RESUMO
In quantitative micro-elastography (QME), a pre-characterized compliant layer with a known stress-strain curve is utilized to map stress at the sample surface. However, differences in the boundary conditions of the compliant layer when it is mechanically characterized and when it is used in QME experiments lead to inconsistent stress estimation and consequently, inaccurate elasticity measurements. Here, we propose a novel in situ stress estimation method using an optical coherence tomography (OCT)-based uniaxial compression testing system integrated with the QME experimental setup. By combining OCT-measured axial strain with axial stress determined using a load cell in the QME experiments, we can estimate in situ stress for the compliant layer, more accurately considering its boundary conditions. Our proposed method shows improved accuracy, with an error below 10%, compared to 85% using the existing QME technique with no lubrication. Furthermore, demonstrations on hydrogels and cells indicate the potential of this approach for improving the characterization of the micro-scale mechanical properties of cells and their interactions with the surrounding biomaterial, which has potential for application in cell mechanobiology.
RESUMO
Quantitative micro-elastography (QME) is a compression-based optical coherence elastography technique capable of measuring the mechanical properties of tissue on the micro-scale. As QME requires contact between the imaging window and the sample, the presence of friction affects the accuracy of the estimated elasticity. In previous implementations, a lubricant was applied at the contact surfaces, which was assumed to result in negligible friction. However, recently, errors in the estimation of elasticity caused by friction have been reported. This effect has yet to be characterized and is, therefore, not well understood. In this work, we present a systematic analysis of friction in QME using silicone phantoms. We demonstrate that friction, and, therefore, the elasticity accuracy, is influenced by several experimental factors, including the viscosity of the lubricant, the mechanical contrast between the compliant layer and the sample, and the time after the application of a compressive strain. Elasticity errors over an order of magnitude were observed in the absence of appropriate lubrication when compared to uniaxial compression testing. Using an optimized lubrication protocol, we demonstrate accurate elasticity estimation (<10% error) for nonlinear elastic samples with Young's moduli ranging from 3 kPa to 130 kPa. Finally, using a structured phantom, we demonstrate that friction can significantly reduce mechanical contrast in QME. We believe that the framework established in this study will facilitate more robust elasticity estimations in QME, as well as being readily adapted to understand the effects of friction in other contact elastography techniques.