(388a) Invited Talk: The Next Dimension of Detection: Biomechanical Analysis of Tissue | AIChE

(388a) Invited Talk: The Next Dimension of Detection: Biomechanical Analysis of Tissue

Authors 

Armani, A. M. - Presenter, University of Southern California
Hudnut, A., University of Southern California
Lash-Rosenberg, L., University of Southern California
Xin, A., University of Southern California
Doblado, J., California State University of Los Angeles
Zurita-Lopez, C., California State University of Los Angeles
Wang, Q., University of Southern California
Since the discovery of the antibody-antigen interactions and the specificity of DNA hybridization, researchers have focused efforts in diagnostic sensor system design around analyzing the chemical properties of biological systems. However, this approach fundamentally limits the type and diversity of data that can be acquired. By expanding this analysis to include the acquisition of other types of data, such as electrical and mechanical analysis, it is possible to greatly increase the data set and sample analysis; thus improving the reliability of the sample analysis.

In the present work, we demonstrate a new approach for analyzing mechanical properties of unprocessed tissue slices. By using polarization maintaining optical fibers as the sensors in a compression testing system, we are able to improve the detection resolution of mechanical analysis of living, recently resected and unprocessed tissue slides. This approach has allowed the mechanical behavior of wide range of living tissues to be characterized, including porcine kidney, pancreas, and liver. The experimental results compare favorably with a visco-elastic model. In complementary work focused on the pancreas, we have designed 3-D printed biomimetic structures based on cross-sectional images of the pancreas. Using compression testing and finite element analysis of these microscale structures, we have identified several characteristic mechanical features, including buckling. When performing similar measurements with the resected tissue using the optical polarimetric system, we observe similar features, indicating that the pancreatic tissue undergoes buckling. This buckling feature can be attributed to the collagen IV network, and is determined to be the dominate contributor to the mechanical response of the tissue. Detection of this behavior in unprocessed living tissue is only possible due to the improved resolution of the optical fiber sensing method. This approach for tissue analysis provides a complementary strategy for understanding biological systems and could enable the development of new approaches for therapeutics.