Research Papers

Mathematical Modeling of Patient-Specific Ventricular Assist Device Implantation to Reduce Particulate Embolization Rate to Cerebral Vessels

[+] Author and Article Information
I. Ricardo Argueta-Morales

The Heart Center at Arnold Palmer
Hospital for Children,
Cardiothoracic Surgery,
92 West Miller St.,
Orlando, FL 32806

Reginald Tran, Andres Ceballos, William Clark, Ruben Osorio

Mechanical and Aerospace
Engineering Department,
University of Central Florida,
4000 Central Florida Blvd.,
Orlando, FL 32816

Eduardo A. Divo

Mechanical and Aerospace
Engineering Department,
University of Central Florida,
4000 Central Florida Blvd.,
Orlando, FL 32816;
Mechanical Engineering Department,
Embry-Riddle Aeronautical University,
600 South Clyde Morris Blvd.,
Daytona Beach, FL 32114

Alain J. Kassab

Mechanical and Aerospace
Engineering Department,
University of Central Florida,
4000 Central Florida Blvd.,
Orlando, FL 32816
email: Alain.Kassab@ucf.edu

William M. DeCampli

The Heart Center at Arnold Palmer
Hospital for Children,
Cardiothoracic Surgery,
92 West Miller St.,
Orlando, FL 32806;
Medical Education Department,
College of Medicine,
University of Central Florida,
6850 Lake Nona Blvd.,
Orlando, FL 32827

1Corresponding author.

Contributed by the Bioengineering Division of ASME for publication in the Journal of Biomechanical Engineering. Manuscript received April 15, 2013; final manuscript received January 13, 2014; accepted manuscript posted January 16, 2014; published online May 16, 2014. Editor: Victor H. Barocas.

J Biomech Eng 136(7), 071008 (May 16, 2014) (8 pages) Paper No: BIO-13-1188; doi: 10.1115/1.4026498 History: Received April 15, 2013; Revised January 13, 2014; Accepted January 16, 2014

Stroke is the most devastating complication after ventricular assist device (VAD) implantation, with an incidence of 14%–47% despite improvements in device design and anticoagulation. This complication continues to limit the widespread implementation of VAD therapy. Patient-specific computational fluid dynamics (CFD) analysis may elucidate ways to reduce this risk. A patient-specific three-dimensional model of the aortic arch was generated from computed tomography. A 12 mm VAD outflow-graft (VAD-OG) “anastomosed” to the aorta was rendered. CFD was applied to study blood flow patterns. Particle tracks, originating from the VAD, were computed with a Lagrangian phase model and percentage of particles entering the cerebral vessels was calculated. Twelve implantation configurations of the VAD-OG and three particle sizes (2, 4, and 5 mm) were considered. Percentage of particles entering the cerebral vessels ranged from 6% for the descending aorta VAD-OG anastomosis, to 14% for the ascending aorta at 90 deg VAD-OG anastomosis. Values were significantly different among all configurations (X2 = 3925, p < 0.0001). Shallower and more cephalad anastomoses prevented formation of zones of recirculation in the ascending aorta. In this computational model and within the range of anatomic parameters considered, the percentage of particles entering the cerebral vessels from a VAD-OG is reduced by nearly 60% by optimizing outflow-graft configuration. Ascending aorta recirculation zones, which may be thrombogenic, can also be eliminated. CFD methods coupled with patient-specific anatomy may aid in identifying the optimal location and angle for VAD-OG anastomosis to minimize stroke risk.

Copyright © 2014 by ASME
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Grahic Jump Location
Fig. 1

Baseline three-dimensional model of aortic arch with inlet and outlet diameters. Ø = diameter of vessel.

Grahic Jump Location
Fig. 6

Descending aorta VAD-OG anastomosis streamlines depicting a large recirculation zone (arrow) where flow from the VAD and the flow from the aortic root conflux

Grahic Jump Location
Fig. 5

Particle tracks for configurations (a) 90 deg-VAD-OG-innominate artery bypass depicting 5 mm particles embolization to coronaries and (b) 90 deg-VAD-OG-left carotid artery bypass depicting 2 mm particles embolization to right coronary. Arrows indicate recirculation zones.

Grahic Jump Location
Fig. 4

Time lapse of 2 mm particles tracking for configurations (a) 90 deg-VAD-OG to the right-lateral mid-ascending aorta; (b) 60 deg-VAD-OG shifted-up; and (c) DA VAD-OG implantation. DA = descending aorta.

Grahic Jump Location
Fig. 8

Fluid pathlines and cross-sectional vector plots of (a) 90 deg-VAD-OG to the right-lateral mid-ascending aorta; (b) 60 deg-VAD-OG shifted-up; and (c) DA VAD-OG implantation. DA = descending aorta.

Grahic Jump Location
Fig. 3

Configuration 60 deg-VAD-OG implantation to the right-lateral ascending aorta. (a) Anastomosis at 3 mm from the root of the innominate artery (graft shifted-up). (b) Anastomosis at 33 mm from the root of the innominate artery (graft shifted-down). (c) Descending aorta VAD-OG implantation.

Grahic Jump Location
Fig. 2

VAD-OG implantation configurations: (a) Variation of angle of anastomosis (90 deg, 60 deg, and 30 deg) to the right-lateral mid-ascending aorta. (b) Configurations with IA bypass (8 mm). (c) Configurations with LCA bypass (6 mm). IA = innominate artery, LCA = left carotid artery.

Grahic Jump Location
Fig. 7

Fluid pathlines of 60 deg shifted-up configuration depicting the jet from the VAD flow carried through the arch toward the left subclavian artery and descending aorta




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