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MOLECULAR IMAGING (G STRIJKERS)
Contrast-Enhanced T
1
-Mapping MRI for the Assessment
of Myocardial Fibrosis
Wolter L. de Graaf &Katrien Vandoorne &Fatih Arslan &
Klaas Nicolay &Gustav J. Strijkers
Published online: 13 February 2014
#Springer Science+Business Media New York 2014
Abstract Fibrosis is a common feature of heart disease and is
associated with adverse cardiac remodeling and poor clinical
outcome. Because of the lack of routine noninvasive patient-
specific tissue characterization tools, the development of new
treatment strategies for cardiovascular disease specifically
targeting undesired fibrosis in the myocardial wall is slow.
Cardiovascular magnetic resonance imaging has developed
into the gold-standard tool to assess various aspects of myo-
cardial anatomy and function. In recent years, magnetic reso-
nance imaging has also emerged as a promising technique to
fulfill the need for a noninvasive assessment of myocardial
fibrosis through the use of Gd-based contrast agents and the
quantification of the longitudinal relaxation time T
1
. This
paper reviews the current use of T
1
mapping for the assess-
ment of myocardial fibrosis, with particular focus on imaging
techniques and their validation.
Keywords Cardiovascular disease .Coronary heart disease .
Myocardial infarction .Fibrosis .Magnetic resonance
imaging .Gd contrast agent .T
1
relaxation time
Introduction
Cardiovascular disease is the most common cause of death in
the Western World. Because of the aging population, in-
creased survival after ischemic heart disease in Western coun-
tries, and the growing prevalence of diabetes, hypertension,
and coronary disease, the incidence of cardiovascular disease
will most likely increase in the future. Fibrosis in the heart is
characterized by enhanced collagen deposition in the myocar-
dium and, as such, one of the hallmarks of cardiovascular
disease. Fibrotic remodeling by accumulation of collagen is
associated with morphologic changes leading to the reduction
of myocardial compliance. Increased fibrosis is a major deter-
minant of increased myocardial stiffness and diastolic dys-
function. This fibrotic remodeling of the cardiac interstitium
often results in the development of diastolic dysfunction. To
anticipate cardiac dysfunction and monitor response to thera-
py, early detection of myocardial fibrosis, both diffuse and
focal, is an emerging aim in the clinic.
This review gives an overview of cardiovascular magnetic
resonance imaging (MRI) of fibrosis. After a short overview
on the role of the extracellular matrix in the normal heart and
on the different types of fibrosis, we discuss the different ways
to image fibrosis using MRI. Particular focus will be on the
use of T
1
mapping. However, alternative MRI techniques will
be discussed as well.
Extracellular Matrix in the Healthy Heart
The normal mammalian heart consists of a cellular compart-
ment and an extracellular matrix. Cardiac muscle cells,
cardiomyocytes, are one of the major cell types in the heart,
occupying approximately 75 % of the myocardial volume. In
This article is part of the Topical Collection on Molecular Imaging
W. L. de Graaf:K. Vandoorne :K. Nicolay :G. J. Strijkers (*)
Biomedical NMR, Department of Biomedical Engineering,
Eindhoven University of Technology, PO Box 513, 5600 MB
Eindhoven, The Netherlands
e-mail: g.j.strijkers@tue.nl
G. J. Strijkers
Biomedical Engineering and Physics, Academic Medical Center,
University of Amsterdam, Amsterdam, The Netherlands
F. Ar sl an
University Medical Center Utrecht, Utrecht, The Netherlands
Curr Cardiovasc Imaging Rep (2014) 7:9260
DOI 10.1007/s12410-014-9260-6
absolute numbers, cardiomyocytes only comprise 35 % of the
total number of cells in the heart. Yet, approximately 65 % of
the cells in the heart are other cells, such as endothelial cells,
fibroblasts, pericytes, smooth muscle cells, and macrophages
[1]. Cardiac fibroblasts are crucial players in cardiac homeo-
stasis by producing and maintaining the extracellular matrix.
Fibroblasts are essential for damage control and remodeling
after myocardial injury and play a crucial role in the patho-
genesis of cardiac fibrosis [2]. The cardiac interstitium con-
tains a network of extracellular matrix components, providing
well-organized tissue architecture and geometry to the heart
(Fig. 1a)[3]. The interstitium tethers cardiomyocytes and
supports cardiac function by transmitting the cardiomyocyte-
generated force [4].
Fibrosis in Cardiovascular Disease
Basically, 2 forms of fibrosis can be distinguished in cardio-
vascular disease. Interstitial fibrosis refers to the increase in
interstitial volume fraction without a significant loss of
cardiomyocytes (Fig. 1b). In contrast, replacement fibrosis
indicates the deposition of extracellular matrix to replace dead
cardiomyocytes (Fig. 1c)[3–5]. In response to hemodynamic
overload deposition of collagen leads to interstitial fibrosis.
The initial interstitial fibrosis is an adaptive mechanism to
normalize wall stress upon pressure overload, and is associat-
ed with cardiomyocyte hypertrophy to preserve cardiac func-
tion in the short term. Yet, when the pressure overload con-
tinues and becomes chronic, replacement fibrosis follows as
hypertrophied cardiomyocytes go through apoptosis and ne-
crosis. When chronic pressure overload occurs, hypertrophied
cardiomyocytes die because of the increase of collagen sur-
rounding the cells, creating a mismatch between supply and
demand of nutrients.
The etiology of left ventricular hemodynamic pressure
overload is varied and ranges from primary hypertension [4]
to chronic kidney disease [6,7]. Furthermore, age-related
peripheral vascular stiffening enhances the left ventricular
hemodynamic overload [8]. Chronically overloaded hearts
primarily develop cardiomyocyte hypertrophy and enhanced
interstitial fibrosis, leading to a stiffer ventricle and diastolic
dysfunction. The development of interstitial fibrosis is related
with heart failure, increased likelihood of ventricular
Fig. 1 Myocardial fibrosis. aHealthy myocardium consists of a compact
arrangement of cardiomyocytes, endothelial cells, smooth muscle cells,
and myofibroblast. bInterstitial fibrosis is characterized by a progressive
increase in the extracellular space. Myofibroblasts and macrophages have
a principal role in increased production and breakdown of extracellular
matrix components under the influence of various factors. cReplacement
fibrosis or scarring results after myocyte death (eg, because of ischemic
damage or myocarditis)
9260, Page 2 of 12 Curr Cardiovasc Imaging Rep (2014) 7:9260
arrhythmia, and high frequency of sudden cardiac death. In
small animal models, pressure overload is induced by trans-
verse aortic constriction to study interstitial fibrosis [9].
Replacement fibrosis also occurs after an acute myocardial
infarction (MI). An acute MI occurs when a coronary artery
occludes and subsequently the downstream cardiac tissue is
deprived from oxygen, resulting in irreversible loss of
cardiomyocytes. There are several MI risk factors, including
atherosclerosis with high lipid blood levels, diabetes, hyper-
tension, and chronic kidney disease [10]. In addition,
nonischemic dilated cardiomyopathy can also give rise to
replacement fibrosis [11]. Sudden death of a large amount of
cardiomyocytes, accompanied by a severe inflammatory reac-
tion, releases signals to synthesize new matrix [12]. The most
commonly used animal model to study MI and subsequent
replacement fibrosis is ligation of the left coronary artery [9].
Regardless of the inciting cause, fibrosis may also impair
systolic function through separate mechanisms associated
with the activation of matrix–degrading pathways. First, un-
coordinated contraction of cardiomyocyte bundles occurs by
loss of collagen impairing the transduction of single cardio-
myocyte contractions [13], and the synchronization of myo-
cardial excitation-contraction coupling [14]. Second, cardio-
myocyte homeostasis depends upon interaction with the inter-
stitial matrix [15]. Finally, augmented matrix degradation can
cause sliding displacement of cardiomyocytes, decreasing the
number of muscular layers in the ventricles leading to ventric-
ular dilation [16].
Measuring Fibrosis with Contrast-Enhanced T
1
-Mapping
Late gadolinium enhancement (LGE) enables excellent visu-
alization of the extent of myocardial scarring and therefore,
has become an accepted standard to assess infarct size in acute
and chronic MI [17]. Standard low molecular weight gadolin-
ium contrast agents (Gd-chelates) are so-called extracellular
contrast agents, which means that the Gd-chelate is not able to
cross the cellular membrane of healthy cardiomyocytes and is
confined to the vasculature and extravascular extracellular
space. The physiological basis for the late MR signal enhance-
ment in the infarct scar compared with noninfarct myocardium
is an increased distribution volume for the contrast agent,
because of cellular apoptosis and necrosis accompanied by
loss of myocyte membrane integrity in the acute infarct and an
enlarged extracellular space occupied by fibrotic tissue in the
chronic infarct. Also, washout of contrast agent from the scar
may be delayed because of a decreased capillary density.
Experimentally, standard LGE imaging employs injection
of a bolus of Gd-chelate contrast agent and an inversion-
recovery T
1
-weighted sequence to “null”remote healthy myo-
cardium and highlight the infarct scar with significantly re-
duced T
1
relaxation time due delayed presence of Gd. LGE
imaging is not limited to MI but can also be employed to
detect and localize focal scarring associated with nonischemic
cardiomyopathies. However, the technique fails to accurately
depict diffuse myocardial fibrosis since the whole myocardi-
um may become “nulled”in the absence of regional differ-
ences in distribution volume and clearance kinetics. Also, a
quantitative determination of the amount of myocardial fibro-
sis is not possible.
An improvement to the standard LGE technique involves a
quantitative measurement of the T
1
relaxation time after ad-
ministration of the contrast agent. This technique does not rely
on an appropriate choice of the inversion time to achieve
signal contrast but on a quantitative measurement and, there-
fore, also detects an increased interstitial volume when fibro-
sis is found diffusely in the whole myocardium. Nevertheless,
the postcontrast T
1
is determined by a variety of confounding
factors, including the magnetic field strength, the injected
dose, the timing of the measurement, contrast agent clearance
rates, hematocrit levels, and presence of edema [18]. In fact,
precontrast T
1
values of healthy and diseased myocardium
may already significantly differ. Postcontrast quantitative T
1
values alone are, therefore, insufficient to reliably classify
diseased and healthy tissues and unable to provide quantita-
tive numbers on the amount of fibrosis.
The critical step in the development of a quantitative tech-
nique to assess fibrosis in the myocardium is the finding that
the limitations of the single postcontrast T
1
mapping technique
can be overcome by a quantitative comparison of pre- and
postcontrast T
1
values of myocardium and blood to compen-
sate for subject specific variations in precontrast tissue T
1
values, contrast agent clearance rates, and hematocrit levels.
Furthermore, this comparison enables a quantitative calcula-
tion of percentage of extracellular space occupied in the myo-
cardium—the extracellular volume fraction (ECV) [19,20].
The concentration of Gd contrast agent in tissue and blood
can be calculated from a measurement of the difference in the
longitudinal relaxation rate R
1
=1/T
1
pre and postcontrast
agent injection.
ΔR1¼r1C:ð1Þ
Here C denotes the Gd concentration in the myocardium
(tissue and blood) C
myo
or the concentration in the blood
C
blood
under the premise that the relaxivity r
1
of the contrast
agent is equal in tissue and blood, which is a reasonable
assumption for a Gd-based low-molecular weight contrast
agent. A partition coefficient for Gd contrast agent in the
myocardial tissue can be defined as the ratio of the concen-
tration of agent in the myocardium and blood.
λ¼Cmyo=Cblood ¼ΔR1;myo =ΔR1;blood:ð2Þ
The plasma concentration of agent C
plasma
relates to the
blood concentration
Curr Cardiovasc Imaging Rep (2014) 7:9260 Page 3 of 12, 9260
Cblood ¼1–HctðÞCplasma;ð3Þ
where Hct is the blood hematocrit value. Additionally, we
define C
extra
as the extracellular extravascular concentration
of agent.
For the calculation of ECV we assume a steady-state equi-
librium of contrast agent concentrations between the extracel-
lular extravascular space and blood plasma.
Cextra ¼Cplasma ¼Cblood=1–HctðÞ:ð4Þ
In a dynamic situation after bolus contrast agent injection
true steady state equilibrium cannot be realized but the calcu-
lation is still valid as long as contrast agent exchange is faster
than the blood clearance rate. This may be achieved by slow
infusion of contrast agent or measuring later after injection
(typically >15 minutes) when first rapid variations of the
amount of contrast agent in the blood are somewhat equili-
brated [21].
The myocardial contrast agent concentration includes the
blood compartment as well as the extracellular extravascular
space and, thus,
Cmyo ¼vplasmaCplasma þvextraCextra;ð5Þ
with v
plasma
and v
extra
the volume fractions of the plasma and
extracellular extravascular spaces. By substitution of Eqs. 2–4
into Eq. 5we obtain.
λ¼vpþve
=1–HctðÞ¼ECV=1–HctðÞ:ð6Þ
ECV, thus, includes both the extracellular as well as the
intravascular spaces (corrected for hematocrit). Using Eq. 1
we finally obtain.
ECV ¼1–HctðÞΔR1;myo=ΔR1;blood:ð7Þ
T
1
-Mapping Protocols
T
1
mapping MRI results in myocardial signal quantification
on a standardized scale (in ms) rather than an image with
arbitrarily scalable pixel gray values. This increases reproduc-
ibility between studies and reduces sensitivity to sequences
parameters, receiver amplifier settings, and coil sensitivity
profiles. Basically, a T
1
map is made from multiple acquisi-
tions of T
1
-weighted images and fitting the signal intensities to
an MRI sequence model that describes T
1
relaxation. T
1
mapping of the heart is challenging because the T
1
quantifi-
cation protocol has to be accurate for a wide range of pre- and
postcontrast T
1
values, whereas sequence parameters cannot
be chosen at will because of cardiac and respiratory motion
that require ECG triggering, navigators, or breath holds.
A number of acquisition protocols for T
1
mapping of the
heart have been introduced in literature [22–24,25•,26–28].
Most of the protocols are based on a Look-Locker inversion
recovery sequence, with modifications to accommodate ECG
triggering and time-efficient acquisition in the period of 1 or a
few breath holds. The most widely applied protocol is the
MOLLI (modified Look-Locker imaging) approach. The stan-
dard MOLLI sequence is schematically depicted in Fig. 2a.
The basic sequence typically collects 11 images after magne-
tization inversion with different inversion times (TI) in 17
heartbeats. The acquisitions are distributed over 3 runs with
3, 3, and 5 inversion times to cover sufficient points along the
recovery curve. The red and blue lines in Fig. 2a (left) are
Bloch simulations of the magnetization evolution during the
protocol for a short (T
1
=400 ms) and very long (T
1
=1600ms)
longitudinal relaxation time, respectively. Figure 2a (right)
shows the sampled data points (symbols) along the inversion
recovery curve and fits (solid lines) to the equations
Signal intensity ¼A–Be
−TI=T1ð8Þ
and
T1¼T11–B=AðÞ:ð9Þ
Strictly, these equations hold for an imaging readout with an
RF-spoiled gradient echo sequence with low excitation flip
angle [29]. Often an SSFP readout is used, which leads to
errors in the T
1
estimations [30]. Additionally, for the longer T
1
relaxation times the magnetization is not fully recovered at the
time of the next inversion pulse (Inv), which leads to underes-
Fig. 2 Examples of myocardial T
1
mapping techniques. a(left) Modified
Look-Locker imaging(MOLLI) protocol. Elevenimages, indicated 1–11,
are collected after magnetization inversion with different inversion times
(TI) in 17 heartbeats. The acquisitions are distributed over 3 runs with 3,
3, and 5 inversion times. The red and blue curves are Bloch calculations
of the longitudinal magnetization for a short (400 ms) and long (1600 ms)
T
1
relaxation time, respectively. A jump in the curve indicates the location
of image acquisition with a flip angle of 35°. Duration of 1 heartbeat is
1000 ms. (right) Signal intensity (symbols) and relaxation curves fitted
with Eqs. 8and 9(solid lines), resulting in T
1
=401 and 1488 ms. b(left)
Shortened MOLLI (shMOLLI) protocol. The sequence acquires 5, 1, and
1 inversion times over 9 heartbeats. For pixels with short T
1
s (red line,
T
1
=400 ms) all 7 images can be included for T
1
fitting. However, for long
T
1
s (blue line, T
1
=1600 ms) magnetization is not fully recovered after the
first and second inversion runs, and therefore, data points 2 and 3 are
omitted. The protocol, therefore, requires an adaptive fitting algorithm
that automatically rejects data points based on an initial guess of T
1
.
(right) For this example, fitting of T
1
resulting in T
1
=400 and 1505 ms. c
Steady-state RF-spoiled gradient-echo T
1
determination with DESPOT1
analysis. (left) Image acquisition is performed in the steady-state as
function of flip-angle. Red and blue lines indicate Bloch simulations for
T
1
=400 ms and 1600 ms, respectively. (right) Linearization of the signal
according to the DESPOT1 method resulted in T
1
=409 and 1725 ms.
Steady-state is not fully reached for the long T
1
during image acquisition
resulting in an overestimation of the relaxation time
b
9260, Page 4 of 12 Curr Cardiovasc Imaging Rep (2014) 7:9260
Curr Cardiovasc Imaging Rep (2014) 7:9260 Page 5 of 12, 9260
timation of the T
1
relaxation time. For the particular example
in Fig. 2a fittings with Eqs. 2and 3resulted therefore, in T
1
=
401 ms and 1488 ms for the red and blue curves, respectively.
Here, underestimation of long T
1
s results from a combination
of incomplete recovery in between the 3 inversion runs and
violation of the low flip-angle assumption of Eq. 9.
A breath-hold period of 17 heartbeats often cannot be
tolerated by patients with serious heart conditions.
Therefore, shortened versions of the original MOLLI se-
quence have been developed. A shMOLLI (shortened
MOLLI) protocol was developed that covers 5, 1, and 1
inversion times over 9 heartbeats (Fig. 2b). This protocol
requires an adaptive fitting algorithm that rejects data points
for which the magnetization was not recovered sufficiently at
the time point of the next inversion pulse (points 2 and 3 for
the blue curve in Fig. 2b). In the specific example of Fig. 2b
fitting of all 7 data points for the short T
1
relaxation time (blue
line) resulted in T
1
=400 ms, whereas fitting of the long
relaxation time from only 5 points resulted in T
1
=1505 ms.
This is still a considerable underestimation of the input T
1
=
1600 ms, resulting from the rather high excitation flip-angle of
35
o
that was used in the simulation, at which point the cor-
rection in Eq. 9partly fails.
An alternative approach to T
1
quantification involves RF-
spoiled steady-state gradient echo imaging with a DESPOT1
(driven equilibrium single-pulse observation of T
1
)analysis
[31]. DESPOT1 is based on the flip-angle dependence of the
steady-state signal intensity to calculate T
1
and proton density.
The acquisition scheme is schematically depicted in Fig. 2c.
Imaging is done in the steady state at various flip-angles (3°,
5°, 8°, and 12° for this particular example). Next, the flip-
angle dependence of the steady-state signal intensity M
ss
is
linearized by dividing M
ss
with the sine and tangent of the flip-
angle (Fig. 2c, right). From the slope m of the linear fit T
1
is
derived using
T1¼−TR=ln mðÞ ð10Þ
with TR the repetition time. DESPOT1 has been primarily
applied for T
1
mapping of the brain [32,33]. Application of the
technique to the heart is more challenging because steady-state
imaging has to be combined with cardiac and/or respiratory
triggering. Triggering issues were solved by Coolen et al who
introduced the technique for contrast-enhanced T
1
mapping of
murine MI using a self-gated steady-state sequence [26,34].
Validation
The T
1
mapping method was initially utilized to determine the
distribution volume of Gd-based contrast agents in healthy
and infarct myocardium [19]. Basically, Gd is an extracellular
contrast agent, ie, it distributes in the intravascular and
extracellular space in healthy myocardium. However, when
cell membrane integrity is compromised Gd spreads into the
intravascular, extracellular, and intracellular space. Expansion
of the extracellular space accompanied by fibrosis is a com-
mon feature of many cardiac pathologic conditions. A mea-
surement of the ECV therefore, provides an indirect readout of
fibrosis.
ECV has been shown to correlate with diffuse myocardial
fibrosis with histologic validation in various studies [24,35••,
36,37]. Sibley et al provided a direct validation of the corre-
lation between the contrast-enhanced T
1
relaxation time and
myocardial collagen content from endomyocardial biopsies in
a cohort of patients with a broad spectrum of cardiomyopa-
thies [35••]. In Figure 3a postcontrast T
1
maps next to Masson
trichrome stained sections of 2 individuals are shown. The top
row is from a heart with normal myocardium and the bottom
row from one with significant fibrosis. Postcontrast T
1
was
significantly lower for the fibrotic myocardium. A linear
regression analysis of the quantitative T
1
time vs the logarithm
of the myocardial fibrosis percentage yielded significant cor-
relation (Fig. 3b). In view of the expected linear relation of
R
1
=1/T
1
vs ECV (Eq. 7) it would have been insightful to
correlate R
1
with the fibrosis percentage rather than T
1
to
validate whether ECV relates to the amount of fibrosis in a
linear fashion. Iles et al observed a strong linear correlation
between post-contrast T
1
and myocardial collagen content in
subjects after cardiac transplantation [24]. A strong linear
correlation between ECV and collagen content was found by
Flett et al in a cohort of patients undergoing aortic valve
replacement for aortic stenosis or myectomy in hypertrophic
cardiomyopathy [36]. On the other hand, only a weak to
moderate correlation between ECV and myocardial collagen
content was found in a hypertensive rat model of myocardial
fibrosis [37].
Clinical Studies
There is considerable clinical value for novel imaging tech-
niques capable of imaging fibrosis, since fibrosis is a hallmark
of various diseases affecting the myocardium. Furthermore,
repeated and accurate assessment of cardiac fibrosis using
traditional biopsy methods is problematic and not without
risk. Recent clinical interest in T
1
mapping involves the as-
sessment of fibrotic scarring after MI [38–41], and diffuse
fibrosis in various nonischemic cardiomyopathies including
aortic regurgitation [42]orstenosis[40,43], chronic heart
failure [24], hypertrophic [40] and dilated cardiomyopathy
[44,45], because of chemotherapeutic cardiotoxicity [46,
47], and atrial fibrillation [48]. Moreover, T
1
mapping finds
application in the assessment of inflammation in cardiac am-
yloidosis [23,40,49] and lipid depositions in Anderson-Fabry
disease [50].
9260, Page 6 of 12 Curr Cardiovasc Imaging Rep (2014) 7:9260
Figure 4illustrates the use of contrast enhanced T
1
-map-
ping for the assessment of fibrosis in several cardiomyopa-
thies. The figure is taken from a large study by Kellman et al
[51••], which included a group of subjects with normal find-
ings and patients with chronic MI, hypertrophic cardiomyop-
athy (HCM), or nonischemic dilated cardiomyopathy (DCM),
acute myocarditis, amyloidosis, and systemic capillary leak
syndrome (SCLS). Figure 4a shows representative pre- and
post-contrast T
1
maps, LGE and ECV maps, selected from the
chronic MI, acute myocarditis, and HCM patients, with focal
changes on LGE images. For these cases ECV maps were in
good agreement with LGE. Figure 4b shows cases from the
DCM, amyloidosis, and SCLS patients, with normal LGE for
DCM, amyloidosis and SLCS, and 1 amyloidosis case with
patchy LGE (2
nd
column). In these more diffuse cases, it is
considerably more challenging to differentiate normal from
affected myocardium on the basis of LGE alone. Quantitative
maps however clearly indicated disease-related changes in
ECV. The mean ECV of the normal subjects was in the range
of 20 %–30 %, whereas significant higher values in the range
of 40 %–60 % were found in the various patient groups, up to
about 70 % in infarcts. This study shows that ECV mapping
can quantitatively assess myocardial tissue characteristics for
various cardiomyopathies, including those, unlike LGE, that
lead to diffuse changes in tissue composition.
Alternative MR Imaging Techniques
Apart from the above-outlined methods to image myocardial
fibrosis through quantification of ECV via MRI contrast-
enhanced T
1
mapping, alternative techniques have been ex-
plored that aim at a more direct visualization of the extracel-
lular matrix constituents through target specific imaging (mo-
lecular imaging) of biomarkers and cells involved in fibrosis,
eg, collagen type-1, matrix metalloproteinases (MMPs),
integrins, angiotensin converting enzyme (ACE), and macro-
phages. In addition, MRI T
2
and T
2
*
mapping have been
suggested as indicators for the presence of fibrotic tissue in
cases for which contrast-enhanced imaging could be incon-
clusive. In Figure 5a few examples are shown of other MRI
approaches to image myocardial fibrosis.
Collagen type-1 is the main constituent of the extracellular
matrix and is most upregulated in the fibrotic myocardium. A
number of groups have developed collagen-targeted contrast
agents to specifically and directly image the presence of
fibrotic tissue. Caravan et al developed an MRI contrast agent,
consisting of a collagen type-1 binding peptide, identified by a
phage-display method, conjugated with 3 Gd-DTPA moieties
[52,53]. Figure 5a shows MR images from a preclinical
validation of this contrast agent in a MI mouse model. The
left column depicts black-blood T
2
-weighted images, in which
the myocardial scar is indiscernible. Pre- and postcontrast
enhanced images were recorded using an inversion recovery
technique to null remote myocardium. For the top row the
specific collagen-binding MRI contrast was used, showing a
bright enhancement in the area of the infarct (indicated by the
red arrow) 40 minutes after injection. No such enhancement
was observed when using a nonspecific control peptide (bot-
tom row). The bacterial protein CNA35 was shown to bind
with high affinity to collagen type-1 [54]. Paramagnetic Gd-
containing liposomes and micelles were conjugated with
Fig. 3 Correlation of post-contrast MRI T
1
values with diffuse fibrosis
from biopsies. a(left) Long-axis cardiac MR images with left ventricular
wall color coded for T
1
. The top image is from a heart with histologically
normal appearing myocardium (right), whereas the bottom image from a
patient with significant interstitial fibrosis, evidenced by histologic
analysis of endomyocardial biopsies. bCorrelation between post-contrast
T
1
time and myocardial fibrosis percentage. Reproduced with permission
Sibley CT, Noureldin RA, Gai N, Nacif MS, Liu S, Turkbey EB, et al.
Radiology. 2012;265:724–32 [35••]
Curr Cardiovasc Imaging Rep (2014) 7:9260 Page 7 of 12, 9260
CNA35 for target specific MR imaging of collagen in athero-
sclerosis and aortic aneurisms [55–57]. Collagen type-1 was
also exploited as a target for molecular imaging of fibrosis
using SPECT with a Tc-99 m-labelled peptide [58]. The
nuclear imaging techniques offer a sensitive readout of sparse
epitopes involved in the fibrotic pathways, including probes
for MMPs [59–61], angiogenesis [62–64], as well as angio-
tensin and ACE [65–67].
The use of contrast-enhanced MRI T
1
-mapping or appli-
cation of molecular imaging methods to address myocardial
fibrosis requires an intravenous injection of a contrast agent,
which may prohibit application of these techniques to heart-
failure patients with renal insufficiencies and poor contrast
agent blood clearance kinetics, because of toxicity hazards.
This has motivated the search for MRI methods which do not
rely on the use of a contrast agent to image collagen in the
myocardium. Such a direct MRI measurement of collagen
could be enabled by a quantification of the myocardial T
2
*
or
T
2
relaxation times, as exemplified in Fig. 5b-c. The MRI
signal of collagen-rich tissue originates to a large extent from
the hydration water molecules that are weakly bound to the
collagen helical structure. These water molecules are charac-
terized by a very short T
2
relaxation time that precludes
direct detection by traditional MRI sequences. De Jong
et al have employed an ultrashort echo time (UTE) imaging
technique to suppress long T
2
tissue components and high-
light collagenous tissue with short T
2
[68]. The technique
was validated ex-vivo in a MI rat model as illustrated in
Fig. 5B. Further in vivo validation of the UTE technique was
performed by van Nierop et al in a MI mouse model of
replacement fibrosis and a mouse model heart failure with
diffuse fibrosis [69].
The fast T
2
relaxing water molecules bound to collagen
are in exchange with bulk tissue water and, therefore, their
presence can also be noticed in the longer T
2
relaxing
components as was demonstrated by Bun et al in a mouse
model of diffuse myocardial fibrosis in diabetic mice [70].
Figure 5c shows 2 histologic slices stained for collagen by
picrosirius red from a control mouse and a mouse with
diabetic cardiomyopathy with extensive diffuse fibrosis.
The graph below shows the excellent correlation between
collagen fractional area from histology and the in-vivo T
2
relaxation time of the myocardium. T
2
*
mapping was
employed by Aguor et al in a MI mouse model [71].
Although no quantitative comparison was made with histol-
ogy, an excellent visual correlation was found between the
location of the fibrotic scar in the chronic phase (days 7 and
28) after MI and areas of decreased T
2
*
. Particularly in the
chronic scar, for which LGE imaging was rather inconclu-
sive, T
2
*
mapping helped to identify location and extent of
the infarct. Recently, a steady state self-gated cardiac cine
imaging sequence was developed, in which the presence of
fibrosis was encoded into the myocardial signal intensity by
selective saturation of collagen magnetization [72].
Fig. 4 Pre- and postcontrast T
1
maps, LGE, and ECV in myocardium of
patients with various cardiomyopathies. aChronic MI,acute myocarditis,
and hypertrophic cardiomyopathy with focal abnormalities in LGE. For
these cases ECV maps were in good agreement with LGE. bCases with
cardiomyopathy (DCM), acute myocarditis, amyloidosis, and systemic
capillary leak syndrome (SCLS), with normal LGE for DCM,
amyloidosis, and SLCS, and 1 amyloidosis case with patchy LGE (2nd
column). In these cases LGE alone was inconclusive whereas quantitative
ECV maps clearly indicated disease-related changes in ECV. Reproduced
with permission Kellman P, Wilson JR, Xue H, Bandettini WP, Shanbhag
SM, Druey KM, et al. J Cardiovasc Magn Reson. 2012;14:64 [51••]
9260, Page 8 of 12 Curr Cardiovasc Imaging Rep (2014) 7:9260
Conclusions
Fibrosis is a general hallmark of heart disease associated with
decline in heart function, adverse cardiac remodeling, and
poor clinical outcome. The introduction of emerging therapies
for cardiovascular disease that target the myocardial wall is
hampered by the lack of routine noninvasive imaging tools to
visualize the amount and distribution of fibrotic tissue com-
ponents. A number of cardiovascular MRI techniques have
been developed in recent years, which may fulfill this need for
specific and noninvasive imaging of myocardial fibrosis. The
most promising technique thus far seems contrast-enhanced
Fig. 5 Alternative cardiovascular MRI techniques for imaging of myo-
cardial fibrosis. aApplication of a collagen-targeted contrast agent in a
MI mouse model. The left column depicts black-blood T
2
-weighted
images, in which the myocardial scar is indiscernible. Pre- and
postcontrast enhanced images were recorded using an inversion recovery
technique to null remote myocardium. For the top row the specific
collagen-binding MRI contrast agent was used, showing a bright en-
hancement in the area of the infarction (indicated by the red a rrow)
40 min after injection. No such enhancement was observed when using
a nonspecific control peptide (bottom row). bThe use of an ultrashort
echo time subtraction (ΔUTE) imaging technique to suppress long T
2
tissue components and highlight collagenous tissue with short T
2
in a MI
rat model. ΔUTE and histology with picrosirius red staining for collagen
were in excellent agreement. cCorrelation of quantitative T
2
values with
amount of interstitial fibrosis, determined by picrosirius red histology, in a
mouse model of diabetic cardiomyopathy. dT
2
*
mapping of the mouse
myocardium in the acute and chronic phase after induction of MI. (left)
Anatomic gradient-echo images. (right) Myocardial wall color-coded for
T
2
*
. Chronic infarcts are characterized by low T
2
*
.Reproducedwith
permissions from: Caravan P, Das B, Dumas S, Epstein FH, Helm PA,
Jacques V, et al. Angew Chem Int Ed Engl. 2008;46:8171–3[52]; de Jong
S, Zwanenburg JJ, Visser F, van der Nagel R, van Rijen HV, Vos MA,
et al. J Mol Cell Cardiol. 2011;1–6[68]; Bun S-S, Kober F, Jacquier A,
Espinosa L, Kalifa J, Bonzi M-F, et al. Invest Radiol. 2012;47:319–23
[70]; Aguor ENE, Arslan F, van de Kolk CWA, Nederhoff MGJ,
Doevendans PA, van Echteld CJA, et al. Magn Reson Mater Phy.
2012;25:369–79 [71]
Curr Cardiovasc Imaging Rep (2014) 7:9260 Page 9 of 12, 9260
T
1
-mapping, which enables quantification of the extracellular
volume fraction in the diseased myocardium. Alternative
techniques, using either endogenous contrast mechanisms or
targeted contrast agents, are explored for direct imaging of
collagen in fibrotic myocardium.
Future challenges lie in the translation of these emerging
fibrosis-imaging techniques to clinical routine, which needs
more research and clinical studies to address robustness of the
protocols, accuracy, and reproducibility, as well as demonstra-
tion of added value for patient management and clinical
outcome.
Compliance with Ethics Guidelines
Conflict of Interest Wolter L. de Graaf declares that he has no conflict
of interest. Katrien Vandoorne declares that she has no conflict of interest.
Fatih Arslan declares that he has no conflict of interest. Klaas Nicolay
declares that he has no conflict of interest. Gustav J. Strijkers declares that
he has no conflict of interest.
Human and Animal Rights and Informed Consent This article does
not contain any studies with human or animal subjects performed by any
of the authors.
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