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Am J Physiol Heart Circ Physiol 293: H2377–H2384, 2007.
First published June 29, 2007; doi:10.1152/ajpheart.00337.2007.
Transmural heterogeneity of diffusion anisotropy in the sheep myocardium
characterized by MR diffusion tensor imaging
Yi Jiang,1,2 Julius M. Guccione,3,4 Mark B. Ratcliffe,3,4 and Edward W. Hsu5
1
Department of Biomedical Engineering, Duke University, and 2Center for In Vivo Microscopy, Duke University Medical
Center, Durham, North Carolina; 3Department of Surgery, University of California, San Francisco, and 4Veterans Affairs
Medical Center, San Francisco, California; and 5Department of Bioengineering, University of Utah, Salt Lake City, Utah
Submitted 16 March 2007; accepted in final form 28 June 2007
and arrangement of the myocardium
are known to have a profound impact on its electrical (10, 37)
and mechanical properties (1, 44). Early histological studies
(27, 31, 45), although labor intensive, destructive, and prone to
tissue-processing artifacts, have provided important insights
into the myocardial structure, including the distinctive counterclockwise transmural rotation of the ventricular myocardial
fiber orientation. By probing the tissue microstructure via its
influence on the molecular diffusion of water, MR diffusion
tensor imaging (DTI) (3) has emerged as a convenient and
reliable alternative for characterization of the three-dimensional (3D) structure of the myocardium (23, 38).
In 3D space, the MRI-measured diffusion tensor is a symmetrical 3 ⫻ 3 matrix; its eigenvalues and eigenvectors represent the motilities along the principal axes of water translational diffusion and their spatial orientations, respectively. The
diffusion tensor eigenvectors have been linked to the orientation of myocardial microstructure. For example, the primary
diffusion tensor eigenvector (i.e., which corresponds to the
largest eigenvalue) has been directly correlated to the myocardial fiber orientation (23), and the tertiary eigenvector (pertaining to the smallest eigenvalue) has been taken as the plane
normal to the myocardial laminar structure (38). Meanwhile,
the diffusion tensor eigenvalues, which are often aggregated
into single scalar indexes for easier quantification of the degree
of diffusion anisotropy, are generally considered to reflect the
underlying cellular composition (e.g., white matter myelination) and organization (cell packing density) (3).
Besides in vivo studies in humans (13, 49), DTI has been
used to characterize in vitro or ex vivo hearts in several
species, including goat (15), dog (20), sheep (47), rabbit (18),
rat (7, 8), and mouse (25), and applied to the study of myocardial structures as functions of cardiac contractile state (7)
and remodeling associated with infarction (8, 47), hypertrophy
(18), and dyssynchronous heart failure (20). These studies have
focused primarily on the measurement and analysis of spatial
variations of the myocardial fiber and sheet structures obtained
from the orientation information in the diffusion tensor. In
contrast, the scalar quantities, including the diffusivities and
anisotropy indexes, have simplistically been assumed to be
homogeneous throughout the myocardium (7, 15, 20, 25, 47),
and the validity of this assumption remains largely untested.
Transmural variations of myocardial microstructure have
been documented in several histological studies. A transmural
gradient of myocyte dimensions has been observed in the rat
left ventricle (LV), with the largest and smallest cell volume
and cross-sectional area found in the endocardium and epicardium, respectively (5). In a dog heart study (27), a progressive
decrease in the relative proportion of myocytes from the
epicardium to the endocardium was accompanied by an increase in the volume fraction occupied by extracellular space.
Transmural differences in connective tissue concentration have
been reported in dog (50) and mouse (32) hearts, as well as cell
types and distribution in different (e.g., canine, rabbit, and
human) hearts (39, 48). Since MR diffusion and DTI measurements are highly sensitive to the underlying tissue structure,
the above-described evidence of structural heterogeneity suggests that DTI scalar quantities are also likely heterogeneous in
the myocardium.
The hypothesis of the present study is that structural heterogeneity of the myocardium gives rise to measurable differences in DTI diffusion anisotropy. Without loss of generality,
the DTI-derived fractional anisotropy (FA) index (34), a commonly used rotationally invariant index of diffusion anisot-
Address for reprint requests and other correspondence: Y. Jiang, Center for
In Vivo Microscopy, Box 3302, Duke Univ. Medical Center, Durham, NC
27710 (e-mail: [email protected]).
The costs of publication of this article were defrayed in part by the payment
of page charges. The article must therefore be hereby marked “advertisement”
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
fractional anisotropy; left ventricle; extracellular volume fraction;
cardiac electrophysiology and biomechanics
CELLULAR MICROSTRUCTURE
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Jiang Y, Guccione JM, Ratcliffe MB, Hsu EW. Transmural
heterogeneity of diffusion anisotropy in the sheep myocardium characterized by MR diffusion tensor imaging. Am J Physiol Heart Circ
Physiol 293: H2377–H2384, 2007. First published June 29, 2007;
doi:10.1152/ajpheart.00337.2007.—The orientation of MRI-measured
diffusion tensor in the myocardium has been directly correlated to the
tissue fiber direction and widely characterized. However, the scalar
anisotropy indexes have mostly been assumed to be uniform throughout the myocardial wall. The present study examines the fractional
anisotropy (FA) as a function of transmural depth and circumferential
and longitudinal locations in the normal sheep cardiac left ventricle.
Results indicate that FA remains relatively constant from the epicardium to the midwall and then decreases (25.7%) steadily toward the
endocardium. The decrease of FA corresponds to 7.9% and 12.9%
increases in the secondary and tertiary diffusion tensor diffusivities,
respectively. The transmural location of the FA transition coincides
with the location where myocardial fibers run exactly circumferentially. There is also a significant difference in the midwall-endocardium FA slope between the septum and the posterior or lateral left
ventricular free wall. These findings are consistent with the cellular
microstructure from histological studies of the myocardium and suggest a role for MR diffusion tensor imaging in characterization of not
only fiber orientation but, also, other tissue parameters, such as the
extracellular volume fraction.
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HETEROGENEITY OF MYOCARDIAL DIFFUSION ANISOTROPY
ropy, as well as the diffusion tensor eigenvalues, are examined
as functions of LV wall depth and circumferential and longitudinal locations. The observations are explained in terms of a
biophysical model of diffusion and correlated to the known
cellular structure, including fiber orientation, of the myocardium. Since the goal of the present study is to point out that
DTI may generate more information about functional significance than is currently utilized, analyses of the fiber or sheet
structure orientations are not included to avoid repetition of
previous studies.
METHODS
Specimen Preparation
Diffusion Tensor Imaging
Imaging experiments were conducted on a 2.0-T MRI instrument
(Oxford Instruments, Oxford, UK) interfaced to a Signa console (Epic
5X, General Electric Medical Systems, Milwaukee, WI). The intact
heart was placed inside a custom-built 10-cm-diameter loop-gap
radio-frequency coil, with the cardiac long axis parallel to the coil
axis. A standard diffusion-weighted spin-echo pulse sequence was
used to acquire 3D volume images (field of view ⫽ 10 ⫻ 10 ⫻ 10 cm,
TR ⫽ 500 ms, TE ⫽ 27.3 ms, and no. of averages ⫽ 1). Diffusion
encoding was performed using a pair of half-sine gradient pulses (10.0
ms wide, 15.0 ms separation, and 18.0 g/cm gradient amplitude, which
corresponds to a diffusion-weighting b value of 1,175 s/mm2). A
reduced encoding DTI methodology (22) was employed to reduce the
scan time without proportional loss in measurement accuracy. Each
DTI dataset consisted of a fully encoded 128 ⫻ 128 ⫻ 128 (readout ⫻
phase ⫻ slice) matrix-size b ⬇ 0 (or b0) and 12 reduced encoded
(128 ⫻ 64 ⫻ 64) diffusion-weighted images sensitized in each of an
optimized set of 12 directions (33). The acquisition time for each
complete DTI dataset was ⬃9.1 h.
Reduced encoded diffusion-weighted images were reconstructed to
128 ⫻ 128 ⫻ 128 matrix size (equivalent to an isotropic resolution of
0.78 mm) by reduced-encoding imaging via a generalized series
reconstruction (RIGR) algorithm (28), with the b0 image used as the
constraining reference. Diffusion tensors were estimated by nonlinear
least-squares curve fitting and diagonalized on a pixel-by-pixel basis,
as described previously (25). The FA for each pixel was also computed.
Data Analysis
Anatomic coordinate system. To provide consistent and objective
placement of the measurement regions of interest, the following
semiautomated procedures were used to define a prolate spheroidbased coordinate system (31) on each LV. 1) Since the imaging and
cardiac short-axis planes were not necessarily parallel, which resulted
in elliptical, rather than circular (15), LV cross sections on the image
slices, points (10 per plane) were manually selected on the epicardial
boundary and fitted to an ellipse on nine equally spaced planes
spanning approximately the middle 75% of the LV volume. 2) The
long axis of the LV was determined by linear regression of the centers
of the fitted ellipses (7, 15), and the entire volume of the heart was
rotated as a rigid body, such that the LV long axis coincides with the
imaging slice axis. Cubic interpolation was used for all image (including diffusion tensor eigenvalue and FA maps) rotations, and the
diffusion tensor eigenvector fields were rotated accordingly by nearAJP-Heart Circ Physiol • VOL
再
y ⫽ y0
y ⫽ y 0 ⫹ m共x ⫺ x 0 兲
x ⱕ x0
x ⬎ x0
(1)
where x is the normalized transmural depth, y is the FA value, y0 is the
intercept of y at x ⫽ 0 (i.e., FA at the epicardium), m is the slope, and
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Specimens were obtained from a separate study (47). Briefly, under
a protocol approved by the University of California, San Francisco,
Institutional Animal Care and Use Committee, intact hearts (n ⫽ 4)
from normal adult castrated male Dorsett sheep were excised, fixed
under retrograde perfusion, and stored in formalin. The average time
between specimen harvest and imaging was 4 ⫾ 1 wk.
est-neighbor interpolation. 3) Because the volume rotation resulted
in new epicardial boundaries in the imaging slice planes, steps 1
and 2 were repeated until the LV long axes between iterations
differed by ⬍ 3°.
Whereas the smooth shape and image contrast of the LV epicardial
boundary make it relatively easy to delineate, the presence of the
papillary muscle and trabeculations has been a significant source of
variation in manual definition of the endocardial boundary (7, 25, 47).
For the present study, the papillary muscle and trabeculations were
observed within regions of the LV where the fiber helix angle [i.e., the
angle of inclination of the primary diffusion tensor eigenvector from
the imaging slice plane (25)] exceeded 50°. To reduce the subjectivity
in defining the boundary and excluding papillary muscles, 10 points
with fiber helix angle of 50° were selected and used to fit an inner
ellipse to approximate the LV endocardial border. Subsequently,
the local LV myocardial wall thickness (i.e., the distance between the
fitted epicardial and endocardial boundaries) was used to obtain the
normalized transmural depth (0.0 and 1.0 at the epicardium and
endocardium, respectively) along radial trajectories that passed
through the LV central long axis (Fig. 1A). The corresponding FA
map of the same slice is displayed in Fig. 1B.
Region-of-interest measurements. The short-axis slice with the
largest cross-sectional area was taken to be the LV hemispherical
plane. Regions of interest were selected on five equally spaced
short-axis slices (1 above, 1 at, and 3 below the hemispherical plane).
The gap between the slices was equal to one-fifth of the distance
between the hemisphere plane and the cardiac apex, and the slices
were labeled S1–S5 in sequential order according to their proximity to
the base (Fig. 1C). Within each slice and along the LV circumference,
four 20° sectors (Fig. 1D) were defined at orthogonal locations
corresponding to the septal, posterior, lateral, and anterior regions of
the LV, where the septal region is located in the middle of the two
right ventricle (RV) fusion sites. Within each sector, the mean FA
profile as a function of normalized transmural depth was computed
from the anisotropy indexes at the same transmural depth along 10
radial trajectories evenly spanning the sector. In total, 80 transmural
FA profiles (4 sectors per slice and 5 slices per heart) were obtained
from 4 hearts. In a similar manner, the transmural profiles of primary,
secondary, tertiary, and mean diffusivities (i.e., diffusion tensor eigenvalues) and primary eigenvector helix angle were obtained. To
determine whether any change in the FA was caused by alterations in
the diffusion tensor characteristics or by differences of goodness of fit
in tensor computation, the uncertainty in the multivariate curve fitting
was quantified by a normalized magnitude of diffusion tensor errors
(NMTE) (6) derived from the corresponding standard error covariance
matrix, which was also analyzed and plotted as a function of the
transmural depth.
Statistical analysis and transmural profile modeling. As a first step
to quantify the transmural trend of the FA, all 80 profiles were pooled
and analyzed as a single group. To reduce statistical false results
originating from excessive comparisons, each FA profile was divided into
four equal zones labeled Z1–Z4 starting at the epicardium (Fig. 2A). The
mean FA values of all 80 profiles across the 4 zones were compared
by one-way ANOVA and post hoc Tukey-Kramer tests. Similarly,
transmural trends of the primary (D1), secondary (D2), tertiary (D3),
and mean (Dav) diffusion tensor diffusivities were examined. Unless
otherwise noted, values are means ⫾ SD, and P ⬍ 0.05 was considered statistically significant.
Because the FA remained relatively constant from the epicardium
to the ventricular midwall and then decreased steadily from the
midwall to the endocardium, individual FA transmural profiles were
empirically fitted to a step-ramp function (Fig. 2B)
HETEROGENEITY OF MYOCARDIAL DIFFUSION ANISOTROPY
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x0 is the depth of transition. Parameters of the step-ramp function, x0,
y0, m, and R2 (for goodness of fit) were determined by least-squares
regression. Each fitted step-ramp parameter (x0, y0, or m) as a function
of longitudinal slice and circumferential sector was compared by
two-way ANOVA and subsequent Tukey-Kramer tests to examine
regional variations of the value and trend of the FA.
To determine whether a correlation exists between the observed
trend of the FA and fiber orientation, locations where the fiber
orientation helix angle is zero (i.e., myocardial fibers run exactly
circumferentially) were determined by linear regression of the helix
angle profile. The zero-helix angle location was chosen, since the
myocardium on either side exhibits quite different material strain
during LV contraction (11, 46). The locations, in terms of normalized
transmural depth, were compared with the transition points (x0) of the
FA profiles by paired Student’s t-test.
RESULTS
In Fig. 3A, FA profiles obtained for all sectors, slices, and
specimens (n ⫽ 80) are plotted as functions of the normalized
transmural depth and overlaid with a bar graph of the FA
(mean ⫾ SD) in each of the quartile transmural zones. The FA
profiles and the bar graph demonstrate a conspicuous decreasing trend of FA from the epicardium toward the endocardium. FA values for the four zones, starting from the
Fig. 1. Determination of regions of interest for analysis of myocardial structure. A: epicardial and endocardial borders were delineated by 2 fitted ellipses
on each true short-axis slice. B: corresponding false-color-coded fractional
anisotropy (FA) map of slice in A. C: 5 equally separated slices, labeled S1–S5,
were selected above, at, and below left ventricular (LV) hemisphere plane.
Separations between adjacent slices were equal to one-fifth of the distance
from the hemisphere to the apex. D: on each selected slice, 4 orthogonal 20°
sectors (septal, posterior, lateral, and anterior) were defined.
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Fig. 2. Definition of transmural zones and modeling of transmural FA profile.
A: four equal zones, labeled Z1–Z4 starting at the epicardium, were defined on
the normalized transmural depth. A representative FA profile is shown.
B: FA profile (solid line) was fitted to a step-ramp function (dashed line), with
the associated intercept, slope, and transition points. (Fitted parameters for this
FA profile were intercept 0.34, slope 0.30, transition point 0.47, with R2
of 0.97.)
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HETEROGENEITY OF MYOCARDIAL DIFFUSION ANISOTROPY
epicardium, are 0.35 ⫾ 0.05, 0.35 ⫾ 0.04, 0.32 ⫾ 0.05, and
0.27 ⫾ 0.06 (mean ⫾ SD, n ⫽ 80). One-way ANOVA
(Table 1) across the four zones for all profiles reveals a
significant difference (P ⬍ 10⫺6) among the mean FA
values. Subsequent Tukey-Kramer tests (Table 1) reveal that
the mean FA in Z1 and Z2 are each significantly larger than
the mean FA in Z3 and Z4, and the mean FA in Z3 is
significantly larger than that in Z4. Mean FA values in Z1
and Z2 are not statistically different.
The individual profiles for D1, D2, D3, Dav, and NMTE are
overlaid with bar graphs of the corresponding zone-averaged
values in Fig. 3, B–F. The averaged values in zones Z1, Z2, Z3,
and Z4 are 1.27 ⫾ 0.13, 1.28 ⫾ 0.13, 1.26 ⫾ 0.01, and 1.24 ⫾
0.15 ⫻ 10⫺3 mm2/s (mean ⫾ SD, n ⫽ 80) for D1, 0.83 ⫾ 0.14,
0.83 ⫾ 0.14, 0.85 ⫾ 0.13, and 0.89 ⫾ 0.14 ⫻ 10⫺3 mm2/s for
D2, 0.64 ⫾ 0.11, 0.64 ⫾ 0.10, 0.67 ⫾ 0.11, and 0.72 ⫾ 0.13 ⫻
10⫺3 mm2/s for D3, 0.91 ⫾ 0.12, 0.92 ⫾ 0.12, 0.93 ⫾ 0.12, and
0.95 ⫾ 0.13 ⫻ 10⫺3 mm2/s for Dav, and 0.023 ⫾ 0.008,
0.022 ⫾ 0.007, 0.022 ⫾ 0.006, and 0.022 ⫾ 0.005 for NMTE.
One-way ANOVA (Table 1) on the four zones indicates
significant differences in D2 (P ⫽ 0.015) and D3 (P ⫽ 10⫺5),
but not D1 (P ⫽ 0.24), Dav (P ⫽ 0.24), and NMTE (P ⫽ 0.94).
AJP-Heart Circ Physiol • VOL
Post hoc Tukey-Kramer tests (Table 1) indicate significantly
higher D2 in Z4 than in Z1 and Z2 and significantly higher D3
in Z4 than in all other zones. As a group, averaged FA of 80
profiles decreases 25.7% from the epicardium to the endocardium, and D2 and D3 increase by 7.9% and 12.9%, respectively, over the same length.
Fitting the transmural FA profiles to step-ramp functions and
pooling results from all 80 profiles yield averaged intercept,
slope, and transition depth of 0.35 ⫾ 0.01, ⫺0.21 ⫾ 0.09, and
0.48 ⫾ 0.05 (mean ⫾ SD), respectively. Moreover, an average
R2 of 0.86 ⫾ 0.10 was obtained, indicating that the fitting
quality was reasonably good.
The fitted FA slope, intercept, and transition point, averaged
in each sector as functions of circumferential and slice locations, are tabulated in Tables 2, 3, and 4, respectively. Twoway ANOVA for the fitted slope (data not shown) reveals a
significant difference among circumferential locations (P ⬍
0.003) but not among longitudinal slices (P ⬎ 0.5). Post hoc
comparisons reveal significant differences between the mean
slope in the septal region (⫺0.12 ⫾ 0.02, mean ⫾ SD, n ⫽ 20)
and posterior (⫺0.26 ⫾ 0.08) and lateral (⫺0.29 ⫾ 0.07)
regions. For the intercept, no significant variation was found
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Fig. 3. Transmural profiles and zonal averages of
diffusion tensor imaging (DTI) parameters obtained
for FA (A), primary (D1; B), secondary (D2; C), tertiary (D3; D), and mean (Dav; E) diffusivity (10⫺3
mm2/s), and normalized magnitude of diffusion tensor
errors (NMTE; F) for all sectors, slices, and specimens
(n ⫽ 80) as functions of normalized transmural depth.
Zonal averages are represented by bar graphs with
corresponding standard deviations as error bars.
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DISCUSSION
Table 1. One-way ANOVA and subsequent Tukey-Kramer
tests of FA, D1, D2, D3, Dav, and NMTE across transmural
zones Z1–Z4
Diff in Means
95% CI
⫺0.00
0.02
0.07
0.03
0.07
0.05
⫺0.02 to 0.02
0.01 to 0.04*
0.05 to 0.09*
0.01 to 0.04*
0.05 to 0.10*
0.03 to 0.07*
⫺0.00
⫺0.02
⫺0.06
⫺0.02
⫺0.06
⫺0.04
⫺0.06 to 0.05
⫺0.08 to 0.03
⫺0.12 to ⫺0.01*
⫺0.08 to 0.04
⫺0.12 to ⫺0.01*
⫺0.10 to 0.02
0.00
⫺0.03
⫺0.08
⫺0.03
⫺0.08
⫺0.05
⫺0.05 to 0.05
⫺0.07 to 0.02
⫺0.13 to ⫺0.03*
⫺0.07 to 0.02
⫺0.13 to ⫺0.03*
⫺0.10 to ⫺0.01*
FA, fractional anisotropy; D1, D2, D3, and Dav, primary, secondary, tertiary,
and mean diffusivity; NMTE, normalized magnitude of diffusion tensor error
(n ⫽ 80). *Significance corresponding to P [i.e., 95% confidence interval (CI)
of difference in means (Diff in means) does not include 0].
among different circumferential or slice locations (P ⬎ 0.9 in
either case). Similarly, no significant dependence was observed
for the transition point with respect to circumferential or
longitudinal slice locations (P ⬎ 0.3). In the analyses of all
three fitted parameters, interactions between the two variables,
circumferential and longitudinal slice locations, are insignificant (P ⬎ 0.2), which indicates that these two variables are
independent.
For the comparison of the zero-fiber orientation helix angle
and FA profile transition points, paired Student’s t-test reveals
no significant difference between the two groups (P ⬎ 0.5).
The zero-helix angle for fiber orientation occurs on average at
a normalized transmural depth of 0.47 ⫾ 0.06 (mean ⫾ SD,
n ⫽ 80) compared with the average FA profile transition point
of 0.48 ⫾ 0.05. Conversely, the average corresponding fiber
orientation helix angle at all FA profile transition points is
⫺1 ⫾ 6° (n ⫽ 80).
The results reveal heterogeneity in the scalar DTI parameters
across the LV myocardial wall. Although the biophysical
mechanisms linking the MRI diffusion (and diffusion tensor)
measurements to the underlying tissue structure are not perfectly understood, intuitively, the diffusion properties are a
function of the intrinsic diffusivities and relative volumes of
the intra- and extracellular spaces, including restriction of the
water molecular motility imposed by the cellular arrangement
(21, 26). Since the DTI primary eigenvector has been correlated to the local myocardial fiber orientation (23, 38), the
generally constant primary diffusion tensor eigenvalue (or
diffusivity) is consistent with a previous report of no significant
difference in myocyte length between transmural LV regions
within several animal species (5). The increases in secondary
and tertiary DTI diffusivities, which may have been due to
reduced restricted diffusion transverse to the myocyte axis, are
also in agreement with past histological studies that reported an
increase in myocyte cross-sectional radius (⬃9.6%) (5) from
the epicardium to the endocardium and a decrease in myocyte
density accompanied by an increase in extracellular volume
fraction (from 0.12 at the epicardium to 0.25 at the endocardium) (27).
Quantitative relationships, both analytic and computer simulation based, between MRI diffusion characteristics and cellular structure have been proposed (26, 43). For example, via
the effective medium theory (40), the water diffusivity (Deff) of
a tissue with cylindrical cells can be related to the cell radius
(␣), membrane permeability (␬), and extracellular volume
fraction (␾) as follows (26)
冉
冊冉 冊
D effceff ⫺ x Dextcext
Dextcext ⫺ x Deffceff
1/2
⫽␾
(2)
where x ⫽ (␬␣Dintcint)/(␬␣ ⫹ Dintcint), ceff ⫽ ␾cext ⫹ (1 ⫺
␾)cint, Dint and Dext are the intrinsic intra- and extracellular
diffusion coefficients, and cint and cext are the intra- and
extracellular water concentrations. With the use of typical
values reported in the literature, ␬ ⫽ 10 ⫻ 10⫺2 mm/s, Dext ⫽
2.5 ⫻ 10⫺3 mm2/s, Dint ⫽ 0.7 ⫻ 10⫺3 mm2/s (21), cext ⫽ 0.9,
cint ⫽ 0.7 (26), and ␣ ⫽ 10.0 ␮m (30) at the epicardium and
11.0 ␮m at endocardium, which corresponds to a 9.6% increase (5), the effective diffusivity transverse to the myocyte
axis (based on the geometric mean of the measured DTI
secondary and tertiary eigenvalues) at the epicardium (0.75 ⫻
10⫺3 mm2/s) and endocardium (0.83 ⫻ 10⫺3 mm2/s) would
correspond to extracellular volume fractions of 0.24 and 0.28,
Table 2. Slopes of transmural FA profiles within different circumferential sectors and longitudinal slices
Slice/Sector
Septal
Posterior
Lateral
Anterior
Mean ⫾ SD
S1
S2
S3
S4
S5
Mean ⫾ SD
⫺0.14
⫺0.11
⫺0.08
⫺0.11
⫺0.15
⫺0.12⫾0.02
⫺0.17
⫺0.26
⫺0.16
⫺0.35
⫺0.35
⫺0.26⫾0.08
⫺0.32
⫺0.22
⫺0.20
⫺0.33
⫺0.38
⫺0.29⫾0.07
⫺0.19
⫺0.18
⫺0.22
⫺0.18
⫺0.09
⫺0.17⫾0.04
⫺0.21⫾0.07
⫺0.19⫾0.06
⫺0.17⫾0.05
⫺0.24⫾0.10
⫺0.24⫾0.12
Each entry (unitless) represents average within sectors at the same location over 4 hearts.
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FA (F ⫽ 36, P ⬍ 10⫺6)*
Z1-Z2
Z1-Z3
Z1-Z4
Z2-Z3
Z2-Z4
Z3-Z4
D1 (F ⫽ 1.4, P ⫽ 0.24)
D2 (F ⫽ 3.5, P ⫽ 0.015)*
Z1-Z2
Z1-Z3
Z1-Z4
Z2-Z3
Z2-Z4
Z3-Z4
D3 (F ⫽ 9.0, P ⫽ 1.0 ⫻ 10⫺5)*
Z1-Z2
Z1-Z3
Z1-Z4
Z2-Z3
Z2-Z4
Z3-Z4
Dav (F ⫽ 1.4, P ⫽ 0.24)
NMTE (F ⫽ 0.13, P ⫽ 0.94)
Transmural Heterogeneity of Diffusion Anisotropy
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Table 3. Intercepts of transmural FA profiles within different circumferential sectors and longitudinal slices
Slice/Sector
Septal
Posterior
Lateral
Anterior
Mean ⫾ SD
S1
S2
S3
S4
S5
Mean ⫾ SD
0.36
0.34
0.34
0.35
0.34
0.35⫾0.01
0.34
0.34
0.35
0.35
0.37
0.35⫾0.01
0.36
0.35
0.35
0.36
0.36
0.35⫾0.01
0.34
0.33
0.35
0.35
0.35
0.34⫾0.01
0.35⫾0.01
0.34⫾0.01
0.35⫾0.00
0.35⫾0.00
0.35⫾0.01
Each entry (unitless) represents average within sectors at the same location over 4 hearts.
Methodological Considerations
Because DTI measurements are sensitive to changes in tissue
microstructure and imaging conditions (particularly signal-tonoise ratio), interpretation of the present results needs to take
into account effects of fixation and image noise on the diffusion anisotropy. Similar to alterations in the relaxation times,
the MRI apparent diffusivity has been found to decrease
significantly as a result of the macromolecular cross-linking
associated with fixation, at least for brain tissues (41, 42).
However, the changes must have been proportional in all
directions (with respect to the tissue structural orientation),
such that the principal or preferred axes of diffusion and the
relative degree of anisotropy (e.g., FA) are preserved (17, 41,
42). Results in the present study are based on the behavior of
FA, an index of anisotropy, and trends of the diffusivity across
the myocardial wall. Consequently, although the individual
diffusivity measurements may have been lowered by fixation,
the observations reported in FA and transmural relative
changes in diffusivity (e.g., higher D2 and D3 in endocardium
than epicardium) likely remain unaffected.
In DTI, it is known that image noise can cause significant
bias, by means of overestimation, in the FA of tissue and that
the degree of bias is disproportionately larger in tissues such as
the myocardium, which have lower intrinsic FA (2, 4, 34).
In the present study, the signal-to-noise ratio was measured and
found not to be significantly different for the inner and outer
halves of the LV in all specimens (data not shown). Moreover,
if image noise were a significant factor, it would have caused
higher artificial inflation of FA in the endocardium, which has
lower intrinsic FA, than in the epicardium and presented only
a situation for false-negative observation of transmural difference. Therefore, although image noise likely impacted the
accuracy of the current FA measurements similar to all DTI
studies, if there is any effect, the observed transmural differences in the FA (i.e., significantly smaller in the endocardium)
and transverse diffusivities are likely reflective of the under-
Table 4. Transition points of transmural FA profiles within different circumferential sectors and longitudinal slices
Slice/Sector
Septal
Posterior
Lateral
Anterior
Mean ⫾ SD
S1
S2
S3
S4
S5
Mean ⫾ SD
0.47
0.46
0.47
0.49
0.60
0.50⫾0.05
0.50
0.45
0.46
0.63
0.46
0.50⫾0.07
0.50
0.44
0.42
0.49
0.48
0.46⫾0.03
0.41
0.50
0.50
0.48
0.48
0.47⫾0.03
0.47⫾0.04
0.46⫾0.02
0.46⫾0.03
0.52⫾0.06
0.50⫾0.06
Each entry (unitless) represents average within sectors at the same location over 4 hearts.
AJP-Heart Circ Physiol • VOL
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respectively, or a 18% increase transmurally. These values are
in general agreement with extracellular volume fractions of
0.26 – 0.28 previously reported for the whole heart (9, 12) but
are somewhat higher than the regional measurement of 0.12 for
the epicardium (27). Although the above-mentioned computations and volume fraction measurements necessarily depend on
the assumptions incorporated (e.g., Dint, Dext, and ␬, which
were based on in vitro measurements and used here only as a
1st approximation) and experimental technique employed, they
demonstrate the plausibility of obtaining quantitative tissue
microstructural information (in this case, extracellular volume
fraction) from scalar DTI measurements.
In addition to differences in the cellular characteristics (e.g.,
myocyte size, density, and extracellular space), a second possible explanation for the transmural heterogeneity of the FA is
the existence of “complex” tissue structure, such as bifurcating
sheet structures in the subendocardium (19). Because of the
greater complexity of these structures (i.e., multiple populations of tissues with different cellular properties, including
fiber or sheet orientations), longer diffusion time is likely
required for water molecules experiencing different subregions
of the tissue to become well mixed. Consequently, along with
reduced FA, a poorer diffusion tensor goodness of fit is also
expected. The results of the NMTE analysis (Fig. 3F) reveal
that the quality of the tensor estimation remains constant across
the ventricular wall. This suggests that the decrease in FA at
the endocardium more likely reflects differences in myocyte
organization than the presence of complex tissue structure.
Throughout the myocardial wall, the average values of the
diffusion tensor eigenvalues, in descending order, are 1.27 ⫾
0.15 for D1, 0.87 ⫾ 0.16 for D2, and 0.68 ⫾ 0.14 ⫻ 10⫺3
mm2/s for D3 (mean ⫾ SD, n ⫽ 1,306,626). The corresponding
Dav is 0.94 ⫾ 0.15 ⫻ 10⫺3 mm2/s, and the mean FA is 0.32 ⫾
0.07. These values are in good agreement with the values
reported previously (8, 13, 15, 25, 38). However, only averaged values have been reported in the literature, because those
values were considered to be uniform throughout the heart.
HETEROGENEITY OF MYOCARDIAL DIFFUSION ANISOTROPY
lying tissue microstructure and represent a lower-limit estimation of the true difference.
Implications for Cardiac Electrophysiological
and Biomechanical Modeling
Summary
Diffusion anisotropy as measured by MR-DTI in the fixed
sheep myocardium remained relatively constant from the epicardium to the midwall and then decreased steadily toward the
endocardium. The transmural location of the transition coincides with the location where myocardial fibers run exactly
circumferentially. There is also a significant difference in the
midwall-endocardium FA slope between circumferential regions of the LV. These results are generally consistent with the
known cellular microstructure from reported histological studAJP-Heart Circ Physiol • VOL
ies of the myocardium. Findings of the present study reinforce
the need to incorporate transmural variations in the myocardial
microstructure in modeling cardiac electrophysiology and biomechanics and suggest that, besides fiber orientation information, additional tissue microstructure parameters such as the
extracellular volume fraction can possibly be inferred from
MR-DTI measurements.
GRANTS
This study was supported by Whitaker Foundation Research Grant RG-010438 and National Institutes of Health Grants P41 RR-005959 (Y. Jiang and
E. W. Hsu), R01-HL-77921 (J. M. Guccione), and R01-HL-63348 (M. B.
Ratcliffe).
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