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Research Papers

Biomechanical Properties of Abdominal Organs In Vivo and Postmortem Under Compression Loads

[+] Author and Article Information
Jacob Rosen1

Department of Electrical Engineering, University of Washington, Box 352500, Seattle, WA 98195-2500rosen@u.washington.edu

Jeffrey D. Brown2

Department of Bioengineering, University of Washington, Box 352500, Seattle, WA 98195-2500jdbrown@alumni.washington.edu

Smita De

Department of Bioengineering, University of Washington, Box 352500, Seattle, WA 98195-2500sd6@alumni.washington.edu

Mika Sinanan

Department of Surgery, University of Washington, Box 356410, Seattle, WA 98195-2500mssurg@u.washington.edu

Blake Hannaford

Department of Electrical Engineering, University of Washington, Box 352500, Seattle, WA 98195-2500blake@u.washington.edu

1

Corresponding author.

2

Present address: Intuitive Surgical, 1266 Kifer Road, Sunnyvale, CA 94086, USA.

J Biomech Eng 130(2), 021020 (Apr 08, 2008) (17 pages) doi:10.1115/1.2898712 History: Received July 15, 2005; Revised September 28, 2007; Published April 08, 2008

Accurate knowledge of biomechanical characteristics of tissues is essential for developing realistic computer-based surgical simulators incorporating haptic feedback, as well as for the design of surgical robots and tools. As simulation technologies continue to be capable of modeling more complex behavior, an in vivo tissue property database is needed. Most past and current biomechanical research is focused on soft and hard anatomical structures that are subject to physiological loading, testing the organs in situ. Internal organs are different in that respect since they are not subject to extensive loads as part of their regular physiological function. However, during surgery, a different set of loading conditions are imposed on these organs as a result of the interaction with the surgical tools. Following previous research studying the kinematics and dynamics of tool/tissue interaction in real surgical procedures, the focus of the current study was to obtain the structural biomechanical properties (engineering stress-strain and stress relaxation) of seven abdominal organs, including bladder, gallbladder, large and small intestines, liver, spleen, and stomach, using a porcine animal model. The organs were tested in vivo, in situ, and ex corpus (the latter two conditions being postmortem) under cyclical and step strain compressions using a motorized endoscopic grasper and a universal-testing machine. The tissues were tested with the same loading conditions commonly applied by surgeons during minimally invasive surgical procedures. Phenomenological models were developed for the various organs, testing conditions, and experimental devices. A property database—unique to the literature—has been created that contains the average elastic and relaxation model parameters measured for these tissues in vivo and postmortem. The results quantitatively indicate the significant differences between tissue properties measured in vivo and postmortem. A quantitative understanding of how the unconditioned tissue properties and model parameters are influenced by time postmortem and loading condition has been obtained. The results provide the material property foundations for developing science-based haptic surgical simulators, as well as surgical tools for manual and robotic systems.

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Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

The MEG: (a) rendered CAD drawing of MEG (protective top cover not shown), (b) close-up photograph of the MEG’s drive mechanism, and (c) close-up photograph of the MEG’s Babcock grasper end effector

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Figure 2

MTS experimental testing machine setup: (a) schematic overview of the system and (b) the setup with a liver ex corpus

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Figure 3

Example stress-strain curves for all organs under study, as measured with the MEG at 5.4mm∕s loading velocity (first and fifth cycles shown): (a) in vivo and (b) ex corpus. Organs’ legends: BL=bladder, GB=gallbladder, LI=large intestine, LV=liver, SI=small intestine, SP=spleen, and ST=stomach. The loading cycle number (1 or 5) is defined in the brackets.

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Figure 4

Stress-strain curves for all organs with average curve-fit parameters across all conditions: (a) in vivo data measured by the MEG, (b) ex corpus data measured by the MEG and (c) ex corpus data measured by the MTS. Organ legend: BL=bladder, GB=gallbladder, LI=large intestine, LV=liver, SI=small intestine, SP=spleen, and ST=stomach. See text for the definitions of the functions EXP, EXP2, and INV.

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Figure 5

Measured data and phenomenological models of liver tissue under compression loading. The same in vivo data measured by the MEG were fitted with various models. The measures of fit for these models are (a) EXP2, R2=0.9989, RMSE=1.5048×103; (b) EXP, R2=0.9984, RMSE=1.5166×103; (c) INV, R2=0.9931, RMSE=3.0291×103.

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Figure 8

Ex corpus stress-strain characteristics of the liver under compression loading to failure: (a) MEG, (b) MTS

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Figure 9

The stiffness indicator scalar βα+γ of the EXP2 phenomenological model plotted for various organs for measured elastic data. The right-hand side of the plot depicts the results from posthoc Tukey–Kramer HSD analysis. The radius of the circle represents the region of confidence (95%).

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Figure 10

The stiffness indicator scalar βα+γ of the EXP2 phenomenological model plotted as a function of loading cycle for measured elastic data. The right-hand side of the plot depicts the results from posthoc Tukey–Kramer HSD analysis. The radius of the circle represents the region of confidence (95%).

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Figure 11

The liver response to compression loads of 40% strain. (a) A cross section of a liver generated as an assembly of multiple tissue slices using standard pathological techniques following an application of compression strain by a Babcock grasper attached to the MEG. Vascular tissue damage is indicated by dark red areas across the tissue slices. The horizontal arrow indicates the approximate span of the grasper jaws. (b) Von Mises stress distribution and the displaced cross section of liver as predicted by a linear FEM. The geometrical dimensions are expressed in meters and stresses are expressed in Pascals.

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Figure 7

Average normalized stress-relaxation curves for internal organs, based on mean values of REXP1, REXP2, and RLOG models: (a) in vivo and (b) ex corpus. Organ legend: BL=bladder, GB=gallbladder, LI= large intestine, LV=liver, SI=small intestine, SP=spleen, and ST=stomach. See text for the definitions of the functions REXP1, REXP2, and RLOG.

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Figure 6

Normalized stress-relaxation curves as a function of time for one liver tested with the MEG: (a) three different testing conditions (IV=in vivo, IS=in situ, and EC=ex corpus) and strain levels (indicated in the legends as a two-digit numeral (% strain); (b) measured data and phenomenological models of two strain levels. Their measures of fit: 46% strain (REXP1 (R2=0.8948, RMSE=0.0042), REXP2 (R2=0.9261, RMSE=0.0030), RLOG (R2=0.9084, RMSE=0.0034)), and strain 50% (REXP1 (R2=0.9387, RMSE=0.0026), REXP2 (R2=0.9526, RMSE=0.0021), RLOG (R2=.9140, RMSE=0.0028))

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