Potential for quantitative microelastography using a multi-channel optical coherence method

Extension of elastographic methods to a microscopic scale is expected to provide invaluable information on soft tissue mechanobiology, by facilitating hitherto impossible experiments to study the relationship between local variations in extracellular matrix stiffness and cellular behaviour. Optical coherence tomography (OCT) is an optical backscatter imaging modality with micron-scale resolution, and ability to measure the sub-micron displacements associated with low-amplitude shear deformation. OCT should therefore be a good imaging modality on which to base a future microelastography system. This work aims to demonstrate the potential of a novel method for quantitative OCT-based microelastography. A vibrating needle was used to generate bursts of 4-10 cycles of 500Hz shear waves within gelatine phantoms of varying stiffness. Shear displacements were measured as a function of time and distance from the needle, using four M-mode images acquired simultaneously using a four-channel swept-source OCT system. Displacement was arranged to be in the OCT-axial direction and the vibrating needle was positioned within the OCT scan plane so that shear waves propagated along the line from one optical channel to another. Shear-wave speed was then calculated from inter-channel differences of shear-wave arrival time and compared with the shear-wave speed determined by a more conventional absolute time-of-arrival (TOA) method. The results confirm that the measured shear-wave speed increases, as expected, in proportion with the gelatine concentration, and the amplitude decreases as gel stiffness rises. The channel-difference (4-channel) method produced results that were equivalent to those from the absolute TOA method. This overall approach shows promise for the eventual provision of microelastography as a research tool in cancer cell biology. Further work is required to optimise the system, to fully characterise and compare the two methods, to automate arrival-time determination a- d to create elasticity images.