Quantification of Myocyte Disarray in Human Cardiac Tissue.

3D FFT 3D cardiomyocyte orientation cytoarchitecture reconstruction disarray quantification tissue modeling

Journal

Frontiers in physiology
ISSN: 1664-042X
Titre abrégé: Front Physiol
Pays: Switzerland
ID NLM: 101549006

Informations de publication

Date de publication:
2021
Historique:
received: 30 07 2021
accepted: 24 09 2021
entrez: 6 12 2021
pubmed: 7 12 2021
medline: 7 12 2021
Statut: epublish

Résumé

Proper three-dimensional (3D)-cardiomyocyte orientation is important for an effective tension production in cardiac muscle. Cardiac diseases can cause severe remodeling processes in the heart, such as cellular misalignment, that can affect both the electrical and mechanical functions of the organ. To date, a proven methodology to map and quantify myocytes disarray in massive samples is missing. In this study, we present an experimental pipeline to reconstruct and analyze the 3D cardiomyocyte architecture in massive samples. We employed tissue clearing, staining, and advanced microscopy techniques to detect sarcomeres in relatively large human myocardial strips with micrometric resolution. Z-bands periodicity was exploited in a frequency analysis approach to extract the 3D myofilament orientation, providing an orientation map used to characterize the tissue organization at different spatial scales. As a proof-of-principle, we applied the proposed method to healthy and pathologically remodeled human cardiac tissue strips. Preliminary results suggest the reliability of the method: strips from a healthy donor are characterized by a well-organized tissue, where the local disarray is log-normally distributed and slightly depends on the spatial scale of analysis; on the contrary, pathological strips show pronounced tissue disorganization, characterized by local disarray significantly dependent on the spatial scale of analysis. A virtual sample generator is developed to link this multi-scale disarray analysis with the underlying cellular architecture. This approach allowed us to quantitatively assess tissue organization in terms of 3D myocyte angular dispersion and may pave the way for developing novel predictive models based on structural data at cellular resolution.

Identifiants

pubmed: 34867455
doi: 10.3389/fphys.2021.750364
pmc: PMC8635020
doi:

Types de publication

Journal Article

Langues

eng

Pagination

750364

Informations de copyright

Copyright © 2021 Giardini, Lazzeri, Vitale, Ferrantini, Costantini, Pavone, Poggesi, Bocchi and Sacconi.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

J Struct Biol. 2018 Jun;202(3):275-285
pubmed: 29477758
Nature. 2013 May 16;497(7449):332-7
pubmed: 23575631
Prog Biophys Mol Biol. 2020 Aug;154:80-93
pubmed: 31337503
J Magn Reson Imaging. 2020 Aug;52(2):348-368
pubmed: 31482620
Cardiovasc Res. 2002 Jan;53(1):192-201
pubmed: 11744028
J Biomech Eng. 2016 Nov 1;138(11):
pubmed: 27617880
PLoS Comput Biol. 2015 Apr 07;11(4):e1004190
pubmed: 25849553
J Am Coll Cardiol. 2019 May 28;73(20):2493-2502
pubmed: 31118142
Am J Physiol Heart Circ Physiol. 2010 May;298(5):H1616-25
pubmed: 20228259
Med Image Anal. 2017 May;38:117-132
pubmed: 28334658
Circulation. 2003 Mar 18;107(10):1433-9
pubmed: 12642366
J Cardiovasc Magn Reson. 2020 Jun 29;22(1):49
pubmed: 32600420
Front Physiol. 2018 Oct 04;9:1380
pubmed: 30337881
Sci Rep. 2020 Aug 31;10(1):14276
pubmed: 32868776
J Am Coll Cardiol. 2017 Feb 14;69(6):661-676
pubmed: 28183509
Curr Pharm Des. 2015;21(4):431-48
pubmed: 25483944
Am J Physiol Cell Physiol. 2016 Aug 1;311(2):C277-83
pubmed: 27335170
Nat Protoc. 2014 Jul;9(7):1682-97
pubmed: 24945384
Biophys J. 2015 Feb 3;108(3):498-507
pubmed: 25650918
PLoS Comput Biol. 2020 Mar 4;16(3):e1007676
pubmed: 32130207
Circ Res. 2019 Apr 12;124(8):1172-1183
pubmed: 30700234
J Med Imaging (Bellingham). 2020 Mar;7(2):023501
pubmed: 32206684
J Physiol. 2019 Jul;597(14):3639-3656
pubmed: 31116413
Prog Biophys Mol Biol. 2021 Aug 4;:
pubmed: 34358555
Sci Rep. 2015 May 07;5:9808
pubmed: 25950610
Front Physiol. 2018 Apr 04;9:239
pubmed: 29670532
Elife. 2020 Oct 20;9:
pubmed: 33078706
Front Physiol. 2018 Oct 25;9:1474
pubmed: 30410446
J Magn Reson Imaging. 2006 Jan;23(1):1-8
pubmed: 16331592
Circ Res. 2013 Sep 13;113(7):863-70
pubmed: 23899961
J Anat. 2019 Nov;235(5):962-976
pubmed: 31347708
Sci Rep. 2016 Apr 06;6:23756
pubmed: 27048757
Biomaterials. 2012 Aug;33(23):5732-41
pubmed: 22594976
Cardiovasc Res. 2016 Apr 1;109(4):467-79
pubmed: 26705366
Front Physiol. 2018 Oct 16;9:1391
pubmed: 30420810
J Am Coll Cardiol. 2008 Feb 26;51(8):802-9
pubmed: 18294563
JACC Clin Electrophysiol. 2017 Jun;3(6):531-546
pubmed: 29159313
Nat Commun. 2020 Jul 24;11(1):3722
pubmed: 32709902
Circ Res. 2013 Aug 30;113(6):725-38
pubmed: 23989715
J Cardiovasc Magn Reson. 2015 Apr 29;17:31
pubmed: 25926126

Auteurs

Francesco Giardini (F)

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

Erica Lazzeri (E)

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

Giulia Vitale (G)

Division of Physiology, Department of Clinical and Experimental Medicine, University of Florence, Florence, Italy.

Cecilia Ferrantini (C)

Laboratory of Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy.
Division of Physiology, Department of Clinical and Experimental Medicine, University of Florence, Florence, Italy.

Irene Costantini (I)

Laboratory of Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy.
National Institute of Optics, National Research Council, University of Florence, Florence, Italy.
Department of Biology, University of Florence, Florence, Italy.

Francesco S Pavone (FS)

Laboratory of Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy.
National Institute of Optics, National Research Council, University of Florence, Florence, Italy.
Department of Physics, University of Florence, Florence, Italy.

Corrado Poggesi (C)

Division of Physiology, Department of Clinical and Experimental Medicine, University of Florence, Florence, Italy.

Leonardo Bocchi (L)

Laboratory of Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy.
Department of Information Engineering, University of Florence, Florence, Italy.

Leonardo Sacconi (L)

Laboratory of Non-Linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy.
National Institute of Optics, National Research Council, University of Florence, Florence, Italy.
Faculty of Medicine, Institute for Experimental Cardiovascular Medicine, University of Freiburg, Freiburg im Breisgau, Germany.

Classifications MeSH