Computational fluid dynamics (CFD) opens up multiple opportunities to investigate the hemodynamics of the human vascular system. However, due to numerous assumptions the acceptance of CFD among physicians is still limited in practice and validation through comparison is mandatory. Time-dependent quantitative phase-contrast magnetic resonance imaging PC-MRI measurements in a healthy volunteer and two intracranial aneurysms were carried out at 3 and 7 Tesla. Based on the acquired images, three-dimensional (3D) models of the aneurysms were reconstructed and used for the numerical simulations. Flow information from the MR measurements were applied as boundary conditions. The four-dimensional (4D) velocity fields obtained by CFD and MRI were qualitatively as well as quantitatively compared including cut planes and vector analyses. For all cases a high similarity of the velocity patterns was observed. Additionally, the quantitative analysis revealed a good agreement between CFD and MRI. Deviations were caused by minor differences between the reconstructed vessel models and the actual lumen. The comparisons between diastole and systole indicate that relative differences between MRI and CFD are intensified with increasing velocity. The findings of this study lead to the conclusion that CFD and MRI agree well in predicting intracranial velocities when realistic geometries and boundary conditions are provided. Due to the considerably higher temporal and spatial resolution of CFD compared to MRI, complex flow patterns can be further investigated in order to evaluate their role with respect to aneurysm formation or rupture. Nevertheless, special care is required regarding the vessel reconstruction since the geometry has a major impact on the subsequent numerical results.

Computational blood flow modeling in intracranial aneurysms (IAs) has enormous potential for the assessment of highly resolved hemodynamics and derived wall stresses. This results in an improved knowledge in important research fields, such as rupture risk assessment and treatment optimization. However, due to the requirement of assumptions and simplifications, its applicability in a clinical context remains limited. This review article focuses on the main aspects along the interdisciplinary modeling chain and highlights the circumstance that computational fluid dynamics (CFD) simulations are embedded in a multiprocess workflow. These aspects include imaging-related steps, the setup of realistic hemodynamic simulations, and the analysis of multidimensional computational results. To condense the broad knowledge, specific recommendations are provided at the end of each subsection. Overall, various individual substudies exist in the literature that have evaluated relevant technical aspects. In this regard, the importance of precise vessel segmentations for the simulation outcome is emphasized. Furthermore, the accuracy of the computational model strongly depends on the specific research question. Additionally, standardization in the context of flow analysis is required to enable an objective comparison of research findings and to avoid confusion within the medical community. Finally, uncertainty quantification and validation studies should always accompany numerical investigations. In conclusion, this review aims for an improved awareness among physicians regarding potential sources of error in hemodynamic modeling for IAs. Although CFD is a powerful methodology, it cannot provide reliable information, if pre- and postsimulation steps are inaccurately carried out. From this, future studies can be critically evaluated and real benefits can be differentiated from results that have been acquired based on technically inaccurate procedures.

Image-based hemodynamic simulations to assess the rupture risk or improve the treatment planning of intracranial aneurysms have become popular recently. However, due to strong modeling assumptions and limitations, the acceptance of numerical approaches remains limited. Therefore, validation using experimental methods is mandatory.In this study, a unique compilation of four in-vitro flow measurements (three particle image velocimetry approaches using a standard (PIV), stereoscopic (sPIV), and tomographic (tPIV) setup, as well as a phase-contrast magnetic resonance imaging (PC-MRI) measurement) were compared with a computational fluid dynamics (CFD) simulation. This was carried out in a patient-specific silicone phantom model of an internal carotid artery aneurysm under steady flow conditions. To evaluate differences between each technique, a similarity index (SI) with respect to the velocity vectors and the average velocity magnitude differences among all involved modalities were computed.The qualitative comparison reveals that all techniques are able to provide a reasonable description of the global flow structures. High quantitative agreement in terms of SI and velocity magnitude differences was found between all PIV methods and CFD. However, quantitative differences were observed between PC-MRI and the other techniques. Deeper analysis revealed that the limited resolution of the PC-MRI technique is a major contributor to the experienced differences and leads to a systematic underestimation of overall velocity magnitude levels inside the vessel. This confirms the necessity of using highly resolving flow measurement techniques, such as PIV, in an in-vitro environment to individually verify the validity of the numerically obtained hemodynamic results.

Purpose: Circumferential enhancement on MR vessel wall imaging has been proposed as a biomarker of a higher risk of rupture in intracranial aneurysms. Focal enhancement is frequently encountered in unruptured aneurysms, but its implication for risk stratification and patient management remains unclear. This study investigates the association of focal wall enhancement with hemodynamic and morphological risk factors and histologic markers of wall inflammation and degeneration. Methods: Patients with an unruptured middle cerebral artery aneurysm who underwent 3D rotational angiography and 3T MR vessel wall imaging showing focal wall enhancement were included. Hemodynamic parameters were calculated based on flow simulations and compared between enhanced regions and the entire aneurysm surface. Morphological parameters were semiautomatically extracted and quantitatively associated with wall enhancement. Histological analysis included detection of vasa vasorum, CD34, and myeloperoxidase staining in a subset of patients. Results: Twenty-two aneurysms were analyzed. Enhanced regions were significantly associated with lower AWSS, lower maxOSI, and increased LSA. In multivariate analysis, higher ellipticity index was an independent predictor of wall enhancement. Histologic signs of inflammation and degeneration and higher PHASES score were significantly associated with focal enhancement. Conclusion: Focal wall enhancement is colocalized with hemodynamic factors that have been related to a higher rupture risk. It is correlated with morphological factors linked to rupture risk, higher PHASES score, and histologic markers of wall destabilization. The results support the hypothesis that focal enhancement could serve as a surrogate marker for aneurysm instability.