Flow residence time in intracranial aneurysms evaluated by in vitro 4D flow MRI. (August 2022)

• Record Type: Journal Article
• Authors: Li, Yinghui; Amili, Omid; Moen, Sean; Van de Moortele, Pierre-François; Grande, Andrew; Jagadeesan, Bharathi; Coletti, Filippo
• Is Part Of: Journal of biomechanics. Volume 141(2022)
• Publication Date: 2022-08
• Subjects: Lagrangian particle tracking -- Aneurysm hemodynamics -- Magnetic resonance imaging -- Residence time; Animal mechanics -- Periodicals; Biomechanics -- Periodicals; Biomechanics -- Periodicals; Mécanique animale -- Périodiques; Biomécanique -- Périodiques; Electronic journals; 571.4305
• DOI: 10.1016/j.jbiomech.2022.111211
• Languages: English
• ISSNs: 0021-9290

Abstract

Abstract: The process of an intracranial aneurysm development, growth, and rupture is multifaceted and complex. In addition, clinical observations have identified the potential of thrombus formation within such aneurysms. While the underlying mechanism is not fully understood, the thrombi represent a potential risk factor for ischemic stroke. Emerging studies indicate that blood residence time (RT) is a promising hemodynamic metric associated with the aneurysm rupture and formation of intra-aneurysmal thrombi. Here, we present a methodology to experimentally evaluate both trajectory-wise and local RT based on magnetic resonance imaging (MRI) velocimetry, and apply it to in vitro flow measurements in scaled-up replicas of 9 patient-specific intracranial aneurysms. Lagrangian tracks of massless tracers are integrated from the velocity fields and averaged to return the mean RT in the aneurysm sac. This is found to be closely approximated by a simple time scale based on the sac diameter and space–time average of the aneurysmal fluid velocity. The mean RT is also correlated with the inflow time scale at the parent artery. These results also provide a basis for the estimation of RT when high-resolution hemodynamic maps are not available. With the continuous increase in accuracy and resolution enabled by progress in MRI technology, the methodology described here may in the future be applicable to in vivo data.