Abstract

Introduction: Computational models of the heart increasingly require detailed microstructural information to capture the impact of tissue remodeling on cardiac electromechanics in, for example, hearts with myocardial infarctions. Myocardial infarctions are surrounded by the infarct border zone (BZ), which is a site of electromechanical property transition. Magnetic resonance imaging (MRI) is an emerging method for characterizing microstructural remodeling and focal myocardial infarcts and the BZ can be identified with late gadolinium enhanced (LGE) MRI. Microstructural remodeling within the BZ, however, remains poorly characterized by MRI due, in part, to the fact that LGE and DT-MRI are not always available for the same heart. Diffusion tensor MRI (DT-MRI) can evaluate microstructural remodeling by quantifying the DT apparent diffusion coefficient (ADC, increased with decreased cellularity), fractional anisotropy (FA, decreased with increased fibrosis), and tissue mode (decreased with increased fiber disarray). The purpose of this work was to use LGE MRI in post-infarct porcine hearts (N = 7) to segment remote, BZ, and infarcted myocardium, thereby providing a basis to quantify microstructural remodeling in the BZ and infarcted regions using co-registered DT-MRI.Methods: Chronic porcine infarcts were created by balloon occlusion of the LCx. 6–8 weeks post-infarction, MRI contrast was administered, and the heart was potassium arrested, excised, and imaged with LGE MRI (0.33 × 0.33 × 0.33 mm) and co-registered DT-MRI (1 × 1 × 3 mm). Myocardium was segmented as remote, BZ, or infarct by LGE signal intensity thresholds. DT invariants were used to evaluate microstructural remodeling by quantifying ADC, FA, and tissue mode.Results: The BZ significantly remodeled compared to both infarct and remote myocardium. BZ demonstrated a significant decrease in cellularity (increased ADC), significant decrease in tissue organization (decreased FA), and a significant increase in fiber disarray (decreased tissue mode) relative to remote myocardium (all p < 0.05). Microstructural remodeling in the infarct was similar, but significantly larger in magnitude (all p < 0.05).Conclusion: DT-MRI can identify regions of significant microstructural remodeling in the BZ that are distinct from both remote and infarcted myocardium.

Highlights

  • Computational models of the heart increasingly require detailed microstructural information to capture the impact of tissue remodeling on cardiac electromechanics in, for example, hearts with myocardial infarctions

  • Balloon occlusion of the left circumflex artery (LCx) resulted in chronic infarcts that exhibited replacement fibrosis as evidenced by the elevated signal intensity (SI) in the late gadolinium enhanced (LGE) images (Figures 1A, 2A)

  • The mean signal-to-noise ratios (SNR) for the LGE Magnetic resonance imaging (MRI) experiments were calculated from each heart by selecting a region of interest (Mewton et al, 2011) in remote/normal myocardium and dividing it by the standard deviation (SD) of an ROI of equal area in the background of the same slice for five spaced slices within each heart

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Summary

Introduction

Computational models of the heart increasingly require detailed microstructural information to capture the impact of tissue remodeling on cardiac electromechanics in, for example, hearts with myocardial infarctions. Myocardial infarctions are surrounded by the infarct border zone (BZ), which is a site of electromechanical property transition. Magnetic resonance imaging (MRI) is an emerging method for characterizing microstructural remodeling and focal myocardial infarcts and the BZ can be identified with late gadolinium enhanced (LGE) MRI. Microstructural remodeling within the BZ, remains poorly characterized by MRI due, in part, to the fact that LGE and DT-MRI are not always available for the same heart. Myocardial fibrosis as a consequence of post-infarct remodeling increases apparent tissue stiffness and decreases anisotropy. Methods to identify the BZ for incorporation into computational models of cardiac electromechanics, are not currently well established

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