Experimental Mechanics

, Volume 59, Issue 2, pp 251–261 | Cite as

In-Vivo Soft Tissues Mechanical Characterization: Volume-Based Aspiration Method Validated on Silicones

  • S. A. Elahi
  • N. ConnessonEmail author
  • G. Chagnon
  • Y. Payan


Simulating the deformations of soft tissues has gained importance in recent years due to the development of 3D patient-specific biomechanical models in the context of Computer Assisted Medical Interventions. To design such models, the mechanical behavior of each soft tissue has to be characterized in-vivo. In this paper, a volume-based aspiration method for in-vivo mechanical characterization of soft tissues was validated on synthetic materials. For this purpose, two silicones with slightly different stiffnesses were made. Samples were characterized using (1) aspiration, and, as references, two classical tests such as (2) uniaxial and (3) equibiaxial extension tests. Performing a Finite Element (FE) inverse identification on the experimental results provided Young’s moduli similar to classical tests with about 7% maximum overestimation for the two silicones. This highlighted a significant improvement of the measurement method accuracy compared to the literature (about 30% relative overestimation). Eventually, the aspiration method ability to discriminate the two silicones was also tested and proven to be similar to classical characterization tests. Based on the presented results, relative mechanical behavior mapping of soft tissues (organ or skin) is possible without requiring an inverse characterization procedure.


Suction/aspiration method Soft tissues characterizations In-vivo measurement Silicone Experimental mechanics 



This work has been started thanks to the CNRS (INS2I) PEPS ”Young researcher” in 2015.

Supplementary material

11340_2018_440_MOESM1_ESM.pdf (6.8 mb)
(PDF 6.79 MB)


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Copyright information

© Society for Experimental Mechanics 2019

Authors and Affiliations

  • S. A. Elahi
    • 1
  • N. Connesson
    • 1
    Email author
  • G. Chagnon
    • 1
  • Y. Payan
    • 1
  1. 1.Univ. Grenoble Alpes, CNRSGrenoble INP, TIMC-IMAGGrenobleFrance

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