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Optimal Constitutive Parameters and Subject Specific Variability: An Application to the Aortic Sinuses

[+] Author Affiliations
Vittoria Flamini

Polytechnic Institute of New York University, Brooklyn, NY

Boyce E. Griffith

New York University School of Medicine, New York, NY

Paper No. SBC2013-14633, pp. V01AT04A020; 2 pages
doi:10.1115/SBC2013-14633
From:
  • ASME 2013 Summer Bioengineering Conference
  • Volume 1A: Abdominal Aortic Aneurysms; Active and Reactive Soft Matter; Atherosclerosis; BioFluid Mechanics; Education; Biotransport Phenomena; Bone, Joint and Spine Mechanics; Brain Injury; Cardiac Mechanics; Cardiovascular Devices, Fluids and Imaging; Cartilage and Disc Mechanics; Cell and Tissue Engineering; Cerebral Aneurysms; Computational Biofluid Dynamics; Device Design, Human Dynamics, and Rehabilitation; Drug Delivery and Disease Treatment; Engineered Cellular Environments
  • Sunriver, Oregon, USA, June 26–29, 2013
  • Conference Sponsors: Bioengineering Division
  • ISBN: 978-0-7918-5560-7
  • Copyright © 2013 by ASME

abstract

Advanced analyses of soft biological tissues have shown substantial subject-specific variability in mechanical properties [1]. Such variability is also easily observed at a geometrical or morphological level, and has been reported also in mechanical tests on biological tissue samples [1, 2]. While there is wide interest in reproducing accurate geometries for subject-specific modeling, constitutive parameters for mechanical models often use averaged data from mechanical tests [3]. Outliers are typically neglected, and only the ‘mean’ tissue behavior is considered. However, due to an increased interest in using multi-scale and finite element (FE) models for medical device testing and surgical planning [4], understanding of the variability of the outlier tests becomes increasingly important. In particular, by using detailed mechanistic constitutive models, it might be possible to classify the different mechanical behaviors observed on the basis of the changes in the constitutive parameters. This process could lead to the definition of a library of different ‘healthy’ or ‘diseased’ constitutive parameters to be used in computational analyses.

Copyright © 2013 by ASME

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