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

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

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Cell Differentiation
  • Embryo, Mammalian
  • Embryonic Stem Cells / physiology
  • Embryonic Stem Cells / ultrastructure*
  • Image Processing, Computer-Assisted / statistics & numerical data
  • Mice
  • Models, Biological
  • Myocardial Contraction / physiology
  • Myocardium / cytology
  • Myocardium / metabolism
  • Myocytes, Cardiac / physiology
  • Myocytes, Cardiac / ultrastructure*
  • Neoplastic Stem Cells / physiology
  • Neoplastic Stem Cells / ultrastructure*
  • Time-Lapse Imaging / instrumentation
  • Time-Lapse Imaging / methods*