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Equilibrium Contrast Cardiovascular Magnetic Resonance for the Measurement
of Diffuse Myocardial Fibrosis: Preliminary Validation in Humans
Andrew S. Flett, Martin P. Hayward, Michael T. Ashworth, Michael S. Hansen,
Andrew M. Taylor, Perry M. Elliott, Christopher McGregor and James C. Moon
Circulation 2010;122;138-144; originally published online Jun 28, 2010;
DOI: 10.1161/CIRCULATIONAHA.109.930636
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Imaging
Equilibrium Contrast Cardiovascular Magnetic Resonance
for the Measurement of Diffuse Myocardial Fibrosis
Preliminary Validation in Humans
Andrew S. Flett, MB, BS, BSc; Martin P. Hayward, MBBS, BSc, MS;
Michael T. Ashworth, MD; Michael S. Hansen, PhD; Andrew M. Taylor, MD;
Perry M. Elliott, MB, BS, MD; Christopher McGregor, MD; James C. Moon, MB, BCh, MD
Background—Diffuse myocardial fibrosis is a final end point in most cardiac diseases. It is missed by the cardiovascular
magnetic resonance (CMR) late gadolinium enhancement technique. Currently, quantifying diffuse myocardial fibrosis
requires invasive biopsy, with inherent risk and sampling error. We have developed a robust and noninvasive technique,
equilibrium contrast CMR (EQ–CMR) to quantify diffuse fibrosis and have validated it against the current gold standard
of surgical myocardial biopsy.
Methods and Results—The 3 principles of EQ–CMR are a bolus of extracellular gadolinium contrast followed by
continuous infusion to achieve equilibrium; a blood sample to measure blood volume of distribution (1⫺hematocrit);
and CMR to measure pre- and postequilibrium T1 (with heart rate correction). The myocardial volume of distribution
is calculated, reflecting diffuse myocardial fibrosis. Clinical validation occurred in patients undergoing aortic valve
replacement for aortic stenosis or myectomy in hypertrophic cardiomyopathy (n⫽18 and n⫽8, respectively). Surgical
biopsies were analyzed for picrosirius red fibrosis quantification on histology. The mean histological fibrosis was
20.5⫾11% in aortic stenosis and 17.1⫾7.4% in hypertrophic cardiomyopathy. EQ–CMR correlated strongly with
biopsy histological fibrosis: aortic stenosis, r2⫽0.86, Kendall Tau coefficient (T)⫽0.71, P⬍0.001; hypertrophic
cardiomyopathy, r2⫽0.62, T⫽0.52, P⫽0.08; combined r2⫽0.80, T⫽0.67, P⬍0.001.
Conclusions—We have developed and validated a new technique, EQ–CMR, to measure diffuse myocardial fibrosis as an
add-on to a standard CMR scan, which allows for the noninvasive quantification of the diffuse fibrosis burden in
myocardial diseases. (Circulation. 2010;122:138-144.)
Key Words: magnetic resonance imaging 䡲 cardiomyopathy 䡲 imaging 䡲 endomyocardial fibrosis 䡲 collagen
F
ibrosis is a final common end point in virtually all pathological processes in human organs and tissues. In the heart,
focal fibrosis (scar) as a result of myocardial infarction is the
leading cause of death and heart failure in the world.1 Cardiovascular magnetic resonance (CMR) using the late gadolinium
enhancement (LGE) contrast technique is the gold standard
method for its assessment.2,3 Focal fibrosis also occurs in other
diseases, including cardiomyopathy,4 myocarditis,5 and infiltrative diseases.6 Scar leads to an increased volume of distribution
for gadolinium and slower contrast kinetics,7 leading to late
enhancement of scar by CMR.
Clinical Perspective on p 144
Diffuse myocardial fibrosis is a covert process that occurs
as a part of normal aging.8 –10 It is accelerated in diseases such
as hypertension, aortic stenosis, and cardiomyopathy,11⫺13
where it contributes to breathlessness, heart failure, and
arrhythmia.14 –16 Unlike scar, however, it may be reversible
and is a treatment target.17,18 Currently, the only method to
quantify diffuse fibrosis is invasive biopsy, which carries
significant morbidity and is prone to sampling error.19 The
LGE technique cannot be used to visualize diffuse fibrosis
because “normal” myocardium with diffuse fibrosis is
“nulled” to highlight focal scar, thereby losing all information of any background interstitial expansion. Recently,
attempts to quantify diffuse fibrosis with CMR have been
made, but they have required complex kinetic modeling
and have not definitively excluded confounding factors
such as heart rate, body composition, and renal clearance
variability. Histological validation, where present, has
Received December 9, 2009; accepted May 14, 2010.
From the Heart Hospital (A.S.F., M.P.H., P.M.E., C.M., J.C.M.), University College London Hospitals National Health Service Trust; Department of
Medicine (A.S.F., P.M.E., C.M., J.C.M.), University College London; Department of Histopathology (M.T.A.), Great Ormond Street Hospital for
Children National Health Service Trust; Cardiovascular Unit (M.S.H., A.M.T.), University College London Institute of Child Health; and Great Ormond
Street Hospital for Children (M.S.H., A.M.T.), London, United Kingdom.
The online-only Data Supplement is available with this article at http://circ.ahajournals.org/cgi/content/full/CIRCULATIONAHA.109.930636/DC1.
Correspondence to Dr James Moon, The Heart Hospital, 16 –18 Westmoreland St, London W1G 8PH, United Kingdom. E-mail
[email protected]
© 2010 American Heart Association, Inc.
Circulation is available at http://circ.ahajournals.org
DOI: 10.1161/CIRCULATIONAHA.109.930636
138
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State University--Columbus on August 6, 2010
Flett et al
EQ–CMR for Diffuse Myocardial Fibrosis
139
Figure 1. Schematic of the CMR protocol.
been limited and predominantly performed in animals20
and ex vivo tissue.21⫺23
In this study, we describe a potentially clinically applicable, robust, noninvasive method to quantify diffuse myocardial fibrosis, equilibrium contrast CMR (EQ–CMR), which
we have prospectively validated against the current gold
standard of surgical myocardial biopsy collagen volume
fraction (CVF) quantification in patients with aortic stenosis
and hypertrophic cardiomyopathy undergoing surgery. This
method is based on 3 elements: a bolus of the extracellular
contrast agent gadolinium (Gd-DTPA) followed by continuous infusion to achieve blood:myocardial contrast equilibrium; a blood test to measure blood contrast volume of
distribution; and CMR before and after contrast equilibrium
to measure changes in tissue signal (T1 measurement with
heart rate correction; see Methods and online-only Data
Supplement). This allows for the calculation of the myocardial contrast volume of distribution (Vd(m)), which closely
reflects the amount of fibrosis because collagen is aqueous
and Gd-DTPA is an extracellular tracer that can occupy this
space freely.23
Methods
Technique: Theory
Gd–DTPA is a magnetic resonance extracellular contrast agent that
potently shortens T1. We measured the change in T1 before and after
a steady-state infusion of Gd-DTPA. This is given by the following
equation:
(1/T1)post⫽(1/T1)pre⫹(1/T1)Gd-DTPA
where
(1/T1)Gd-DTPA⫽R1[Gd-DTPA]
post⫽measured T1 after contrast, pre⫽T1 before contrast, R1⫽T1
relaxivity of Gd-DTPA (known).
At contrast equilibrium, extracellular [Gd-DTPA] is the same in
blood and myocardium. The volume of distribution in blood (Vd(b))
is known, so Vd(m) is as follows23,24:
(1/T1)myo.post–(1/T1)myo.pre
Vd(m)⫽(1⫺hematocrit)⫻
(1/T1)blood.post–(1/T1)blood.pre
Achieving Contrast Equilibrium
Contrast equilibrium was achieved by primed infusion (a loading
bolus followed by a slow continuous infusion). The induction of an
early steady state was optimized in preliminary work by iteration of
infusion rate and timing, with confirmation in 8 study patients and 8
normal volunteers, who remained in the scanner for the duration of
the infusion. For rapid within-subject T1 measurement, a TI (time to
inversion) scout sequence (steady-state free precession, TR⫽3 ms,
TE⫽1.27 ms, slice thickness 8 mm, Flip angle 30°, TI range [105 –
the RR interval] phases ⬎14, centric reordering of phase encoding)
in the transverse plane was used to measure TI⬘ (TI prime, the TI
without heart rate or readout correction [ie, a reliable reflection of
intrasubject T1 variation over time], but confounded by the heart
rate, so unsuitable for intersubject comparison) repeated every 5
minutes. Steady state was defined as occurring when the variation in
TI⬘ on serial measurements within an individual was within 5% of
the final 10 minutes of TI⬘ measurements.
Clinical Validation
All research was carried out at Great Ormond Street Hospital for
Children and University College London Hospitals, London, United
Kingdom, between October 2008 and July 2009. An ethics committee of the UK National Research Ethics Service approved the study,
and all patients and volunteers gave informed consent conforming to
the declaration of Helsinki (V revision, 2000). We validated the in
vivo measurements against human operative myocardial biopsy in
patients with aortic stenosis. Consecutive preoperative patients were
invited to participate, unless they had uncontrolled tachyarrhythmia,
a contraindication to CMR, or severely impaired renal function
(glomerular filtration rate ⬍30 mL/min). A second disease model
was also studied: hypertrophic cardiomyopathy with outflow tract
obstruction requiring myectomy. The LGE images were reported by
2 experienced operators, and patients with LGE (by visual inspection) in an area that was likely to be involved in the myectomy,
biopsy site, or T1 measurement region of interest (n⫽5) were
excluded (as prespecified) from analysis. Blood samples were taken
at the time of CMR to measure Vd(b).
CMR Protocol
The CMR protocol is outlined in Figure 1. CMR was performed on
a 1.5T magnet (Avanto, Siemens Medical Solutions). Within a
standard clinical scan (Pilots, transverse black blood images, volumes, aortic valve view with flow maps, and LGE imaging), a T1
measurement sequence was performed precontrast (8 breath-holds,
details below). After a bolus of Gadoteric acid (0.1 mmol/kg,
Dotarem; Guerbet SA) and standard LGE imaging, the patient was
removed from the scanner. We aimed to achieve contrast equilibrium
within 1 hour using a 0.1 mmol/kg Gd-DTPA bolus (Dotarem;
Guerbet), followed by a 15-minute pause, then an infusion at a rate
of 0.0011 mmol/kg/min (equivalent to 0.1 mmol/kg over 90 minutes). At any time between 45 and 80 minutes after the bolus, the
patient was returned to the scanner and the T1 measurement repeated
(with repiloting, a total of 9 breath-holds). Some patients (n⫽8;
normal volunteers, n⫽8) remained in the scanner to test contrast
equilibrium, and some (n⫽22) had the T1 measurements performed
twice to assess repeatability.
T1 Measurement
The T1 measurement used a standard LGE sequence. This is a
multi– breath-hold, spoiled gradient echo inversion recovery (IR)
sequence with the following parameters: slice thickness 8 mm, TR
9.8 ms, TE⫽4.6 ms, ␣⫽21°, field of view 340⫻220 mm (transverse
plane), sampled matrix size 256⫻105, 21 k–space lines acquired
every other RR interval (21 segments with linear reordered phase
encoding), spatial resolution 1.3⫻2.1⫻8 mm, no parallel imaging.
T1 measurement was performed before and after equilibrium contrast in a single transverse slice in a single phase using increasing
inversion times (TI) per breath-hold of 140 ms, then 200 to 800 ms
in 100-ms increments (Figure 2). Regions of interest were drawn in
the blood and in the septum at a point that was likely to encompass
the biopsy/myectomy site. Mean signal intensities were plotted with
restoration of phase (performed manually by making all points to the
left of the magnitude minimum negative), and a curve-fitting
technique was used to find the null point: TI⬘. A heart rate correction
algorithm corrected for incomplete longitudinal recovery, and phantom work demonstrated that the combination of low flip angle, short
readout, and no parallel imaging constrained readout-related deviation of the derived T1 compared with T1 relaxometry to ⬍5%
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Figure 2. Measuring Vd(m) with CMR. The T1 measurement technique uses 7 CMR breath-hold images, each with an increasing inversion time. The signal intensity of a region of interest is plotted with the phase restored to the magnitude measurement, giving an inversion recovery curve and the tissue TI⬘. This is then corrected for heart rate and the tissue T1 derived. This is performed before and
after contrast, and the ratio of the change in myocardial:blood T1 multiplied by the Vd(b) (1⫺hematocrit) gives the Vd(m).
(online-only Data Supplement). Key factors used in the methodology
are as follows: (1) the use of null points, which are coil location and
scanner image scaling independent; (2) pre- and postscanning with a
single change: equilibrium contrast (no significant heart rate change
pre- to postcontrast [mean RR interval 875⫾220 ms versus 901⫾198
ms], meticulous isocentering and reimporting of the prescan sequence), and (3) the use of the blood:myocardial ratio such that any
systematic changes affecting both tissue signals may affect their
signal ratio less.
Histology
For histological analysis, an intraoperative deep myocardial biopsy
(Tru-Cut needle) was taken in aortic stenosis (from the basal septum
in the outflow tract with guidance from author A.S.F.), and the
myectomy specimen was used in hypertrophic cardiomyopathy.
Samples were fixed immediately in 10% buffered formalin, embedded in paraffin, and stained with picrosirius red. High-power
magnification (⫻200) digital images excluding subendocardial or
perivascular areas underwent automated image analysis (macro
written in ImageJ26). A combination of SD from mean signal and
isodata automatic thresholding derived the collagen area, expressed
as a percentage of total myocardial area, excluding fixation artifact.
On average, 12 high-power fields were assessed per biopsy, and the
mean percent fibrosis and fibrosis heterogeneity (coefficient of
variation between fields) were obtained.
Data Analysis and Statistics
All CMR studies were performed before the intracardiac biopsy. All
data were analyzed in a blinded fashion, with independent analysis of
the CMR data (A.S.F., J.C.M.) and histology (M.A.). Interstudy
repeatability for the CMR measurement of T1 and the CVF measurement was assessed by calculating the coefficient of variability
(equal to the SD of the difference between 2 measurements over the
mean of the 2 measurements, expressed as a percentage) as well as
intraclass correlation coefficient (ICC). Correlation was assessed
using Kendall’s test. Analyses were performed in SPSS version 15.
Results
Achieving Contrast Equilibrium
In the subset of patients (n⫽8; normal volunteers, n⫽8) who
remained in the scanner during equilibration, contrast equilibrium (Figure 3) was achieved within 30 and 45 minutes of
the contrast bolus in 90% and 100% of subjects, respectively.
The mean time to contrast equilibrium for myocardium,
blood, and their ratio were 19⫾8, 26⫾10 and 20⫾8 minutes,
respectively. We incorporated a margin for error. The mean
length of infusion was 40⫾7.9 minutes, the time for the
second scan acquisition (9 breath-holds) was 5 minutes⫾42
seconds, and the total Gd-DTPA contrast dose was 0.14⫾
0.009 mmol/kg.
Myocardial Biopsy
All biopsies were uneventful. The mean histological CVF was
20.5% in aortic stenosis (intersubject range 6% to 39.8%,
SD⫽11.0, n⫽18), and 17.1% in hypertrophic cardiomyopathy
(intersubject range 10.4% to 30.6%, SD⫽7.37, n⫽8) (Figure 4).
EQ–CMR Measurement of Fibrosis
In this validation study, fibrosis was quantified in the basal
septum at a point that was likely to encompass the cardiac
biopsy/myectomy. Of 31 patients, 19 (11 aortic stenosis and
8 hypertrophic cardiomyopathy) patients had focal fibrosis
detected as LGE. In 5 patients, this was in the potential area
of biopsy and, as prespecified, these patients were excluded
from further analysis (Figure 5). In the remaining 26 patients,
Vd(m) measured by EQ–CMR correlated strongly with CVF
in aortic stenosis and the combined population: r2⫽0.86,
Kendall’s Tau coefficient (T)⫽0.71, P⬍0.001, and r2⫽0.80,
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Flett et al
EQ–CMR for Diffuse Myocardial Fibrosis
141
Figure 3. Blood and myocardial TI⬘ after a contrast bolus or bolus plus infusion. Graph demonstrating the effects of a contrast bolus on
blood and myocardial TI⬘ (the measured TI without heart rate correction, using a TI scout SSFP sequence) in 2 different subjects without continuous infusion (left), and the steady state achieved with the addition of a continuous infusion (right). TI⬘ is directly related to
the T1 within an individual and therefore can map contrast-related T1 changes over time, but is subject to confounders such as heart
rate and readout effects and so cannot be used for interindividual comparisons.
T⫽0.67, P⬍0.001, respectively (Figure 6). In hypertrophic
cardiomyopathy the correlation approached statistical significance: r2⫽0.62, T⫽0.52, P⫽0.08. The linear correlation
equation for this relation was CVF%⫽197⫻Vd(m)–36.
Measurement Repeatability
In a subset of patients (n⫽22), CMR measurement and
analysis were repeated. Intrastudy CMR reproducibility was
1%, SD ⬍1% (ICC⫽0.969). For CVF assessment, automated
image analysis reproducibility was 5% (ICC⫽0.989); however, within the same biopsy, CVF extent was not uniform
between high-power fields, with a mean normalized (to
CVF%) SD of 37% in aortic stenosis and 41% in hypertrophic cardiomyopathy across an average of 12 high-power
fields per biopsy.
Discussion
In this study, we have developed and validated a novel
technique, EC–CMR, to measure diffuse myocardial fibrosis,
an important parameter previously only quantifiable with
cardiac biopsy. In aortic stenosis, there is a strong correlation
between EQ–CMR and histological biopsy CVF, which
directly reflects diffuse fibrosis. EQ–CMR is potentially
clinically applicable, adding only 10 minutes of scan time to
a conventional CMR, and uses existing technologies (standard clinical contrast dose [0.2 mmol/kg], standard sequences, and standard scanner). The patient spends additional
time in the department (30 to 90 minutes) during the
continuous infusion, but the flexibility in timing of the
postinfusion scan means this can be easily incorporated into
clinical workflow.
In aortic stenosis patients, the extent and range of diffuse
fibrosis was broad: 6% to 40% of total myocardium. In this
condition, as in other diseases, evidence suggests that the
extent of fibrosis is an important determinant of outcome and
may explain why valve stenosis severity and hemodynamic
parameters alone only partially explain symptoms and outcome.27–29 Diffuse fibrosis is an important clinical parameter
and is associated with worsening ventricular systolic and
diastolic function and adverse remodeling. More extensive
fibrosis is associated with advanced heart failure, regardless
of its cause. It is also a potentially reversible phenomenon,
and several therapies seem to exert their beneficial effects via
myocardial fibrosis regulation.14 The correlation in aortic
stenosis was stronger than that found in hypertrophic cardiomyopathy (r2 0.86 versus 0.62). This was an expected
finding, as fibrosis in hypertrophic cardiomyopathy is thought
to be less diffuse in nature than fibrosis in our primary disease
model, aortic stenosis.30,31
Other noninvasive measures of diffuse fibrosis have limitations: Blood biomarkers are relatively nonspecific because
collagen degradation products may arise in other tissues, and
levels are influenced by clearance variability. Echocardiog-
Figure 4. Histology in 3 biopsies from aortic stenosis patients. This demonstrates the range of fibrosis in aortic stenosis. Red is collagen (fibrosis), and the yellow counter stain is myocytes.
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Figure 5. Examples of excluded patients.
Patients with LGE in the basal septum, the
likely area of biopsy, were prespecified as
not for analysis (n⫽5). The 2 shown here
(upper, aortic stenosis; lower, hypertrophic
cardiomyopathy), had a Vd(m) that was
lower than expected from the biopsy CVF,
suggesting the biopsy had sampled the
area of late gadolinium enhancement (left).
raphy parameters that assess diastolic function are dependent
not only on fibrosis, but also on filling pressures and active
myocyte relaxation. An in vivo measure of diffuse fibrosis
could be important across the whole spectrum of cardiac
conditions, with applications including research, diagnostics,
disease progression, prognostics, and therapeutics. Applications could include diseases of massive interstitial expansion,
such as cardiac amyloidosis, or even simple ageing, where
interstitial expansion may be modest and invasive biopsy not
warranted. Furthermore, the principles of EQ–CMR may be
more widely applicable. Equilibrium contrast magnetic resonance imaging (EQ–MRI) should be possible, indeed more
straightforward, in other organs, such as the liver, ovary,
bowel, arterial wall, or lymph nodes.
Over the last 5 years, LGE CMR has become routine for
noninvasive clinical assessment of focal scar such as myocardial
infarction. Despite the success of this technique, it is limited by
its inability to detect diffuse fibrosis. Prior CMR studies have
shown that diffuse fibrosis causes subtle ex vivo intrinsic tissue
signal differences.20 –22 Using a bolus of contrast, the presence of
diffuse fibrosis has been inferred by detecting elevated peak
tissue concentrations in cardiomyopathy compared with normals.32,33 Recently, mathematical modeling of this effect has
been used to derive partition coefficient estimates.25 Contrast has
been used as a continuous infusion instead of a bolus to image
focal scar,34 to measure the scar partition coefficient,7 and
in autopsy samples to measure the contrast volume of
distribution of diffuse fibrosis,24 but it has not been used in
vivo. In this study we used a primed continuous infusion
(removing contrast kinetic effects), a direct blood volume
of distribution measure (1⫺hematocrit) to obtain Vd(m)
rather than partition coefficient, and measured diffuse
fibrosis in vivo. A robust but simple MRI technique and
Microsoft Excel– based heart rate correction algorithm
were used with human tissue correlation (not surrogate or
animal model) in 2 different diseases.
Figure 6. MRI-measured myocardial volume of distribution against histological CVF. Vd(m) correlates with CVF in aortic stenosis (left,
n⫽18), hypertrophic cardiomyopathy (middle, n⫽8), and the combined population (right, n⫽26).
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Flett et al
Our preliminary investigations suggest EQ–CMR is reproducible and may be more reliable than the current biopsy gold
standard. We attempted to optimize the gold standard by
using intraoperative, deep sampling in a disease model with
relative fibrosis homogeneity. However, the biopsy sample
size of ⬍0.1 g, less than a thousandth of the total myocardial
volume, remains more prone to sampling error than our
chosen CMR analysis volume, which is 30 to 50 times larger.
With further refinement, EQ–CMR has the potential for
whole-heart fibrosis quantification/mapping to truly reflect
the global myocardial burden.
Limitations
Our data show that 80% of the between-subject differences in
Vd(m) are explained by the measured CVF, but that this
relationship is not one to one. A number of factors may
influence this offset correlation. The measured CVF is the
volume after fixation, not the in vivo volume, and it is
assumed to be entirely available for Gd-DTPA distribution
(as if no interstitial matrix components are present). Similarly, the measured Vd(b) assumes all plasma is available for
Gd-DTPA distribution, yet proteins such as albumin are
present, and additionally, the hematocrit may underestimate
the available Vd(b). Myocardium contains blood vessels, and
therefore a blood volume, that may differ in increasing
diffuse fibrosis (although this volume is only of the order of
a few percent35). Finally, there are differences in the macromolecular environment between blood and tissue, potentially
affecting the relaxivity of Gd-DTPA, although prior work
suggests such differences are negligible.36 Finally, there was
an up to 5% offset of our T1 measurements to actual T1.
Despite all these factors, EQ–CMR is a potentially clinically
applicable technique. Before it can be applied in routine
practice, however, it would be necessary to establish the
distribution in healthy individuals (especially as diffuse
fibrosis is known to occur as part of aging). In addition, the
sample size in this validation study was small.
Conclusions
We have developed a new technique, EC–CMR, that can
quantify diffuse myocardial fibrosis with a strong correlation
with the current gold standard of histological biopsy. The
technique has the potential for wide applicability in disease
characterization, monitoring, outcome prediction, and therapeutics. The principles described for this technique are likely
to prove transferable to other organs.
Acknowledgments
We thank M. Donovan for assistance with patient liaison, the Hatter
Cardiovascular Institute laboratory for microscopy access, and the
surgical teams at the Heart hospital (G. Bognolo, C. Di Salvo, S.
Kolvekar, M. Lawrence, and J. Yap).
Sources of Funding
Dr Flett holds a Clinical Research Training Fellowship from the
British Heart Foundation (Grant FS/08/028/24767). Dr Moon is
supported by the Higher Education Funding Council for England. Dr
Taylor is supported by a UK National Institute for Health Research
Senior Research Fellowship. The Centre for Cardiovascular MR at
Great Ormond Street Hospital for Children is funded by the British
Heart Foundation. This work was undertaken at University College
EQ–CMR for Diffuse Myocardial Fibrosis
143
London Hospital and University College London, which received a
proportion of funding from the Department of Health’s National
Institute for Health Research Biomedical Research Centres funding
scheme.
Disclosures
None.
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CLINICAL PERSPECTIVE
Diffuse myocardial fibrosis is a final common end point in cardiovascular disease and is associated with symptoms,
impaired ventricular function, and adverse prognosis. Even though it is thought to be a key “missing parameter” in clinical
cardiology, and it is a target for many therapies (eg, angiotensin-converting enzyme inhibitors, aldosterone antagonists),
it can only be quantified by histology on biopsy, with inherent risk and sampling error. As a result, it is not well understood
in the clinical arena. Echocardiographic surrogates such as markers of diastolic dysfunction are unsatisfactory because they
are influenced by multiple other factors. We developed and performed initial validation for a new technique, equilibrium
contrast cardiovascular magnetic resonance (EQ–CMR), as a method to quantify diffuse myocardial fibrosis. We designed
it to be easy to implement on any scanner. EQ–CMR involves standard MRI technology and contrast agent and can be
integrated into a standard CMR protocol. We have shown that EQ–CMR correlates with histological fibrosis in 2
conditions, aortic stenosis and hypertrophic cardiomyopathy. This work is at an early stage, but it appears that, for the first
time, it is possible to measure the diffuse myocardial fibrosis burden noninvasively. With further work, this technique could
have widespread implications in disease characterization, monitoring, outcome prediction, and therapeutics.
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Flett et al ID#:CIRCULATIONAHA/2009/930636
1 of 3
EQ–CMR for Diffuse Myocardial Fibrosis
SUPPLEMENTAL MATERIAL
a) T1 measurement technique development
Phantom samples were manufactured using agar jelly (10 g/l) and pippetted drops of
Gd-DTPA and MnCl2 to produce phantoms with varying T1 and T2 properties.
These were imaged using the standard gradient echo IR sequence (Slice thickness
8.0 mm, TR 9.8 ms, TE 4.6 ms) with varying heart rates, segmentation and repeat
times with the gold standard being T1 relaxometry (We used a non-segmented IR
GRE sequence, with TR 5000 ms, TE 2.67 ms, acquiring images at inversion times
of 120ms, 200ms, 400ms, 800ms, 1600ms, 3200ms and no inversion. We performed
a curve fit and calculated the x axis crossing as the null point and TI of the phantom).
b) Heart rate correction
The heart rate at the time of the T1 measurement sequence heavily influences the
measured T1. We used a spoiled gradient echo inversion recovery technique and
corrected the derived TI for incomplete longitudinal recovery using the following
method:
After a 180° inversion pulse, Mz (longitudinal magnetization) recovers exponentially
from –1 to +1:
(1)
Mz= 1 – 2e-t / T1
For breath-hold cardiac imaging the choice of TR is restrained to a multiple of the RR
interval. During a segmented inversion recovery sequence, after a dummy pulse, Mz
reaches a ‘steady state’ somewhat less than 1, assuming the heart rate (TR) is
regular. Call this ƒ, the restoration factor. At steady state, magnetization recovers
from – ƒ to ƒ during time TR.
(2)
ƒ = 1 – (1+f)e-TR/T1
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Furthermore, when the image shows no signal (Mz=0), at time TI’, magnetization has
recovered from -ƒ to zero.
(3)
0 = 1 – (1+ƒ)e –TI’/T1
We can isolate T1 from Eq. 3:
T1
= TI’/ln(1+ƒ)
Now if we substitute T1 into Eq.2 we derive ƒ:
ƒ
= 1 – (1+ƒ)1–TR/TI’
That gives us the equations for both ƒ and T1, which can be solved for 0<ƒ<1 (see
supplementary Excel file).
This method was proven in phantom experiments, (supplemental figure). At the limit,
when TR and T1 are similar, imaging ghosting is present and the correction breaks
down. In post-hoc analysis, when T1 (corrected and uncorrected) were compared to
CVF from histology removing the correction caused the r2 to fall from 0.80 to 0.54.
c) Readout effect.
Multiple different readout combinations were tried iteratively. We found that a
segmented readout reduced measured TI compared to relaxometry, but provided the
segmentation and flip angle were relatively low (21 segments, α=21º), the difference
from measured to true T1 was kept to 5%.
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Supplemental Figure Legend
Effects of mathematical heart rate correction
Left – Phantom experiment showing that HR correction restores measured T1 to
actual T1 as TR shortens within reasonable limits. Right – a post-hoc analysis
showing how important HR correction is – without it, the Vd(m):CVF correlation falls
from 0.8 to 0.54.
Supplemental Figure
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