RIS ID

135394

Publication Details

Ruland , A., Gilmore, K. J., Daikuara, L. Y., Fay, C. D., Yue, Z. & Wallace, G. G. (2019). Quantitative ultrasound imaging of cell-laden hydrogels and printed constructs. Acta Biomaterialia, 91 173-185.

Abstract

In the present work we have revisited the application of quantitative ultrasound imaging (QUI) to cellular hydrogels, by using the reference phantom method (RPM) in combination with a local attenuation compensation algorithm. The investigated biological samples consisted of cell-laden collagen hydrogels with PC12 neural cells. These cell-laden hydrogels were used to calibrate the integrated backscattering coefficient (IBC) as a function of cell density, which was then used to generate parametric images of local cell density. The image resolution used for QUI and its impact on the relative IBC error was also investigated. Another important contribution of our work was the monitoring of PC12 cell proliferation. The cell number estimates obtained via the calibrated IBC compared well with data obtained using a conventional quantitative method, the MTS assay. Evaluation of spectral changes as a function of culture time also provided additional information on the cell cluster size, which was found to be in close agreement with that observed by microscopy. Last but not least, we also applied QUI on a 3D printed cellular construct in order to illustrate its capabilities for the evaluation of bioprinted structures. Statement of Significance: While there is intensive research in the areas of polymer science, biology, and 3D bio-printing, there exists a gap in available characterisation tools for the non-destructive inspection of biological constructs in the three-dimensional domain, on the macroscopic scale, and with fast data acquisition times. Quantitative ultrasound imaging is a suitable characterization technique for providing essential information on the development of tissue engineered constructs. These results provide a detailed and comprehensive guide on the capabilities and limitations of the technique.

Grant Number

ARC/CE140100012

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