A long-time exposure to lack of oxygen (hypoxia) in some regions of the cerebrovascular system is believed to be one of the causes of cerebral neurological diseases. In the present study, we show how a combination of magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) can provide a noninvasive alternative for studying blood flow and transport of oxygen within the cerebral vasculature. We perform computer simulations of oxygen mass transfer in the subject-specific geometry of the circle of Willis. The computational domain and boundary conditions are based on four-dimensional (4D)-flow MRI measurements. Two different oxygen mass transfer models are considered: passive (where oxygen is treated as a dilute chemical species in plasma) and active (where oxygen is bonded to haemoglobin) models. We show that neglecting haemoglobin transport results in a significant underestimation of the arterial wall mass transfer of oxygen. We identified the hypoxic regions along the arterial walls by introducing the critical thresholds that are obtained by comparison of the estimated range of Damköhler number (Da, 〈9; 57〉) with the local Sherwood number. Finally, we recommend additional validations of the combined MRI/CFD approach proposed here for larger groups of subject- or patient-specific brain vasculature systems.

Introduction: Wall shear stress (WSS) is associated with the growth and rupture of an intracranial aneurysm. To reveal their underlying connections, many image-based computational fluid dynamics (CFD) studies have been conducted. However, the methodological validations using both in vivo medical imaging and in vitro optical flow measurements were rarely accompanied in such studies. Methods: In the present study, we performed a comparative assessment on the hemodynamics of a patient-specific intracranial saccular aneurysm using in vivo 4D Flow MRI, in silico CFD, in vitro stereoscopic and tomographic particle imaging velocimetry (Stereo-PIV and Tomo-PIV) techniques. PIV experiments and CFD were conducted under steady state corresponding to the peak systole of 4D Flow MRI. Results: The results showed that all modalities provided similar flow features and overall surface distribution of WSS. However, a large variation in the absolute WSS values was found. 4D Flow MRI estimated a 2- to 4-fold lower peak WSS (3.99 Pa) and a 1.6- to 2-fold lower mean WSS (0.94 Pa) than Tomo-PIV, Stereo-PIV, and CFD. Bland-Altman plots of WSS showed that the differences between PIV-/CFD-based WSS and 4D Flow MRI-based WSS increase with higher WSS magnitude. Such proportional trend was absent in the Bland-Altman comparison of velocity where the resolutions of PIV and CFD datasets were matched to 4D Flow MRI. We also found that because of superior resolution in the out-of-plane direction, WSS estimation by Tomo-PIV was higher than Stereo-PIV. Conclusions: Our results indicated that the differences in spatial resolution could be the main contributor to the discrepancies between each modality. The findings of this study suggest that with current techniques, care should be taken when using absolute WSS values to perform a quantitative risk analysis of aneurysm rupture.

Phase-Contrast Magnetic Resonance Imaging (PC-MRI) surpasses all other imaging methods in quality and completeness for measuring time-varying volumetric blood flows and has shown potential to improve both diagnosis and risk assessment of cardiovascular diseases. However, like any measurement of physical phenomena, the data are prone to noise, artefacts and has a limited resolution. Therefore, PC-MRI data itself do not fulfil physics fluid laws making it difficult to distinguish important flow features. For data analysis, physically plausible and high-resolution data are required. Computational fluid dynamics provides high-resolution physically plausible flows. However, the flow is inherently coupled to the underlying anatomy and boundary conditions, which are difficult or sometimes even impossible to adequately model with current techniques. We present a novel methodology using data assimilation techniques for PC-MRI noise and artefact removal, generating physically plausible flow close to the measured data. It also allows us to increase the spatial and temporal resolution. To avoid sensitivity to the anatomical model, we consider and update the full 3D velocity field. We demonstrate our approach using phantom data with various amounts of induced noise and show that we can improve the data while preserving important flow features, without the need of a highly detailed model of the anatomy.

BACKGROUNDANDPURPOSE: Hemodynamics are thought to play an important role in the rupture of intracranial aneurysms.Wetested whether hemodynamics, determined from computational fluid dynamics models, have additional value in discriminating ruptured and unruptured aneurysms. Such discriminative power could provide better prediction models for rupture. MATERIALS AND METHODS: A cross-sectional study was performed on patients eligible for endovascular treatment, including 55 ruptured and 62 unruptured aneurysms. Association with rupture status was tested for location, aneurysm type, and 4 geometric and 10 hemodynamic parameters. Patient-specific spatiotemporal velocities measured with phase-contrast MR imaging were used as inflow conditions for computational fluid dynamics. To assess the additional value of hemodynamic parameters, we performed 1 univariate and 2 multivariate analyses: 1 traditional model including only location and geometry and 1 advanced model that included patient-specific hemodynamic parameters. RESULTS: In the univariate analysis, high-risk locations (anterior cerebral arteries, posterior communicating artery, and posterior circulation), daughter sacs, unstable inflow jets, impingements at the aneurysm body, and unstable complex flow patterns were significantly present more often in ruptured aneurysms. In both multivariate analyses, only the high-risk location (OR, 3.92; 95% CI, 1.77-8.68) and the presence of daughter sacs (OR, 2.79; 95% CI, 1.25-6.25) remained as significant independent determinants. CONCLUSIONS: In this study population of patients eligible for endovascular treatment, we found no independent additional value of aneurysmal hemodynamics in discriminating rupture status, despite high univariate associations. Only traditional parameters (high-risk location and the presence of daughter sacs) were independently associated with ruptured aneurysms.