Unraveling the relationship between arterial flow and intra-aneurysmal hemodynamics
Introduction
Hemodynamics influences the arterial wall behavior and regulates the blood coagulation process (Wootton and Ku, 1999, Reneman et al., 2006). In cerebral aneurysms, hemodynamics has been related to their initiation, development and rupture (Gao et al., 2008, Xiang et al., 2011, Meng et al., 2013) and is known to affect endovascular therapies, such as flow divertion (Mut et al., 2014a, Pereira et al., 2013a).
To understand intra-aneurysmal hemodynamics, vascular morphology and arterial flow conditions have to be considered. Morphology defines unique characteristics of the studied system (arterial calibers, aneurysm size and shape, etc.), those measurable from medical images. Several morphological features have been described like size, shape, aspect ratio, and correlated with aneurysmal rupture (Ujiie et al., 2001, Xiang et al., 2011). In contrast, it is not clear how arterial flow conditions alter intra-aneurysmal hemodynamics.
Through computational fluid dynamics (CFD) simulations, it has been shown that intra-aneurysmal hemodynamics depends on the arterial flow rates. Inside aneurysms, flow patterns and quantitative variables, such as velocity and wall shear stress (WSS), vary if flow conditions change (Jiang and Strother, 2009, Marzo et al., 2011, McGah et al., 2014). Moreover, CFD-based studies have highlighted the importance of imposing patient-specific flow rates and have quantified the errors when derived boundary conditions are used (Marzo et al., 2011, McGah et al., 2014). Nevertheless, patient-specific measurements are limited to the temporal frame of the examination. In other words, patient-specific flow conditions are time-dependent measurements, because arterial flow rates change during patient׳s lifetime. An example of such flow rate variation is when resting or exercising (Poulin et al., 1999).
In the lack of flow measurements, a wide range of possible boundary conditions is available from the literature. Some of those conditions are based on the geometry, like an area–inflow relation (Cebral et al., 2008) or based on physiological conditions, like a WSS of 1.5 Pa at the inlet of the model (Reneman et al., 2006). Other flow conditions can be obtained from mean values over young and elder populations (Hoi et al., 2010, Ford et al., 2005). The variety of boundary conditions makes unfeasible the comparison among experimental studies, particularly those conducted with CFD.
Indeed, a better understanding of the relationship “arterial flow-aneurysm hemodynamics” is required. In clinical practice for example, the uncertainties in this relationship hinder the comparison among medical image sequences, since flow conditions may differ among image acquisition times (Chien and Viñuela, 2013, Pereira et al., 2013a). More precisely, an evaluation of endovascular device performance by functional imaging could be done during clinical interventions (Bonnefous et al., 2012), or to assess longitudinal studies with several follow-ups if the relationship arterial flow-aneurysm hemodynamics is known.
The purpose of this work is to unravel the relationship between arterial flow and intra-aneurysmal hemodynamics when the full physiological range of arterial flow rates is covered. Quantitative characterizations of the averaged intra-aneurysmal velocity, WSS and pressure are pursuit. A clear relationship “artery-aneurysm flow” allows the comparison among experimental studies and clinical observations under different flow conditions.
Section snippets
Materials
Fifteen aneurysms from ten patients were studied. All aneurysms were located in one of the internal carotid arteries (ICA), between the carotid siphon and the ICA bifurcation. Two aneurysms were terminal and 13 lateral. Depending or their size, four aneurysms were classified as small (), five as medium (size between 3 mm and 5 mm) and six as large aneurysms (). To visualize these aneurysms, volumetric images were acquired by an X-ray system (Allura Xper FD20 system of Philips
Results
Fig. 2A depicts temporal-averaged WSS distribution for 3 cases (3 aneurysms) for some . Temporal-averaged WSS magnitude increases with in all the vascular models, including the aneurysm walls. OSI distributions in 7 aneurysm models (3 cases) are shown in Fig. 2B. For these aneurysms, OSI seems to be stable from , excepting for terminal aneurysms (case 2). Maximum OSI values in case 10 were located around the aneurysm bleb.
Spatiotemporal-averaged variables (, and
Discussion
The influence of the arterial flow rates on intra-aneurysmal hemodynamics was analyzed. , and increase with higher flow rates (Fig. 2). Nevertheless, this study revealed that these variables can be characterized as functions of the arterial flow rate for each aneurysm. A good fitting (minimum ) was found for all characteristic curves. These curves are generic and do not depend on the shape of the waveform.
linearly increases with arterial flow rate and can be
Conclusions
, and can be characterized as functions of the mean arterial flow rate, which can be obtained with few measurements. Characterizing these variables within the full physiological range of flow rates provides a complete view of intra-aneurysmal hemodynamics compared to a single-flow condition assessment. These curves go beyond any patient-specific temporal-dependent flow conditions and provide a complete view for comparison of experimental and clinical studies under any
Conflict of interest statement
None declared.
Acknowledgments
Authors would like to thank the Department of Medical Imaging and Information Sciences, Interventional Neuroradiology Unit, University Hospitals of Geneva, Switzerland, for providing the medical images from which vascular models were extracted. Authors would like to thank Dr. Laurence Rouet and Dr. Cécile Dufour from Medisys – Philips Research Paris, France, for the revision of this paper.
References (37)
- et al.
A study of wall shear stress in 12 aneurysms with respect to different viscosity models and flow conditions
J. Biomech.
(2013) - et al.
Approximating hemodynamics of cerebral aneurysms with steady flow simulations
J. Biomech.
(2014) - et al.
Peak systolic or maximum intra-aneurysmal hemodynamic condition? Implications on normalized flow variables
J. Biomech.
(2014) - et al.
Newtonian and non-Newtonian blood flow in coiled cerebral aneurysms
J. Biomech.
(2013) - et al.
Evaluation of the influence of inlet boundary conditions on computational fluid dynamics for intracranial aneurysmsa virtual experiment
J. Biomech.
(2013) - Antiga, L., Steinman, D.A., 2009. Vascular Modeling Toolkit....
- et al.
Quantification of arterial flow using digital subtraction angiography
Med. Phys.
(2012) - et al.
Flow-area relationship in internal carotid and vertebral arteries
Physiol. Meas.
(2008) - et al.
Quantitative characterization of the hemodynamic environment in ruptured and unruptured brain aneurysms
Am. J. Neuroradiol. AJNR
(2011) - et al.
IS FlowMap a novel tool to examine blood flow changes induced by flow diverter stent treatmentinitial experiences with pipeline cases
J. Neurointerv. Surg.
(2013)