Research Papers

Impact of Patient-Specific Inflow Velocity Profile on Hemodynamics of the Thoracic Aorta

[+] Author and Article Information
Pouya Youssefi

Department of Cardiothoracic Surgery,
St. George's Hospital,
London SW17 0QT, UK;
Department of Biomedical Engineering,
King's College London,
London SE1 7EH, UK
e-mail: pyyoussefi@aol.com

Alberto Gomez

Department of Biomedical Engineering,
King's College London,
London SE1 7EH, UK
e-mail: alberto.gomez@kcl.ac.uk

Christopher Arthurs

Department of Biomedical Engineering,
King's College London,
London SE1 7EH, UK
e-mail: christopher.arthurs@kcl.ac.uk

Rajan Sharma

Department of Cardiology,
St. George's Hospital,
London SW17 0QT, UK
e-mail: rajan.sharma@stgeorges.nhs.uk

Marjan Jahangiri

Department of Cardiothoracic Surgery,
St. George's Hospital,
London SW17 0QT, UK
e-mail: marjan.jahangiri@stgeorges.nhs.uk

C. Alberto Figueroa

Department of Biomedical Engineering,
King's College London,
London SE1 7EH, UK;
Departments of Surgery
and Biomedical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: alberto.figueroa@kcl.ac.uk

Manuscript received July 28, 2016; final manuscript received June 9, 2017; published online October 19, 2017. Assoc. Editor: Ender A. Finol.

J Biomech Eng 140(1), 011002 (Oct 19, 2017) (14 pages) Paper No: BIO-16-1322; doi: 10.1115/1.4037857 History: Received July 28, 2016; Revised June 09, 2017

Computational fluid dynamics (CFD) provides a noninvasive method to functionally assess aortic hemodynamics. The thoracic aorta has an anatomically complex inlet comprising of the aortic valve and root, which is highly prone to different morphologies and pathologies. We investigated the effect of using patient-specific (PS) inflow velocity profiles compared to idealized profiles based on the patient's flow waveform. A healthy 31 yo with a normally functioning tricuspid aortic valve (subject A), and a 52 yo with a bicuspid aortic valve (BAV), aortic valvular stenosis, and dilated ascending aorta (subject B) were studied. Subjects underwent MR angiography to image and reconstruct three-dimensional (3D) geometric models of the thoracic aorta. Flow-magnetic resonance imaging (MRI) was acquired above the aortic valve and used to extract the patient-specific velocity profiles. Subject B's eccentric asymmetrical inflow profile led to highly complex velocity patterns, which were not replicated by the idealized velocity profiles. Despite having identical flow rates, the idealized inflow profiles displayed significantly different peak and radial velocities. Subject A's results showed some similarity between PS and parabolic inflow profiles; however, other parameters such as Flowasymmetry were significantly different. Idealized inflow velocity profiles significantly alter velocity patterns and produce inaccurate hemodynamic assessments in the thoracic aorta. The complex structure of the aortic valve and its predisposition to pathological change means the inflow into the thoracic aorta can be highly variable. CFD analysis of the thoracic aorta needs to utilize fully PS inflow boundary conditions in order to produce truly meaningful results.

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Grahic Jump Location
Fig. 1

Geometric mapping between the flow-MRI derived contour (blue: variable in time) and the MRA-derived geometric model contour (red: fixed in time) at the inlet. (a) Rotational alignment between the flow-MRI derived contour and the geometric model inlet is resolved by pointwise correspondence (indicated by numbers) between the two contours. (b) Corresponding points establish a reference deformation between the two contours as indicated by the arrows. (c) The contourwise deformation illustrated in (b) is extended to the entire area of the inlet by using a dense smooth B-spline deformation field (represented by black arrows).

Grahic Jump Location
Fig. 2

Inflow boundary conditions. 2D and 3D visualizations of the patient-specific (VPS), parabolic (Vpara), and plug (Vplug) velocity magnitude (first and second rows, respectively) at peak systole. The 3D visualization of the velocity magnitude was obtained by warping the measured through-plane phase contrast data by a factor of 0.02.

Grahic Jump Location
Fig. 3

(a) 2D representation of the velocity magnitude during peak systole, (b) velocity magnitude represented by individual dots for each nodal point of the aortic inflow computational mesh, and (c) red dots represent the top 15% of velocities at peak systole (Vmax15%), x⇀a represents the centroid of the inflow face, x⇀b represents the centroid of Vmax15%, and Req represents the equivalent radius of the inflow face

Grahic Jump Location
Fig. 4

2D and 3D representations of velocity magnitude, and radial (e.g., in-plane) velocity components at three planes of the thoracic aorta for subject A. Plane 1 corresponds to midascending aorta, plane 2 to transverse aortic arch, and plane 3 to mid-descending aorta.

Grahic Jump Location
Fig. 5

2D and 3D representations of velocity magnitude, and radial (e.g., in-plane) velocity components at three planes of the thoracic aorta for subject B. Plane 1 corresponds to midascending aorta, plane 2 to transverse aortic arch, and plane 3 to mid-descending aorta.

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Fig. 6

Maximal through-plane velocity (Vmax), radial (in-plane) velocity and flow rate along the cardiac cycle at three planes for subjects A and B

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Fig. 7

Pathlines and mean absolute HFI calculated using the subject-specific inflow velocity profile for subject A (top) and subject B (bottom) at t = 100, 200, 400, and 900 ms. Even though the numerical values of HFI are not substantially different between the healthy (subject A) and diseased (subject B) cases (see Table 2), the difference in particle trajectories is remarkable. In subject A, the particles have moved in a unidirectional manner down the aorta and by the end of the first cycle, they have almost left the domain. In contrast, particles injected in subject B are still in the ascending aorta after 900 ms, having followed a very tortuous path. Note: only a small number of particles are tracked for the sake of clarity in the visualization. The HFI indices were calculated using a much larger number of pathlines (approximately 700,000).

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Fig. 8

Flowasymmetry along three planes of the thoracic aorta for subjects A and B

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Fig. 9

Flowdispersion along three planes of the thoracic aorta for subjects A and B



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