Computational Investigation of Transmural Differences in Left Ventricular Contractility

Hua Wang, Xiaoyan Zhang, Shauna M. Dorsey, Jeremy R. McGarvey, Kenneth S. Campbell, Jason A. Burdick, Joseph H. Gorman, James J. Pilla, Robert C. Gorman, Jonathan F. Wenk

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Myocardial contractility of the left ventricle (LV) plays an essential role in maintaining normal pump function. A recent ex vivo experimental study showed that cardiomyocyte force generation varies across the three myocardial layers of the LV wall. However, the in vivo distribution of myocardial contractile force is still unclear. The current study was designed to investigate the in vivo transmural distribution of myocardial contractility using a noninvasive computational approach. For this purpose, four cases with different transmural distributions of maximum isometric tension (Tmax) and/or reference sarcomere length (lR) were tested with animal-specific finite element (FE) models, in combination with magnetic resonance imaging (MRI), pressure catheterization, and numerical optimization. Results of the current study showed that the best fit with in vivo MRI-derived deformation was obtained when Tmax assumed different values in the subendocardium, midmyocardium, and subepicardium with transmurally varying lR. These results are consistent with recent ex vivo experimental studies, which showed that the midmyocardium produces more contractile force than the other transmural layers. The systolic strain calculated from the best-fit FE model was in good agreement with MRI data. Therefore, the proposed noninvasive approach has the capability to predict the transmural distribution of myocardial contractility. Moreover, FE models with a nonuniform distribution of myocardial contractility could provide a better representation of LV function and be used to investigate the effects of transmural changes due to heart disease.

Original languageEnglish
Article number114501
JournalJournal of Biomechanical Engineering
Volume138
Issue number11
DOIs
StatePublished - Nov 1 2016

Bibliographical note

Funding Information:
This study was supported by the National Institutes of Health Grant Nos. R01 HL063954 (R. Gorman), R01 HL111090 (J. Burdick), R01 HL73021 (J. Gorman), and by a grant from the National Science Foundation CMMI-1538754 (J. Wenk).

Publisher Copyright:
© Copyright 2016 by ASME.

Keywords

  • MRI
  • finite element modeling
  • maximum isometric tension
  • numerical optimization
  • transmural variation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Physiology (medical)

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