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Annals of Biomedical Engineering

, Volume 44, Issue 9, pp 2661–2673 | Cite as

Parametric Modeling of the Mouse Left Ventricular Myocardial Fiber Structure

  • Samer S. Merchant
  • Arnold David Gomez
  • James L. Morgan
  • Edward W. Hsu
Article

Abstract

Magnetic resonance diffusion tensor imaging (DTI) has greatly facilitated detailed quantifications of myocardial structures. However, structural patterns, such as the distinctive transmural rotation of the fibers, remain incompletely described. To investigate the validity and practicality of pattern-based analysis, 3D DTI was performed on 13 fixed mouse hearts and fiber angles in the left ventricle were transformed and fitted to parametric expressions constructed from elementary functions of the prolate spheroidal spatial variables. It was found that, on average, the myocardial fiber helix angle could be represented to 6.5° accuracy by the equivalence of a product of 10th-order polynomials of the radial and longitudinal variables, and 17th-order Fourier series of the circumferential variable. Similarly, the fiber imbrication angle could be described by 10th-order polynomials and 24th-order Fourier series, to 5.6° accuracy. The representations, while relatively concise, did not adversely affect the information commonly derived from DTI datasets including the whole-ventricle mean fiber helix angle transmural span and atlases constructed for the group. The unique ability of parametric models for predicting the 3D myocardial fiber structure from finite number of 2D slices was also demonstrated. These findings strongly support the principle of parametric modeling for characterizing myocardial structures in the mouse and beyond.

Keywords

DTI Cardiac Parametric modelling Cardiac fiber architecture prediction Cardiac DTI atlas 

Notes

Acknowledgements

The authors would like to thank Brian Watson for laboratory assistance, and Osama Abdullah and Dr. S. Joshi for their technical discussion. This work was supported by National Institutes of Health (NIH) Grants R01 HL092055 and S10 RR023017.

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Copyright information

© Biomedical Engineering Society 2016

Authors and Affiliations

  1. 1.Department of BioengineeringUniversity of UtahSalt Lake CityUSA
  2. 2.Division of Cardiothoracic SurgeryUniversity of UtahSalt Lake CityUSA

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