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In Situ Measurement and Modeling of Biomechanical Response of Human Cadaveric Soft Tissues for Physics-Based Surgical Simulation

Identifieur interne : 001022 ( Pmc/Corpus ); précédent : 001021; suivant : 001023

In Situ Measurement and Modeling of Biomechanical Response of Human Cadaveric Soft Tissues for Physics-Based Surgical Simulation

Auteurs : Yi E Lim ; Dhanannjay Deo ; Tejinder P. Singh ; Daniel B. Jones ; Suvranu De

Source :

RBID : PMC:2693244

Abstract

Development of a laparoscopic surgery simulator that delivers high fidelity visual and haptic (force) feedback, based on the physical models of soft tissues, requires the use of empirical data on the mechanical behavior of intra-abdominal organs under the action of external forces. As experiments on live human patients present significant risks, the use of cadavers presents an alternative. We present techniques of measuring and modeling the mechanical response of human cadaveric tissue for the purpose of developing a realistic model. The major contribution of this paper is the development of physics-based models of soft tissues that range from linear elastic models to nonlinear viscoelastic models which are efficient for application within the framework of a real time surgery simulator.

To investigate the in situ mechanical, static and dynamic properties of intra-abdominal organs, we have developed a high precision instrument by retrofitting a robotic device from Sensable Technologies (position resolution of 0.03 mm) with a six-axis Nano 17 force-torque sensor from ATI Industrial Automation (force resolution of 1/1280 N along each axis), and used it to apply precise displacement stimuli and record the force response of liver and stomach of 10 fresh human cadavers.

The mean elastic modulus of liver and stomach is estimated as 5.9359 kPa and 1.9119 kPa, respectively over the range of indentation depths tested. We have also obtained the parameters of a quasi linear viscoelastic (QLV) model to represent the nonlinear viscoelastic behavior of the cadaver stomach and liver over a range of indentation depths and speeds. The models are found to have an excellent goodness of fit (with R2>0.99).

The data and models presented in this paper together with additional ones based on the principles presented in this paper would result in realistic physics-based surgical simulators.


Url:
DOI: 10.1007/s00464-008-0154-z
PubMed: 18813984
PubMed Central: 2693244

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