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Sci Rep. 2019 Dec 5;9(1):18382. doi: 10.1038/s41598-019-54768-w.

Spatiotemporal Characterizations of Spontaneously Beating Cardiomyocytes with Adaptive Reference Digital Image Correlation.

Author information

1
Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA.
2
Mary & Dick Holland Regenerative Medicine Program, University of Nebraska Medical Center, Omaha, NE, 68198, USA.
3
Division of Cardiology, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, NE, 68198, USA.
4
Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA.
5
Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA. jlim4@unl.edu.
6
Mary & Dick Holland Regenerative Medicine Program, University of Nebraska Medical Center, Omaha, NE, 68198, USA. jlim4@unl.edu.

Abstract

We developed an Adaptive Reference-Digital Image Correlation (AR-DIC) method that enables unbiased and accurate mechanics measurements of moving biological tissue samples. We applied the AR-DIC analysis to a spontaneously beating cardiomyocyte (CM) tissue, and could provide correct quantifications of tissue displacement and strain for the beating CMs utilizing physiologically-relevant, sarcomere displacement length-based contraction criteria. The data were further synthesized into novel spatiotemporal parameters of CM contraction to account for the CM beating homogeneity, synchronicity, and propagation as holistic measures of functional myocardial tissue development. Our AR-DIC analyses may thus provide advanced non-invasive characterization tools for assessing the development of spontaneously contracting CMs, suggesting an applicability in myocardial regenerative medicine.

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