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Related Experiment Video

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Quantification of Myocyte Disarray in Human Cardiac Tissue.

Francesco Giardini1, Erica Lazzeri1, Giulia Vitale2

  • 1Laboratory of Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy.

Frontiers in Physiology
|December 6, 2021
PubMed
Summary

This study introduces a new method to map and quantify cardiomyocyte disarray in large heart tissue samples. The technique reveals significant differences in tissue organization between healthy and diseased hearts, aiding in predictive model development.

Keywords:
3D FFT3D cardiomyocyte orientationcytoarchitecture reconstructiondisarray quantificationtissue modeling

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Area of Science:

  • Cardiovascular Science
  • Biomedical Engineering
  • Microscopy and Imaging

Background:

  • Proper three-dimensional (3D) cardiomyocyte orientation is crucial for cardiac muscle tension production.
  • Cardiac diseases induce remodeling, causing cellular misalignment that impairs heart function.
  • A quantitative method to assess cardiomyocyte disarray in large tissue samples is currently lacking.

Purpose of the Study:

  • To develop and validate an experimental pipeline for reconstructing and analyzing 3D cardiomyocyte architecture in massive myocardial samples.
  • To quantitatively assess tissue organization and myocyte angular dispersion in healthy and pathologically remodeled human cardiac tissue.
  • To establish a foundation for novel predictive models based on cellular-level structural data.

Main Methods:

  • Employed tissue clearing, staining, and advanced microscopy to visualize sarcomeres in human myocardial strips.
  • Utilized Z-band periodicity and frequency analysis to extract 3D myofilament orientation and create orientation maps.
  • Developed a virtual sample generator to correlate multi-scale disarray analysis with cellular architecture.

Main Results:

  • The method successfully mapped 3D myofilament orientation in human cardiac tissue strips with micrometric resolution.
  • Healthy cardiac tissue exhibited well-organized structure with log-normally distributed disarray, minimally scale-dependent.
  • Pathological cardiac tissue displayed significant disorganization, with disarray highly dependent on the scale of analysis.

Conclusions:

  • The developed pipeline reliably quantifies 3D cardiomyocyte organization and disarray in large tissue samples.
  • Significant differences in tissue organization were observed between healthy and diseased human hearts.
  • This approach provides quantitative structural data at cellular resolution, enabling the development of predictive cardiac models.