Soft Tissue Thermomechanics

Ultrasound Elastography

Mechanical characterization of the nonlinear, anisotropic behavior of soft tissue, accounting for internal stresses, is a challenging problem. For multi-layer tissues such as the stomach and skin, being able to discern accurate layer-specific properties adds significantly to this complexity. To address these challenges, we have developed an ultrasound elastography-based technique to characterize the mechanical behavior of multi-layer tissues. A Soft Tissue Elastography Robotic Arm (STiERA) system is designed and developed to identify the layer-specific material properties without separating or destroying the layers. The STiERA compression testing instrument is composed of a robotic arm and a custom designed compression head fixture that is equipped with two load cells and a high frequency ultrasound probe (Figure 1).

Figure 1. Left side schematic depicts the STiERA system. The details of the compression head fixture are shown on the right.

The identification of the material parameters of multilayer biological material is an inverse problem. We have adopted an iterative approach to solve the inverse problem, because it is robust and applicable to nonlinear material models, in contrast to the ‘direct method’, which solves the ‘inverse’ balance of momentum equation as a single, linear, hyperbolic partial differential equation for the material parameter (i.e. shear modulus) with appropriate boundary conditions. The ‘iterative method’ recasts the inverse problem as a minimization problem and the solution is sought for which the difference between the experimental and simulated force and displacement data is minimized.

A significant part of our work on the characterization of material properties of layered soft tissue is based on this approach, where the experimental quantities are measured using STiERA system and the simulation results are obtained by solving a ‘forward’ problem using finite element method. Most recently this approach has been used to identify the material properties of the layers of both the ex vivo and in vivo porcine stomach tissue, shown in Figure 2.

Figure 2. Left panel shows layer specific hyperelastic material behavior of the ex vivo porcine gastric tissue as modeled using the STiERA framework. In the right panel, the comparison of shear modulus of the cardiac and fundic regions for each layer of the in vivo porcine tissue shows that the muscularis is the stiffest followed by the submucosa and mucosa.

Relevant publications

1. Dargar, S., Akyildiz, A. C., and De, S. (2017). In situ mechanical characterization of multilayer soft tissue using ultrasound imaging. IEEE Transactions on Biomedical Engineering, 64(11), 2595-2606.
2. Dargar, S., Rahul, Kruger, U., and De, S. In vivo determination of layer-specific mechanical properties for porcine stomach tissue using ultrasound elastography. In preparation.

Burn Mechanics

Burns are some of the most common injuries in both civilian and combat scenarios. Prompt and accurate identification of burn degree is of vital importance to the clinical treatment of burns since it helps reduce the mortality rate and shorten hospital stay of patients. However, the accuracy of clinical assessment of burn degree is only 50%-80%. Numerous experimental and numerical studies have been done to facilitate clinical determination of burn degree. However, most of these studies focus only on analyzing the results of burns, rather than studying the underlying physics and mechanism. As a result, a significant knowledge gap exists in quantifying changes in tissue characteristics as a result of burn injuries that are linked to altered tissue morphology. Our aim is to develop experimental and numerical techniques to gain fundamental understanding of acute burn of skin tissue by identifying the altered nonlinear, anisotropic, and layer specific thermomechanical properties and by quantifying the thermomechanical damage due to burn.

More recently, we have developed a noninvasive technique based on ultrasound elastography using STiERA system, which is shown to reliably assess the altered nonlinear mechanical properties of burnt ex vivo porcine skin tissue (Figure 3(left)). Additionally, tissue is observed to soften due to the change in structure of the collagen fibers (Figure 3(right)).

Figure 3. Left panel shows the nonlinear parameter (C₂₀) of a reduced second order polynomial hyperelastic material model for both unburnt and burnt tissue samples in four burning groups. The results indicate that C₂₀ reliably identifies three of the four cases (p<0.05) when comparing burnt with unburnt tissue. The ‘*’ indicates significant difference in paired t-test (or signed test). Right panel compared the stress-strain curves for unburnt tissue with the tissue burnt at 450 ºF for 10 seconds. The solid lines indicate the median response, whereas, the shaded areas are response between the 1st and 3rd quartile.

Relevant Publications

1. Ye, H., and De., S. (2017). Thermal injury of skin and subcutaneous tissues: A review of experimental approaches and numerical models. Burns, 43(5), 909-932.
2. Ye, H., Rahul, Dargar, S., Kruger, U., and De, S., Ultrasound elastography reliably identifies altered mechanical properties of burnt soft tissues. Submitted to Burns.

Thermal Characterization of Soft Tissues

An accurate understanding of heat transfer and temperature variation in soft tissue during electrosurgical procedures can help us to predict areas of tissue damage and necrosis. However, this is challenging in the absence of accurate knowledge of tissue thermal properties including specific heat and thermal conductivity for a wide range of temperature encountered in electrosurgery. While inaccuracy of thermal conductivity may be of lesser importance, as tissue heating is rapid and heat conduction is not the dominant mode of energy dissipation, the lack of high-temperature specific heat values is critical. To this end, we have developed an inverse optimization model to characterize the apparent specific heat of liver tissue. The "apparent" specific heat is thus obtained by minimizing the error between experimental and simulated temperature data in some norm. Tissue surface temperature for monopolar electrode configuration is measured using infrared thermometry. The simulation results are obtained by solving forward transient heat transfer problem using finite element method. An interesting observation is that as temperatures approaches the boiling point of water, apparent specific heat increases by a factor of five, indicating that vaporization plays an important role in the energy dissipation through latent heat loss (Figure 4).

Figure 4. Thermal characterization of apparent specific heat (c_app) of liver tissue. Plot shows comparison of temperature dependent c_app with literature.

Relevant Publications

1. Karaki, W., Akyildiz, A., De, S., and Borca-Tasciuc, D. A. (2017). Energy dissipation in ex vivo porcine liver during electrosurgery. IEEE Transactions on Biomedical Engineering, 64(6), 1211-1217.