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Broad consensus emerged on the protective role against dementia of leisure activities. Conflicting results were found for the association between dementia and putative risk factors (smoking) and protective factors (mild-to-moderate alcohol consumption, dietary antioxidants, Mediterranean diet, and living with others). However, studies varied largely in the quantification of lifestyle factors in terms of intensity, frequency and duration of exposure, and in the choice of confounders in statistical analyses. The need for standardized quantification criteria emerges, together with the current limitation in reliably tracking the past history of each patient, from childhood and young adulthood to midlife.

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Abstract-Modeling of flow in intracranial aneurysms (IAs) requires flow information at the model boundaries. In absence of patient-specific measurements, typical or modeled boundary conditions (BCs) are often used. This study investigates the effects of modeled versus patient-specific BCs on modeled hemodynamics within IAs. Computational fluid dynamics (CFD) models of five IAs were reconstructed from threedimensional rotational angiography (3DRA). BCs were applied using in turn patient-specific phase-contrast-MR (pc-MR) measurements, a 1D-circulation model, and a physiologically coherent method based on local WSS at inlets. The Navier-Stokes equations were solved using the Ansys Ò -CFX TM software. Wall shear stress (WSS), oscillatory shear index (OSI), and other hemodynamic indices were computed. Differences in the values obtained with the three methods were analyzed using boxplot diagrams. Qualitative similarities were observed in the flow fields obtained with the three approaches. The quantitative comparison showed smaller discrepancies between pc-MR and 1D-model data, than those observed between pc-MR and WSS-scaled data. Discrepancies were reduced when indices were normalized to mean hemodynamic aneurysmal data. The strong similarities observed for the three BCs models suggest that vessel and aneurysm geometry have the strongest influence on aneurysmal hemodynamics. In absence of patient-specific BCs, a distributed circulation model may represent the best option when CFD is used for large cohort studies.

One-dimensional models of the cardiovascular system can capture the physics of pulse waves but involve many parameters. Since these may vary among individuals, patient-specific models are difficult to construct. Sensitivity analysis can be used to rank model parameters by their effect on outputs and to quantify how uncertainty in parameters influences output uncertainty. This type of analysis is often conducted with a Monte Carlo method, where large numbers of model runs are used to assess input-output relations. The aim of this study was to demonstrate the computational efficiency of variance-based sensitivity analysis of 1D vascular models using Gaussian process emulators, compared to a standard Monte Carlo approach. The methodology was tested on four vascular networks of increasing complexity to analyse its scalability. The computational time needed to perform the sensitivity analysis with an emulator was reduced by the 99.96% compared to a Monte Carlo approach. Despite the reduced computational time, sensitivity indices obtained using the two approaches were comparable. The scalability study showed that the number of mechanistic simulations needed to train a Gaussian process for sensitivity analysis was of the order O(d), rather than O(d × 103 ) needed for Monte Carlo analysis (where d is the number of parameters in the model). The efficiency of this approach, combined with capacity to estimate the impact of uncertain parameters on model outputs, will enable development of patient-specific models of the vascular system, and has the potential to produce results with clinical relevance.

Cerebral aneurysms are a multi-factorial disease with severe consequences. A core part of the European project @neurIST was the physical characterization of aneurysms to find candidate risk factors associated with aneurysm rupture. The project investigated measures based on morphological, haemodynamic and aneurysm wall structure analyses for more than 300 cases of ruptured and unruptured aneurysms, extracting descriptors suitable for statistical studies. This paper deals with the unique challenges associated with this task, and the implemented solutions. The consistency of results required by the subsequent statistical analyses, given the heterogeneous image data sources and multiple human operators, was met by a highly automated toolchain combined with training. A testimonial of the successful automation is the positive evaluation of the toolchain by over 260 clinicians during various hands-on workshops. The specification of the analyses required thorough investigations of modelling and processing choices, discussed in a detailed analysis protocol. Finally, an abstract data model governing the management of the simulation-related data provides a framework for data provenance and supports future use of data and toolchain. This is achieved by enabling the easy modification of the modelling approaches and solution details through abstract problem descriptions, removing the need of repetition of manual processing work.Keywords: cerebral aneurysms; computational imaging and modelling; computational physiology; virtual physiological human

Haemodynamics is believed to play an important role in the initiation, growth and rupture of intracranial aneurysms. In this context, computational haemodynamics has been extensively used in an effort to establish correlations between flow variables and clinical outcome. It is common practice in the application of Dirichlet boundary conditions at domain inlets to specify transient velocities as either a flat (plug) profile or a spatially developed profile based on Womersley's analytical solution. This paper provides comparative haemodynamics measures for three typical cerebral aneurysms. Three dimentional rotational angiography images of aneurysms at three common locations, viz. basilar artery tip, internal carotid artery and middle cerebral artery were obtained. The computational tools being developed in the European project @neurIST were used to reconstruct the fluid domains and solve the unsteady Navier-Stokes equations, using in turn Womersley and plug-flow inlet velocity profiles. The effects of these assumptions were analysed and compared in terms of relevant haemodynamic variables within the aneurismal sac. For the aneurysm at the basilar tip geometries with different extensions of the afferent vasculature were considered to study the plausibility of a fully-developed axial flow at the inlet boundaries. The study shows that assumptions made on the velocity profile while specifying inlet boundary conditions have little influence on the local haemodynamics in the aneurysm, provided that a sufficient extension of the afferent vasculature is considered and that geometry is the primary determinant of the flow field within the aneurismal sac. For real geometries the Womersley profile is at best an unnecessary over-complication, and may even be worse than the plug profile in some anatomical locations (e.g. basilar confluence).