Influence of fiber connectivity in simulations of cardiac biomechanics
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.
KeywordsCardiac electromechanical simulations Fiber connectivity Diffusion tensor imaging
This work was funded by Spanish Projects DPI2015- 430 65286-R, 2017-SGR-1624, the CERCA Programme, the Serra Hunter Programme and the grant BES-2016-078042.
Compliance with ethical standards
Conflict of Interest
The authors declare that they have no conflict of interest.
For this type of study, formal consent is not required.
This articles does not contain patient data.
- 1.Bishop M, Hales P, Plank G, Gavaghan DJ, Scheider J, Grau V (2009) Comparison of rule-based and dtmri-derived fibre architecture in a whole rat ventricular computational model. In: Functional imaging and modeling of the heart, pp 87–96Google Scholar
- 2.Carapella V, Bordas R, Pathmanathan P, Lohezic M, Schneider JE, Kohl P, Burrage K, Grau V (2014) Quantitative study of the effect of tissue microstructure on contraction in a computational model of rat left ventricle. PloS one 9(4):e92792. https://doi.org/10.1371/journal.pone.0092792 CrossRefGoogle Scholar
- 3.Carreras F, Garcia J, Gil D, Pujadas S, Li CH, Suarez-Arias R, Leta R, Alomar X, Ballester M, Pons-Llado G (2012) Left ventricular torsion and longitudinal shortening: two fundamental components of myocardial mechanics assessed by tagged cine-mri in normal subjects. Int J Cardiovasc Imaging 28(2):273–84CrossRefGoogle Scholar
- 4.Casero R, Burton R.A, Quinn T.A, Bollensdorff C, Hales P, Schneider J, Kohl P, Grau V (2010) Cardiac valve annulus manual segmentation using computer assisted visual feedback in three-dimensional image data. In: EMBC, pp 738–741Google Scholar
- 5.Ferreira PF, Kilner PJ, McGill LA, Nielles-Vallespin S, Scott AD, Ho SY, McCarthy KP, Haba M, Ismail T, Gatehouse P, Silva R, Lyon A, Prasad S, Firmin D (2014) In vivo cardiovascular magnetic resonance diffusion tensor imaging shows evidence of abnormal myocardial laminar orientations and mobility in hypertrophic cardiomyopathy. J Cardiovasc Mag Res 16(87):1–16Google Scholar
- 7.Gil D, Borras A, Aris R, Vazquez M, Lafortune P, Houzeaux G, Aguado J, Ballester M, Li CH, Carreras F (2012) What a difference in biomechanics cardiac fiber makes. In: STACOMGoogle Scholar
- 8.Gonzalez Tendero A, Zhang C, Balicevic V, Cardenes R, Loncaric S, Butakoff C, Paun B, Bonnin A, Garcia-Canadilla P, Munoz-Moreno E, Gratacos E, Crispi F, Bijnens (2017) Whole heart detailed and quantitative anatomy, myofibre structure and vasculature from x-ray phase-contrast synchrotron radiation-based micro computed tomography. EHJ Cardiovasc Imaging 18:732–41CrossRefGoogle Scholar
- 11.Humphrey J (2001) Cardiovascular solid mechanics. Cells, tissues, and organs. Springer, BerlinGoogle Scholar
- 18.Santiago A (2018) Fluid Electro Mechanical model of the human heart for supercomputers. Ph.D. Thesis. UPC, Barcelona, SpainGoogle Scholar
- 20.Scollan D, Holmes A, Winslow R, Forder J (1998) Histological validation of myocardial microstructure obtained from diffusion tensor magnetic resonance imaging. Am J Physiol 275:2308–2318Google Scholar
- 23.Teh I, McClymont D, Burton R, Maguire M, Whittington H, Lygate C, Kohl P, Schneider J (2016) Resolving fine cardiac structures in rats with high-resolution dti. Nat Sci Rep 6(30573):1–14Google Scholar
- 26.Vázquez M, Arís R, Aguado-Sierra J, Houzeaux G, Santiago A, López M, Córdoba P, Rivero M, Cajas JC (2015) Alya red ccm: Hpc-based cardiac computational modeling. In: Selected topics of computational and experimental fluid mechanics pp 189–207Google Scholar