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Image-Based Mechanical Characterization of Soft Tissue using Three Dimensional Ultrasound

P. Jordan1,3, S. Socrate2, T. Zickler1, R.D. Howe1,3
1School of Engineering and Applied Sciences, Harvard University
2Department of Mechanical Engineering, Massachusetts Institute of Technology
3Harvard-MIT Division of Health Sciences and Technology

Support provided by United States Army Medical Research and Material Command and the National Institutes of Health
Graduate Student Support provided by the Harvard-MIT Division of Health Sciences and Technology

Surgical simulation and virtual surgical environments aim at improving the quality of medical personnel training, reduction in training costs, and elimination of animal subject needs. Accurate mechanical models of tissue and whole organ behavior are crucial for successful implementation of these technologies. Historically, the focus of biomechanics research has been on hard tissues (bone, teeth, etc.) and load-bearing soft tissues, such as muscle and cartilage, while the mechanics of non-load-bearing soft tissues received much less attention. Our ultimate goal, in collaboration with the Center for Integration of Medicine and Innovative Technology (CIMIT) Simulation Group, is the development of whole organ mechanical models for real-time implementation in surgical simulators. Our initial focus is on modeling the slow deformation of frequently manipulated and highly homogeneous organs, including the liver, spleen, and kidney.

Formulation of a robust mechanical model along with tissue-specific and pathology-specific model parameters are key to accurate modeling of soft tissue mechanical response. The specific goal of this project is the development of in-vivo imaging technique for mechanical characterization (parameter identification) of abdominal organs and soft tissues.

Soft Tissue Modeling and Characterization
The process of mechanical organ modeling requires an accurate description of three key components: organ geometry, constitutive law and its parameters, and boundary conditions. With a complete description of these components, the mechanical response of an organ or tissue can be estimated with numerical techniques, such as the finite-element method. The task of tissue characterization involves identification of unique model parameters that provide agreement between experimental observation and modeling. The solution is obtained through an iterative finite-element modeling (FEM) process, which estimates model parameters, such that the mean-square error between model and experiment is minimized.

Image-Based Mechanical Characterization
Conventional material testing methods, such as indentation experiments, only provide a limited local insight into material response. We aim to overcome the limitations of traditional indentation testing by supplementing it with three-dimensional ultrasound (3DUS) imaging of the volumetric tissue response.

Estimates of complete deformation fields obtained through imaging are incorporated into an iterative finite-element modeling (FEM) scheme [1,2] to identify tissue-specific parameters of a physically-based nonlinear poro-viscoelastic constitutive law [3].

Experimental arrangement during a liver indentation test


A cut through the three-dimensional finite-element model (red) and an associated 3DUS deformation sequence (gray).

The key benefit of image-based mechanical characterization is its ability to observe transient volumetric effects, which are essential in complex biphasic materials with viscous properties. The testing methodologies developed during the period of this project will be independent of imaging modality and mechanical tissue model used. Therefore, the technique will be easily adaptable to other in-vivo and ex-vivo tissue testing applications. We hypothesize that by using image-based mechanical characterization techniques, we can improve material parameter sensitivity and uniqueness, which are limiting current tissue testing methodologies.


[1] Kerdok AE, Jordan P, Liu Y, Wellman PS, Socrate S, Howe RD. "Identification of Nonlinear Constitutive
Law Parameters of Breast Tissue." Proc. of the 2005 Summer Bioengineering Conference, ASME, 2005.

[2] Jordan P, Socrate S, Howe RD. “Image-Based Mechanical Characterization of Porcine Liver using 3D Ultrasound.” Second International Conference on Mechanics of Biomaterials & Tissues. Lihue, HI, 2007. 

[3] Kerdok AE. "Characterizing the nonlinear mechanical response of liver to surgical manipulation."
Ph.D. thesis, Harvard University, 2006.

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