Research Papers

Validation of the Strain Assessment of a Phantom of Abdominal Aortic Aneurysm: Comparison of Results Obtained From Magnetic Resonance Imaging and Stereovision Measurements

[+] Author and Article Information
Yufei Wang

Laboratoire D'électronique,
Informatique et Image,
Art et Métiers Paristech,
Université de Bourgogne-France-Comté,
Site d'Auxerre, Route des Plaines de l'Yonne,
Auxerre 89 000, France
e-mail: jinlibua@hotmai.com

David Joannic

IUT Dijon-Auxerre, Laboratoire D'électronique,
Informatique et Image,
Art et Métiers Paristech,
Université de Bourgogne-France-Comté,
site d'Auxerre, route des plaines de l'Yonne,
Auxerre 89 000, France
e-mail: david.joannic@iut-dijon.u-bourgogne.fr

Patrick Juillion

Laboratoire D'électronique,
Informatique et Image,
Art et Métiers Paristech,
Université de Bourgogne-France-Comté,
Site d'Auxerre, Route des Plaines de l'Yonne,
Auxerre 89 000, France
e-mail: patrick.juillion@u-bourgogne.fr

Aurélien Monnet

Siemens Healthcare France,
40 Avenue des FRUITIERS,
Saint-Denis 93527, France
e-mail: a.monnet@siemens.fr

Patrick Delassus

Galway-Mayo Institute of Technology,
Galway H91 T8NW, Ireland
e-mail: patrick.delassus@gmit.ie

Alain Lalande

Laboratoire D'électronique,
Informatique et Image,
Art et Métiers Paristech,
Faculté de Médecine,
Université de Bourgogne-Franche-Comté,
7 bd Jeanne d'Arc,
Dijon 21 079, Cedex, France
e-mail: alain.lalande@u-bourgogne.fr

Jean-François Fontaine

IUT Dijon-Auxerre, Laboratoire D'électronique,
Informatique et Image,
Art et Métiers Paristech,
Université de Bourgogne-France-Comté,
Site D'auxerre, Route des Plaines de l'Yonne,
Auxerre 89 000, France
e-mail: jffont@iut-dijon.u-bourgogne.fr

1Corresponding author.

Manuscript received January 11, 2017; final manuscript received December 9, 2017; published online January 17, 2018. Assoc. Editor: Jonathan Vande Geest.

J Biomech Eng 140(3), 031001 (Jan 17, 2018) (9 pages) Paper No: BIO-17-1016; doi: 10.1115/1.4038743 History: Received January 11, 2017; Revised December 09, 2017

Predicting aortic aneurysm ruptures is a complex problem that has been investigated by many research teams over several decades. Work on this issue is notably complex and involves both the mechanical behavior of the artery and the blood flow. Magnetic resonance imaging (MRI) can provide measurements concerning the shape of an organ and the blood that flows through it. Measuring local distortion of the artery wall is the first essential factor to evaluate in a ruptured artery. This paper aims to demonstrate the feasibility of this measure using MRI on a phantom of an abdominal aortic aneurysm (AAA) with realistic shape. The aortic geometry is obtained from a series of cine-MR images and reconstructed using Mimics software. From 4D flow and MRI measurements, the field of velocity is determined and introduced into a computational fluid dynamic (CFD) model to determine the mechanical boundaries applied on the wall artery (pressure and ultimately wall shear stress (WSS)). These factors are then converted into a solid model that enables wall deformations to be calculated. This approach was applied to a silicone phantom model of an AAA reconstructed from a patient's computed tomography-scan examination. The calculated deformations were then compared to those obtained in identical conditions by stereovision. The results of both methods were found to be close. Deformations of the studied AAA phantom with complex shape were obtained within a gap of 12% by modeling from MR data.

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Fig. 1

Global diagram of the deformation determination from MRI measurements of a silicon AAA phantom with realistic shape. (See text for detailed description.)

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Fig. 2

Evolution of velocity fields of the phantom with realistic shape determined by the 4D-flow MRI

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Fig. 3

(a) Mesh for the phantom with definition of the inlet and outlet (top) and (b) velocity and pressure time history applied to the boundary conditions over a cycle (bottom)

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Fig. 4

(a) Velocity fields determined by CFD for a phantom with realistic shape (top) and (b) computed spatial pressure distribution (t = 0.34 s) (bottom)

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Fig. 5

Comparison of changes in the average velocity (Vm) versus time (T) as determined by MRI and simulation for five sections of the phantom

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Fig. 6

Variation of the phantom thickness

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Fig. 7

Tensile sample with spray for identification of silicon behavior by stereovision

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Fig. 8

Maximal in-plane-principal GL strain cartography obtained by modeling with abaqus outside the phantom and plotted on initial geometry

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Fig. 9

Stereovision measurement: maximum principal GL strain distribution for three areas of the AAA

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Fig. 10

Definition of the areas for comparison between simulation and stereovision results of maximum main GL-strain given in Table 2



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