- Poster presentation
- Open Access
In-vivo waveguide cardiac magnetic resonance elastography
© Mazumder et al; licensee BioMed Central Ltd. 2015
- Published: 3 February 2015
- Diffusion Tensor Imaging
- Heart Failure With Preserve Ejection Fraction
- Preserve Ejection Fraction
- Diffusion Tensor Imaging Data
- Diffusion Tensor Imaging Parameter
Myocardial stiffness (MS) is elevated in heart failure with preserved ejection fraction(HFPEF). In addition, stiffness elevation in HFPEF exhibits directional dependency. Conventional determinants of MS such as pressure-volume relationship and mechanical testing are invasive and hence clinically inefficient. Therefore, there is a need to non-invasively estimate anisotropic MS to assist in diagnosis and prognosis of HFPEF. In this study we implement waveguide cardiac magnetic resonance elastography (CMRE) to demonstrate the feasibility of estimating anisotropic MS non-invasively in an in-vivo porcine model.
Waveguide CMRE involves performing diffusion tensor imaging (DTI) in conjunction with conventional CMRE. In-vivo CMRE was performed on a pig in a 1.5T MRI scanner. CMRE imaging parameters: TE/TR=9.7/21.4; flip angle 25○; mechanical frequency 80 Hz; encoding frequency 160 Hz. Post CMRE acquisition the heart was arrested in diastole using potassium chloride and in-situ cardiac DTI was performed. Cardiac DTI parameters: TE/TR=80/3200; flip angle 90○; b-value=0/1000 s/mm2; number of directions=12; number of averages=10. CMRE and DTI was performed at the same resolution and the parameters were FOV=320mm3; imaging matrix 128x128; slice thickness=2.5mm; DTI was registered with CMRE to exactly match the voxel information from both sets of acquisition. Then both CMRE and DTI were masked to extract the left ventricle. Masked images were processed to estimate i) principle eigenvectors from DTI data sets; ii) and first harmonic displacements from CMRE wave data. Next, a spatial spectral filter was applied on the first harmonic displacement data to isolate waves traveling in particular directions defined by the principle eigenvector. Simultaneously, Helmholtz decomposition was performed to separate the filtered displacements into its longitudinal and transverse components. An orthotropic inversion  was performed to calculate compressional (C11,C22,C33) and shear (C44,C55,C66) stiffness coefficients.
Anisotropic Stiffness Measurements
Compressional Stiffness Coefficients
Shear Stiffness Coefficients
13.97 ± 0.38
8.68 ± 0.19
27.34 ± 1.02
6.57 ± 1.23
6.44 ± 0.62
6.45 ± 0.68
5.49 ± 0.07
7.02 ± 0.22
20.00 ± 0.54
5.52 ± 0.31
5.56 ± 0.39
5.53 ± 0.31
We have demonstrated the feasibility of estimating in-vivo anisotropic stiffness using CMRE. However further validation and application in a diseased model is required.
This study has been supported by AHA 13SDG14690027.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.