Quantitative characterization of the hemodynamic environment in ruptured and unruptured brain aneurysms

A model with multiple intracranial aneurysms: possible hemodynamic mechanisms of aneurysmal initiation, rupture and recurrence

BACKGROUND

Hemodynamic factors play an important role in aneurysm initiation, growth, rupture, and recurrence, while the mechanism of the hemodynamic characteristics is still controversial. A unique model of multiple aneurysms (initiation, growth, rupture, and recurrence) is helpful to avoids the confounders and further explore the possible hemodynamic mechanisms of aneurysm in different states.

METHODS

We present a model with multiple aneurysms, and including the states of initiation, growth, rupture, and recurrence, discuss the proposed mechanisms, and describe computational fluid dynamic model that was used to evaluate the likely hemodynamic effect of different states of the aneurysms.

RESULTS

The hemodynamic analysis suggests that high flow impingement and high WSS distribution at normal parent artery was found before aneurysmal initiation. The WSS distribution and flow velocity were decreased in the new sac after aneurysmal growth. Low WSS was the risk hemodynamic factor for aneurysmal rupture. High flow concentration region on the neck plane after coil embolization still marked in recanalized aneurysm.

CONCLUSIONS

Associations have been identified between high flow impingement and aneurysm recanalization, while low WSS is linked to the rupture of aneurysms. High flow concentration and high WSS distribution at normal artery associated with aneurysm initiation and growth, while after growth, the high-risk hemodynamics of aneurysm rupture was occurred, which is low WSS at aneurysm dome.

Hemodynamic characteristics and mechanism for intracranial aneurysms initiation with the circle of Willis anomaly

Clinically, circle of Willis (CoW) is prone to anomaly and is also the predominant incidence site of intracranial aneurysms (IAs). This study aims to investigate the hemodynamic characteristics of CoW anomaly, and ascertain the mechanism of IAs initiation from the perspective of hemodynamics. Thus, the flow of IAs and pre-IAs were analyzed for one type of cerebral artery anomaly, that is, anterior cerebral artery A1 segment (ACA-A1) unilateral absence. Three patient geometrical models with IAs were selected from Emory University Open Source Data Center. IAs were virtually removed from the geometrical models to simulate the pre-IAs geometry. For calculation methods, a one-dimensional (1-D) solver and a three-dimensional (3-D) solver were combined to obtain the hemodynamic characteristics. The numerical simulation revealed that the average flow of Anterior Communicating Artery (ACoA) is almost zero when CoW is complete. In contrast, ACoA flow increases significantly in the case of ACA-A1 unilateral absence. For per-IAs geometry, the jet flow is found at the bifurcation between contralateral ACA-A1 and ACoA, which exhibits characteristics of high Wall Shear Stress (WSS) and high wall pressure in the impact region. It triggers the initiation of IAs from the perspective of hemodynamics. The vascular anomaly that leads to jet flow should be considered as a risk factor for IAs initiation.

A Computational Pipeline to Investigate Longitudinal Blood Flow Changes in the Circle of Willis of Patients with Stable and Growing Aneurysms

Changes in cerebral blood flow are often associated with the initiation and development of different life-threatening medical conditions including aneurysm rupture and ischemic stroke. Nevertheless, it is not fully clear how haemodynamic changes in time across the Circle of Willis (CoW) are related with intracranial aneurysm (IA) growth. In this work, we introduced a novel reduced-order modelling strategy for the systematic quantification of longitudinal blood flow changes across the whole CoW in patients with stable and unstable/growing aneurysm. Magnetic Resonance Angiography (MRA) images were converted into one-dimensional (1-D) vessel networks through a semi-automated procedure, with a level of geometric reconstruction accuracy controlled by user-dependent parameters. The proposed pipeline was used to systematically analyse longitudinal haemodynamic changes in seven different clinical cases. Our preliminary simulation results indicate that growing aneurysms are not necessarily associated with significant changes in mean flow over time. A concise sensitivity analysis also shed light on which modelling aspects need to be further characterized to have reliable patient-specific predictions. This study poses the basis for investigating how time-dependent changes in the vasculature affect the haemodynamics across the whole CoW in patients with stable and growing aneurysms.

Differences and Correlations of Morphological and Hemodynamic Parameters between Anterior Circulation Bifurcation and Side-wall Aneurysms

OBJECTIVE

The objective of this research was to explore the difference and correlation of the morphological and hemodynamic features between sidewall and bifurcation aneurysms in anterior circulation arteries, utilizing computational fluid dynamics as a tool for analysis.

METHODS

In line with the designated inclusion criteria, this study covered 160 aneurysms identified in 131 patients who received treatment at Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, China, from January 2021 to September 2022. Utilizing follow-up digital subtraction angiography (DSA) data, these cases were classified into two distinct groups: the sidewall aneurysm group and the bifurcation aneurysm group. Morphological and hemodynamic parameters in the immediate preoperative period were meticulously calculated and examined in both groups using a three-dimensional DSA reconstruction model.

RESULTS

No significant differences were found in the morphological or hemodynamic parameters of bifurcation aneurysms at varied locations within the anterior circulation. However, pronounced differences were identified between sidewall and bifurcation aneurysms in terms of morphological parameters such as the diameter of the parent vessel (Dvessel), inflow angle (θF), and size ratio (SR), as well as the hemodynamic parameter of inflow concentration index (ICI) (P<0.001). Notably, only the SR exhibited a significant correlation with multiple hemodynamic parameters (P<0.001), while the ICI was closely related to several morphological parameters (R>0.5, P<0.001).

CONCLUSIONS

The significant differences in certain morphological and hemodynamic parameters between sidewall and bifurcation aneurysms emphasize the importance to contemplate variances in threshold values for these parameters when evaluating the risk of rupture in anterior circulation aneurysms. Whether it is a bifurcation or sidewall aneurysm, these disparities should be considered. The morphological parameter SR has the potential to be a valuable clinical tool for promptly distinguishing the distinct rupture risks associated with sidewall and bifurcation aneurysms.

Nomograms for assessing the rupture risk of anterior choroid artery aneurysms based on clinical, morphological, and hemodynamic features

Background and purpose

A notable prevalence of subarachnoid hemorrhage is evident among patients with anterior choroidal artery aneurysms in clinical practice. To evaluate the risk of rupture in unruptured anterior choroidal artery aneurysms, we conducted a comprehensive analysis of risk factors and subsequently developed two nomograms.

Methods

A total of 120 cases of anterior choroidal artery aneurysms (66 unruptured and 54 ruptured) from 4 medical institutions were assessed utilizing computational fluid dynamics (CFD) and digital subtraction angiography (DSA). The training set, consisting of 98 aneurysms from 3 hospitals, was established, with an additional 22 cases from the fourth hospital forming the external validation set. Statistical differences between the two data sets were thoroughly compared. The significance of 9 clinical baseline characteristics, 11 aneurysm morphology parameters, and 4 hemodynamic parameters concerning aneurysm rupture was evaluated within the training set. Candidate selection for constructing the nomogram models involved regression analysis and variance inflation factors. Discrimination, calibration, and clinical utility of the models in both training and validation sets were assessed using area under curves (AUC), calibration plots, and decision curve analysis (DCA). The DeLong test, net reclassification index (NRI), and integrated discrimination improvement (IDI) were employed to compare the effectiveness of classification across models.

Results

Two nomogram models were ultimately constructed: model 1, incorporating clinical, morphological, and hemodynamic parameters (C + M + H), and model 2, relying primarily on clinical and morphological parameters (C + M). Multivariate analysis identified smoking, size ratio (SR), normalized wall shear stress (NWSS), and average oscillatory shear index (OSIave) as optimal candidates for model development. In the training set, model 1 (C + M + H) achieved an AUC of 0.795 (95% CI: 0.706 ~ 0.884), demonstrating a sensitivity of 95.6% and a specificity of 54.7%. Model 2 (C + M) had an AUC of 0.706 (95% CI: 0.604 ~ 0.808), with corresponding sensitivity and specificity of 82.4 and 50.3%, respectively. Similarly, AUCs for models 1 and 2 in the external validation set were calculated to be 0.709 and 0.674, respectively. Calibration plots illustrated a consistent correlation between model evaluations and real-world observations in both sets. DCA demonstrated that the model incorporating hemodynamic parameters offered higher clinical benefits. In the training set, NRI (0.224, p = 0.007), IDI (0.585, p = 0.002), and DeLong test (change = 0.089, p = 0.008) were all significant. In the external validation set, NRI, IDI, and DeLong test statistics were 0.624 (p = 0.063), 0.572 (p = 0.044), and 0.035 (p = 0.047), respectively.

Conclusion

Multidimensional nomograms have the potential to enhance risk assessment and patient-specific treatment of anterior choroidal artery aneurysms. Validated by an external cohort, the model incorporating clinical, morphological, and hemodynamic features may provide improved classification of rupture states.

The biomechanical effects of different membrane layer structures and material constitutive modeling on patient-specific cerebral aneurysms

The prevention, control and treatment of cerebral aneurysm (CA) has become a common concern of human society, and by simulating the biomechanical environment of CA using finite element analysis (FEA), the risk of aneurysm rupture can be predicted and evaluated. The target models of the current study are mainly idealized single-layer linear elastic cerebral aneurysm models, which do not take into account the effects of the vessel wall structure, material constitution, and structure of the real CA model on the mechanical parameters. This study proposes a reconstruction method for patient-specific trilaminar CA structural modeling. Using two-way fluid-structure interaction (FSI), we comparatively analyzed the effects of the differences between linear and hyperelastic materials and three-layer and single-layer membrane structures on various hemodynamic parameters of the CA model. It was found that the numerical effects of the different CA membrane structures and material constitution on the stresses and wall deformations were obvious, but does not affect the change in its distribution pattern and had little effect on the blood flow patterns. For the same material constitution, the stress of the three-layer membrane structure were more than 10.1% larger than that of the single-layer membrane structure. For the same membrane structure, the stress of the hyperelastic material were more than 5.4% larger than that of the linear elastic material, and the displacement of the hyperelastic material is smaller than that of the linear elastic material by about 20%. And the maximum value of stress occurred in the media, and the maximum displacement occurred in the intima. In addition, the upper region of the tumor is the maximum rupture risk region for CA, and the neck of the tumor and the bifurcation of the artery are also the sub-rupture risk regions to focus on. This study can provide data support for the selection of model materials for CA simulation and analysis, as well as a theoretical basis for clinical studies and subsequent research methods.

Assessing the risk of intracranial aneurysm rupture using computational fluid dynamics: a pilot study

Objective

This study compared 2 representative cases with ruptured aneurysms to explore the role of hemodynamic and morphological parameters in evaluating the rupture risk of intracranial aneurysms (IAs).

Methods

CTA and 3-dimensional rotational angiography (3DRA) of 3 IAs in 2 patients were retrospectively analyzed in this study. Hemodynamics and morphological parameters were compared between a ruptured IA and an unruptured IA in case1, and between before and after aneurysm rupture in case 2.

Results

In case 1, the ruptured aneurysm had larger morphological parameters including size ratio (SR), aspect ratio (AR), aneurysm vessel angle (θF), Aneurysm inclination angle (θA), Undulation index (UI), Ellipticity index (EI), and Non-sphericity Index (NSI) than the unruptured aneurysm. And oscillatory shear index (OSI) is also larger. Higher rupture resemblance score (RRS) was shown in the ruptured aneurysm. In case 2, the aneurysm had one daughter sac after 2 years. Partial morphological and hemodynamic parameters including SR, AR, θF, θA, UI, EI, NSI, OSI, and relative residence time (RRT) increased, and normalized wall shear stress (NWSS) was significantly reduced. RRS increased during this period.

Conclusion

SR and OSI may have predictive values for the risk of intracranial aneurysm rupture. It is possible that WSS Changes before and after IA rupture, yet the influence of high or low WSS on growth and rupture of IA remains unclear. RRS is promising to be used in the clinical assessment of the rupture risk of IAs and to guide the formulation of treatment plans.

A matched-pair case control study identifying hemodynamic predictors of cerebral aneurysm growth using computational fluid dynamics

Introduction: Initiation and progression of cerebral aneurysms is known to be driven by complex interactions between biological and hemodynamic factors, but the hemodynamic mechanism which drives aneurysm growth is unclear. We employed robust modeling and computational methods, including temporal and spatial convergence studies, to study hemodynamic characteristics of cerebral aneurysms and identify differences in these characteristics between growing and stable aneurysms. Methods: Eleven pairs of growing and non-growing cerebral aneurysms, matched in both size and location, were modeled from MRA and CTA images, then simulated using computational fluid dynamics (CFD). Key hemodynamic characteristics, including wall shear stress (WSS), oscillatory shear index (OSI), and portion of the aneurysm under low shear, were evaluated. Statistical analysis was then performed using paired Wilcoxon rank sum tests. Results: The portion of the aneurysm dome under 70% of the parent artery mean wall shear stress was higher in growing aneurysms than in stable aneurysms and had the highest significance among the tested metrics (p = 0.08). Other metrics of area under low shear had similar levels of significance. Discussion: These results align with previously observed hemodynamic trends in cerebral aneurysms, indicating a promising direction for future study of low shear area and aneurysm growth. We also found that mesh resolution significantly affected simulated WSS in cerebral aneurysms. This establishes that robust computational modeling methods are necessary for high fidelity results. Together, this work demonstrates that complex hemodynamics are at play within cerebral aneurysms, and robust modeling and simulation methods are needed to further study this topic.

Clinical, 3D Morphological, and Hemodynamic Risk Factors for Instability of Unruptured Intracranial Aneurysms

PURPOSE

Neurosurgeons can manage unruptured intracranial aneurysms (UIAs). However, the stability of UIAs under follow-up remains uncertain. This study aimed to examine the risk factors associated with the instability (rupture or growth) of UIAs during follow-up.

METHODS

We obtained information on patients with UIA who underwent ≥ 6 months of the time of flight-magnetic resonance angiography (TOF-MRA) imaging follow-up in two centers. Computer-assisted semi-automated measurement (CASAM) techniques were used for recording morphological parameters and determining the growth of these aneurysms. We also recorded hemodynamic parameters at the beginning of the follow-up. The univariate and multivariate Cox regression analyses were performed to calculate hazard ratios with corresponding 95% confidence intervals for the clinical, morphological, and hemodynamic risk factors for aneurysm instability.

RESULTS

A total of 304 aneurysms from 263 patients (80.4%) were included for analysis. The annual aneurysm growth rate was 4.7%. Significant predictive factors for aneurysm instability in the multivariate analysis were as follows: poorly controlled hypertension (hazard ratio (HR), 2.97 (95% CI, 1.27-6.98), P = 0.012); aneurysms located on posterior circulation (HR, 7.81 (95% CI, 2.28-26.73), P = 0.001), posterior communication artery (HR, 3.01 (95% CI, 1.07-8.46), P = 0.036), and cavernous carotid artery (HR, 3.78 (95% CI, 1.18-12.17), P = 0.026); and size ratio ≥ 0.87 (HR, 2.54 (95% CI, 1.14-5.68), P = 0.023).

CONCLUSIONS

The management of UIAs should focus on the control of hypertension during the follow-up. Aneurysms on the posterior communicating artery, posterior circulation, and cavernous carotid arteries require intensive surveillance or timely treatment.

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.

Assessing a heterogeneous model for accounting for endovascular devices in hemodynamic simulations of cerebral aneurysms

The heterogeneous model developed by Berod et al [Int J Numer Method Biomed Eng 38, 2021] for representing the hemodynamic effects of endovascular prostheses is applied to a series of 10 patient specific cerebral aneurysms, 6 being treated by flow diverters, 4 being equipped with WEBs. Two markers correlated with the medical outcome of the treatment are used to assess the potential of the model, namely the saccular mean velocity and the inflow rate at the neck of the aneurysm. The comparison with the corresponding wire-resolved simulations is very favorable in both cases, and the model-based simulations also retrieve the jetting-type flows generated downstream of the struts. Noteworthy, the very same model was used for representing the flow diverters and the WEBs, showing the versatility and robustness of the heterogeneous modeling of the devices.

Aneurysmal Inflow Rate Coefficient Predicts Ultra-early Rebleeding in Ruptured Intracranial Aneurysms: Preliminary Report of a Computational Fluid Dynamics Study

Rebleeding from a ruptured intracranial aneurysm has poor outcomes. Although numerous factors are associated with rebleeding, studies on computational fluid dynamics (CFD) on hemodynamic parameters associated with early rebleeding are scarce. In particular, no report of rebleeding in ultra-early phase exists. We aimed to elucidate the specific hemodynamic parameters associated with ultra-early rebleeding using CFD. In this study, the rebleeding group included patients with aneurysmal subarachnoid hemorrhage (aSAH) that rebled within 6 h from the onset. The control group included patients without rebleeding, observed for >10 h following the initial rupture. Clinical images after initial rupture and before rebleeding were used to build 3D vessel models for hemodynamic analysis focusing on the following parameters: time-averaged wall shear stress (WSS), normalized WSS, low shear area, oscillatory shear index, relative residence time, pressure loss coefficient, and aneurysmal inflow rate coefficient (AIRC). Five and 15 patients in the rebleeding and control groups, respectively, met the inclusion criteria. The World Federation of Neurosurgical Surgeons grade was significantly higher in the rebleeding group (p = 0.0088). Hemodynamic analysis showed significantly higher AIRC in the rebleeding group (p = 0.042). The other parameters were not significantly different between groups. There were no significant differences or correlations between SAH severity and AIRC. AIRC was identified as a hemodynamic parameter associated with ultra-early rebleeding of ruptured intracranial aneurysms. Thus, AIRC calculation may enable the prediction of ultra-early rebleeding.

How does the recurrence-related morphology characteristics of the Pcom aneurysms correlated with hemodynamics?

Introduction

Posterior communicating artery (Pcom) aneurysm has unique morphological characteristics and a high recurrence risk after coil embolization. This study aimed to evaluate the relationship between the recurrence-related morphology characteristics and hemodynamics.

Method

A total of 20 patients with 22 Pcom aneurysms from 2019 to 2022 were retrospectively enrolled. The recurrence-related morphology parameters were measured. The hemodynamic parameters were simulated based on finite element analysis and computational fluid dynamics. The hemodynamic differences before and after treatment caused by different morphological features and the correlation between these parameters were analyzed.

Result

Significant greater postoperative inflow rate at the neck (Qinflow), relative Qinflow, inflow concentration index (ICI), and residual flow volume (RFV) were reported in the aneurysms with wide neck (>4 mm). Significant greater postoperative RFV were reported in the aneurysms with large size (>7 mm). Significant greater postoperative Qinflow, relative Qinflow, and ICI were reported in the aneurysms located on the larteral side of the curve. The bending angle of the internal carotid artery at the initiation of Pcom (αICA@PCOM) and neck diameter had moderate positive correlations with Qinflow, relative Qinflow, ICI, and RFV.

Conclusion

The morphological factors, including aneurysm size, neck diameter, and αICA@PCOM, are correlated with the recurrence-inducing hemodynamic characteristics even after fully packing. This provides a theoretical basis for evaluating the risk of aneurysm recurrence and a reference for selecting a surgical plan.

Common mechanisms of physiological and pathological rupture events in biology: novel insights into mammalian ovulation and beyond

Ovulation is a cyclical biological rupture event fundamental to fertilisation and endocrine function. During this process, the somatic support cells that surround the germ cell undergo a remodelling process that culminates in breakdown of the follicle wall and release of a mature egg. Ovulation is driven by known proteolytic and inflammatory pathways as well as structural alterations to the follicle vasculature and the fluid-filled antral cavity. Ovulation is one of several types of systematic remodelling that occur in the human body that can be described as rupture. Although ovulation is a physiological form of rupture, other types of rupture occur in the human body which can be pathological, physiological, or both. In this review, we use intracranial aneurysms and chorioamniotic membrane rupture as examples of rupture events that are pathological or both pathological and physiological, respectively, and compare these to the rupture process central to ovulation. Specifically, we compared existing transcriptomic profiles, immune cell functions, vascular modifications, and biomechanical forces to identify common processes that are conserved between rupture events. In our transcriptomic analysis, we found 12 differentially expressed genes in common among two different ovulation data sets and one intracranial aneurysm data set. We also found three genes that were differentially expressed in common for both ovulation data sets and one chorioamniotic membrane rupture data set. Combining analysis of all three data sets identified two genes (Angptl4 and Pfkfb4) that were upregulated across rupture systems. Some of the identified genes, such as Rgs2, Adam8, and Lox, have been characterised in multiple rupture contexts, including ovulation. Others, such as Glul, Baz1a, and Ddx3x, have not yet been characterised in the context of ovulation and warrant further investigation as potential novel regulators. We also identified overlapping functions of mast cells, macrophages, and T cells in the process of rupture. Each of these rupture systems share local vasoconstriction around the rupture site, smooth muscle contractions away from the site of rupture, and fluid shear forces that initially increase and then decrease to predispose one specific region to rupture. Experimental techniques developed to study these structural and biomechanical changes that underlie rupture, such as patient-derived microfluidic models and spatiotemporal transcriptomic analyses, have not yet been comprehensively translated to the study of ovulation. Review of the existing knowledge, transcriptomic data, and experimental techniques from studies of rupture in other biological systems yields a better understanding of the physiology of ovulation and identifies avenues for novel studies of ovulation with techniques and targets from the study of vascular biology and parturition.

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 rupture risk factors of mirror intracranial aneurysms: A systematic review and meta-analysis based on morphological and hemodynamic parameters

OBJECTIVE

Intracranial aneurysms (IAs) are a prevalent form of vascular disease that can lead to fatal outcomes upon rupture. Mirror intracranial aneurysms (MIAs) are a specific type of multiple aneurysms situated symmetrically on both sides of the parent arteries. The factors contributing to the risk of MIA rupture, based on morphological and hemodynamic parameters, are currently controversial. Thus, we conducted a systematic review and meta-analysis to investigate the risk factors for MIA rupture.

METHODS

The study performed an electronic search of Chinese and English databases, including China national Knowledge Infrastructure (CNKI), WanFang, VIP, PubMed, Embase, Web of Science, Scopus, and the Cochrane Library databases, and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The morphological parameters (IA size, aspect ratio [AR], size ratio [SR], bottleneck factor [BNF], height-width ratio [HWR], irregular shape) and hemodynamic parameters (wall shear stress [WSS], low WSS area [LSA], oscillatory shear index [OSI]) were analyzed for their significance in determining the risk of MIA rupture.

RESULTS

The analysis comprised 18 retrospective studies involving 647 patients, with a total of 1294 IAs detected, including 605 ruptured and 689 unruptured. The meta-analysis revealed that IA size, AR, SR, and irregular shape exhibited significant differences between the ruptured and unruptured groups, but HWR did not. In terms of hemodynamic parameters, WSS, OSI, and LSA were found to have significant differences between the two groups.

CONCLUSIONS

Our results demonstrate that larger IAs, higher AR, SR, and BNF are associated with a higher risk of rupture in patients with MIAs, regardless of their location. there is no significant difference in HWR between the ruptured and unruptured groups. These preliminary findings offer valuable insights for clinical decision-making and a more comprehensive comprehension of the current MIA status. Nevertheless, larger and multi-center studies are indispensable for corroborating these findings. Systematic review registration: https://www.crd.york.ac.uk/prospero/ identifier: CRD42022345587.

Fetal-type posterior cerebral artery and association of rupture in posterior communicating artery aneurysms: A systematic review and meta-analysis

BACKGROUND

The morbidity and mortality of intracranial aneurysm rupture motivate the risk evaluation of the patient´s characteristics and aneurysm's morphology. Brain vessel variants lead to hemodynamic changes that could increase risk. This study aims to evaluate the fetal posterior cerebral artery (fPCA) as a risk factor for the formation, rupture, and recurrence of the posterior communicating artery (PComA) aneurysm.

METHODS

A search strategy was performed in MEDLINE, Scopus, Web of Science, and EMBASE databases for studies that evaluated the risk of appearance, rupture, and recurrence of PComA aneurysms with the presence of fPCA. Newcastle-Ottawa Scale and AXIS were used for quality assessment. The primary and secondary outcomes were evaluated and interpreted with an odds ratio (OR) and their 95% confidence intervals (CI).

RESULTS

A total of 577 articles were reviewed. Thirteen studies were included for the qualitative analysis, and ten studies for the meta-analysis. All cohort studies were classified as poor quality, and all cross-sectional studies with moderate risk. The unadjusted OR resulted in 1.57 (n = 6, 95% CI 1.13-2.19, p = <0.001, I² =0%) between the presence of fPCA and PComA aneurysm rupture.

CONCLUSION

There is a significant association of aneurysm formation and rupture of PComA aneurysms in the presence of fPCA. This may be triggered by the hemodynamic alterations caused by the variation, leading to changes in the vessel wall.

The Application of Multiple Magnetic Resonance Scanning Techniques in Evaluating the Stability of Intracranial Aneurysms

Purpose

To evaluate the stability of unruptured intracranial aneurysm (UIA) with high-resolution magnetic resonance imaging of the vessel wall (HR-VWI).

Materials and Methods

A total of 92 UIA patients were enrolled. After MRA, HR-VWI imaging, the reconstruction of volume rendering (VR) and maximum intensity projection (MIP) were performed to observe the location and size of aneurysms, AR value (ratio of aneurysm height to aneurysmal diameter), SR value (ratio of maximum tumor depth to proximal parent artery diameter), and signal intensity were measured.

Results

There were 7 aneurysms with UIA located in the anterior cerebral artery, 31 aneurysms with UIA in the middle cerebral artery, 1 aneurysm with UIA in the posterior cerebral artery, 18 aneurysms with UIA in the anterior communication, 5 aneurysms with UIA in the posterior communication, 34 aneurysms with UIA in the intracranial segment of the internal carotid artery and 3 aneurysms with UIA in the vertebral artery. Among them, 8 patients had more than two multiple aneurysms. The lesion size was 2-38mm (6.3 ± 5.09). There are 46 aneurysms with wall enhancement: the maximum SR value was 7.03 and the minimum 1.2, and the maximum AR value was 7.5 and the minimum 1.0. Fifty-five aneurysms showed no enhancement of the tumor wall. The maximum SR value was 4.55 and the minimum 0.58, and the maximum AR value was 4.0 and the minimum 0.6, respectively. Patients were divided into a stable group and an unstable group according to the aneurysm wall. The enhancement rate, SR value, and AR value in the stable aneurysm group were significantly lower than those in the unstable aneurysm group (P < 0.05).

Conclusion

MRA and HR-VWI can objectively reflect the stability of aneurysms by judging the morphology, SR value, and signal enhancement of UIA, and can provide a certain basis for diagnosis and treatment, which has become routine examination.

Virtual high-resolution MR angiography from non-angiographic multi-contrast MRIs: synthetic vascular model populations for in-silico trials

Despite success on multi-contrast MR image synthesis, generating specific modalities remains challenging. Those include Magnetic Resonance Angiography (MRA) that highlights details of vascular anatomy using specialised imaging sequences for emphasising inflow effect. This work proposes an end-to-end generative adversarial network that can synthesise anatomically plausible, high-resolution 3D MRA images using commonly acquired multi-contrast MR images (e.g. T1/T2/PD-weighted MR images) for the same subject whilst preserving the continuity of vascular anatomy. A reliable technique for MRA synthesis would unleash the research potential of very few population databases with imaging modalities (such as MRA) that enable quantitative characterisation of whole-brain vasculature. Our work is motivated by the need to generate digital twins and virtual patients of cerebrovascular anatomy for in-silico studies and/or in-silico trials. We propose a dedicated generator and discriminator that leverage the shared and complementary features of multi-source images. We design a composite loss function for emphasising vascular properties by minimising the statistical difference between the feature representations of the target images and the synthesised outputs in both 3D volumetric and 2D projection domains. Experimental results show that the proposed method can synthesise high-quality MRA images and outperform the state-of-the-art generative models both qualitatively and quantitatively. The importance assessment reveals that T2 and PD-weighted images are better predictors of MRA images than T1; and PD-weighted images contribute to better visibility of small vessel branches towards the peripheral regions. In addition, the proposed approach can generalise to unseen data acquired at different imaging centres with different scanners, whilst synthesising MRAs and vascular geometries that maintain vessel continuity. The results show the potential for use of the proposed approach to generating digital twin cohorts of cerebrovascular anatomy at scale from structural MR images typically acquired in population imaging initiatives.

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

OBJECTIVE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Association of local solid mechanical, hemodynamic and morphological characteristics with ruptured intracranial aneurysm

The rupture of intracranial aneurysms (IAs) is a complicated phenomenon of which the mechanism is not fully understood. The purpose of this study is to associate local solid mechanical, hemodynamic, and morphological characteristics with rupture regions through statistical means, in an attempt to identify the parameters that are indicative of rupture propensity for IAs. Twenty patient-specific ruptured IA models were reconstructed from digital subtraction angiography (DSA), and applied in the analysis of wall tension, wall shear stress (WSS) and curvature. The precise rupture locations were marked out through intraoperative videos. Pearson correlation analysis was employed to investigate the correlations of these three parameters with patient characteristics and global geometric features. Univariate and multivariate logistic regression analysis were further performed on wall tension, WSS and curvature with regards to rupture and nonrupture regions. Receiver operating characteristic (ROC) analysis defining area under the curve (AUC) was performed on these three parameters. The univariate model of wall tension (AUC, 0.9750), WSS (AUC, 0.9300), curvature (0.8150) and their combined multivariate model (AUC, 0.9875) all present high AUC values. The wall tension, WSS and curvature are acceptable parameters relating to rupture regions. The rupture odd is more sensitive to the wall tension and WSS than curvature. Each logistic model is capable in discriminating ruptures from nonrupture regions, while the multivariate model is the most efficient.

An attention residual u-net with differential preprocessing and geometric postprocessing: Learning how to segment vasculature including intracranial aneurysms

OBJECTIVE

Intracranial aneurysms (IA) are lethal, with high morbidity and mortality rates. Reliable, rapid, and accurate segmentation of IAs and their adjacent vasculature from medical imaging data is important to improve the clinical management of patients with IAs. However, due to the blurred boundaries and complex structure of IAs and overlapping with brain tissue or other cerebral arteries, image segmentation of IAs remains challenging. This study aimed to develop an attention residual U-Net (ARU-Net) architecture with differential preprocessing and geometric postprocessing for automatic segmentation of IAs and their adjacent arteries in conjunction with 3D rotational angiography (3DRA) images.

METHODS

The proposed ARU-Net followed the classic U-Net framework with the following key enhancements. First, we preprocessed the 3DRA images based on boundary enhancement to capture more contour information and enhance the presence of small vessels. Second, we introduced the long skip connections of the attention gate at each layer of the fully convolutional decoder-encoder structure to emphasize the field of view (FOV) for IAs. Third, residual-based short skip connections were also embedded in each layer to implement in-depth supervision to help the network converge. Fourth, we devised a multiscale supervision strategy for independent prediction at different levels of the decoding path, integrating multiscale semantic information to facilitate the segmentation of small vessels. Fifth, the 3D conditional random field (3DCRF) and 3D connected component optimization (3DCCO) were exploited as postprocessing to optimize the segmentation results.

RESULTS

Comprehensive experimental assessments validated the effectiveness of our ARU-Net. The proposed ARU-Net model achieved comparable or superior performance to the state-of-the-art methods through quantitative and qualitative evaluations. Notably, we found that ARU-Net improved the identification of arteries connecting to an IA, including small arteries that were hard to recognize by other methods. Consequently, IA geometries segmented by the proposed ARU-Net model yielded superior performance during subsequent computational hemodynamic studies (also known as "patient-specific" computational fluid dynamics [CFD] simulations). Furthermore, in an ablation study, the five key enhancements mentioned above were confirmed.

CONCLUSIONS

The proposed ARU-Net model can automatically segment the IAs in 3DRA images with relatively high accuracy and potentially has significant value for clinical computational hemodynamic analysis.

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 semantic vessel graph extraction for intracranial aneurysm rupture risk management

PURPOSE

Intracranial aneurysms are vascular deformations in the brain which are complicated to treat. In clinical routines, the risk assessment of intracranial aneurysm rupture is simplified and might be unreliable, especially for patients with multiple aneurysms. Clinical research proposed more advanced analysis of intracranial aneurysm, but requires many complex preprocessing steps. Advanced tools for automatic aneurysm analysis are needed to transfer current research into clinical routine.

METHODS

We propose a pipeline for intracranial aneurysm analysis using deep learning-based mesh segmentation, automatic centerline and outlet detection and automatic generation of a semantic vessel graph. We use the semantic vessel graph for morphological analysis and an automatic rupture state classification.

RESULTS

The deep learning-based mesh segmentation can be successfully applied to aneurysm surface meshes. With the subsequent semantic graph extraction, additional morphological parameters can be extracted that take the whole vascular domain into account. The vessels near ruptured aneurysms had a slightly higher average torsion and curvature compared to vessels near unruptured aneurysms. The 3D surface models can be further employed for rupture state classification which achieves an accuracy of 83.3%.

CONCLUSION

The presented pipeline addresses several aspects of current research and can be used for aneurysm analysis with minimal user effort. The semantic graph representation with automatic separation of the aneurysm from the parent vessel is advantageous for morphological and hemodynamical parameter extraction and has great potential for deep learning-based rupture state classification.

Computational Fluid Dynamics Analysis of Blood Flow Changes during the Growth of Saccular Abdominal Aortic Aneurysm

Computational fluid dynamics analysis of the growth process of saccular abdominal aortic aneurysm was performed. A 3D model of aortic aneurysm was created based on CT images. Properties in terms of wall shear stress, mean flow velocity, mean pressure, energy loss, and pressure loss coefficient were calculated using thermal fluid analysis software "ANSYS CFX." As the aneurysm expanded, the mean flow velocity decreased and the wall shear stress, mean pressure, energy loss, and pressure loss coefficient increased. Wall shear stress increased when the aneurysm was small, suggesting that is related to the development and growth of the aneurysm. (This is secondary publication from J Jpn Coll Angiol 2021; 61: 3-10.).

High-fidelity fluid structure interaction simulations of turbulent-like aneurysm flows reveals high-frequency narrowband wall vibrations: A stimulus of mechanobiological relevance?

Recent high-fidelity/resolution computational fluid dynamics simulations of intracranial aneurysm hemodynamics have revealed turbulent-like flows. We hypothesized that the associated high-frequency pressure fluctuations could promote aneurysm wall vibrations. We performed fully coupled high-fidelity transient fluid structure interaction simulations between the blood flow and compliant aneurysm sac wall taking 5,000 time steps per second using a 3D patient-specific model previously shown to harbour turbulent-like flow. Our results show that the flow velocity contained fluctuations with a smooth and continuously decaying energy up to ∼160Hz, and fluctuating pressures with characteristic frequency peaks at approximately 30, 130 and 210Hz. There was a strong two-way coupling between the pressure and the wall deformation, for which the frequency spectrum showed similar characteristics, but with a narrow band peak at ∼120Hz with large regional differences in amplitude up to 80μm. The physics of the flow is broadly consistent with clinical reports of turbulent-like flows, while the physics of the wall is consistent with reports of spectral peaks in aneurysm patients. As many aneurysms are known to harbour turbulent-like flows, wall vibrations could be a widespread phenomenon. Finally, since aneurysms are vascular pathologies by definition and many/most aneurysms do not have endothelial cells but still display a focal remodeling, we hypothesize that vibrations and stresses within the wall itself might play a role in the mechanobiological processes of vessel wall pathology.

Hemodynamics and bio-mechanics of morphologically distinct saccular intracranial aneurysms at bifurcations: Idealised vs Patient-specific geometries

Understanding the factors that influence the rupture of aneurysms is of primary concern to the clinicians, who are grappled with patient management. It is important to know how the relation between morphological features of the cerebral aneurysm, and the mechanical stresses on the containing arterial walls are influenced by the hemodynamic forces. Present study investigates three different shapes, which have been identified correspondingly in patient-specific scenarios as well. The primary objective is to categorize the bifurcation aneurysms into standard shapes such as, spherical, beehive and pear-shaped, based on patient-specific clinical studies and further compare and contrast the model aneurysms with the patient specific configurations, for their hemodynamic factors as well as the attendant stresses on the wall. MethodsComputational fluid dynamic simulations are performed accounting for the fluid-structure interaction (FSI) effects between the flowing fluid and the containing vessel wall. Blood is assumed to be Newtonian, while the arterial walls are assumed to be linearly elastic. A commercial solver is used for performing detailed calculations. Hemodynamic and bio-mechanical rupture predictions are carried out for the three different shapes. Observations derived from the idealised simulations are compared and contrasted against their patient-specific counterparts. ResultsFrom detailed numerical simulations, it was observed that pear-shaped aneurysms exhibit large re-circulation bubble and flow stagnation zone, with higher residence time for the particles, which may lead to atherosclerotic lesions. Beehive shape allows for maximum flow into the aneurysmal sac with concentrated jet impinging on the dome, leading to high values of maximum WSS (MWSS) resulting in great propensity to form a secondary bleb. However, flow field inside a spherical aneurysm is found to be stable with fewer vortices, and nearly uniform distribution of wall stresses are observed though-out the sac, which perhaps signifies hemodynamically and bio-mechanically stable condition. ConclusionCategorizing patient-specific intracranial aneurysms into standard shapes viz, spherical, beehive and pear could generalize the process of prediction of hemodynamic and bio-mechanical rupture indicators. Comparative assessment of the flow field and stresses reported from the simulations on idealised models, with corresponding patient-specific simulations reveal that, these studies could aid in understanding the generalised shape dependence of hemodynamic and bio-mechanical behaviour of aneurysms.

Reliability of using generic flow conditions to quantify aneurysmal haemodynamics: A comparison against simulations incorporating boundary conditions measured in vivo

BACKGROUND AND OBJECTIVES

Initiation, growth, and rupture of intracranial aneurysms are believed to be closely related to their local haemodynamic environment. While haemodynamics can be characterised by use of computational fluid dynamics (CFD), its reliability depends heavily upon accurate assumption of the boundary conditions. Herein, we compared the simulated aneurysmal haemodynamics obtained by use of generic boundary conditions against those obtained under flow conditions measured in vivo.

METHODS

We prospectively recruited 19 patients with intracranial aneurysms requiring 3-dimensional rotational angiography, during which blood pressure at the internal carotid artery was probed by catheter and flowrate measured by a dedicated software tool. Using these flow conditions measured in vivo, we quantified the aneurysmal haemodynamics for each patient by CFD, and then compared the results with those derived from a generic condition reported in the literature, in terms of the time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and percentage of the intra-aneurysmal flow (PIAF). In addition, the effects on aneurysmal haemodynamics of different outflow strategies (splitting method vs. Murray's Law) and simulation schemes (transient vs. steady-state) relative to each flow condition were also assessed.

RESULTS

Differences in the simulated TAWSS (-6.08 ± 10.64 Pa, p = 0.001), OSI (0.06 ± 0.13, p = 0.001), and PIAF (-0.05 ± 0.20, p = 0.012) between the patient-specific and generic boundary conditions were found to be statistically significant, in contrast to that in the RRT (49 ± 307 Pa^-1, p = 0.062). Outflow strategies did not yield statistically significant differences in any of the investigated parameters (all p > 0.05); rather, the resulting parameters were found to be in good correlations (all r > 0.71, p < 0.001). Difference between the aneurysmal TAWSS and the WSS derived from cycle-averaged flowrate condition was found to be minor (0.66 ± 1.36 Pa, p = 0.000), so was that between PIAFs obtained respectively from the transient and steady-state simulations (0.02 ± 0.05, p = 0.000).

CONCLUSIONS

Incorporating into simulation the patient-specific boundary conditions is critical for CFD to characterise aneurysmal haemodynamics, while outflow strategies may not introduce significant uncertainties. Steady-state simulation incorporating the cycle-averaged flow condition may produce unbiased WSS and PIAF compared to the transient analysis.

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.

Non-contrast enhanced silent MR angiography to evaluate hemodynamics and morphology of unruptured intracranial aneurysms: a comparative computational fluid dynamics study

BACKGROUND

Silent MR angiography (silent MRA) is a new generation of non-contrast enhanced angiography with outstanding advantages in visualizing cerebrovascular lesions and the follow-up after endovascular treatment for intracranial aneurysms (IAs). This study aims to investigate the reliability of silent MRA-based three-dimensional (3D) geometric description and hemodynamic calculation of IAs.

METHODS

19 patients with 23 unruptured IAs, who underwent both silent MRA and 3D rotational angiography (3DRA), were included in this study. Computational fluid dynamics simulations were performed on all patient-specific 3D reconstruction images to compare the morphology and hemodynamics of the two different imaging models for IAs.

RESULTS

Silent MRA models had smaller maximum and perpendicular height (mm), aneurysmal surface area (mm²), and aneurysmal volume (mm³) than 3DRA (p<0.05); the differences of the above parameters between the two models were 9.0±6.2%, 7.7±7.4%, 15.9±13.0%, and 21.4±17.5%, respectively. However, correlation analysis of morphological parameters in various dimensions and model comparison showed good overall consistency in geometrical characteristics between the two models. Moderate coherence was observed between models in time-averaged wall shear stress of aneurysm and parent vessel (TAWSS, PAWSS), aneurysm velocity (AV), parent vessel velocity, and oscillatory shear index (OSI). However, strong correlations were observed among normalized aneurysm wall shear stress (NWSS), low shear area (LSA), inflow concentration index (ICI), and normalized aneurysm velocity (NAV).

CONCLUSION

Both morphological and hemodynamic assessments of IAs for silent MRA are comparable to 3DRA. Additionally, normalized indicators such as NWSS, LSA, ICI, and NAV were better than TAWSS, AV, and OSI in silent MRA-related hemodynamic 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.

Evaluation of aneurysm rupture risk based upon flowrate-independent hemodynamic parameters: a multi-center pilot study

BACKGROUND

Specifying generic flow boundary conditions in aneurysm hemodynamic simulations yields a great degree of uncertainty for the evaluation of aneurysm rupture risk. Herein, we proposed the use of flowrate-independent parameters in discriminating unstable aneurysms and compared their prognostic performance against that of conventional absolute parameters.

METHODS

This retrospective study included 186 aneurysms collected from three international centers, with the stable aneurysms having a minimum follow-up period of 24 months. The flowrate-independent aneurysmal wall shear stress (WSS) and energy loss (EL) were defined as the coefficients of the second-order polynomials characterizing the relationships between the respective parameters and the parent-artery flows. Performance of the flowrate-independent parameters in discriminating unstable aneurysms with the logistic regression, Adaboost, and support-vector machine (SVM) methods was quantified and compared against that of the conventional parameters, in terms of sensitivity, specificity, and area under the curve (AUC).

RESULTS

In discriminating unstable aneurysms, the proposed flowrate-independent EL achieved the highest sensitivity (0.833, 95% CI 0.586 to 0.964) and specificity (0.833, 95% CI 0.672 to 0.936) on the SVM, with the AUC outperforming the conventional EL by 0.133 (95% CI 0.039 to 0.226, p=0.006). Likewise, the flowrate-independent WSS outperformed the conventional WSS in terms of the AUC (difference: 0.137, 95% CI 0.033 to 0.241, p=0.010).

CONCLUSION

The flowrate-independent hemodynamic parameters surpassed their conventional counterparts in predicting the stability of aneurysms, which may serve as a promising set of hemodynamic metrics to be used for the prediction of aneurysm rupture risk when physiologically real vascular boundary conditions are unavailable.

Hemodynamic Characteristic Analysis of Aneurysm Wall Enhancement in Unruptured Middle Cerebral Artery Aneurysm

Background and Purpose

Aneurysm wall enhancement (AWE) on vessel wall magnetic resonance imaging has been suggested as a marker of the unstable status of intracranial aneurysm (IA) and may predict IA rupture risk. However, the role of abnormal hemodynamics in unruptured IAs with AWE remains poorly understood. This study aimed to determine the association between abnormal hemodynamics and AWE in unruptured middle cerebral artery (MCA) aneurysms.

Methods

A total of 28 patients with 32 bifurcation aneurysms of the middle cerebral artery>3mm in size were retrospectively selected for this study. Vessel wall magnetic resonance images were reviewed, and the AWE pattern of each aneurysm was classified as no AWE, partial AWE, and circumferential AWE. Computational fluid dynamics were used to calculate the hemodynamic variables of each aneurysm. Univariate and multivariate analyses investigated the association between AWE and hemodynamic variables.

Results

AWE was present in 13 aneurysms (40.6%), with 7 (21.9%) showing partial AWE and 6 (18.7%) showing circumferential AWE. Kruskal-Wallis H analysis revealed that hemodynamic variables including wall shear stress (WSS), oscillatory shear index, aneurysm pressure (AP), relative residence time, and low shear area (LSA) were significantly associated with AWE (p < 0.05). Further ordinal logistic regression analysis found that WSS was the only factor with a significant association with AWE (p = 0.048); similar trends were identified for LSA (p = 0.055) and AP (p = 0.058). Spearman's correlation analysis showed that AWE was negatively correlated with WSS (rs = -0.622, p < 0.001) and AP (rs = -0.535, p = 0.002) but positively correlated with LSA (rs = 0.774, p < 0.001).

Conclusion

Low wall shear stress, low aneurysm pressure, and increased low shear area were associated with aneurysm wall enhancement on vessel wall magnetic resonance imaging in unruptured cerebral aneurysms. These abnormal hemodynamic parameters may induce inflammation and cause aneurysm wall enhancement. However, the association between these parameters and their underlying pathological mechanisms requires further investigation.

Different Hemodynamic Characteristics and Resulting in Different Risks of Rupture Between Wide-Neck and Narrow-Neck Aneurysms

Objective

This study aimed to determine the ruptured rate and hemodynamic difference between wide-neck aneurysms (WNAs) and narrow-neck aneurysms (NNAs), as well as the hemodynamic parameters of risk factors for aneurysm rupture.

Methods

A total of 121 cases of intracranial aneurysms (IAs) were studied retrospectively between January 2019 and April 2021 at Renmin Hospital of Wuhan University. Intracranial aneurysms were classified into four types: ruptured wide-neck aneurysms (RWNAs), unruptured wide-neck aneurysms (UWNAs), ruptured narrow-neck aneurysms (RNNAs), and unruptured narrow-neck aneurysms (UNNAs). The Chi-square test was used to compare differences in rupture ratios. The clinical characteristics and hemodynamics were analyzed statistically to reveal the rupture risk factors. Moreover, significant parameters were subjected to binary logistic regression analysis to identify the independent predictive factors. The receiver operating characteristic (ROC) curve was performed to obtain cutoff values.

Results

WNAs ruptured more frequently than NNAs (P = 0.033). Ruptured intracranial aneurysms (RIAs) were characterized by significantly higher intra-aneurysmal pressure (IAP), wall shear stress (WSS), wall shear stress gradient (WSSG), and lower normalized wall shear stress (NWSS) than unruptured intracranial aneurysms (UIAs). RWNAs had higher IAP, WSS, and lower NWSS than UWNAs (P < 0.05). RNNAs had higher IAP, Streamwise WSSG and lower NWSS compared to UNNAs (P < 0.05). Binary logistic regression revealed that IAP and WSS were independent predictive risk factors for WNAs rupture, with cut-off values of 405.5 and 6.66 Pa, respectively. Also, IAP was an independent predictive risk factor for NNA rupture, with a cut-off value of 255.3 Pa.

Conclusions

Wide-neck aneurysms and narrow-neck aneurysms have diverse hemodynamics, which prompts a higher rupture ratio for WNAs. IAP could characterize the rupture risk in both WNAs and NNAs independently, but WSS could only predict the rupture risk in WNAs. This research might assist neurosurgeons with fostering a more sensible strategy for the treatment of IAs.

Impinging Flow Induces Expression of Monocyte Chemoattractant Protein-1 in Endothelial Cells Through Activation of the c-Jun N-terminal Kinase/c-Jun/p38/c-Fos Pathway

OBJECTIVE

Monocyte chemoattractant protein-1 (MCP-1) is an important regulator of the formation and development of intracranial aneurysms. This study explored the molecular mechanisms underlying the induction of MCP-1 and related inflammatory factors in human umbilical vein endothelial cells (HUVECs) under hemodynamic conditions.

METHODS

A modified T chamber was used to simulate fluid flow at the bifurcation of the artery and wall shear stress on HUVECs in vitro. Changes in HUVECs were analyzed in response to impinging flow. And HUVECs without impinging flow were used as the control group. Protein expression levels of extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK), p38, activator protein-1, and MCP-1 were detected by Western blot, and the messenger RNA expression levels of MCP-1, interleukin (IL)-1β, and IL-6 were determined by quantitative reverse transcription polymerase chain reaction.

RESULTS

Under impinging flow, the phosphorylation levels of ERK, JNK, and p38, as well as the protein levels of MCP-1, c-Jun, and c-Fos, increased. The messenger RNA expression of MCP-1, IL-1β, and IL-6 also increased in HUVECs. Pretreatment of the HUVECs with inhibitors of JNK and p38 significantly attenuated the increased expression of MCP-1, IL-1β, and IL-6, while ERK inhibitors had no obvious effect.

CONCLUSIONS

Under impinging flow, MCP-1 and inflammatory factors are regulated through the JNK/c-Jun/p38/c-Fos pathway and participate in EC inflammation.

An Integrated Model Combining Machine Learning and Deep Learning Algorithms for Classification of Rupture Status of IAs

Background

The rupture risk assessment of intracranial aneurysms (IAs) is clinically relevant. How to accurately assess the rupture risk of IAs remains a challenge in clinical decision-making.

Purpose

We aim to build an integrated model to improve the assessment of the rupture risk of IAs.

Materials and Methods

A total of 148 (39 ruptured and 109 unruptured) IA subjects were retrospectively computed with computational fluid dynamics (CFDs), and the integrated models were proposed by combining machine learning (ML) and deep learning (DL) algorithms. ML algorithms that include random forest (RF), k-nearest neighbor (KNN), XGBoost (XGB), support vector machine (SVM), and LightGBM were, respectively, adopted to classify ruptured and unruptured IAs. A Pointnet DL algorithm was applied to extract hemodynamic cloud features from the hemodynamic clouds obtained from CFD. Morphological variables and hemodynamic parameters along with the extracted hemodynamic cloud features were acted as the inputs to the classification models. The classification results with and without hemodynamic cloud features are computed and compared.

Results

Without consideration of hemodynamic cloud features, the classification accuracy of RF, KNN, XGB, SVM, and LightGBM was 0.824, 0.759, 0.839, 0.860, and 0.829, respectively, and the AUCs of them were 0.897, 0.584, 0.892, 0.925, and 0.890, respectively. With the consideration of hemodynamic cloud features, the accuracy successively increased to 0.908, 0.873, 0.900, 0.926, and 0.917. Meanwhile, the AUCs reached 0.952, 0.881, 0.950, 0.969, and 0.965 eventually. Adding consideration of hemodynamic cloud features, the SVM could perform best with the highest accuracy of 0.926 and AUC of 0.969, respectively.

Conclusion

The integrated model combining ML and DL algorithms could improve the classification of IAs. Adding consideration of hemodynamic cloud features could bring more accurate classification, and hemodynamic cloud features were important for the discrimination of ruptured IAs.

Hemodynamic impact of proximal anterior cerebral artery aneurysm: Mind the posteriorly projecting ones!

Intracranial aneurysm projected posteriorly is associated with high risk of aneurysm rupture. In order to investigate the biomechanical mechanisms for the adverse event, three-dimension intracranial cerebral aneurysms were constructed based on clinical data, and we numerically compared effect of location, position, size, and shape of aneurysm on hemodynamic conditions including velocity, pressure, and wall shear stress (WSS). The numerical results showed that the aneurysm projected posteriorly even at small sizes led to abnormal hemodynamic environment, which was featured by a local high pressure and stress concentration near aneurysm neck area. Moreover, the one located at the proximal A1 segment and ellipsoidal aneurysm would further worse local hemodynamic environment, causing high local stresses. These findings indicated the potential mechanical mechanism for high rupture rate of the aneurysms projected posteriorly, underscoring importance of early and accurate diagnosis and promptly treatment for improved the clinical outcome, even if these aneurysms are of small sizes.

Numerical Assessment of the Risk of Abnormal Endothelialization for Diverter Devices: Clinical Data Driven Numerical Study

Numerical modeling is an effective tool for preoperative planning. The present work is devoted to a retrospective analysis of neurosurgical treatments for the occlusion of cerebral aneurysms using flow-diverters and hemodynamic factors affecting stent endothelization. Several different geometric approaches have been considered for virtual flow-diverters deployment. A comparative analysis of hemodynamic parameters as a result of computational modeling has been carried out basing on the four clinical cases: one successful treatment, one with no occlusion and two with in stent stenosis. For the first time, a quantitative assessment of both: the limiting magnitude of shear stresses that are necessary for the occurrence of in stent stenosis (MaxWSS > 1.23) and for conditions in which endothelialization is insufficiently active and occlusion of the cervical part of the aneurysm does not occur (MaxWSS < 1.68)—has been statistacally proven (p < 0.01).

EFFECTS OF THE ANEURYSM TREATMENT METHOD ON COIL PACKING DENSITY AND ITS RELATIONSHIP WITH THE OSTIUM AREA

PURPOSE

To test the following hypotheses: (1) balloon or stent assistance increases coil packing density (CPD) in the endovascular treatment of intracranial aneurysms and (2) CPD is related to the ostium area and volume of the aneurysm.

MATERIALS AND METHODS

This retrospective study included 60 ruptured and unruptured (54 and 6, respectively) aneurysms treated between August 2017 and December 2019 in the authors' institution with simple coiling (n=18), balloon-assisted coiling (n=7), or stent-assisted coiling (n=35). Aneurysm volume and ostium area measurements were obtained using commercial software from three-dimensional digital subtraction angiography images. Coil sizes were retrieved from patient files, and coil volume measurements were obtained using https://www.angiocalc.com/. Analysis of covariance, multivariable covariance analysis, and Pearson's correlation analyses were performed.

RESULTS

The median values for the aneurysm volume, coil volume, CPD, and ostium area were 63.4 (range 5.5-1771.4) mm³, 23.13 (2.03-296.95) mm³, 33.29% (13.41%-81.02%), and 10.7 (2.7-49.9) mm², respectively. Multivariate analysis showed that the CPD values were not significantly different among the treatment groups, although the ostium area differed significantly between the simple and stent-assisted coiling groups (P<.05). Pearson's correlations showed that similar to aneurysm volume, the ostium area was negatively correlated with CPD (r=-0.321, P<.05).

CONCLUSION

In cerebral aneurysms treated with balloon- or stent-assisted coiling, the CPD value does not differ from that in aneurysms treated with simple coiling.

Morphology-aware multi-source fusion-based intracranial aneurysms rupture prediction

OBJECTIVES

We proposed a new approach to train deep learning model for aneurysm rupture prediction which only uses a limited amount of labeled data.

METHOD

Using segmented aneurysm mask as input, a backbone model was pretrained using a self-supervised method to learn deep embeddings of aneurysm morphology from 947 unlabeled cases of angiographic images. Subsequently, the backbone model was finetuned using 120 labeled cases with known rupture status. Clinical information was integrated with deep embeddings to further improve prediction performance. The proposed model was compared with radiomics and conventional morphology models in prediction performance. An assistive diagnosis system was also developed based on the model and was tested with five neurosurgeons.

RESULT

Our method achieved an area under the receiver operating characteristic curve (AUC) of 0.823, outperforming deep learning model trained from scratch (0.787). By integrating with clinical information, the proposed model's performance was further improved to AUC = 0.853, making the results significantly better than model based on radiomics (AUC = 0.805, p = 0.007) or model based on conventional morphology parameters (AUC = 0.766, p = 0.001). Our model also achieved the highest sensitivity, PPV, NPV, and accuracy among the others. Neurosurgeons' prediction performance was improved from AUC=0.877 to 0.945 (p = 0.037) with the assistive diagnosis system.

CONCLUSION

Our proposed method could develop competitive deep learning model for rupture prediction using only a limited amount of data. The assistive diagnosis system could be useful for neurosurgeons to predict rupture.

KEY POINTS

• A self-supervised learning method was proposed to mitigate the data-hungry issue of deep learning, enabling training deep neural network with a limited amount of data. • Using the proposed method, deep embeddings were extracted to represent intracranial aneurysm morphology. Prediction model based on deep embeddings was significantly better than conventional morphology model and radiomics model. • An assistive diagnosis system was developed using deep embeddings for case-based reasoning, which was shown to significantly improve neurosurgeons' performance to predict rupture.

Combination of Morphological and Hemodynamic Parameters for Assessing the Rupture Risk of Intracranial Aneurysms: a Retrospective Study On Mirror Middle Cerebral Artery Aneurysms

Discordant findings were frequently reported by studies dedicated to exploring the association of morphological/hemodynamic factors with the rupture of intracranial aneurysms (IAs), probably owing to insufficient control of confounding factors. In this study, we aimed to minimize the influences of confounding factors by focusing IAs of interest on mirror aneurysms and, meanwhile, modeling IAs together with the cerebral arterial network to improve the physiological fidelity of hemodynamic simulation. 52 mirror aneurysms located at the middle cerebral artery (MCA) in 26 patients were retrospectively investigated. Numerical tests performed on two randomly selected patients demonstrated that over truncation of cerebral arteries proximal to the MCA during image-based model reconstruction led to uncertain changes in computed values of intra-aneurysmal hemodynamic parameters, which justified the minimal truncation strategy adopted in our study. Five morphological parameters (i.e., volume (V), height (H), dome area (DA), non-sphericity index (NSI), and size ratio (SR)) and two hemodynamic parameters (i.e., peak WSS (peakWSS), and pressure loss coefficient (PLc)) were found to differ significantly between the ruptured and unruptured aneurysms and proved by receiver operating characteristic (ROC) analysis to have potential value for differentiating the rupture status of aneurysm with the areas under curve (AUCs) ranging from 0.681 to 0.763. Integrating V, SR, peakWSS and PLc or some of them into regression models considerably improved the classification of aneurysms, elevating AUC up to 0.864, which indicates that morphological and hemodynamic parameters have complementary roles in assessing the risk of aneurysm rupture.

Characterizing Intracranial Hemodynamics in Sickle Cell Anemia: Impact of Patient-Specific Viscosity

PURPOSE

Pediatric and adult patients with sickle cell anemia (SCA) are at increased risk of stroke and cerebrovascular accident. In the general adult population, there is a relationship between arterial hemodynamics and pathology; however, this relationship in SCA patients remains to be elucidated. The aim of this work was to characterize circle of Willis hemodynamics in patients with SCA and quantify the impact of viscosity choice on pathophysiologically-relevant hemodynamics measures.

METHODS

Based on measured vascular geometries, time-varying flow rates, and blood parameters, detailed patient-specific simulations of the circle of Willis were conducted for SCA patients (n = 6). Simulations quantified the impact of patient-specific and standard blood viscosities on wall shear stress (WSS).

RESULTS

These results demonstrated that use of a standard blood viscosity introduces large errors into the estimation of pathophysiologically-relevant hemodynamic parameters. Standard viscosity models overpredicted peak WSS by 55% and 49% for steady and pulsatile flow, respectively. Moreover, these results demonstrated non-uniform, spatial patterns of positive and negative WSS errors related to viscosity, and standard viscosity simulations overpredicted the time-averaged WSS by 32% (standard deviation = 7.1%). Finally, differences in shear rate demonstrated that the viscosity choice alters the simulated near-wall flow field, impacting hemodynamics measures.

CONCLUSIONS

This work presents simulations of circle of Willis arterial flow in SCA patients and demonstrates the importance and feasibility of using a patient-specific viscosity in these simulations. Accurately characterizing cerebrovascular hemodynamics in SCA populations has potential for elucidating the pathophysiology of large-vessel occlusion, aneurysms, and tissue damage in these patients.

Morphological and Hemodynamic Characteristics Associated With the Rupture of Multiple Intracranial Aneurysms

Background and Purpose

The objective of this study was to identify the morphological and hemodynamic factors associated with the rupture of multiple intracranial aneurysms regardless of patient-related factors and establish a statistical model for aneurysm rupture risk assessment.

Methods

The digital subtraction angiography (DSA) data of 104 mirror intracranial aneurysms in 52 consecutive patients were retrospectively analyzed in this study. 21 morphological parameters and hemodynamic parameters were calculated by 3-dimensional reconstruction and computational fluid dynamics (CFD) simulation. Significant differences (p < 0.05) between the two groups were subsequently tested with the multivariate logistic regression to identify the independent risk factors. A prediction model was established based on the independent risk factors. The receiver operating characteristics (ROCs) were generated to estimate the prediction performance. A cohort of patients with multiple intracranial aneurysms admitted in our institute from January 2021 to October 2021 was introduced to verify the value of the model.

Results

Significant differences between the ruptured and unruptured aneurysms were found in 15 out of 19 parameters. Bleb formation, neck width, and size ratio were independent factors in the multivariate logistic regression. A prediction model based on the three independent risk factors was established: Odds = −1.495 – 0.707 × _(Neckwidth) + 3.061 × _{(Blebformation)} + 2.1 × _(SR) (bleb formation: Yes = 1, No = 0). The area under the curve (AUC) value of the model was 0.901. In the validation cohort, the prediction model showed satisfying performance in assessing multiple aneurysm rupture risk with a sensitivity of 100% and specificity of 88.46%.

Conclusion

Bleb formation, neck width, and size ratio were independently associated with aneurysm rupture status. The prediction model may help in identifying the aneurysm with high rupture risk.

Fluid-structure interaction simulation of tissue degradation and its effects on intra-aneurysm hemodynamics

Tissue degradation plays a crucial role in vascular diseases such as atherosclerosis and aneurysms. Computational modeling of vascular hemodynamics incorporating both arterial wall mechanics and tissue degradation has been a challenging task. In this study, we propose a novel finite element method-based approach to model the microscopic degradation of arterial walls and its interaction with blood flow. The model is applied to study the combined effects of pulsatile flow and tissue degradation on the deformation and intra-aneurysm hemodynamics. Our computational analysis reveals that tissue degradation leads to a weakening of the aneurysmal wall, which manifests itself in a larger deformation and a smaller von Mises stress. Moreover, simulation results for different heart rates, blood pressures and aneurysm geometries indicate consistently that, upon tissue degradation, wall shear stress increases near the flow-impingement region and decreases away from it. These findings are discussed in the context of recent reports regarding the role of both high and low wall shear stress for the progression and rupture of aneurysms.

Hemodynamic Characteristics and Clinical Outcome for Intracranial Aneurysms treated with the Derivo Embolization Device, a Novel Second-Generation Flow Diverter

BACKGROUND AND PURPOSE

We investigated the relationship between hemodynamic characteristics and clinical outcomes for aneurysms treated by the Derivo Embolization Device (DED), a novel second-generation Flow-Diverter Stent, using computational fluid dynamics (CFD).

MATERIALS AND METHODS

Data were retrospectively obtained from two centers between 2017 and 2019. During the period, 23 patients were treated for 23 aneurysms with DED. In 17 patients we were able to conduct CFD analysis as six were excluded due to pre-coiling, unsuitable arterial geometry, and complex geometric form. Aneurysm occlusion was rated with the O`Kelly-Marotta (OKM) grading scale on DSA 6 months after stent placement in all patients. Hemodynamic and morphological parameters were statistically compared between two groups: with full occlusion and with a remnant.

RESULTS

Full occlusion was observed in 17 out of 23 (73.9%) patients. In the group suitable for CFD analysis, we observed 13 fully occluded aneurysms and 4 with any remnant (specifically 1 OKM C, 1 B and 2 A). The energy loss per volume (ELV), which indicates the energy loss through the aneurysm, was significantly larger in pre and post stenting (p<.05) in the complete occlusion cases. In addition, the inflow concentration index (ICI) and inflow area ratio (IAR) of the remnant cases were significantly larger and lower, respectively (p<.05).

CONCLUSION

Our CFD results indicate that the energy loss involved with the blood flow passing through an aneurysm and concentrated inflow into aneurysm were the most important factors to determine whether an aneurysm will become a complete occlusion or remnant case.

Underlying mechanism of hemodynamics and intracranial aneurysm

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

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.