Research Papers

Computational Fluid Dynamic Study for aTAA Hemodynamics: An Integrated Image-Based and Radial Basis Functions Mesh Morphing Approach

[+] Author and Article Information
Katia Capellini

Fondazione CNR-Regione
Toscana “G. Monasterio,”
Ospedale del Cuore,
Via Aurelia Sud,
Massa 54100, Italy
e-mail: katia.capellini@ftgm.it

Emanuele Vignali

Fondazione CNR-Regione
Toscana “G. Monasterio,”
Ospedale del Cuore,
Via Aurelia Sud,
Massa 54100, Italy
e-mail: emanuele.vignali@ftgm.it

Emiliano Costa

RINA Consulting S.p.A.,
Viale Cesare Pavese, 305,
Roma 00144, Italy
e-mail: emiliano.costa@rina.org

Emanuele Gasparotti

Fondazione CNR-Regione
Toscana “G. Monasterio,”
Ospedale del Cuore,
Via Aurelia Sud,
Massa 54100, Italy
e-mail: emanuele.gasparotti@ftgm.it

Marco Evangelos Biancolini

Department of Enterprise Engineering,
University of Rome Tor Vergata,
Via del Politecnico 1,
Roma 00133, Italy
e-mail: biancolini@ing.uniroma2.it

Luigi Landini

Department of Information Engineering,
University of Pisa,
Via Girolamo Caruso, 16,
Pisa 56122, Italy
e-mail: luigi.landini@unipi.it

Vincenzo Positano

Fondazione CNR-Regione
Toscana “G. Monasterio,”
Ospedale del Cuore,
Via Aurelia Sud,
Massa 54100, Italy
e-mail: positano@ftgm.it

Simona Celi

Fondazione CNR-Regione
Toscana “G. Monasterio,”
Ospedale del Cuore,
Via Aurelia Sud,
Massa 54100, Italy
e-mail: s.celi@ftgm.it

1Corresponding author.

Manuscript received February 9, 2018; final manuscript received July 9, 2018; published online August 20, 2018. Assoc. Editor: Giuseppe Vairo.

J Biomech Eng 140(11), 111007 (Aug 20, 2018) (10 pages) Paper No: BIO-18-1079; doi: 10.1115/1.4040940 History: Received February 09, 2018; Revised July 09, 2018

We present a novel framework for the fluid dynamics analysis of healthy subjects and patients affected by ascending thoracic aorta aneurysm (aTAA). Our aim is to obtain indications about the effect of a bulge on the hemodynamic environment at different enlargements. Three-dimensional (3D) surface models defined from healthy subjects and patients with aTAA, selected for surgical repair, were generated. A representative shape model for both healthy and pathological groups has been identified. A morphing technique based on radial basis functions (RBF) was applied to mold the shape relative to healthy patient into the representative shape of aTAA dataset to enable the parametric simulation of the aTAA formation. Computational fluid dynamics (CFD) simulations were performed by means of a finite volume solver using the mean boundary conditions obtained from three-dimensional (PC-MRI) acquisition. Blood flow helicity and flow descriptors were assessed for all the investigated models. The feasibility of the proposed integrated approach pertaining the coupling between an RBF morphing technique and CFD simulation for aTAA was demonstrated. Significant hemodynamic changes appear at the 60% of the bulge progression. An impingement of the flow toward the bulge was observed by analyzing the normalized flow eccentricity (NFE) index.

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Fig. 1

Definition of the RBF mesh morphing process applied to the ascending aorta. Source and target points correspond to the healthy and pathological aorta respectively. (Source in red and target in blue in the colored online version).

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Fig. 2

Results of the RBF mesh morphing phase: SM20 (a), SM40 (b), SM60 (c), SM80 (d), and SM100 (e)

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Fig. 3

Results of the effect of the morphing both at geometry and mesh quality level. Histogram of the maximum distance between the SSA and SM100 geometries (a). Map of the errgeom between the SSA and the SM100 geometries (b). Number of cells with a skewness value greater than 0.85 at different percentage of the morphed bulge (c) and localization of the cells with a skewness value greater than 0.85 in SSC and SM100 (d). The value equal to 0.85 has been chosen as an intermediate value between the imposed target skewness of 0.75 and the maximum suggested (0.95) by the CFD code.

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Fig. 4

Scheme of the 0D–3D coupling assumption with the three parameters defined for the Windkessel models and results of the flow and pressure curves for the four outlets and the inlet

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Fig. 5

Streamlines at systole for four configurations: the SSC (a), the SM60 (b), the SM80 (c), and SM100 (d)

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Fig. 6

Vector plots of the in-plane velocity (a)–(d) and contour plots of the through-plane velocity (e)–(h) for SSC (a) and (e), SM60 (b) and (f), SM80 (c) and (g) and SM100 (d) and (h). Plots of the NFE index for SSC (i), SM60 (j), SM80 (k), and SM100 (l). All plots correspond to T2 time.

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Fig. 7

TAWSS (a)–(d) and OSI (e)–(h) resulting from the CFD analysis for the SSC, SM60, SM80, SM100 geometries

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Fig. 8

Isosurfaces of LNH at three different phases of the cardiac cycle (T1, T2, and T3) for each one of the four configurations: SSC (a)–(c), SM60 (d)–(f), SM80 (g)–(i), and SM100 (j)–(l). High threshold values of LNH (= ±0.8) are used for the visualization of markedly aligned/opposed velocity and vorticity vector fields. Positive and negative LNH values indicate counter-rotating flow structures.



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