Distribution of rupture sites and blebs on intracranial aneurysm walls suggests distinct rupture patterns in ACom and MCA aneurysms.

The mechanisms behind intracranial aneurysm formation and rupture are not fully understood, with factors such as location, patient demographics, and hemodynamics playing a role. Additionally, the significance of anatomical features like blebs in ruptures is debated. This highlights the necessity for comprehensive research that combines patient-specific risk factors with a detailed analysis of local hemodynamic characteristics at bleb and rupture sites. Our study analyzed 359 intracranial aneurysms from 268 patients, reconstructing patient-specific models for hemodynamic simulations based on 3D rotational angiographic images and intraoperative videos. We identified aneurysm subregions and delineated rupture sites, characterizing blebs and their regional overlap, employing statistical comparisons across demographics, and other risk factors. This work identifies patterns in aneurysm rupture sites, predominantly at the dome, with variations across patient demographics. Hypertensive and anterior communicating artery (ACom) aneurysms showed specific rupture patterns and bleb associations, indicating two pathways: high-flow in ACom with thin blebs at impingement sites and low-flow, oscillatory conditions in middle cerebral artery (MCA) aneurysms fostering thick blebs. Bleb characteristics varied with gender, age, and smoking, linking rupture risks to hemodynamic factors and patient profiles. These insights enhance understanding of the hemodynamic mechanisms leading to rupture events. This analysis elucidates the role of localized hemodynamics in intracranial aneurysm rupture, challenging the emphasis on location by revealing how flow variations influence stability and risk. We identify two pathways to wall failure-high-flow and low-flow conditions-highlighting the complexity of aneurysm behavior. Additionally, this research advances our knowledge of how inherent patient-specific characteristics impact these processes, which need further investigation.

Evaluation of predictive models of aneurysm focal growth and bleb development using machine learning techniques.

BACKGROUND: The presence of blebs increases the rupture risk of intracranial aneurysms (IAs). OBJECTIVE: To evaluate whether cross-sectional bleb formation models can identify aneurysms with focalized enlargement in longitudinal series. METHODS: Hemodynamic, geometric, and anatomical variables derived from computational fluid dynamics models of 2265 IAs from a cross-sectional dataset were used to train machine learning (ML) models for bleb development. ML algorithms, including logistic regression, random forest, bagging method, support vector machine, and K-nearest neighbors, were validated using an independent cross-sectional dataset of 266 IAs. The models' ability to identify aneurysms with focalized enlargement was evaluated using a separate longitudinal dataset of 174 IAs. Model performance was quantified by the area under the receiving operating characteristic curve (AUC), the sensitivity and specificity, positive predictive value, negative predictive value, F1 score, balanced accuracy, and misclassification error. RESULTS: The final model, with three hemodynamic and four geometrical variables, along with aneurysm location and morphology, identified strong inflow jets, non-uniform wall shear stress with high peaks, larger sizes, and elongated shapes as indicators of a higher risk of focal growth over time. The logistic regression model demonstrated the best performance on the longitudinal series, achieving an AUC of 0.9, sensitivity of 85%, specificity of 75%, balanced accuracy of 80%, and a misclassification error of 21%. CONCLUSIONS: Models trained with cross-sectional data can identify aneurysms prone to future focalized growth with good accuracy. These models could potentially be used as early indicators of future risk in clinical practice.

Prediction of bleb formation in intracranial aneurysms using machine learning models based on aneurysm hemodynamics, geometry, location, and patient population.

BACKGROUND: Bleb presence in intracranial aneurysms (IAs) is a known indication of instability and vulnerability. OBJECTIVE: To develop and evaluate predictive models of bleb development in IAs based on hemodynamics, geometry, anatomical location, and patient population. METHODS: Cross-sectional data (one time point) of 2395 IAs were used for training bleb formation models using machine learning (random forest, support vector machine, logistic regression, k-nearest neighbor, and bagging). Aneurysm hemodynamics and geometry were characterized using image-based computational fluid dynamics. A separate dataset with 266 aneurysms was used for model evaluation. Model performance was quantified by the area under the receiving operating characteristic curve (AUC), true positive rate (TPR), false positive rate (FPR), precision, and balanced accuracy. RESULTS: The final model retained 18 variables, including hemodynamic, geometrical, location, multiplicity, and morphology parameters, and patient population. Generally, strong and concentrated inflow jets, high speed, complex and unstable flow patterns, and concentrated, oscillatory, and heterogeneous wall shear stress patterns together with larger, more elongated, and more distorted shapes were associated with bleb formation. The best performance on the validation set was achieved by the random forest model (AUC=0.82, TPR=91%, FPR=36%, misclassification error=27%). CONCLUSIONS: Based on the premise that aneurysm characteristics prior to bleb formation resemble those derived from vascular reconstructions with their blebs virtually removed, machine learning models can identify aneurysms prone to bleb development with good accuracy. Pending further validation with longitudinal data, these models may prove valuable for assessing the propensity of IAs to progress to vulnerable states and potentially rupturing.

Hemodynamics in aneurysm blebs with different wall characteristics.

BACKGROUND: Blebs are important secondary structures of intracranial aneurysms associated with increased rupture risk and can affect local wall stress and hemodynamics. Mechanisms of bleb development and evolution are not clearly understood. We investigate the relationship between blebs with different wall characteristics and local hemodynamics and rupture sites. METHODS: Blebs with different wall appearances in intra-operative videos were analyzed with image-based computational fluid dynamics. Thin red blebs were compared against thick atherosclerotic/hyperplastic white/yellow blebs. Rupture points were identified in videos of ruptured aneurysms harboring blebs. RESULTS: Thin blebs tended to be closer to the inflow than atherosclerotic blebs of the same aneurysm (P=0.0234). Blebs near the inflow had higher velocity (P=0.0213), vorticity (P=0.0057), shear strain rate (P=0.0084), wall shear stress (WSS) (P=0.0085), and WSS gradient (P=0.0151) than blebs far from the inflow. In a subset of 12 ruptured aneurysms harboring blebs, rupture points were associated with thin blebs in 42% of aneurysms, atherosclerotic blebs in 25%, and were away from blebs in the remaining 33%. CONCLUSIONS: Not all blebs are equal; some have thin translucent walls while others have thick atherosclerotic walls. Thin blebs tend to be located closer to the inflow than atherosclerotic blebs. Blebs near the inflow are exposed to stronger flows with higher and spatially variable WSS than blebs far from the inflow which tend to have uniformly lower WSS. Aneurysms can rupture at thin blebs, atherosclerotic blebs, and even away from blebs. Further study of wall failure in aneurysms with different bleb types is needed.

Hemodynamic conditions that favor bleb formation in cerebral aneurysms.

BACKGROUND: Although it is generally believed that blebs represent weaker spots in the walls of intracranial aneurysms (IAs), it is largely unknown which aneurysm characteristics favor their development. OBJECTIVE: To investigate possible associations between aneurysm hemodynamic and geometric characteristics and the development of blebs in intracranial aneurysms. METHODS: A total of 270 IAs in 199 patients selected for surgical clipping were studied. Blebs were visually identified and interactively marked on patient-specific vascular models constructed from presurgical images. Blebs were then deleted from the vascular reconstruction to approximate the aneurysm before bleb formation. Computational fluid dynamics studies were performed in these models and in cases without blebs. Hemodynamic and geometric characteristics of aneurysms with and without blebs were compared. RESULTS: A total of 173 aneurysms had no blebs, while 97 aneurysms had a total of 122 blebs. Aneurysms favoring bleb formation had stronger (p<0.0001) and more concentrated inflow jets (p<0.0001), higher flow velocity (p=0.0061), more complex (p<0.0001) and unstable (p=0.0157) flow patterns, larger maximum wall shear stress (WSS; p<0.0001), more concentrated (p=0.0005) and oscillatory (p=0.0004) WSS distribution, and a more heterogeneous WSS field (p<0.0001), than aneurysms without blebs. They were also larger (p<0.0001), more elongated (p<0.0001), had wider necks (p=0.0002), and more distorted and irregular shapes (p<0.0001). CONCLUSIONS: Strong and concentrated inflow jets, high-speed, complex, and unstable flow patterns, and concentrated, oscillatory, and heterogeneous WSS patterns favor the formation of blebs in IAs. Blebs are more likely to form in large, elongated, and irregularly shaped aneurysms. These adverse characteristics could be considered signs of aneurysm instability when evaluating aneurysms for conservative observation or treatment.

Blebs in intracranial aneurysms: prevalence and general characteristics.

BACKGROUND: Blebs are rupture risk factors in intracranial aneurysms (IAs), but their prevalence, distribution, and associations with clinical factors as well as their causes and effects on aneurysm vulnerability remain unclear. METHODS: A total of 122 blebs in 270 IAs selected for surgery were studied using patient-specific vascular reconstructions from 3D angiographic images. Bleb geometry, location on the aneurysm, and frequency of occurrence in aneurysms at different locations were analyzed. Associations between gender, age, smoking, hypertension, hormone therapy, dental infection, and presence of blebs were investigated. RESULTS: Of all aneurysms with blebs, 77% had a single bleb and 23% had multiple blebs. Only 6% of blebs were at the neck, while 46% were in the body and 48% in the dome. Aneurysms with blebs were larger (p<0.0001), more elongated (p=0.0002), and with wider necks than aneurysms without blebs. Bleb presence was associated with dental infection (p=0.0426) and negatively associated with hormone therapy (p=0.0426) in women. Anterior and posterior communicating arteries had larger percentages of aneurysms with blebs than internal carotid arteries. Patients with a history of hypertension tended to have a larger percentage of aneurysms with blebs. However, these trends did not reach significance in this sample. CONCLUSIONS: Blebs are common in IAs, and most aneurysms harboring blebs have a single bleb. Blebs in the aneurysm neck are rare, but they are equally common in the body and dome. The presence of blebs in IAs was associated with dental infection, and negatively associated with hormone replacement therapy.

Comparison of statistical learning approaches for cerebral aneurysm rupture assessment.

PURPOSE: Incidental aneurysms pose a challenge to physicians who need to decide whether or not to treat them. A statistical model could potentially support such treatment decisions. The aim of this study was to compare a previously developed aneurysm rupture logistic regression probability model (LRM) to other machine learning (ML) classifiers for discrimination of aneurysm rupture status. METHODS: Hemodynamic, morphological, and patient-related information of 1631 cerebral aneurysms characterized by computational fluid dynamics simulations were used to train support vector machines (SVMs) with linear and RBF kernel (RBF-SVM), k-nearest neighbors (kNN), decision tree, random forest, and multilayer perceptron (MLP) neural network classifiers for predicting the aneurysm rupture status. The classifiers' accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were evaluated and compared to the LRM using 249 test cases obtained from two external cohorts. Additionally, important variables were determined based on the random forest and weights of the linear SVM. RESULTS: The AUCs of the MLP, LRM, linear SVM, RBF-SVM, kNN, decision tree, and random forest were 0.83, 0.82, 0.80, 0.81, 0.76, 0.70, and 0.79, respectively. The accuracy ranged between 0.76 (decision tree,) and 0.79 (linear SVM, RBF-SVM, and MLP). Important variables for predicting the aneurysm rupture status included aneurysm location, the mean surface curvature, and maximum flow velocity. CONCLUSION: The performance of the LRM was overall comparable to that of the other ML classifiers, confirming its potential for aneurysm rupture assessment. To further improve the predictions, additional information, e.g., related to the aneurysm wall, might be needed.

Calcification in Human Intracranial Aneurysms Is Highly Prevalent and Displays Both Atherosclerotic and Nonatherosclerotic Types.

OBJECTIVE: Although the clinical and biological importance of calcification is well recognized for the extracerebral vasculature, its role in cerebral vascular disease, particularly, intracranial aneurysms (IAs), remains poorly understood. Extracerebrally, 2 distinct mechanisms drive calcification, a nonatherosclerotic, rapid mineralization in the media and a slower, inflammation driven, atherosclerotic mechanism in the intima. This study aims to determine the prevalence, distribution, and type (atherosclerotic, nonatherosclerotic) of calcification in IAs and assess differences in occurrence between ruptured and unruptured IAs. Approach and Results: Sixty-five 65 IA specimens (48 unruptured, 17 ruptured) were resected perioperatively. Calcification and lipid pools were analyzed nondestructively in intact samples using high resolution (0.35 µm) microcomputed tomography. Calcification is highly prevalent (78%) appearing as micro (<500 µm), meso (500 µm-1 mm), and macro (>1 mm) calcifications. Calcification manifests in IAs as both nonatherosclerotic (calcification distinct from lipid pools) and atherosclerotic (calcification in the presence of lipid pools) with 3 wall types: Type I-only calcification, no lipid pools (20/51, 39%), Type II-calcification and lipid pools, not colocalized (19/51, 37%), Type III-calcification colocalized with lipid pools (12/51, 24%). Ruptured IAs either had no calcifications or had nonatherosclerotic micro- or meso-calcifications (Type I or II), without macro-calcifications. CONCLUSIONS: Calcification in IAs is substantially more prevalent than previously reported and presents as both nonatherosclerotic and atherosclerotic types. Notably, ruptured aneurysms had only nonatherosclerotic calcification, had significantly lower calcification fraction, and did not contain macrocalcifications. Improved understanding of the role of calcification in IA pathology should lead to new therapeutic targets.

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

PURPOSE: Assessing the rupture probability of intracranial aneurysms (IAs) remains challenging. Therefore, hemodynamic simulations are increasingly applied toward supporting physicians during treatment planning. However, due to several assumptions, the clinical acceptance of these methods remains limited. METHODS: To provide an overview of state-of-the-art blood flow simulation capabilities, the Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH) was conducted. Seventeen research groups from all over the world performed segmentations and hemodynamic simulations to identify the ruptured aneurysm in a patient harboring five IAs. Although simulation setups revealed good similarity, clear differences exist with respect to the analysis of aneurysm shape and blood flow results. Most groups (12/71%) included morphological and hemodynamic parameters in their analysis, with aspect ratio and wall shear stress as the most popular candidates, respectively. RESULTS: The majority of groups (7/41%) selected the largest aneurysm as being the ruptured one. Four (24%) of the participating groups were able to correctly select the ruptured aneurysm, while three groups (18%) ranked the ruptured aneurysm as the second most probable. Successful selections were based on the integration of clinically relevant information such as the aneurysm site, as well as advanced rupture probability models considering multiple parameters. Additionally, flow characteristics such as the quantification of inflow jets and the identification of multiple vortices led to correct predictions. CONCLUSIONS: MATCH compares state-of-the-art image-based blood flow simulation approaches to assess the rupture risk of IAs. Furthermore, this challenge highlights the importance of multivariate analyses by combining clinically relevant metadata with advanced morphological and hemodynamic quantification.

Downstream vascular changes after flow-diverting device deployment in a rabbit model.

BACKGROUND: Flow diverters (FDs) are increasingly used in the treatment of intracranial aneurysms, and carry the risk of thromboembolic complications, even in patients treated with dual antiplatelet therapy. The effect of FDs on the downstream vascular is unknown. The aim of the study was to investigate vascular wall pulse wave velocity (PWV) and contractility changes following FD treatment in a rabbit model. METHODS: FDs (Pipeline Embolic Device, Medtronic Inc., Irvine, California, USA) were implanted in the aorta of normal rabbits and sham-operated aorta were used as controls (n=6 per group). Pulse wave imaging with ultra-fast ultrasound at 1600 frames per second (Vantage, Verasonics, Inc., Kirkland, WA) was performed in the vessel wall distal to FD prior to device implantation and at 8- week follow-up to measure the PWV. Force contraction vascular reactivity studies were conducted in the aortic rings using an organ bath. RESULTS: The difference in mean PWV in the follow-up compared with pre-implantation was significantly higher in the distal vessels compared with sham controls (1.18 m/s [SD=0.54] vs. 0.37 m/s [SD=1.09], P=0.03). Conversely, the aortic segments distal to the FD exhibited a 55% increase in vascular contractility compared with proximal segments (P=0.002). We observed a significant positive correlation between mean PWV and mean vascular contractility. CONCLUSION: Implantation of FD was associated with increased PWV and vascular contractility, suggesting that FD implantation causes changes to the vascular wall. Further studies are needed to understand the clinical implication of changes in vascular PWV and contractility.

Development and internal validation of an aneurysm rupture probability model based on patient characteristics and aneurysm location, morphology, and hemodynamics.

PURPOSE: Unruptured cerebral aneurysms pose a dilemma for physicians who need to weigh the risk of a devastating subarachnoid hemorrhage against the risk of surgery or endovascular treatment and their complications when deciding on a treatment strategy. A prediction model could potentially support such treatment decisions. The aim of this study was to develop and internally validate a model for aneurysm rupture based on hemodynamic and geometric parameters, aneurysm location, and patient gender and age. METHODS: Cross-sectional data from 1061 patients were used for image-based computational fluid dynamics and shape characterization of 1631 aneurysms for training an aneurysm rupture probability model using logistic group Lasso regression. The model's discrimination and calibration were internally validated based on the area under the curve (AUC) of the receiver operating characteristic and calibration plots. RESULTS: The final model retained 11 hemodynamic and 12 morphological variables, aneurysm location, as well as patient age and gender. An adverse hemodynamic environment characterized by a higher maximum oscillatory shear index, higher kinetic energy and smaller low shear area as well as a more complex aneurysm shape, male gender and younger age were associated with an increased rupture risk. The corresponding AUC of the model was 0.86 (95% CI [0.85, 0.86], after correction for optimism 0.84). CONCLUSION: The model combining variables from various domains was able to discriminate between ruptured and unruptured aneurysms with an AUC of 86%. Internal validation indicated potential for the application of this model in clinical practice after evaluation with longitudinal data.

Hemodynamic characteristics of stable and unstable vertebrobasilar dolichoectatic and fusiform aneurysms.

BACKGROUND AND PURPOSE: Vertebrobasilar dolichoectatic and fusiform aneurysms (VBDAs) are known to have a poor natural history, with high rates of growth, rupture, and stroke. The purpose of this study was to identify hemodynamic characteristics that differ between VBDAs associated with growth, rupture, and stroke. MATERIALS AND METHODS: VBDAs with CT angiography or MR angiography followed longitudinally without treatment were studied. Unstable aneurysms were defined as those that grew or ruptured during follow-up. Aneurysms associated with stroke were defined as those associated with posterior circulation infarct at follow-up. Baseline data, including demographics, comorbidities, and aneurysm morphology and size were collected. Image based computational fluid dynamics models were created and run under pulsatile flow conditions. Relevant hemodynamic and geometric variables were calculated and compared between groups (stable vs unstable and no stroke vs stroke) using the Wilcoxon test. RESULTS: A total of 37 VBDAs were included (24 stable, 13 unstable; 30 no stroke, 7 stroke). Unstable aneurysms had lower shear rates (P=0.05), blood flow velocity (P=0.03), and lower vorticity (P=0.049) than stable aneurysms. In addition, unstable aneurysms had higher mean oscillatory shear indices (P=0.001). There were no differences in the hemodynamic characteristics of aneurysms in the stroke group compared with the non-stroke group. CONCLUSION: This small study suggests there may be hemodynamic differences between unstable and stable VBDAs. Unstable VBDAs appear to be under lower flow conditions with lower velocity, vorticity, and shear rates, and have more oscillatory flow. There was no difference in the hemodynamic characteristics of aneurysms in the stroke and no stroke group.

Hemodynamic differences between unstable and stable unruptured aneurysms independent of size and location: a pilot study.

BACKGROUND: While clinical and angiographic risk factors for intracranial aneurysm instability are well established, it is reasonable to postulate that intra-aneurysmal hemodynamics also have a role in aneurysm instability. OBJECTIVE: To identify hemodynamic characteristics that differ between radiologically unstable and stable unruptured intracranial aneurysms. MATERIALS AND METHODS: 12 pairs of unruptured intracranial aneurysms with a 3D rotational angiographic set of images and followed up longitudinally without treatment were studied. Each pair consisted of one stable aneurysm (no change on serial imaging) and one unstable aneurysm (demonstrated growth of at least 1 mm diameter or ruptured during follow-up) of matching size (within 10%) and locations. Patient-specific computational fluid dynamics models were created and run under pulsatile flow conditions. Relevant hemodynamic and geometric variables were calculated and compared between groups using the paired Wilcoxon test. RESULTS: The area of the aneurysm under low wall shear stress (low shear stress area (LSA)) was 2.26 times larger in unstable aneurysms than in stable aneurysms (p=0.0499). The mean aneurysm vorticity was smaller by a factor of 0.57 in unstable aneurysms compared with stable aneurysms (p=0.0499). No statistically significant differences in geometric variables or shape indices were found. CONCLUSIONS: This pilot study suggests there may be hemodynamic differences between unstable and stable unruptured cerebral aneurysms. In particular, the area under low wall shear stress was larger in unstable aneurysms. These findings should be considered tentative until confirmed by future larger studies.

Hemodynamics in growing and stable cerebral aneurysms.

OBJECTIVE: The detailed mechanisms of cerebral aneurysm evolution are poorly understood but are important for objective aneurysm evaluation and improved patient management. The purpose of this study was to identify hemodynamic conditions that may predispose aneurysms to growth. METHODS: A total of 33 intracranial unruptured aneurysms longitudinally followed with three-dimensional imaging were studied. Patient-specific computational fluid dynamics models were constructed and used to quantitatively characterize the hemodynamic environments of these aneurysms. Hemodynamic characteristics of growing (n=16) and stable (n=17) aneurysms were compared. Logistic regression statistical models were constructed to test the predictability of aneurysm growth by hemodynamic features. RESULTS: Growing aneurysms had significantly smaller shear rate ratios (p=0.01), higher concentration of wall shear stress (p=0.03), smaller vorticity ratios (p=0.01), and smaller viscous dissipation ratios (p=0.01) than stable aneurysms. They also tended to have larger areas under low wall shear stress (p=0.06) and larger aspect ratios (p=0.18), but these trends were not significant. Mean wall shear stress was not significantly different between growing and stable aneurysms. Logistic regression models based on hemodynamic variables were able to discriminate between growing and stable aneurysms with a high degree of accuracy (94-100%). CONCLUSIONS: Growing aneurysms tend to have complex intrasaccular flow patterns that induce non-uniform wall shear stress distributions with areas of concentrated high wall shear stress and large areas of low wall shear stress. Statistical models based on hemodynamic features seem capable of discriminating between growing and stable aneurysms.

Hemodynamic analysis of fast and slow aneurysm occlusions by flow diversion in rabbits.

PURPOSE: To assess hemodynamic differences between aneurysms that occlude rapidly and those occluding in delayed fashion after flow diversion in rabbits. METHODS: Thirty-six elastase-induced aneurysms in rabbits were treated with flow diverting devices. Aneurysm occlusion was assessed angiographically immediately before they were sacrificed at 1 (n=6), 2 (n=4), 4 (n=8) or 8 weeks (n=18) after treatment. The aneurysms were classified into a fast occlusion group if they were completely or near completely occluded at 4 weeks or earlier and a slow occlusion group if they remained incompletely occluded at 8 weeks. The immediate post-treatment flow conditions in aneurysms of each group were quantified using subject-specific computational fluid dynamics and statistically compared. RESULTS: Nine aneurysms were classified into the fast occlusion group and six into the slow occlusion group. Aneurysms in the fast occlusion group were on average significantly smaller (fast=0.9 cm, slow=1.393 cm, p=0.024) and had smaller ostia (fast=0.144 cm2, slow=0.365 cm2, p=0.015) than aneurysms in the slow occlusion group. They also had a lower mean post-treatment inflow rate (fast=0.047 mL/s, slow=0.155 mL/s, p=0.0239), kinetic energy (fast=0.519 erg, slow=1.283 erg, p=0.0468), and velocity (fast=0.221 cm/s, slow=0.506 cm/s, p=0.0582). However, the differences in the latter two variables were only marginally significant. CONCLUSIONS: Hemodynamic conditions after flow diversion treatment of cerebral aneurysms in rabbits are associated with the subsequent aneurysm occlusion time. Specifically, smaller inflow rate, kinetic energy, and velocity seem to promote faster occlusions, especially in smaller and small-necked aneurysms. These results are consistent with previous studies based on clinical series.

Association between hemodynamic conditions and occlusion times after flow diversion in cerebral aneurysms.

BACKGROUND: Evaluation of flow diversion treatment of intracranial aneurysms is difficult owing to lack of knowledge of the target hemodynamic environment. OBJECTIVE: To identify hemodynamic conditions created after flow diversion that induce fast aneurysm occlusion. METHODS: Two groups of aneurysms treated with flow diverters alone were selected: (a) aneurysms completely occluded at 3 months (fast occlusion), and (b) aneurysms patent or incompletely occluded at 6 months (slow occlusion). A total of 23 aneurysms were included in the study. Patient-specific computational fluid dynamics models were constructed and used to characterize the hemodynamic environment immediately before and after treatment. Average post-treatment hemodynamic conditions between the fast and slow occlusion groups were statistically compared. RESULTS: Aneurysms in the fast occlusion group had significantly lower post-treatment mean velocity (fast=1.13 cm/s, slow=3.11 cm/s, p=0.02), inflow rate (fast=0.47 mL/s, slow=1.89 mL/s, p=0.004) and shear rate (fast=20.52 1/s, slow=32.37 1/s, p=0.02) than aneurysms in the slow occlusion group. Receiver operating characteristics analysis showed that mean post-treatment velocity, inflow rate, and shear rate below a certain threshold could discriminate between aneurysms of the fast and slow occlusion groups with good accuracy (84%, 77%, and 76%, respectively). CONCLUSIONS: The occlusion time of cerebral aneurysms treated with flow diverters can be predicted by the hemodynamic conditions created immediately after device implantation. Specifically, low post-implantation flow velocity, inflow rate, and shear rate are associated with fast occlusion times.

Analysis of hemodynamics and wall mechanics at sites of cerebral aneurysm rupture.

BACKGROUND: It is thought that aneurysms evolve as the result of progressive degradation of the wall in response to abnormal hemodynamics characterized by either high or low wall shear stress (WSS). OBJECTIVE: To investigate the effects of these two different hemodynamic pathways in a series of cerebral aneurysms with known rupture sites. METHODS: Nine aneurysms in which the rupture site could be identified in three-dimensional images were analyzed. The WSS distribution was obtained from computational fluid dynamics (CFD) simulations. Internal wall stresses were computed using structural wall models under hemodynamic loads determined by the CFD models. Wall properties (thickness and stiffness) were modulated with the WSS distribution (increased or decreased in regions of high or low WSS) to test possible wall degradation pathways. Rupture probability indices (RPI) were calculated to compare different wall models. RESULTS: Most rupture sites aligned with the intrasaccular flow stream and downstream of the primary impaction zone. The model that best explained the rupture site (produced higher RPI) in eight of the nine aneurysms (89%) had thinner and stiffer walls in regions of abnormally high WSS. The remaining case (11%) was best explained by a model with thinner and stiffer walls in regions of abnormally low WSS. CONCLUSIONS: Aneurysm rupture seems to be caused by localized degradation and weakening of the wall in response to abnormal hemodynamics. Image-based computational models assuming wall thinning and stiffening in regions of abnormally high WSS were able to explain most of the observed rupture sites.

Suggested connections between risk factors of intracranial aneurysms: a review.

The purpose of this article is to review studies of aneurysm risk factors and the suggested hypotheses that connect the different risk factors and the underlying mechanisms governing the aneurysm natural history. The result of this work suggests that at the center of aneurysm evolution there is a cycle of wall degeneration and weakening in response to changing hemodynamic loading and biomechanic stress. This progressive wall degradation drives the geometrical evolution of the aneurysm until it stabilizes or ruptures. Risk factors such as location, genetics, smoking, co-morbidities, and hypertension seem to affect different components of this cycle. However, details of these interactions or their relative importance are still not clearly understood.

Tracheal and central bronchial aerodynamics using virtual bronchoscopy and computational fluid dynamics.

Virtual bronchoscopy reconstructions of the airway noninvasively provide useful morphologic information of structural abnormalities such as stenoses and masses. In this paper, we show how virtual bronchoscopy can be used to perform aerodynamic calculations in anatomically realistic models. Pressure and flow patterns in a human airway were computed noninvasively. These showed decreased pressure and increased shear stress in the region of a stenosis.