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Parametric Deconvolution for Cancer Cells Viscoelasticity Measurements from Quantitative Phase Images

Vicar, T.; Gumulec, J.; Kolar, R.; Chmelik, J.; Navratil, J.; Chmelikova, L.; Cmiel, V.; Provaznik, I.; Masarik, M.

2021-04-08 bioengineering
10.1101/2021.04.06.438595 bioRxiv
Show abstract

In this contribution, we focused on optimising a dynamic flow-based shear stress system to achieve a reliable platform for cell shear modulus (stiffness) and viscosity assessment using quantitative phase imaging. The estimation of cell viscoelastic properties is influenced by distortion of the shear stress waveform, which is caused by the properties of the flow system components (i.e., syringe, flow chamber and tubing). We observed that these components have a significant influence on the measured cell viscoelastic characteristics. To suppress this effect, we applied a correction method utilizing parametric deconvolution of the flow systems optimized impulse response. Achieved results were compared with the direct fitting of the Kelvin-Voigt viscoelastic model and the basic steady-state model. The results showed that our novel parametric deconvolution approach is more robust and provides a more reliable estimation of viscosity with respect to changes in the syringes compliance compared to Kelvin-Voigt model.

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