Influence of fiber connectivity in simulations of cardiac biomechanics.
Cardiac electromechanical simulations
Diffusion tensor imaging
Fiber connectivity
Journal
International journal of computer assisted radiology and surgery
ISSN: 1861-6429
Titre abrégé: Int J Comput Assist Radiol Surg
Pays: Germany
ID NLM: 101499225
Informations de publication
Date de publication:
Jan 2019
Jan 2019
Historique:
received:
12
01
2018
accepted:
14
08
2018
pubmed:
21
9
2018
medline:
26
3
2019
entrez:
21
9
2018
Statut:
ppublish
Résumé
Personalized computational simulations of the heart could open up new improved approaches to diagnosis and surgery assistance systems. While it is fully recognized that myocardial fiber orientation is central for the construction of realistic computational models of cardiac electromechanics, the role of its overall architecture and connectivity remains unclear. Morphological studies show that the distribution of cardiac muscular fibers at the basal ring connects epicardium and endocardium. However, computational models simplify their distribution and disregard the basal loop. This work explores the influence in computational simulations of fiber distribution at different short-axis cuts. We have used a highly parallelized computational solver to test different fiber models of ventricular muscular connectivity. We have considered two rule-based mathematical models and an own-designed method preserving basal connectivity as observed in experimental data. Simulated cardiac functional scores (rotation, torsion and longitudinal shortening) were compared to experimental healthy ranges using generalized models (rotation) and Mahalanobis distances (shortening, torsion). The probability of rotation was significantly lower for ruled-based models [95% CI (0.13, 0.20)] in comparison with experimental data [95% CI (0.23, 0.31)]. The Mahalanobis distance for experimental data was in the edge of the region enclosing 99% of the healthy population. Cardiac electromechanical simulations of the heart with fibers extracted from experimental data produce functional scores closer to healthy ranges than rule-based models disregarding architecture connectivity.
Identifiants
pubmed: 30232706
doi: 10.1007/s11548-018-1849-9
pii: 10.1007/s11548-018-1849-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
63-72Références
J Thorac Cardiovasc Surg. 2001 Aug;122(2):389-92
pubmed: 11479518
Circ Res. 2006 Jan 6;98(1):125-32
pubmed: 16339482
IEEE Trans Biomed Eng. 2006 Dec;53(12 Pt 1):2425-35
pubmed: 17153199
Biomech Model Mechanobiol. 2011 Jun;10(3):295-306
pubmed: 20589408
Conf Proc IEEE Eng Med Biol Soc. 2010;2010:738-41
pubmed: 21095899
Int J Cardiovasc Imaging. 2012 Feb;28(2):273-84
pubmed: 21305357
PLoS Comput Biol. 2011 May;7(5):e1002061
pubmed: 21637795
Proc Natl Acad Sci U S A. 2012 Jun 12;109(24):9248-53
pubmed: 22645368
IEEE Trans Med Imaging. 2013 Jan;32(1):45-55
pubmed: 23047864
Med Image Anal. 2013 Dec;17(8):1243-55
pubmed: 23523287
Biomech Model Mechanobiol. 2014 Jun;13(3):627-41
pubmed: 23990017
PLoS One. 2014 Apr 02;9(4):e92792
pubmed: 24695115
Rev Esp Cardiol (Engl Ed). 2013 Oct;66(10):782-90
pubmed: 24773858
J Cardiovasc Magn Reson. 2014 Nov 12;16:87
pubmed: 25388867
Int J Numer Method Biomed Eng. 2012 Jan;28(1):72-86
pubmed: 25830206
Sci Rep. 2016 Jul 28;6:30573
pubmed: 27466029
Eur Heart J Cardiovasc Imaging. 2017 Jul 1;18(7):732-741
pubmed: 28329054
Int J Numer Method Biomed Eng. 2018 Dec;34(12):e3140
pubmed: 30117302
Circ Res. 1972 Feb;30(2):217-43
pubmed: 5061320
Circ Res. 1969 Mar;24(3):339-47
pubmed: 5766515
Prog Biophys Mol Biol. 1998;69(2-3):289-331
pubmed: 9785944
Am J Physiol. 1998 Dec;275(6 Pt 2):H2308-18
pubmed: 9843833