Journal of Cardiovascular Magnetic Resonance (2007) 9, 525–537
Copyrightc ?2007 Informa Healthcare
ISSN: 1097-6647 print / 1532-429X online
Imaging Sequences for First Pass
Peter Kellman, PhD and Andrew E. Arai, MD
Laboratory of Cardiac Energetics, National Heart, Lung and Blood Institute,
National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
Myocardial perfusion imaging sequences and analysis techniques continue to improve. We
review the state-of-the-art in cardiovascular magnetic resonance first pass perfusion pulse se-
quences including the application of parallel imaging. There are a wide range of sequence
designs and parameters to consider when optimizing an acquisition protocol. The interdepen-
dence of these parameters forces the user to make compromises. We describe the technical
issuesand provide insights into the variousperformancetradeoffs. We also review the basicde-
sign for T1-weighted first pass myocardial perfusion imaging and go on to discuss the tradeoffs
associated with various schemes to provide multi-slice coverage. Artifact mechanisms are dis-
cussed and related to sequence design and parameters. The selection of quantitative versus
qualitative analysis affects various performance requirements, such as spatial and temporal
resolution and linearity of enhancement. Understanding the interaction between the pulse se-
quence parameters and resulting image quality is important for improving myocardial perfusion
resonance (CMR) has undergone steady improvement since it
was first proposed over 20 years ago (1, 2). Yet there remain
challenges for widespread clinical acceptance, and there is still
application of parallel imaging for accelerated acquisition. Per-
formance optimization is difficult due to the large number of
parameters affecting image acquisition. Furthermore, the inter-
dependence of these parameters forces the user to make com-
promises. As the field has not come to clear methodological
Keywords: Myocardial Perfusion, Cardiovascular MR, Ischemia,
Supported by a grant from the National Heart, Lung, and Blood
Institute, National Institutes of Health, Intramural Research
Laboratory of Cardiac Energetics
National Institutes of Health
National Heart, Lung and Blood Institute
10 Center Drive, MSC-1061
Building 10, Room B1D416
Bethesda, MD 20892-1061
tel: (301) 496-2513; fax (301) 402-2389
consensus, we do not answer the debate on which is the best
method. Rather, we describe the technical issues and provide
insights into the various performance tradeoffs.
To maintain a focus on first pass perfusion methods, only
certain topics could be included in this review. We start with
the basic design for T1-weighted first pass myocardial perfu-
sion imaging, and go on to discuss the tradeoffs associated with
anisms are discussed and related to the sequence design and
parameters. For simplicity, we consider only gadolinium based
extracellular contrast agents, although there may be advantages
to alternative contrast agents.
resolution, temporal resolution, and T1-linearity. The topic of
image analysis is another source of debate, and there remain
questions on the value and accuracy of various performance in-
dices. For issues beyond those dealt with in the current review,
comparisons between methods (18–22), review papers (23–27),
and papers dealing with the subject of quantitative perfusion
analysis (26, 28–33).
MYOCARDIAL PERFUSION IMAGING
Myocardial perfusion imaging is based on measuring the de-
livery of contrast agent to the myocardium during the first pass
following a bolus injection. The signal intensity is enhanced
by the contrast agent, which shortens the T1 relaxation time
and results in a brighter signal using a T1-weighted imaging
sequence. Regions with lower regional blood flow will appear
hypointense and may be detected given adequate image quality.
Quantitative measurement of blood flow may be made through
surement as a function of time. Myocardial flow reserve may be
estimated by comparing the flow measurements acquired at rest
and at stress. Stress perfusion is most commonly studied using
vasodilation such as adenosine or dipyridamole. Vasodilators
increase the blood flow in normal vessels while stenotic vessels
have a reduced vasodilator response.
Regions with prior myocardial infarction may appear hypo-
intense despite normal blood flow, following revascularization,
due to the low flow into scar tissue. Therefore, the interpreta-
tion of perfusion images usually also incorporates viability as-
sessment by delayed enhancement imaging as described in the
section on analysis.
Successful myocardial perfusion imaging requires optimiz-
ing sequence and parameters to meet often contradictory re-
quirements. The basic requirements are:
1. Temporal Resolution Two distinct measures of tempo-
ral resolution are important for perfusion imaging. The
time between two images of the same slice location af-
fects the ability to sample the dynamic signal intensity
ics of blood flow to the myocardium. Typically, images
are acquired every 1–2 heartbeats to adequately sam-
ple myocardial blood flow. For quantitative perfusion,
an accurate estimate of the arterial input function may
require sampling the LV blood signal every heartbeat.
cardiac cycle, and the actual duration of imaging read-
motion, both indicated in Fig. 1a.
2. Spatial Resolution The spatial resolution must be ade-
quate to distinguish sub-endocardial ischemia (<3 mm
in-plane) and to assess transmural extent of defects.
3. Spatial Coverage It is desirable to have full coverage of
the heart. A minimum of 3 slices is needed to cover at
least 16 segments of the heart (34). A greater number of
slices are desirable.
4. Linearity A linear or quantifiable relationship between
signal intensity and contrast agent concentration is de-
sirable in order to quantify perfusion.
5. Image Quality Image quality must be sufficient to pro-
vide contrast between normal and ischemic regions and
must be free of artifacts.
requirements regarding accurate knowledge of the arterial input
function, which represents the delivery of contrast to the heart
and is commonly estimated from the blood signal. Therefore,
Figure 1. Magnetization preparation schemes for T1-weighted
myocardial perfusion imaging: (a) saturation recovery (SR), (b) in-
version recovery (IR), and (c) magnetization driven steady state.
quantitative myocardial perfusion imaging requires measuring
both the blood and myocardial signals. The blood and my-
ocardium have different contrast agent concentrationsas well as
T1, T2, and T2∗relaxation parameters leading to significantly
trast between blood and myocardium is also affected by blood
T1-weighted imaging sequences
First-pass perfusion imaging typically acquires multiple
slices of T1-weighted images that portray perfusion. Ideally,
the signal intensity on such images should closely reflect the
temporal change of the contrast agent concentration, which is
inversely related to the achieved T1 ([Gd] ∼ 1/T1). A saturation
recovery (SR) preparation (Fig. 1a) is the most commonly im-
plemented method to achieve T1-weighting and may be used in
conjunction with various methods for image readout.
In early work, inversion recovery (IR) approaches (Fig. 1b)
were used (7–9, 17, 35, 36). IR approaches have the potential
for increased dynamic range but are vulnerable to R-R variation
or missed triggers which will cause signal intensity variation
due to incomplete magnetization recovery. With IR preparation,
the images are usually acquired at a time following inversion
(TI) which nulls the pre-contrast blood to maximize the contrast
and to avoid loss of contrast, which might result from mag-
nitude detection. This results in a comparatively long imaging
duration and commonly limits the imaging to a single slice per
526 P. Kellman and A. E. Arai
In both SR and IR preparation schemes, there is generally a
trigger delay (TD) between the RF preparation and the start of
mined by the delay to the center of k-space, which is commonly
in the center of readout for linear phase encode ordering. This
ture contains reference to both often making direct comparisons
An alternative magnetization driven steady state preparation
approach (Fig. 1c) was proposed (10) to achieve a higher degree
of linearity than IR (i.e., signal intensity vs [Gd]). However,
linearity was achieved at the expense of contrast-to-noise ratio
(CNR) and had a lengthy preparation time limiting the acqui-
sition to a single slice per heartbeat. In this scheme, the longi-
tudinal magnetization was driven to steady state by a series of
In the steady state limit, the signal intensity is linearly propor-
tional to 1/T1 when using 90◦readout pulses and was found to
(improved SNR) with only slight compromise in linearity (10).
Hybrid T1-preparation schemes
A number of hybrid preparation schemes can achieve T1-
mia insensitive approaches which combine SR preparation with
IR have been proposed (Fig. 2a) (37). This scheme increases
the length of preparation thereby reducing the number of slices
that may be covered. By using a 90◦SR preparation, which sets
the longitudinal magnetization to zero, the 180◦IR preparation
which follows after a fixed short recovery period becomes in-
sensitive to the RR interval. The dynamic range is somewhat
compromised depending on the saturation recovery delay.
The magnetization driven steady state scheme may also be
used with a 90◦SR preparation (Fig. 2b) to reduce the time
Figure 2. Hybrid magnetization preparation schemes for T1-
weighted myocardial perfusion imaging: (a) arrhythmia insensitive
preparation using SR followed by IR, and (b) magnetization driven
steady state with SR preparation to decrease time to steady state.
required to reach steady state. However, the linearity is still
achieved at the expense of contrast-to-noise ratio (CNR) and
slightly longer time per slice.
There are several approaches to providing multi-slice cover-
age during first-pass imaging as shown in Fig. 3 for SR prepara-
tion. Other preparation schemes might be implemented as well
if the time per slice permits. In each of these schemes, imaging
is performed across the cardiac cycle; therefore, each slice will
be acquired at a different phase of the cardiac cycle. Thus, the
wall thickness and motion will vary slice-to-slice using these
approaches. While it is possible to acquire fewer slices with less
variation, for instance, only during diastole, this may reduce the
overall spatial coverage, particularly if single RR temporal res-
olution is required. Furthermore, diastolic images have reduced
wall thickness placing a higher demand on spatial resolution.
Using a single SR preparation per slice (Fig. 1a) provides
reasonable coverage with uniform image quality. Approaches
that acquire multiple slices per SR preparation offer increased
efficiency. In one approach, multiple slices are readout sequen-
In this scheme the TI varies from slice-to-slice and thus the T1-
scheme does reduce the time per slice slightly providing greater
spatial coverage. A second approach which acquires multiple
Figure 3. Approaches to multi-slice coverage. (a) Multiple SR
preps per RR, (b) multiple slices readout sequentially per SR prep,
(c) multiple interleaved slices per SR prep, and (d) multiple slice
selective notched pulse preparations per RR.
First Pass Perfusion Imaging 527
Figure 4. Saturation performance comparison of different SR prep pulses for GRE-EPI perfusion sequence with TI = 85 ms. (a) proton density
reference without SR prep, (b) 90◦SR prep pulse demonstrating B1 inhomogeneity and incomplete saturation, (c) sequel of 3 each 90◦RECT
pulses, (d) BIR4 adiabatic SR prep. All images are window-leveled the same. Incomplete saturation is evident using the 90◦RECT (b).
slices per SR preparation acquires multiple interleaved slices
(e.g., 2 slices) (Fig. 3c) (11). In this scheme, the TI remains
constant. Although this approach increases the acquisition ef-
ficiency and thus spatial coverage, the actual imaging time per
individual slice is increased thereby increasing the sensitivity
to motion artifacts. A benefit of slice interleaving is the length-
ening of the pulse repetition time (TR) between pulses of the
same slice. An increased TR permits greater magnetization re-
covery and use of a higher readout flip angle for improved
A novel scheme for multi-slice coverage uses selective notch
pulse preparations (15) where each notch selective SR prepara-
(Fig. 3d). In this scheme, the selective notch pulse saturates the
volume except for the next slice to be imaged. Thus, the satura-
tion preparation for any given slice was played out prior to the
A longer TI may result in increased SNR although this comes at
the cost of reduced linearity. A problem with this scheme is that
the first slice may need to be discarded due to RR variations,
eroding some of the efficiency gain. Furthermore, the selective
notch pulse frequently results in non-uniform blood pool signal
intensity due to heterogeneous through plane motion. Myocar-
dial signal intensity is also sensitive to through plane motion,
either cardiac or respiratory related.
Saturation recovery preparation
The 90◦SR preparation is commonly used since an ideal
90◦SR is insensitive to arrhythmia and/or missed ECG triggers.
SR preparations using a lower flip angle (60◦–70◦) have been
reported (3, 5) in cases of very short TD (10–15 ms) increasing
given an adequate TI (3).
A few RF pulse designs have been proposed to achieve
the ideal 90◦SR preparation in the presence of B1-field in-
homogeneity. The adiabatic BIR4 pulse provides improved
insensitivity to both B1 and B0 (40, 41). The BIR4 has excel-
lent performance as long as the adiabatic condition is achieved
(i.e., adequate power). Alternatively, a pulse sequel design with
several repeated 90◦rectangular pulses with gradient crushers
(42) improves the overall effectiveness of the saturation pulse
in the event that the 90◦rectangular pulse is not a true 90◦due
to B1-field inhomogeneity. In our experience both of these ap-
proaches are very effective and make a significant improvement
over the simple 90◦rectangular pulse (Fig. 4). The sensitivity to
RR variation is illustrated in Fig. 5, which shows the effect of
missed ECG triggers on the signal intensity for both 90◦rectan-
gular SR preparation and pulse sequel (3 pulses) with imperfect
90◦pulses. The effect of missed ECG triggers is insignificant
for the pulse sequel design.
ration RF pulse can lead to stimulated echo artifacts which de-
grade image quality. Stimulated echo artifacts due to these gra-
dients may be mitigated by use of variable crushers.
Figure 5. Time intensity curves for 2 cases with missed ECG trig-
gers showing (a) sensitivity of signal intensity to missed triggers
using 90 RECT SR prep with incomplete saturation (left) and (b) in-
sensitivity to missed triggers using pulse sequel for SR prep (right).
Incomplete saturation causes increased intensity following missed
trigger (left). Samples following missed ECG trigger are marked
528P. Kellman and A. E. Arai
The saturation performance of the 90◦SR preparation is par-
ticularly important for semi- and fully-quantitative perfusion
measurements which rely on accurate baseline correction. Im-
perfect saturation biases the pre-contrast baseline by an amount
that is not readily correctable.
Image readout & parallel imaging
ed using IR or SR recovery in combination with either snap-
shot FLASH (7, 8), GRE-EPI (5), or balanced steady state free
precession (SSFP, also known as FISP, FIESTA, or Balanced
FFE) (13). There is no clear consensus regarding the sequence
of choice for myocardial perfusion imaging, although there is
There are also a number of approaches to parallel imaging
(43–47) and other accelerated imaging methods (48–50) that
may be applied to myocardial perfusion imaging. The appli-
cation of parallel imaging is closely coupled with the image
readout since the number of phase encodes may be substan-
tially reduced, thus, altering the optimization of sequence pa-
rameters normally associated with the readout. The optimum
choice of methods is a difficult question due to the large para-
meter space for each method and differing details of implemen-
tation between institutions and vendor platforms. It is not the
objective of this paper to answer this debate. Rather, it is to re-
view the current methods in light of advances, such as parallel
imaging, and to highlight the pros and cons and performance
Tradeoffs between spatial resolution and SNR, spatial and
temporal resolution, and so on, are quite familiar in CMR. With
the addition of the SR preparation, the number of variables and
their interdependence grows. For example, a longer TI may in-
trast agent concentration (see below section). Some sequences
have been optimized for linearity (10) while others have been
optimized for CNR (3). In general, a longer TI will also re-
duce the spatial coverage. While one can optimize sequence
parameters for SNR, coverage, and resolution, the interplay of
sequence parameters and image artifacts is less understood. As
described later, the presence of image artifacts in myocardial
perfusion imaging is a large factor limiting clinical acceptance.
spread function (PSF) and other artifact mechanisms. The PSF
is the term used to describe imperfect mapping between points
in the image.
In order to illustrate the influence of sequence parameters, an
example is presented comparing SSFP, FLASH, and GRE-EPI
readouts, all accelerated with SENSE parallel imaging at rate
R = 2 (43, 44). The sequence parameters (Table 1) are based on
the recent literature (21, 51) and are based on high performance
gradients capable of 45 mT/m at 200 mT/m/ms slew rate. This
and the uniformity of k-space which affects the PSF.
Table 1. Myocardial perfusion sequence imaging parameters.
MethodSR-SSFP SR-FLASH SR-GRE-EPI
Readout Flip Angle
TD (ms) (to 1st line)
TI (ms) (to center)
Slices per RR @ 60/90/120 bpm
128 × 80
R = 2
128 × 80
R = 2
128 × 80
R = 2
In these examples, the matrix size = 128 × 80, and the TI =
85 ms. Both are held constant between sequences. All the se-
quences provide similar spatial coverage (slices per RR), with
the GRE-EPI providing slightly greater coverage at the highest
heart rates due to the increase acquisition efficiency of an EPI
readout (Tslice= 117 ms vs 130 or 132 ms). The most signif-
icant difference given these parameters is the actual imaging
duration within the cardiac cycle (Timaging), which ranges from
61 ms for GRE-EPI to 92 ms for SSFP. The imaging duration
may contribute to motion induced artifacts especially near the
endocardium. Selection of the bandwidth (BW) is a tradeoff be-
tween the SNR and minimizing TR which affects Timaging, Tslice,
and number of slices per RR. It also affects the TE which in turn
determines the T2∗loss at peak contrast concentrations and the
sensitivity to off-resonance due to B0-inhomogeneity and bolus
susceptibility. TE is particularly important for a SSFP readout.
reduction of artifacts due to motion sensitivity (proportional to
iod which consists of the RF pulse and actual readout decreased
with increasing BW, reaching a point where the overhead of the
RF pulse duration is a significant fraction. At this point, there
is diminishing return in further BW increase. In this example
(Table 1), the BWs were selected accordingly. Using a constant
readout flip angle, the value of flip angle was selected for best
variable readout flip angle might be considered.
The simulated responses of myocardial signal intensity are
shown in Fig. 6 for varying contrast agent concentrations from
0 to 4 mmol/L, where the expected concentration in the my-
ocardium is in the range 1–2 mmol/L for single dose (0.1
mmol/kg). Simulations used the method by Sekihara (52) with
precontrast T1 = 850 ms and T2 = 50 ms in the myocardium,
and 4.5 (sec mmol/L)−1relaxivity of Gd based contrast agent.
Note that the 40 actually acquired phase encodes are recon-
structed to a full resolution of 80 lines by means of paral-
lel imaging. Non-uniformity of the k-space response due to
SR recovery and transient approach to the steady state of the
readout leads to distortion of the PSF. Distorted PSF may
cause edge artifacts or ghosting. The GRE-EPI has been re-
ordered based on a modified center-out phase encode order (5)
First Pass Perfusion Imaging 529
Figure 6. Simulated magnetization for SR myocardial perfusion imaging sequences with SSFP (left), FLASH (center), and GRE-EPI (right)
readouts (parameters in Table 1) for contrast agent concentration ranging from 0 to 4 mmol/L (in 0.5 steps). Note that these plots represent
to 80 using R = 2 parallel imaging.
chosen to acquire the central portion of k-space on the first
echo (TE1) of the echotrain, thereby minimizing T2∗losses
and flow sensitivity. This results in a rapid periodic fluctuation
in k-space which may lead to ghosting if the amplitude is too
The SSFP readout has the greatest signal (transverse mag-
netization), while the FLASH readout has the least signal. The
The imaging parameters may be selected to meet different
criteria. Note that the TI for each sequence might be varied
to effect greater uniformity across k-space or variable readout
flip angle might be considered. It may be noted that the SSFP
sequence achieves higher SNR than GRE-EPI for instance, but
requires a longer acquisition time. The SSFP sequence might
be accelerated at R = 3 reducing Timagingfrom 92 ms to 61 ms
(same as GRE-EPI) trading SNR for speed, making the SSFP
duration and SNR. The SNR decrease between R = 3 and 2 is
√(3/2) considering the SNR loss of√R.
Figure 7. Spatial coverage and spatial resolution versus heart rate for SSFP, FLASH, and GRE-EPI sequences with and without parallel imaging.
R = 2 denotes parallel imaging at acceleration rate 2, and R = 1 denotes no acceleration.
Spatial resolution & coverage
The tradeoff between spatial resolution and coverage for SR
with various readouts is described in Fig. 7, which plots the
bpm for various matrix sizes and parallel imaging acceleration
rates. Using a 360 × 270 mm2rectangular FOV, the spatial
resolution is 2.8 × 3.4 mm2using a 128 × 80 matrix size, and
1.9 × 2.8 mm2using a 192 × 96 matrix size. These calculations
assume TI = 100 ms for 128 × 80 at rate = 1 (no acceleration),
1, and TI = 125 ms for 192 × 96 at rate 2. Using a 192 readout
for FLASH, and 6.1 to 6.6 for GRE-EPI. All sequence methods
may achieve 3 slices per RR coverage at 192 × 96 matrix size
at 120 bpm using parallel imaging at rate = 2. Of course, the
higher spatial resolution will decrease the SNR proportional to
considerably higher than rest. Thus, pulse sequence parameters
530 P. Kellman and A. E. Arai
Figure 8. Relative CNR versus dose for SSFP, GRE-EPI, and FLASH readouts after baseline correction and scaling for bandwidth (sequence
parameters per Table 1).
should be selected to achieve adequate spatial coverage at stress
CNR & signal intensity linearity
The exponential recovery following saturation results in a
non-linear relationship between signal intensity and contrast
agent concentration. Ignoring the effect of readout on magneti-
zation, the magnetization recovery following saturation is sim-
ply described by M = [1- exp(-TI/T1)], with T1described by
(1/T1) = (1/T1o)+ (γ [Gd]), where T1o = 850 ms is the pre-
contrast T1, and γ = 4.5 (sec mmol/L)−1is the relaxivity of
Gd based contrast agent with concentration [Gd]. For TI<<T1,
the magnetization is approximately proportional to [Gd] as seen
by simple substitution, since exp(-TI/T1)≈(1 − TI/T1). In the
example (Table 1) with TI = 85 ms, there is already signifi-
cant departure from linearity at [Gd] = 1.5 mmol/L where T1 ≈
zation effects of readout yields curves (Fig. 8) that demonstrate
the non-linear relation versus contrast dose for the example se-
quence parameters listed in Table 1. The upper plots are the
in each sequence. The lower plots correspond to relative CNR
after scaling for√BW and correction of baseline intensity. The
CNR for these plots is defined as signal difference between pre-
contrast and post-contrast at a myocardial concentration of 2
mmol/L divided by the noise standard deviation. The CNR ver-
sus TI (Fig. 9) shows that small increases in CNR are possible
with a large increase in non-linearity. Optimization for CNR
without consideration of linearity and k-space uniformity will
lead to selection of long TI (3).
The simulation for the parameters of Table 1 predicts that
SSFP has approximately 40% higher CNR than GRE-EPI and
higher CNR than FLASH. These predictions are fairly consis-
tent with reported measurements using similar parameters (21)
and with results that use FLASH with GRAPPA (45) parallel
and 12 extra in-place reference lines results in an effective ac-
celeration of R = 1.6.
the CNR penalty is estimated to be 50% or greater compared to
The presence of image artifacts in myocardial perfusion
imaging is a large factor limiting clinical acceptance. In partic-
ular, artifacts that appear as a dark subendocardial rim (example
Figure 9. Relative CNR versus TI (between 0 and 2 mmol/L) for
SSFP, GRE-EPI, and FLASH readouts after baseline correction
and scaling for bandwidth (other parameters per Table 1).
First Pass Perfusion Imaging531
Figure 10. Dark rim artifact observed on both stress (left) and rest (right) studies using SR-SSFP for patient with negative cath (images courtesy
of Jonathan Lyne, Royal Brompton Hospital, London).
Fig. 10) that may be confused with actual hypointense regions
of reduced blood flow (53). Such artifacts can lead to false diag-
noses and are of paramount concern. Strategies (54) have been
Understanding the artifact mechanisms may lead to sequence
designs which minimize these deleterious effects.
Artifact mechanisms that may lead to dark sub-endocardial
ing period (Timage), Gibb’s ringing (53) caused by truncation of
k-space, non-uniformity of k-space weighting due to saturation
recovery and readout, and partial volume cancellation between
the myocardium and LV blood pool. Contribution of each of
Minimizing cardiac motion artifacts may be accomplished
either by using a small imaging duration (Timaging) or by timing
the acquisition to occur in periods with relatively low motion.
Reducing the imaging duration may be accomplished by re-
ducing the matrix size (low spatial resolution), using acceler-
ated imaging such as parallel imaging, and using short TRs
and/or EPI sequences. Diastole may provide a longer motion
free window but comes at the cost of reduced left ventricular
wall thickness thereby increasing the demand for better spatial
Gibb’s ringing is generally mitigated to some extent by re-
construction with the use of raw filtering, also known as win-
dowing or apodization. The ringing is suppressed at the expense
of spatial resolution. In this case, it may be advantageous to
acquire a larger matrix size and use a stronger raw filter (53).
This will cost some spatial coverage but might be a worthwhile
tradeoff. The extent of Gibb’s ringing is determined by the step
in intensity or contrast between the myocardium and blood.
The SSFP sequence has a much higher blood-myocardium
contrast, and therefore, will have commensurately larger
The non-uniformity across k-space (Fig. 6) leads to point
spread function (PSF) distortion causing both blurring (loss of
rim artifacts. With the exception of the magnetization driven
steady state (10) approach (Fig. 1[c]), myocardial perfusion
imaging is not performed in a steady state condition, and the
non-uniformity of the k-space response is determined by the tis-
sue T1 values, TI, and readout flip angle. The dependence on T1
means that the PSF for the blood pool during peak bolus con-
centrations may be quite different than for the myocardium and
may lead to rim artifacts at the sub-endocardial border between
blood and myocardium. Ramp flip angle techniques might be
considered to improve uniformity but are only effective for a
single T1 value. In EPI sequences, which acquire at multiple
echo times, the T2* loss at peak bolus concentration contributes
pool signal. Non-uniform k-space weighting with the EPI phase
encode order may lead to ghosting.
Partial volume effects may lead to dark rim artifacts when
the blood and myocardium are out of phase. Spatial variation
in phase may result from a number of effects including strong
gradients in contrast agent concentration. These effects are re-
lated to the spatial resolution, therefore, it is desirable to have
as many pixels transmurally as possible.
Other artifacts occur in addition to the dark rim artifact, al-
readout, dark banding artifacts arise due to B0-field inhomo-
geneity caused by inadequate shim or susceptibility gradient
associated with the bolus of contrast agent. Shim problems can
be observed prior to contrast injection and mitigated by center
frequency or shim re-adjustment. GRE-EPI readout is marred
by ghosting due to off-resonance since there are phase shifts
at each echo delay. This can be mitigated to a large extent by
using an interleaved phase encode order with echo-time shifting
(5). Chemical shift due to fat may cause ghosting; therefore,
fat suppression pulses (56) are often used in conjunction with a
GRE-EPI readout and can be implemented during the prepara-
may be eliminated by means of time varying gradient spoiling.
Aliasing artifacts or wrap due to accelerated imaging may
lead to interference in the region of interest (Fig. 11). While
532 P. Kellman and A. E. Arai
artifact due to dynamic contrast enhancement of RV. Case 2 illustrates UNFOLD artifact due to breathing motion. In this example, these artifacts
are suppressed with TSENSE parallel imaging.
the same consequence as the rim artifact, they may degrade the
time intensity curves preventing accurate analysis. Since these
to non-diagnostic exams.
As illustrated in this section on artifacts, there are a wide
range of factors that can result in artifacts. The worst artifacts
result in subendocardial rims that can be misdiagnosed as per-
fusion defects. Factors that mitigate one mechanism generating
rim artifacts may worsen another factor. For example, Gibbs
ringing and partial volume errors can be improved by increas-
ing image resolution, but higher spatial resolution may require
longer readouts that exacerbate motion artifacts. Recognizing
of gadolinium is highest in the ventricular cavities is important
since this is a time when real perfusion defects should also be
Qualitative assessment of myocardial perfusion deficit is
ficity (54, 57–61) while quantitative analysis is currently more
time consuming. A qualitative readout basically consists of ex-
amining the time course of images for evidence of hypointense
Due to issues of noise and artifacts, additional interpreta-
tion strategies have been developed to minimize false positive
diagnoses due to dark subendocardial rim artifacts. One strat-
egy tested by the group at Duke University (54) combines stress
and rest perfusion studies with delayed enhancement according
to the following logic. Interpretation of coronary artery disease
(CAD) begins with delayed enhancement. Positive delayed en-
hancement is a highly specific indicator of CAD. Negative de-
layed enhancements leads to examining the stress perfusion
study. Negative delayed enhancement combined with negative
stress perfusion results in a negative diagnosis for CAD. How-
ever, a positive stress perfusion deficit requires an analysis of
region coincides with the stress perfusion hypointense region,
then the result is qualified as a rim artifact, under the suppo-
sition that the rest study should have normal flow in regions
without prior MI. Finally, an apparent stress perfusion deficit
with normal rest perfusion would indicate CAD as illustrated in
example of Fig. 12, which had no delayed enhancement. This
strategy deals effectively with no prior recognized MI but does
not address cases of ischemia in patients with prior MI. An ex-
ample of stress and rest studies with a dark rim artifact is shown
in Fig. 10, which was corroborated by a negative finding on a
diagnostic catheterization (example provided by Jonathan Lyne
and Peter Gatehouse, Royal Brompton Hospital).
by qualitative analysis of time intensity curves. This procedure
required tracing endo- and epi-cardial contours to divide the
myocardium into sectors. Each sector may be further subdi-
vided transmurally into endo and epi layers. Tracing contours
can be time consuming when there is respiratory motion. In
this case, automatic registration methods may be applied (62,
63), although the performance of automatic registration is still
Time intensity curves may be assessed qualitatively as well
as quantitatively. For stress perfusion, the expected response for
normal vessels with vasodilation show a peak (Fig. 13) in the
myocardial signal intensity time course followed by a washout
First Pass Perfusion Imaging533
Figure 12. Example first-pass contrast-enhanced perfusion images for patient with stress perfusion deficit in antero-septal region shown for
single slice of 3 acquired slices using GRE-EPI sequence using rate-2 TSENSE. The bottom row is at rest and top row is with stress: (a), (e)
pre-contrast, (b), (f) RV enhanced, (c), (g) LV enhanced, and (d), (h) myocardium enhanced. Delayed enhancement images were negative for
prior to the plateau. Absence of this overshoot indicates a lack
of vasodilation and may be used to further augment the inter-
pretation of findings based on visual image assessment.
First-pass myocardial perfusion images may be used to char-
quantitative methods. MBF (expressed in mL/min/g) and my-
ocardial perfusion reserve (MPR) are defined as the ratio of
hyperemic and resting blood flow. Both are clinically important
indices for assessing myocardial ischemia, and are more objec-
tive than qualitative assessment. Fully quantitative myocardial
blood flow (MBF) may be estimated using a Fermi model con-
strained deconvolution (29, 31, 32).
In order to quantify perfusion, it is necessary to have an ac-
curate estimate of the arterial input function (AIF), which is
normally measured from the LV blood pool signal. Due to non-
linear effects of saturation recovery and T2∗losses at high bo-
lus concentration, the AIF estimated directly from the myocar-
dial perfusion images becomes significantly distorted. For this
reason, various solutions have been proposed. The dual-bolus
using 6 endocardial sectors. Normal sectors show a vasodilated
response, whereas the antero-septal region is hypo-intense.
first-pass perfusion method uses a high dose of contrast for my-
ocardial analysis, preceded by a lower concentration bolus to
maintain the linearity of the left ventricle (LV) signal intensity
(29, 32). The dual sequence method (6, 12, 64), which acquires
AIF reference images using a low TE and short saturation re-
covery delay, has been proposed to avoid distortion in the AIF.
to provide an adequately linear response without noticeable dis-
tortion. The dual sequence method (Fig. 14) acquires low reso-
lution blood pool images each heart beat requiring on the order
In order to maintain linearity at peak bolus concentration, it is
necessary to have a TI on the order of 10 ms or less. This is
accomplished using a center-out phase encode acquisition or-
der with a short trigger delay to avoid edge enhancement due
to highly non-uniform k-space response and a very low spatial
resolution image. TE values on the order of 0.6 ms are used to
for single dose (Fig. 15), corresponding to T2∗losses of 5–10%
using the dual sequence method with TE = 0.6 ms for the AIF
measurement (65). The dual sequence method could be modi-
fied for greater spatial coverage by sampling of the myocardial
perfusion signal every other heart beat while still maintaining
single heartbeat temporal resolution for the AIF.
The myocardial signal intensity does not have a linear rela-
tionship to [Gd] as desired due to T1-related effects. Although
this has received less attention than the highly non-linear dis-
tortion of the blood pool signal, the effect of T1-nonlinearity
on myocardial signal intensity may significantly affect perfu-
sion quantification (66, 67). The myocardial perfusion signal
non-linearity for SR sequences is largely determined by the TI
as previously described and will affect the estimates of MBF
even for relatively short TI (67). Look-up table (LUT) correc-
flow estimates (66, 67). The LUT, which may be based on either
534 P. Kellman and A. E. Arai
Figure 14. Dual sequence method for estimating arterial input function using a low resolution image with short TD for linear response of LV
blood-pool signal at high Gd concentrations, and short TE to minimize T2∗effects at peak bolus. Note that low spatial resolution AIF image
(upper right) is adequate for sampling LV blood pool time intensity curve, but does not have adequate resolution to detect myocardial perfusion
deficit (lower right image).
Figure 15. T2∗effects observed in time intensity curves for LV
blood pool ROI measured at different TE values using a multi-echo
sequence. The TE = 0 curve (dotted line) is estimated based on a
least squares fit to the multi-echo dataset. The initial 2 time frames
are proton density reference images.
Figure 16. Correction of inhomogeneity due to surface coil inten-
sity variation performed by scaling the raw myocardial time inten-
sity curves (left) for each myocardial sector ROI by the value of
the initial acquired proton density reference image for the same
corresponding sector ROI (right).
theoretical or simulated curves, corrects the measured signal
intensity for the non-linear relationship to Gd concentration.
geneity will affect quantitative assessment and must be factored
nal coil intensity correction may be implemented by normal-
ization with proton density weighted images. Proton density
weighted images may be acquired either in a separate pre-scan
or as part of the myocardial perfusion imaging sequence at the
low readout flip angle without SR preparation), ensuring image
registration. Fig. 16 illustrates the time intensity curved before
and after surface coil correction.
Typical acquisition of first-pass perfusion studies are 40-50
heartbeats in duration, which is too long for a single breath-
hold in many patients. Registration of the images with endo
and epi-cardial borders is, therefore, a critical step in generating
high quality time intensity curves used in quantitative perfusion
measurement (62, 63). Unless this step is reliably automated,
this is the most time consuming aspect affecting the analysis.
A fully quantitative myocardial perfusion protocol generally
for qualitative interpretation of dark rim artifacts as previously
described. The stress study, which is most critical, is performed
first. There will be a residual concentration of contrast agent
for the rest study, which is typically performed at least 10–15
minutes following the first bolus.
It is important to note that the measure of Gd contrast agent
is detected indirectly through its effect on the 1H signal. Thus,
and the intercellular space must be considered (68).
Myocardial perfusion imaging sequences and analysis tech-
niques continue to improve. There are a wide range of sequence
First Pass Perfusion Imaging 535
approval. There is also a need for common nomenclature. Dark
rim artifacts may be minimized by careful design but remain a
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