Synopsis
Diffusion tensor imaging
(DTI) is widely used for structural characterization of the heart. However, the
measured fractional anisotropy (FA) is influenced by diffusion anisotropy as
well as orientation dispersion. In the heart, orientation dispersion is
ubiquitous and stems from the transmural variation in cardiomyocyte orientation
and regions where multiple cell populations intersect. We propose microscopic
FA (µFA) as a more robust measure of intrinsic diffusion anisotropy that is
insensitive to orientation dispersion, and demonstrate this with simulations
and ex vivo MRI.Purpose
Diffusion tensor imaging
(DTI) is widely used for structural characterization of the heart. One metric,
the fractional anisotropy (FA), describes the macroscopic average of the microscopic
diffusion tensors. While this is sensitive to tissue anisotropy, FA is also
influenced by orientation dispersion. In the heart, a transmural variation in
helix angle of the cardiomyocytes is observed
1, along with the
presence of multiple cell populations in regions such as the intersection of
the left and right ventricles (LV and RV), and the apex
2. Both
situations give rise to a decrease in FA due to the orientation dispersion of
cells within a voxel. In contrast, the double diffusion encoding (DDE) method
enables measurement of the microscopic FA (µFA) that describes the underlying
anisotropy insensitive to orientation dispersion
3,4. We propose µFA
as a more robust measure of cardiomyocyte integrity in the heart than FA, and
assess this with simulations and ex vivo MRI.
Methods
3D Monte Carlo simulations
of diffusion were performed along a 1D transmural profile in the simulated LV wall.
Cardiomyocytes were simulated as impermeable cylinders with diameters of 10 μm
using the Camino software5,6. These were arranged in a parallel
manner within sheets. Sheets were then layered across the myocardial wall, with
a similar range of helix angles (α) as reported by Streeter, et al1.
The helix angle distribution is described below, where s = normalized wall thickness.
Simulated free diffusivity was set to 1.0e-3 mm2/s and
diffusion timings were similar to those in the ex vivo MRI experiments.
$$\alpha=90^\circ \times \frac{{log(1-s) - log(s)}}{\parallel log(1-s)-log(s) \parallel}$$
One heart was excised from
a female Sprague-Dawley rat, fixed in 4% paraformaldehyde and embedded in a
tube of 1% agarose gel for MRI. Imaging was performed on a 4.7 T preclinical
scanner (Agilent Technologies, Santa Clara, CA) with a 12 cm bore using a
transmit-receive quadrature coil. DDE and DTI data were acquired with a 2D spin
echo double pulsed field gradient (dPFG) sequence with bipolar diffusion
encoding. The DDE parameters were: TR/TE = 3000/30 ms, matrix = 96 x 96, in-plane
resolution = 0.17 mm, slice thickness = 2 mm, #B0 images = 3, #DW images = 72 with
gradient direction pairs arranged for rotationally invariant sampling3,
δ = 4 ms, Δ = 5 ms, mixing time, τ = 13 ms,
b-value = 2,000 s/mm2, acquisition time = 6 h. The DTI parameters
differed from the DDE as follows: #DW images = 12, b-value = 1,000 s/mm2.
FA and µFA were calculated in the simulated and experimental data3 using
custom code in Matlab (Mathworks, Natick, USA).
Results
Figure 1A illustrates the
helix angles across a 1D profile in the simulated LV wall. Figure 1B shows the
FA and µFA across the same profile. We find that FA was consistently lower than
µFA, particularly in regions where the rate of change in helix angle was
greatest. In contrast, µFA was consistent across the full LV wall thickness.
Figures 2A and 2B depict the FA and µFA maps in a mid-myocardial short axis
slice of an ex vivo rat heart. We found that FA = 0.31 ± 0.07 and µFA = 0.34 ± 0.05 across
the entire slice. Lower FA was observed particularly where the LV and RV intersect. This
heterogeneity was not seen in the µFA data. Figure 3A shows that the helix
angle profile across the lateral wall of the LV is approximately linear. The
corresponding FA was lower than µFA (Figure 3B), consistent with the
sensitivity of FA to orientation dispersion. The shapes of the FA and µFA were
similar, suggesting a transmural variation in intrinsic diffusion anisotropy.
Discussion
The simulations show that
FA is sensitive to transmural variation in helix angle (dα/ds), and is
consistently underestimated relative to the µFA. On the other hand, µFA is
stable and consistent with the simulated diffusion anisotropy. A wide range of
dα/ds have been described in the literature, ranging from non-linear to almost
linear behavior. This is dependent on species
7 and contraction state
2.
The experimental data show that dα/ds was predominantly linear across the LV
wall, and explains the indistinct transmural variation in FA. However, FA was
lower in regions where the LV and RV wall intersect, as is consistent with the
presence of multiple cell populations. µFA was generally higher and more
homogeneous than FA as might be expected in healthy myocardium. We have
demonstrated a technique for measuring intrinsic diffusion anisotropy in the
heart that is insensitive to the macroscopic orientation dispersion effects
that confound DTI measurements.
Acknowledgements
This work was supported by the EPSRC, UK
(EP/J013250/1), BBSRC, UK (BB/I012117/1) and the British Heart Foundation
Centre for Research Excellence, UK (FS/11/50/29038). The authors acknowledge a
Wellcome Trust Core Award (090532/Z/09/Z).References
1. Streeter DD, Jr., Spotnitz HM, Patel DP, Ross J, Jr., Sonnenblick EH. Fiber orientation in the canine left ventricle during diastole and systole. Circ Res 1969;24(3):339-347.
2. Lohezic M, Teh I, Bollensdorff C, Peyronnet R, Hales PW, Grau V, Kohl P, Schneider JE. Interrogation of living myocardium in multiple static deformation states with diffusion tensor and diffusion spectrum imaging. Prog Biophys Mol Biol 2014;115(2-3):213-225.
3. Jespersen SN, Lundell H, Sonderby CK, Dyrby TB. Orientationally invariant metrics of apparent compartment eccentricity from double pulsed field gradient diffusion experiments. NMR Biomed 2013;26(12):1647-1662.
4. Shemesh N, Jespersen SN, Alexander DC, Cohen Y, Drobnjak I, Dyrby TB, Finsterbusch J, Koch MA, Kuder T, Laun F, Lawrenz M, Lundell H, Mitra PP, Nilsson M, Ozarslan E, Topgaard D, Westin CF. Conventions and nomenclature for double diffusion encoding NMR and MRI. Magn Reson Med 2015.
5. Cook PA, Bai Y, Nedjati-Gilani S, Seunarine KK, Hall MG, Parker GJM, Alexander DC. Camino: Open-Source Diffusion-MRI Reconstruction and Processing. In: Proceedings of the 14th Annual Meeting of ISMRM, Seattle, Canada2006. p 2759.
6. Hall MG, Alexander DC. Convergence and parameter choice for Monte-Carlo simulations of diffusion MRI. IEEE Trans Med Imaging 2009;28(9):1354-1364.
7. Healy LJ, Jiang Y, Hsu EW. Quantitative comparison of myocardial fiber structure between mice, rabbit, and sheep using diffusion tensor cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2011;13:74.