A new method for the in vivo identification of mechanical properties in arteries from cine MRI images: Theoretical framework and validation

Franquet, A., Avril, S., Le Riche, R., Badel, P., Schneider, F. C., Li, Z. Y., Boissier, C., & Favre, J. P. (2013) A new method for the in vivo identification of mechanical properties in arteries from cine MRI images: Theoretical framework and validation. IEEE Transactions on Medical Imaging, 32(8), pp. 1448-1461.

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Quantifying the stiffness properties of soft tissues is essential for the diagnosis of many cardiovascular diseases such as atherosclerosis. In these pathologies it is widely agreed that the arterial wall stiffness is an indicator of vulnerability. The present paper focuses on the carotid artery and proposes a new inversion methodology for deriving the stiffness properties of the wall from cine-MRI (magnetic resonance imaging) data. We address this problem by setting-up a cost function defined as the distance between the modeled pixel signals and the measured ones. Minimizing this cost function yields the unknown stiffness properties of both the arterial wall and the surrounding tissues. The sensitivity of the identified properties to various sources of uncertainty is studied. Validation of the method is performed on a rubber phantom. The elastic modulus identified using the developed methodology lies within a mean error of 9.6%. It is then applied to two young healthy subjects as a proof of practical feasibility, with identified values of 625 kPa and 587 kPa for one of the carotid of each subject.

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3 citations in Scopus
5 citations in Web of Science®
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ID Code: 90297
Item Type: Journal Article
Refereed: No
Keywords: Artery, elasticity, finite elements, identification, in vivo analysis, inverse method, mechanical properties, common carotid-artery, human atherosclerotic plaques, elastic-modulus, wall material, stiffness, behavior, atheroma, strain, model
DOI: 10.1109/tmi.2013.2257828
ISSN: 0278-0062
Divisions: Current > Institutes > Institute of Health and Biomedical Innovation
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 IEEE
Deposited On: 20 Nov 2015 01:00
Last Modified: 26 Jun 2017 08:01

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