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.

Description of the local hemodynamic environment in intracranial aneurysm wall subdivisions.

Intracranial aneurysms (IAs) pose severe health risks influenced by hemodynamics. This study focuses on the intricate characterization of hemodynamic conditions within the IA walls and their influence on bleb development, aiming to enhance understanding of aneurysm stability and the risk of rupture. The methods emphasized utilizing a comprehensive dataset of 359 IAs and 213 IA blebs from 268 patients to reconstruct patient-specific vascular models, analyzing blood flow using finite element methods to solve the unsteady Navier-Stokes equations, the segmentation of aneurysm wall subregions and the hemodynamic metrics wall shear stress (WSS), its metrics, and the critical points in WSS fields were computed and analyzed across different aneurysm subregions defined by saccular, streamwise, and topographical divisions. The results revealed significant variations in these metrics, correlating distinct hemodynamic environments with wall features on the aneurysm walls, such as bleb formation. Critical findings indicated that regions with low WSS and high OSI, particularly in the body and central regions of aneurysms, are prone to conditions that promote bleb formation. Conversely, areas exposed to high WSS and positive divergence, like the aneurysm neck, inflow, and outflow regions, exhibited a different but substantial risk profile for bleb development, influenced by flow impingements and convergences. These insights highlight the complexity of aneurysm behavior, suggesting that both high and low-shear environments can contribute to aneurysm pathology through distinct mechanisms.

Computational fluid dynamics-based virtual angiograms for the detection of flow stagnation in intracranial aneurysms.

The goal of this study was to test if CFD-based virtual angiograms could be used to automatically discriminate between intracranial aneurysms (IAs) with and without flow stagnation. Time density curves (TDC) were extracted from patient digital subtraction angiography (DSA) image sequences by computing the average gray level intensity inside the aneurysm region and used to define injection profiles for each subject. Subject-specific 3D models were reconstructed from 3D rotational angiography (3DRA) and computational fluid dynamics (CFD) simulations were performed to simulate the blood flow inside IAs. Transport equations were solved numerically to simulate the dynamics of contrast injection into the parent arteries and IAs and then the contrast retention time (RET) was calculated. The importance of gravitational pooling of contrast agent within the aneurysm was evaluated by modeling contrast agent and blood as a mixture of two fluids with different densities and viscosities. Virtual angiograms can reproduce DSA sequences if the correct injection profile is used. RET can identify aneurysms with significant flow stagnation even when the injection profile is not known. Using a small sample of 14 IAs of which seven were previously classified as having flow stagnation, it was found that a threshold RET value of 0.46 s can successfully identify flow stagnation. CFD-based prediction of stagnation was in more than 90% agreement with independent visual DSA assessment of stagnation in a second sample of 34 IAs. While gravitational pooling prolonged contrast retention time it did not affect the predictive capabilities of RET. CFD-based virtual angiograms can detect flow stagnation in IAs and can be used to automatically identify aneurysms with flow stagnation even without including gravitational effects on contrast agents.