We present a modeling framework designed for patient-specific computational hemodynamics to be performed in the context of large-scale studies. The framework takes advantage of the integration of image processing, geometric analysis and mesh generation techniques, with an accent on full automation and high-level interaction. Image segmentation is performed using implicit deformable models taking advantage of a novel approach for selective initialization of vascular branches, as well as of a strategy for the segmentation of small vessels. A robust definition of centerlines provides objective geometric criteria for the automation of surface editing and mesh generation. The framework is available as part of an open-source effort, the Vascular Modeling Toolkit, a first step towards the sharing of tools and data which will be necessary for computational hemodynamics to play a role in evidence-based medicine.

Background and Purpose-That certain vessels might be at so-called geometric risk of atherosclerosis rests on assumptions of wide interindividual variations in disturbed flow and of a direct relationship between disturbed flow and lumen geometry. In testing these often-implicit assumptions, the present study aimed to determine whether investigations of local risk factors in atherosclerosis can indeed rely on surrogate geometric markers of disturbed flow. Methods-Computational fluid dynamics simulations were performed on carotid bifurcation geometries derived from MRI of 25 young adults. Disturbed flow was quantified as the surface area exposed to low and oscillatory shear beyond objectively-defined thresholds. Interindividual variations in disturbed flow were contextualized with respect to effects of uncertainties in imaging and geometric reconstruction. Relationships between disturbed flow and various geometric factors were tested via multiple regression. Results-Relatively wide variations in disturbed flow were observed among the 50 vessels. Multiple regression revealed a significant (PϽ0.002) relationship between disturbed flow and both proximal area ratio (␤Ϸ0.5) and bifurcation tortuosity (␤ϷϪ0.4), but not bifurcation angle, planarity, or distal area ratio. These findings were shown to be insensitive to assumptions about the flow conditions and to the choice of disturbed flow indicator and threshold. Conclusions-Certain geometric features of the young adult carotid bifurcation are robust surrogate markers of its exposure to disturbed flow. It may therefore be reasonable to consider large-scale retrospective or prospective imaging studies of local risk factors for atherosclerosis without the need for time-consuming and expensive flow imaging or CFD studies.

Purpose: To develop a high isotropic-resolution sequence to evaluate intracranial vessels at 3.0 Tesla (T).Materials and Methods: Thirteen healthy volunteers and 4 patients with intracranial stenosis were imaged at 3.0T using 0.5-mm isotropic-resolution three-dimensional (3D) Volumetric ISotropic TSE Acquisition (VISTA; TSE, turbo spin echo), with conventional 2D-TSE for comparison. VISTA was repeated for 6 volunteers and 4 patients at 0.4-mm isotropic-resolution to explore the trade-off between SNR and voxel volume. Wall signal-to-noise-ratio (SNR wall ), wall-lumen contrast-to-noise-ratio (CNR wall-lumen ), lumen area (LA), wall area (WA), mean wall thickness (MWT), and maximum wall thickness (maxWT) were compared between 3D-VISTA and 2D-TSE sequences, as well as 3D images acquired at both resolutions. Reliability was assessed by intraclass correlations (ICC).Results: Compared with 2D-TSE measurements, 3D-VISTA provided 58% and 74% improvement in SNR wall and CNR wall-lumen , respectively. LA, WA, MWT and maxWT from 3D and 2D techniques highly correlated (ICCs of 0.96, 0.95, 0.96, and 0.91, respectively). CNR wall-lumen using 0.4-mm resolution VISTA decreased by 27%, compared with 0.5-mm VISTA but with reduced partial-volume-based overestimation of wall thickness. Reliability for 3D measurements was good to excellent. Conclusion:The 3D-VISTA provides SNR-efficient, highly reliable measurements of intracranial vessels at high isotropic-resolution, enabling broad coverage in a clinically acceptable time.

Knowledge of normal cerebrovascular volumetric flow rate (VFR) dynamics is of interest for establishing baselines, and for providing input data to cerebrovascular model studies. Retrospectively gated phase contrast magnetic resonance imaging was used to measure time-resolved VFR waveforms from the two internal carotid arteries (ICA) and two vertebral arteries (VA) of 17 young, normal volunteers (16M:1F) at rest in a supine posture. After normalizing each waveform to its respective cycle-averaged VFR, the timing and amplitude of feature points from the individual waveforms were averaged together to produce archetypal ICA and VA waveform shapes. Despite significant inter-individual differences in cycle-averaged VFR within the ICA compared to VA (275+/-52 versus 91+/-18 mL min-1), the respective waveform shapes were qualitatively similar overall. The VA waveform shape did, however, exhibit significantly higher amplitudes (e.g., peak:average VFR of 1.78+/-0.30 versus 1.66+/-0.16; p<0.05) and significantly higher variability both between and within subjects. A significant correlation was observed between peak and cycle-averaged VFR, suggesting that the representative waveform shapes presented here-when scaled by an individual's cycle-averaged VFR-may be used to characterize normal ICA and VA flow rate dynamics. This capability may be of particular utility for studies where cerebrovascular flow dynamics are required, but only average flow rates are available.

There is well-documented evidence that vascular geometry has a major impact in blood flow dynamics and consequently in the development of vascular diseases, like atherosclerosis and cerebral aneurysmal disease. The study of vascular geometry and the identification of geometric features associated with a specific pathological condition can therefore shed light into the mechanisms involved in the pathogenesis and progression of the disease. Although the development of medical imaging technologies is providing increasing amounts of data on the three-dimensional morphology of the in vivo vasculature, robust and objective tools for quantitative analysis of vascular geometry are still lacking. In this paper, we present a framework for the geometric analysis of vascular structures, in particular for the quantification of the geometric relationships between the elements of a vascular network based on the definition of centerlines. The framework is founded upon solid computational geometry criteria, which confer robustness of the analysis with respect to the high variability of in vivo vascular geometry. The techniques presented are readily available as part of the VMTK, an open source framework for image segmentation, geometric characterization, mesh generation and computational hemodynamics specifically developed for the analysis of vascular structures. As part of the Aneurisk project, we present the application of the present framework to the characterization of the geometric relationships between cerebral aneurysms and their parent vasculature.