Hemodynamic and morphological characteristics of a growing cerebral aneurysm

Abstract

<jats:p>The growth of cerebral aneurysms is linked to local hemodynamic conditions, but the driving mechanisms of the growth are poorly understood. The goal of this study was to examine the association between intraaneurysmal hemodynamic features and areas of aneurysm growth, to present the key hemodynamic parameters essential for an accurate prediction of the growth, and to gain a deeper understanding of the underlying mechanisms. Patient-specific images of a growing cerebral aneurysm in 3 different growth stages acquired over a period of 40 months were segmented and reconstructed. A unique aspect of this patient-specific case study was that while one side of the aneurysm stayed stable, the other side continued to grow. This unique case enabled the authors to examine their aims in the same patient with parent and daughter arteries under the same inlet flow conditions. Pulsatile flow in the aneurysm models was simulated using computational fluid dynamics and was validated with in vitro experiments using particle image velocimetry measurements. The authors’ detailed analysis of intrasaccular hemodynamics linked the growing regions of aneurysms to flow instabilities and complex vortex structures. Extremely low velocities were observed at or around the center of the unstable vortex structure, which matched well with the growing regions of the studied cerebral aneurysm. Furthermore, the authors observed that the aneurysm wall regions with a growth greater than 0.5 mm coincided with wall regions of lower (&lt; 0.5 Pa) time-averaged wall shear stress (TAWSS), lower instantaneous (&lt; 0.5 Pa) wall shear stress (WSS), and high (&gt; 0.1) oscillatory shear index (OSI). To determine which set of parameters can best identify growing and nongrowing aneurysms, the authors performed statistical analysis for consecutive stages of the growing CA. The results demonstrated that the combination of TAWSS and the distance from the center of the vortical structure has the highest sensitivity and positive predictive value, and relatively high specificity and negative predictive value. These findings suggest that an unstable, recirculating flow structure within the aneurysm sac created in the region adjacent to the aneurysm wall with low TAWSS may be introduced as an accurate criterion to explain the hemodynamic conditions predisposing the aneurysm to growth. The authors’ findings are based on one patient’s data set, but the study lays out the justification for future large-scale verification. The authors’ findings can assist clinicians in differentiating stable and growing aneurysms during preinterventional planning.</jats:p>

Analysis on Characteristics of Magnetic Resonance Imaging Image under Low-Rank Matrix Denoising Algorithm in the Diagnosis of Cerebral Aneurysm

“…MRI has features that allow accurate localization of lesions, acquisition of multidirectional imaging of tissues and organs, observation of cerebrovascular network distribution, etc., and is currently an important marker for the diagnosis of intracranial aneurysms [ 11 , 12 ]. MRI is susceptible to Rician noise pollution during imaging or transmission.…”

Predictive Factors of Cerebral Aneurysm Rerupture After Clipping

“…In the multiple regression analysis, we found that aneurysms located on the Pcom artery also have a very high risk of rerupture (HR = 2.934, 95% CI: 1.313–6.556, P = 0.009) ( Table 4 ). Compared with the middle cerebral artery or the posterior cerebral artery, common aneurysm sites are the anterior communicating (Acom) and Pcom arteries, as Acom and Pcom are of small vessel calibers and prone to unstable systemic blood pressure leading to the formation of the aneurysm and subsequent rupture event ( 4 , 5 ). In this study, since the case numbers of posterior circulation vessel datasets are few, more studies are required to validate this finding ( 11 – 13 ).…”

“…However, there is a lack of knowledge over the chance of rupture in patients undergoing aneurysmal clipping operation and the subsequent long-term functionality. Additionally, most aneurysms are found over the anterior circulation of the Circle of Willis, of which the reason why this is the case is yet to be studied in depth, although it has been postulated that it has something to do with blood flow fluctuations and plaque predilection over anterior circulation rather than in the posterior circulation ( 5 ). There has been little documentation of the mechanisms and weight of risk based on the various locations of aneurysms.…”

A data-driven approach to modeling cancer cell mechanics during microcirculatory transport

“…Simulations are performed using HARVEY, a 3D lattice Boltzmann method (LBM)-based computational fluid dynamics solver 37 , 40 , 56 – 58 . HARVEY has been used to study a wide range of physiological applications, such as the hemodynamics of a growing cerebral aneurysm 59 , computing the ankle-brachial index for diagnosing conditions such as peripheral artery disease 60 , cell adhesion in microvessels and impacts on wall shear stress 47 , and large-scale RBC simulations in a cerebral vasculature 40 . For modeling flows of deformable cells, HARVEY utilizes the immersed boundary method (IBM), and with this approach cancer cells are modeled as membranes of infinitesimal thickness surrounded by and enclosing a viscous fluid with which they flow.…”