporal resolution, acquisition noise, velocity aliasing, and phase-offset artifacts have hampered its clinical application. In this research, we developed a purely data-driven method for super-resolution and denoising of 4D-Flow MRI.

METHODS

The flow velocities, pressure, and the MRI image magnitude are modeled as a patient-specific deep neural net (DNN). For training, 4D-Flow MRI images in the complex Cartesian space are used to impose data-fidelity. Physics of fluid flow is imposed through regularization. Creative loss function terms have been introduced to handle noise and super-resolution. The trained patient-specific DNN can be sampled to generate noise-free high-resolution flow images. The proposed method has been implemented using the TensorFlow DNN library and tested on numerical phantoms and validated in-vitro using high-resolution particle image velocitmetry (PIV) and 4D-Flow MRI experiments on transparent models subjected to pulsatile flow conditions.

RESULTS

In case of numerical phantoms, we were able to increase spatial resolution by a factor of 100 and temporal resolution by a factor of 5 compared to the simulated 4D-Flow MRI. There is an order of magnitude reduction of velocity normalized root mean square error (vNRMSE). In case of the in-vitro validation tests with PIV as reference, there is similar improvement in spatio-temporal resolution. Although the vNRMSE is reduced by 50%, the method is unable to negate a systematic bias with respect to the reference PIV that is introduced by the 4D-Flow MRI measurement.

CONCLUSIONS

This work has demonstrated the feasibility of using the readily available machinery of deep learning to enhance 4D-Flow MRI using a purely data-driven method. Unlike current state-of-the-art methods, the proposed method is agnostic to geometry and boundary conditions and therefore eliminates the need for tedious tasks such as accurate image segmentation for geometry, image registration, and estimation of boundary flow conditions. Arbitrary regions of interest can be selected for processing. This work will lead to user-friendly analysis tools that will enable quantitative hemodynamic analysis of vascular diseases in a clinical setting.

Characterization of anisotropic turbulence behavior in pulsatile blood flow

Turbulent-like hemodynamics with prominent cycle-to-cycle flow variations have received increased attention as a potential stimulus for cardiovascular diseases. These turbulent conditions are typically evaluated in a statistical sense from single scalars extracted from ensemble-averaged tensors (such as the Reynolds stress tensor), limiting the amount of information that can be used for physical interpretations and quality assessments of numerical models. In this study, barycentric anisotropy invariant mapping was used to demonstrate an efficient and comprehensive approach to characterize turbulence-related tensor fields in patient-specific cardiovascular flows, obtained from scale-resolving large eddy simulations. These techniques were also used to analyze some common modeling compromises as well as MRI turbulence measurements through an idealized constriction. The proposed method found explicit sites of elevated turbulence anisotropy, including a broad but time-varying spectrum of characteristics over the flow deceleration phase, which was different for both the steady inflow and Reynolds-averaged Navier–Stokes modeling assumptions. Qualitatively, the MRI results showed overall expected post-stenotic turbulence characteristics, however, also with apparent regions of unrealizable or conceivably physically unrealistic conditions, including the highest turbulence intensity ranges. These findings suggest that more detailed studies of MRI-measured turbulence fields are needed, which hopefully can be assisted by more comprehensive evaluation tools such as the once described herein.

How patient-specific do internal carotid artery inflow rates need to be for computational fluid dynamics of cerebral aneurysms?

BACKGROUND

Computational fluid dynamics (CFD) has become a popular tool for studying 'patient-specific' blood flow dynamics in cerebral aneurysms; however, rarely are the inflow boundary conditions patient-specific. We aimed to test the impact of widespread reliance on generalized inflow rates.

METHODS

Internal carotid artery (ICA) flow rates were measured via 2D cine phase-contrast MRI for 24 patients scheduled for endovascular therapy of an ICA aneurysm. CFD models were constructed from 3D rotational angiography, and pulsatile inflow rates imposed as measured by MRI or estimated using an average older-adult ICA flow waveform shape scaled by a cycle-average flow rate (Q_avg) derived from the patient's ICA cross-sectional area via an assumed inlet velocity.

RESULTS

There was good overall qualitative agreement in the magnitudes and spatial distributions of time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), and spectral power index (SPI) using generalized versus patient-specific inflows. Sac-averaged quantities showed moderate to good correlations: R²=0.54 (TAWSS), 0.80 (OSI), and 0.68 (SPI). Using patient-specific Q_avg to scale the generalized waveform shape resulted in near-perfect agreement for TAWSS, and reduced bias, but not scatter, for SPI. Patient-specific waveform had an impact only on OSI correlations, which improved to R²=0.93.

CONCLUSIONS

Aneurysm CFD demonstrates the ability to stratify cases by nominal hemodynamic 'risk' factors when employing an age- and vascular-territory-specific recipe for generalized inflow rates. Q_avg has a greater influence than waveform shape, suggesting some improvement could be achieved by including measurement of patient-specific Q_avg into aneurysm imaging protocols.