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Research Papers

Toward the Virtual Benchmarking of Pneumatic Ventricular Assist Devices: Application of a Novel Fluid–Structure Interaction-Based Strategy to the Penn State 12 cc Device

[+] Author and Article Information
Alessandro Caimi

Department of Electronics,
Information and Bioengineering,
Politecnico di Milano,
Milano 20133, Italy
e-mail: alessandro.caimi@polimi.it

Francesco Sturla

Department of Electronics,
Information and Bioengineering,
Politecnico di Milano,
Milano 20133, Italy
e-mail: francesco.sturla@polimi.it

Bryan Good

Department of Biomedical Engineering,
The Pennsylvania State University,
State College, PA 16802
e-mail: bcg5069@psu.edu

Marco Vidotto

Department of Electronics,
Information and Bioengineering,
Politecnico di Milano,
Milano 20133, Italy
e-mail: marco.vidotto@polimi.it

Rachele De Ponti

Department of Electronics,
Information and Bioengineering,
Politecnico di Milano,
Milano 20133, Italy
e-mail: rachele.deponti@mail.polimi.it

Filippo Piatti

Department of Electronics,
Information and Bioengineering,
Politecnico di Milano,
Milano 20133, Italy
e-mail: filippo.piatti@polimi.it

Keefe B. Manning

Mem. ASME
Department of Biomedical Engineering,
The Pennsylvania State University,
University Park, PA 16802
e-mail: kbm10@psu.edu

Alberto Redaelli

Mem. ASME
Department of Electronics,
Information and Bioengineering,
Politecnico di Milano,
Milano 20133, Italy
e-mail: alberto.redaelli@polimi.it

1Corresponding author.

Manuscript received January 27, 2017; final manuscript received May 18, 2017; published online June 16, 2017. Assoc. Editor: Ching-Long Lin.

J Biomech Eng 139(8), 081008 (Jun 16, 2017) (10 pages) Paper No: BIO-17-1034; doi: 10.1115/1.4036936 History: Received January 27, 2017; Revised May 18, 2017

The pediatric use of pneumatic ventricular assist devices (VADs) as a bridge to heart transplant still suffers for short-term major complications such as bleeding and thromboembolism. Although numerical techniques are increasingly exploited to support the process of device optimization, an effective virtual benchmark is still lacking. Focusing on the 12 cc Penn State pneumatic VAD, we developed a novel fluid–structure interaction (FSI) model able to capture the device functioning, reproducing the mechanical interplay between the diaphragm, the blood chamber, and the pneumatic actuation. The FSI model included the diaphragm mechanical response from uniaxial tensile tests, realistic VAD pressure operative conditions from a dedicated mock loop system, and the behavior of VAD valves. Our FSI-based benchmark effectively captured the complexity of the diaphragm dynamics. During diastole, the initial slow diaphragm retraction in the air chamber was followed by a more rapid phase; asymmetries were noticed in the diaphragm configuration during its systolic inflation in the blood chamber. The FSI model also captured the major features of the device fluid dynamics. In particular, during diastole, a rotational wall washing pattern is promoted by the penetrating inlet jet with a low-velocity region located in the center of the device. Our numerical analysis of the 12 cc Penn State VAD points out the potential of the proposed FSI approach well resembling previous experimental evidences; if further tested and validated, it could be exploited as a virtual benchmark to deepen VAD-related complications and to support the ongoing optimization of pediatric devices.

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Figures

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Fig. 1

Geometrical model of the Penn State 12 cc pVAD: (a) acrylic model of the device for in vitro tests at the Artificial Heart Lab; (b) top view of the device pointing out the diaphragm diameter (dpVAD) and the position of the mitral (MV) and aortic (AV) ports; (c) frontal view of the computer-aided design model reporting the height of both air (hair) and blood (hblood) chambers. A detail view of the tilting disk valves (rv, disk radius) is reported on the left (MV) and on the right (AV), highlighting the axis of rotation on each valve disk (dv, distance between the center of the valve and the rotational axis).

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Fig. 2

(a) Numerical 12 cc pVAD FSI model: The pVAD case is immersed in a control volume consisting of the fluid domain (green grid), the air reservoir (light blue grid), the mitral (yellow grid), and the aortic (red grid) reservoirs. (b) Boundary conditions extracted from the in vitro benchmark and adopted in the FSI model: pressure time-dependent waveforms and the observed opening and closing timing of the tilting disk valves. (c) Experimental uniaxial tensile tests performed on the five diaphragm samples; (d) stress–strain response for each sample and the linear elastic approximation in the strain range 0–50% (see color figure online).

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Fig. 3

Contour maps of von Mises stress (σVM, left column), circumferential strain (εcirc, central column), and radial strain (εrad, right column) computed on the pVAD diaphragm from diastolic pVAD filling (t = 650 ms) up to the peak of systolic ejection (t = 1000 ms)

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Fig. 4

(a) Time course of the diaphragm profile, along two diametrical principal axes, during both diastole (550–750 ms) and systole (850–1050 ms). For each point of the profile, the Yp coordinate, i.e., normal to the diaphragm housing plane, and RN, i.e., normalized membrane radius, are computed. (b) Diastolic diaphragm opening (DO) averaged on nine equidistant points selected on the central portion of the diaphragm (see color figure online).

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Fig. 5

(a) Time-dependent waveforms of flow rate extracted at the inflow, i.e., mitral valve (top panel), and at the outflow, i.e., aortic valve (bottom panel), from the in vitro mock loop (light blue) and from the numerical model (red); (b) contour maps of the velocity field computed at the 11 mm parallel plane cross section during the diastolic filling phase of the device (t = 650, 700, 750, 800 ms) and the first instants of the systolic ejection phase (t = 850, 900 ms) (see color figure online)

Grahic Jump Location
Fig. 6

Visualization of the 3D fluid dynamics of the device during the diastolic filling phase (t = 600, 700, 800 ms) by means of (a) pathlines injected from the location of the mitral port and (b) two velocity magnitude isosurfaces (λ1 = 0.5 m/s, brown; λ2 = 1 m/s, green) (see color figure online)

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Fig. 7

Preliminary comparison between the computed FSI results and ground-truth in vitro data collected on the 12 cc Penn State prototype: (a) maximum diaphragm excursion (i.e., YP coordinate) at systole, as computed on both the diametrical diaphragm axes from the FSI model (dashed line) and high-speed video acquisitions (continuous line); (b) fluid dynamic comparison between the simulated FSI model and data from particle image velocimetry, during diastole (left panel) and systole (right panel), respectively

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