title: Predicting flow in aortic dissection: comparison of computational model with PC-MRI velocity measurements.
abstract: Aortic dissection is a life-threatening process in which the weakened wall develops a tear, causing separation of wall layers. The dissected layers separate the original true aortic lumen and a newly created false lumen. If untreated, the condition can be fatal. Flow rate in the false lumen is a key feature for false lumen patency, which has been regarded as one of the most important predictors of adverse early and later outcomes. Detailed flow analysis in the dissected aorta may assist vascular surgeons in making treatment decisions, but computational models to simulate flow in aortic dissections often involve several assumptions. The purpose of this study is to assess the computational models adopted in previous studies by comparison with in vivo velocity data obtained by means of phase-contrast magnetic resonance imaging (PC-MRI). Aortic dissection geometry was reconstructed from computed tomography (CT) images, while PC-MRI velocity data were used to define inflow conditions and to provide distal velocity components for comparison with the simulation results. The computational fluid dynamics (CFD) simulation incorporated a laminar-turbulent transition model, which is necessary for adequate flow simulation in aortic conditions. Velocity contours from PC-MRI and CFD in the two lumens at the distal plane were compared at four representative time points in the pulse cycle. The computational model successfully captured the complex regions of flow reversal and recirculation qualitatively, although quantitative differences exist. With a rigid wall assumption and exclusion of arch branches, the CFD model over-predicted the false lumen flow rate by 25% at peak systole. Nevertheless, an overall good agreement was achieved, confirming the physiological relevance and validity of the computational model for type B aortic dissection with a relatively stiff dissection flap.
authors: Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
authors: Z
authors: Z
authors: Cheng
authors: Department of Radiology, St Mary's Hospital, Imperial College Healthcare NHS Trust, London W2 1NY, UK.
authors: C
authors: C
authors: Juli
authors: Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
authors: N B
authors: NB
authors: Wood
authors: Imperial Vascular Unit, St Mary's Hospital, Imperial College Healthcare NHS Trust, London W2 1NY, UK.
authors: R G J
authors: RG
authors: Gibbs
authors: Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK. Electronic address: yun.xu@imperial.ac.uk.
authors: X Y
authors: XY
authors: Xu
mesh_terms: D000784:Aortic Dissection / Q000473:pathology / Q000503:physiopathology*; D001014:Aortic Aneurysm / Q000473:pathology / Q000503:physiopathology*; D001783:Blood Flow Velocity; D003198:Computer Simulation; D003971:Diastole / Q000502:physiology; D006801:Humans; D057446:Hydrodynamics; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D013599:Systole / Q000502:physiology; D014057:Tomography, X-Ray Computed
keywords: Aortic dissection; Computational fluid dynamics; Magnetic resonance velocity imaging