Correction of Through-Plane Deformation Artifacts inStimulated Echo Acquisition Mode Cardiac Imaging

Ahmed S. Fahmy,1,2 Li Pan,3 Matthias Stuber,1,2 and Nael F. Osman1,2*

Attempts to use a stimulated echo acquisition mode (STEAM) incardiac imaging are impeded by imaging artifacts that result insignal attenuation and nulling of the cardiac tissue. In this work,we present a method to reduce this artifact by acquiring twosets of stimulated echo images with two different demodula-tions. The resulting two images are combined to recover thesignal loss and weighted to compensate for possible deforma-tion-dependent intensity variation. Numerical simulations wereused to validate the theory. Also, the proposed correctionmethod was applied to in vivo imaging of normal volunteers(n � 6) and animal models with induced infarction (n � 3). Theresults show the ability of the method to recover the lost myo-cardial signal and generate artifact-free black-blood cardiacimages. Magn Reson Med 55:404–412, 2006. © 2006 Wiley-Liss, Inc.

Key words: stimulated echo mode; STEAM; cardiac imaging;black-blood; artifact; deformation.

The stimulated echo acquisition mode (STEAM) (1,2) iscurrently used in a wide range of applications for imagingtissue parameters, such as spin density, T1, T2, (3), andchemical shift (4), or for other functional parameters, suchas measurements of flow (5), diffusion coefficients (6),displacement (7–9), and deformation (10). The sensitivityof STEAM to the latter class of parameters and its inherentblack-blood property make the technique particularly ap-pealing in the area of functional cardiac imaging.

A typical (high-speed) STEAM pulse sequence is illus-trated in Fig. 1 (2). The first RF pulse tips the magnetiza-tion into the transverse plane and the modulation gradient,Gm, modulates the spin phase with a certain phase valuebased on its location. The effect of the second RF pulse isto restore the modulated magnetization to the longitudinaldirection, where it can persist for a long time since mag-netization decays with the relatively slow T1 relaxation. Atthe acquisition stage, refocusing of spins is achieved byapplying a demodulating gradient, Gd � Gm, and thus, astimulated echo is acquired.

As reported in a number of articles (2,7–9,11,12) whenapplying STEAM for cardiac imaging, the contraction (orstretching) of the cardiac tissue results in intravoxeldephasing of the magnetization, which leads to a substan-tial loss of the myocardial signal. Fischer et al. (12) pro-posed a method to correct for through-plane motion ateach cardiac phase by adapting the demodulation fre-quency to the anticipated amount of tissue deformation.However, this solution has limitations because of the het-erogeneity of contraction of the myocardium, which makesit difficult for a single demodulation frequency to compen-sate for a range of contraction. Recently published work ondisplacement encoding using stimulated echoes (DENSE)by Kim et al. (9) proposed reducing the effect of intravoxeldephasing by using low modulating gradients while sup-pressing the FID echo (which can overlap the stimulatedecho and causes artifact) by subtracting two complemen-tary echoes (9). However, increasing the modulating gra-dients in order to improve the black-blood contrast or toincrease the motion sensitivity may make the sequencemore vulnerable to through-plane deformation artifacts(11). Aletras and Wen (8) recently presented artifact-freeSTEAM images, but their method does not provide directcine images of the heart as it requires nulling the FID echoat a single phase on the cardiac cycle.

In this work, we present a method to correct for thethrough-plane deformation artifact despite the heterogene-ity of myocardial contraction and the use of strong modu-lating gradients. The technique requires the acquisition oftwo sets of STEAM images with two different demodula-tion frequencies. The two sets of images are then combinedto produce a new set of images that does not suffer fromsignal loss induced by tissue contraction.

METHODSSources of the STEAM Artifact

The STEAM pulses, shown in Fig. 1, induce a spatialmodulation of the magnetization in the through-planedirection with a sinusoidal pattern of frequency�m � � � � � Gm , where � is the gyromagnetic ratio, and� is the duration of the applied gradient (10). After modu-lation of magnetization, the modulation frequency is uni-form in the imaging volume. In case the tissue does notdeform (static), demodulation with frequency �d � �m

will produce an artifact-free STEAM image. However, incase of tissue deformation, as in the heart, the modulationfrequency at a location (x,y) on the imaging plane and attime t varies according to the local tissue deformationstrain, �(x,y;t). The deformation strain is defined here asthe change of the tissue length per unit length in thethrough-plane direction. The exact relation between localmodulation frequency and the through-plane strain can bedescribed by the equation (10):

1Department of Electrical and Computer Engineering, Johns Hopkins Univer-sity, Baltimore, Maryland, USA.2Russell H. Morgan Department of Radiology and Radiological Science,Johns Hopkins University, Baltimore, Maryland, USA.3Department of Biomedical Engineering, Johns Hopkins University, Baltimore,Maryland, USAGrant sponsor: National Heart, Lung, and Blood Institute; Grant number:HL072704 Grant sponsor: Whitaker Foundation; Grant number: BiomedicalEngineering Grant RG-02–0745; Grant sponsor: Donald W. Reynolds Foun-dation; Grant sponsor: NIH; Grant number: HL61912.*Correspondence to: Nael F. Osman, Johns Hopkins Outpatient Center,Room 4243, 601 N Caroline Street, Baltimore, MD 21287, USA. E-mail:nael@jhu.eduReceived 17 March 2005; revised 6 September 2005; accepted 14 October2005.DOI 10.1002/mrm.20781Published online 11 January 2006 in Wiley InterScience (www.interscience.wiley.com).

Magnetic Resonance in Medicine 55:404–412 (2006)

© 2006 Wiley-Liss, Inc. 404

��x,y;t� ��m

1 � ε�x,y;t�[1]

Another way to view this change in the modulation fre-quency is to consider it intravoxel dephasing that reducesthe signal intensity from this voxel as reported in (2,7,12).Alternatively, the frequency change can be considered ashift of the stimulated echo in k-space, as in the work ofOsman et al. (10). Based on this, the signal intensity of avoxel at (x,y) acquired using demodulation frequency �d

can be computed by simple integration of the magnetiza-tion on z (through-plane direction)

I�x,y,t;�d� � �p�x,y,t�s�z�cos���x,y,t�z�exp� � j�dz�dz,

[2]

where p(.) represents the signal intensity of the pixel dueto tissue properties such as proton density and T1 and T2

parameters. The function s(.) is the slice profile, whichdescribes the spatial distribution of the excited magneti-zation in the direction perpendicular to the imaging plane.Assuming homogeneous tissue inside the voxel, the signalintensity of that voxel can be simplified to

I�x,y,t;�d� � p�x,y,t��s�z�cos���x,y,t�z�exp� � j�dz�dz

�12p�x,y,t�S��d � ��x,y,t�� � S��d � ��x,y,t��. [3]

The new function S(.) is the Fourier transform of s(.), andit is of special importance because it describes the amountof signal attenuation caused by the deformation. We callthis function the S-profile to differentiate it from the sliceprofile described by s(.). Assuming that �d is close to�(x,y,t) and �m is larger than the bandwidth of the S-profile, the second term of Eq. [3] can be neglected (10),and the resulting image becomes

I�x,y,t;�d� �12p�x,y,t�S��d � ��x,y,t��. [4]

Equation [4] indicates that the signal intensity of a voxel isgiven by the true NMR properties of the tissue at that voxelmultiplied by a deformation-dependent function, S(.). It is

worth noting that the 1⁄2 factor in Eq. [4] indicates the factthat STEAM images suffers from a 50% inherent signalloss.

Assuming the conventional rectangular imaging slicewith a slice thickness L, the S-profile is then a sincfunction with a main lobe of the width 2/L. This meansthat for Eq. [4] to be valid, the modulating frequencyshould be larger than 2/L. In practice, however, higherfrequencies can be used to obtain better black-bloodcontrast. In case of no deformation, a demodulationfrequency �d � �m yields a maximum signal intensity.The deformation of tissue, however, causes a frequencyshift �(x,y,t) � �m , which results in a decay of signalintensity according to Eq. [4]. Specifically, a frequencyshift less than 1/L will cause signal attenuation as de-picted in the shaded area Fig. 2a, and a shift equal to 1/Lwill lead to a complete loss of the signal. Moreover, ashift that exceeds 1/L (outside the shaded area) causesthe signal intensity to slightly increase due to the sidelobe of the sinc function (dealing with magnitude im-ages implies that all signal values to be nonnegative).Equation [4] then provides a good explanation for thereported artifact in STEAM images of the heart (2,12).Note that for the rest of this paper, we will assume thecase of rectangular imaging slice, but the method isapplicable to more varieties of slice profiles.

Proposed Method to Suppress the STEAM Artifact

To recover the signal loss caused by tissue deformations,we propose the acquisition of two images, I(x,y,t;�min)and I(x,y,t;�max), using two different demodulation fre-quencies, �min and �max. These two frequencies aredefined as the lower and upper bound on the frequencyshifts caused by the tissue deformation. The lowerbound, �min, is selected to correspond to a maximumstretching not exceeded by the myocardium during thecardiac cycle (and we can be conservative). Similarly,the upper bound is selected to correspond to maximumcontraction. For the rest of the paper and for the sake ofclarity, we define the frequency shifts �s � �m � �min

and �c � �max � �m.Let ��x,y,t��� �(x,y,t)��min; therefore, its value will

range from 0 to (�s � �c), which we can assume, forsimplicity, is equal to 1/L. The signal intensity I(x,y,t;�min)is at a maximum if the tissue at that pixel (x,y) is atmaximum stretch ( � � 0) and drops to zero at maximumcontraction ( � � �s � �c). Conversely, the intensity willbe the opposite for I(x,y,t;�max): a maximum intensity atfull contraction and zero intensity at maximum stretching.The relation between the signal intensity of the images andthe local frequency shift can be shown by the solid anddashed curves in Fig. 2b, which show that the loss ofsignal intensity in one image is compensated by a gain ofsignal intensity in the other image. It is clear, then, that acombination (for example, summation) of the two imagescan recover the signal lost in both images. Mathematically,and using Eq. [4], the summation of the two images yieldsan image whose pixel signal intensity is

FIG. 1. Basic high-speed STEAM pulse sequence. The boxes onthe X/Y gradient axis represent the x- and y- gradients that are usedto traverse the k-space, which can be a spiral trajectory.

Correcting Deformation Artifact in STEAM 405

Isum�x,y,t� �� I�x,y,t;�min� � I�x,y,t;�max�

�12p�x,y,t� � S���x,y,t� � �min� � S���x,y,t� � �max�

�12p�x,y,t� � S� ��x,y,t�� � S��s � �c � ��x,y,t��. [5]

The signal intensity of a pixel in the resulting summationimage can be shortened to

Isum�x,y,t� �12p�x,y,t� � W� ��x,y,t��, [6]

where W� � � represents the terms between square bracketsin Eq. [5]. The bold curve in Fig. 2b shows the relationbetween W� � � and �, which shows that the function W� � �does not drop below unity at any level of frequency shift,i.e., no loss of signal intensity in the resulting summationimage.

Deformation-Independent Intensity

Although the summation image is satisfactory, a perfectintensity correction would require the signal intensity of apixel to be independent of the frequency shift, �. Thisideal case can be represented by a flat curve—the bolddashed line in Fig. 2b. This can be achieved by dividingIsum by W� �� at each pixel. While W(.) can be known for agiven slice profile, � is a deformation dependent and isnot known a priori. However, W� �� can be estimated fromthe images I(x,y,t;�min) and I(x,y,t;�max) without explicitlyestimating �.

Consider the ratio between the signal intensities of thetwo images

R�x,y,t� �� I�x,y,t;�max�

I�x,y,t;�min� � I�x,y,t;�max�

�S��s � �c � ��x,y,t��

S� ��x,y,t�� � S��s � �c � ��x,y,t��. [7]

Although this ratio is computed from the acquired signalsof a pixel, it is independent of the NMR properties of thetissue at this pixel. Since the terms �s and �c are prede-termined constants, the ratio R depends only on the fre-quency shift, �. A plot of the relation between R and �from Eq. [7] is shown in Fig. 2c. It can be seen from the plotthat the relation can be inverted so that given R, we canobtain an estimate, �̂, of �. Therefore, the appropriateweight W� �̂� at any pixel can be computed from the in-tensities of the pixel from the two acquired images. Thesignal intensity after correction is given by

Ic�x,y,t� �Isum�x,y,t�

W� �̂|�x,y,t��, [8]

Numerical Simulations

To test the performance of the proposed technique in thepresence of noise, the signal intensity was numericallysimulated for a homogeneous voxel of tissue undergoingdeformation. The voxel signal intensity was simulated viaEq. [4] with white Gaussian noise added in order to exam-ine the effect of noise. For simplicity, all of the simulationparameters were normalized (divided) by the slice thick-ness L. Therefore, the frequency shift, �, was changedfrom 0 to 1 (with increments of 0.05) to simulate the effectof the tissue deformation. At each increment of �, theshifted profile was sampled at points 0 and 1 to obtain thesimulated pixel intensities in the two images, I(x,y,t;�min)and I(x,y,t;�max), respectively. The sum of the two sam-ples, Isum, was obtained and weighted by W� �̂� as de-scribed above to obtain the corrected signal Ic.

In order to measure the amount of the resulting signaldependency on deformation (the fluctuation of Ic as a

FIG. 2. (a) A plot of the magnitude of the S-profile showing thesignal decay due to tissue contraction. (b) The signal intensitybehavior of a pixel as a function of the frequency shift (covering theshaded area in (a)) with the horizontal dashed line represents anideal deformation-independent signal behavior. (c) A plot of theratio, R, versus the frequency shift shows that there is a uniquevalue of R for each amount of frequency shift.

406 Fahmy et al.

function of �), the standard deviation (STD) of the signalIc was computed and normalized by the STD of Isum.

Another simulation was performed by following thesame steps as discussed above excluding the addition ofthe noise. In addition the shift, �, was incremented from0 to 2 in order to test the effect of having deformationlevels higher than the maximum anticipated limits.

Human Subject Experiment

Short- and long-axis cardiac images of six healthy volun-teers were obtained using a fast STEAM sequence. Written,informed consents were obtained in accordance with theprotocol approved by our Institutional Review Board. Theimages were acquired using spiral acquisition (12 inter-leaves) on an Intera 1.5 T scanner (Phillips Medical Sys-tems, Best, The Netherlands) equipped with a six-elementcardiac phased-array coil. The imaging parameters were256 � 256 matrix size, slice thickness � 10 mm, 25 cardiacphases, spiral acquisition window � 12 ms, TE/TR �4.9/23 ms, FOV � 350 mm, and total area of the modula-tion gradient (in the slice-selection direction) � 3.92 G.ms/cm. Also, a ramped flip angle with a maximum � 40o wasused to maintain constant signal intensity throughout thecardiac cycle despite the T1-related signal decay (13). Theuse of high modulating gradients increases the sensitivityof the pulse sequence to motion, which can be useful toenhance the dephasing of the blood magnetization; result-ing in better black-blood contrast.

For each imaging view (short-axis or long-axis), two setsof images were acquired with two different demodulationfrequencies. The initial tagging was applied at end diastolephase (full stretching state); thus, a value of �s � 0 wasused since the myocardium is not expected to undergofurther stretch during the rest of the cardiac cycle. Thevalue of �c was set to 0.33�m, which corresponds to amaximum contraction level of 25%—reasonable for ahealthy human (14).

Given a time plot of the myocardial signal intensity(averaged at selected myocardial points), the flatness of the

intensity curve is to be computed as a measure of theintensity variation caused by the local deformation. Thisflatness is computed as the STD of the given myocardialsignal intensity normalized by the STD of the static tissue(chest wall) signal intensity.

Animal Model Experiment

Animal models were used to test the ability of the pro-posed method to generate artifact-free images in case ofmyocardial motion abnormality. Three dogs were imaged9 weeks after an induced infarction. The imaging param-eters were 176 � 176 matrix size, slice thickness � 10 mm,25 cardiac phases, rectangular FOV � 256 mm, flip an-gle � 40o, spiral acquisition window � 12 ms, TE/TR �4.9/23 ms, and number of signal averages � 2. The mod-ulation and demodulation gradients were the same asthose that were described under “Human Subject Experi-ment. ” Localization of the infarcted region was achievedby acquiring a delayed enhancement image. The imagewas acquired 15 min after injection of a contrast agent(Gd-DTPA (0.2 mmol.kg�1, Magnevist, Berlex Laborato-ries, Wayne, NJ, USA),) using a fast field echo sequencewith inversion recovery (inversion time � 175 ms).

RESULTS

Simulation

The results of two cases of additive white Gaussian noisewith the peak signal-to-noise levels (at minimum deforma-tion level) equal to 30 and 15 dB are shown in Figs. 3a andb, respectively. The bold curves show the sum of the signalintensity after correction using W� ��, while the othercurves show the intensity without correction. Figure 3cshows a plot of the STD of the signal, with and withoutcorrection, at different levels of SNR (calculated at mini-mum deformation level).

Figure 3d shows the results (noise-free case) when thedeformation level exceeds the maximum anticipated

FIG. 3. The result of combining the twosignal intensities of the pixel with and with-out weighting at various frequency shiftsand at SNR � (a) 30 dB and (b) 15 dB witherror bars representing SD. (c) Intensity vari-ation at the different levels of SNR. (d) Sig-nal intensity at deformation levels spanninga larger range than the anticipated one.

Correcting Deformation Artifact in STEAM 407

value. The corrected signal drops after the point �� �s � �c. Nevertheless, the correction improves thesignal intensity substantially.

Human Subjects

Figure 4a shows short-axis images of five cardiac phases(at 58, 103, 148, 193, and 237 ms after ECG trigger) ob-tained with a conventional high-speed STEAM pulse se-quence (2), i.e., with �d � �m. It is clear from Fig. 4 thatcontracting regions disappear gradually until a completeloss of the cardiac tissue occurs, which is consistent withthe observations of Fischer et al. (12). Figure 4b shows theimages that correspond to Fig. 4a when acquired with ademodulation frequency of �d � (1 � 0.33) �m. As shownin Fig. 4, disappearing myocardial regions in Fig. 4a ap-pear in Fig. 4b. Combining the counterpart images of thetwo sets and compensating for the possible intensity fluc-tuation results in the images in Fig. 4c. Figure 5 shows aset of long-axis images from the same volunteer acquiredwith the same parameters as those in Fig. 4. It is clear fromFig. 5 that recovery of the signal loss was achieved bycombining the two acquired sets of images.

Visual inspection of the resulting images from the otherfive volunteers revealed the capability of the proposedmethod to recover the myocardial signal loss. These re-sults are summarized in Tables 1 and 2. Table 1 shows therelative contrast-to-noise ratio (rCNR) defined as the CNRof the myocardium in the compensated image Ic dividedby the CNR of the STEAM image, I1. The CNR was com-puted as the difference between the mean myocardial sig-nal (at manually selected points) and the mean back-ground intensity divided by the STD of the backgroundnoise. A considerable gain in the CNR can be seen fromTable 1. The flatness indicators of the myocardial signalintensity of images Isum and Ic are shown in Table 2 andillustrate the effect of the intensity weighting. Since theflatness is measured by STD of the signal, the lower thevalue in the table, the flatter the signal—i.e., better defor-mation independence. Clearly, the compensated imageshows a signal that is more deformation-independent thanthat of the summation image. Figure 6 shows the scatter ofthe (spatial) averages of myocardial signal intensitythroughout the cardiac cycle in the different images I1, I2,Isum, and Ic (for the case shown in Fig. 4). The signal

FIG. 4. Short-axis images of a healthy volunteer’sheart using a high-speed STEAM pulse sequence.Images (a.1–5) were acquired with Gd1 � Gm, whileimages (b.1–5) were acquired with Gd2 � 1.33Gm.Images (c.1–5) are the result of combining the cor-responding images in the other two columns,weighted as described in the text.

408 Fahmy et al.

intensity of the static tissue (chest wall) is shown in orderto indicate the variation of the signal intensity that is notrelated to deformation. All values displayed in Fig. 6 werenormalized by the average intensity of the static tissue.

Animal Model

The bright apical region in the right ventricle indicatedin the delayed enhancement image (Fig. 7) representsthe infarcted region. Figure 8 shows a four-chamberview of five cardiac phases (at 39, 84, 129, 174, and219 ms after ECG trigger). Images in Fig. 8a were ob-tained with a conventional high-speed STEAM pulse

sequence. It can be seen that the infarcted region re-mains visible in all time frames (Figs. 8a.1–a.5) whilethe normal region (lateral wall) fades as a function oftime until it disappears completely later in the cardiaccycle (Figs. 8a.4 and a.5). The corrected STEAM imagesare shown in Fig. 8b, where the infarcted region of themyocardium as well as the normal myocardium regionshave relatively constant intensity over all timeframes.Moreover, and as noticed in the human subject experi-ments, the corrected STEAM images show high contrastbetween the blood and the myocardium. Observationsfrom the other dog experiments were consistent with

FIG. 5. Long-axis images of a volunteer’s heartacquired using the same parameters of the imagesshown in Fig. 4.

Table 1The Relative Contrast-To-Noise Ratio (rCNR) of the Myocardium (Myocardial CNR in the Corrected STEAM Images Divided by theMyocardial CNR of the Conventional STEAM Images)

Human experiments Dog experiments

Subj 1 Subj 2 Subj 3 Subj 4 Subj 5 Subj 6 Dog 1 Dog 2 Dog 3

rCNR 7.83 4.52 3.66 3.36 3.37 4.70 3.14 3.62 3.89

Correcting Deformation Artifact in STEAM 409

those described above. A summary of these results isshown in Tables 1 and 2.

DISCUSSION

Although the deformation of tissue results in dephasing ofthe STEAM modulation, this dephasing is predictable andcan be eliminated by combining two STEAM images ac-quired with two different demodulation frequencies. Theintensity correction of the sum of the two acquired imagesis necessary to reduce the nonuniformity of the resultingimage and the dependence on local deformation. It isshown in Fig. 3b that the signal variation of the weightedsignal is very low compared to the unweighted signal athigh SNR. At low SNR levels, the main source of signalvariation is noise rather than deformation, and thus, therole of the intensity weighting may not be significant—although the weighted signal is more uniform than theunweighted one. The SNR of the in vivo images (in thedifferent myocardium regions) were in the range of 7–15dB, and thus the intensity weighting, albeit with variabledegrees of effectiveness, provides less deformation-depen-dency of the signal intensity.

Despite the low SNR of the STEAM pulse sequence, highcontrast between the myocardium and the blood can benoticed throughout the entire cardiac cycle (Figs. 4 and 5).This is due to the inherent black-blood property of theSTEAM technique, which represents a major advantage forthe application of this technique in cardiac imaging. Inaddition, although the proposed method requires doublingthe number of acquired images, with a subsequent 100%increase in scan time, rapid imaging sequences would

enable data acquisition in a single breath-hold. It is alsoworth noting that image misregistration may occur due toarrhythmias and variable length of the cardiac cycles. Nev-ertheless, this is a common limitation of MR imaging usingcardiac gating and can be minimized by speeding up theacquisition.

It can be seen in Fig. 6 that the lowest myocardial inten-sity in the compensated image is similar to the maximumintensity of the myocardium in the conventional STEAMimage. Also, as shown Fig. 6, the variation of the myocar-dial signal intensity in the corrected image (ranges from0.62 to 0.8 times the average intensity of the static tissue)is similar to that of the static tissue. Therefore, this signalvariation is explained mainly by imaging artifacts andnoise rather than deformation effects.

For the entire set of the examined subjects, as shown inTable 1, the CNR of the myocardium in the compensatedimage, Ic, is about 3 to 8 times that of the CNR in conven-tional STEAM images. It was found that the higher theSNR of the acquired images the higher the CNR gain whenapplying the proposed method. Moreover, it can be seen inTable 2 that the STD of the corrected image, Ic, is consis-tently lower than that of the summation image, Isum. Nev-ertheless, the difference between the two sets of STD wasnot statistically significant (P � 0.2). The reason for thisinefficient performance of the intensity weighting, whichagrees with the simulations findings, is the low SNR of theacquired images. However, when images of higher SNR areacquired (by increasing the number of signal average(NSA) or using a scanner with a higher magnetic field), theintensity weighting can play a more significant role.

An interesting finding is that, in the standard STEAMimages (Fig. 8a), the lateral wall disappears completelywith time while the signal of the infarcted regions is only

FIG. 7. Delayed enhancement image of a canine heart. The arrowsmark the location of the infarction.

Table 2The Flatness Measure of the Myocardial Signal Intensity (� STD (Myocardial Signal)/STD (Chest Wall Signal)) in Both the Summationand the Corrected Images. The Lower the Flatness Measure the Lower the Deformation-Dependency of the Myocardial Signal

Human experiments Dog experiments

Subj 1 Subj 2 Subj 3 Subj 4 Subj 5 Subj 6 Dog 1 Dog 2 Dog 3

STD(Isum) 5.50 1.03 2.97 0.32 0.44 0.40 0.79 0.23 2.51STD(Ic) 4.26 1.01 2.25 0.22 0.32 0.29 0.59 0.17 1.72

FIG. 6. Myocardial signal intensity at the different time frames inimages I1, I2, summation image (Isum), and the compensated image(Ic). The intensity of the static tissue at the different time frames isshown for comparison. All values are normalized to the (temporal)average intensity of the static tissue.

410 Fahmy et al.

slightly attenuated. This is due to the difference in thecontraction levels between the infarcted and the normalmyocardial regions. This can be a method of viewing sta-tionary regions of the myocardium, but more work needsto be done to explore this finding.

The high modulating gradients in the presented methodenhance the dephasing of the blood magnetization and,thus, lead to a better black-blood contrast. Also, applying

these gradients along the slice-selection direction (ratherthan in the x- or y-directions) prohibits the phase andfrequency encoding gradients from refocusing the FIDecho or the conjugate stimulated echo. This is advanta-geous because it allows increasing the in-plane spatialresolution without having artifactual interference fromsuch echoes.

It is worth noting, however, that if the modulation gra-dients are used in the x- or y- directions, a similar intra-voxel dephasing phenomenon may occur due to in-planedeformation. However, this turns out to be an advantage initself as it enables tracking of the myocardial points, whichhas been utilized in a number of techniques (7–9,11,15).These techniques avoid signal attenuation by combininglow in-plane modulating gradients (�0.6 G.ms/cm) andusing relatively high in-plane spatial resolution imaging(e.g., 2 � 2 mm). This selection of sequence parametersgives coverage of the (in-plane) k-space that is largeenough to capture the stimulated echo despite the shiftcaused by the dephasing. Other forms of tissue motionmay also affect STEAM images. For example, rotationaround an in-plane axis leads to intravoxel dephasing andthus may lead to signal loss (12). Nevertheless, thisdephasing can be used to determine the tilting of themyocardium (10). Translational motion, on the otherhand, changes only the modulation phase, rather than thefrequency, and thus does not lead to intravoxel dephasing.

One issue could be the side lobes of the S-profile. Al-though their effect is not significant for the image correc-tion, it is better to limit the total shift of the S-profile,caused by tissue deformation, to less than 1/L. In a realimaging situation, this can be guaranteed by selecting theright combination of slice thickness and modulation gra-dient according to the maximum expected tissue deforma-tion. For example, if the maximum expected regional de-formation in the heart muscle is 5% (stretching) and�20% (contraction), then using Eq. [1], the total shift rangeof the S-profile will be 33%. Therefore, given a modulationfrequency, �m, the quantity 1/L should be equal to 0.33�m,i.e., a slice thickness of L � 3/�m should be used. Con-versely, given a specific slice thickness, the modulationfrequency, �m, and hence, the gradient, Gm, can be se-lected to satisfy the above assumption. Analogous to thecase of selecting the Venc (velocity encoding anti-aliasinglimit) in phase-contrast methods, a trade-off exists whenanticipating the value of the deformation range (16). Ingeneral, when the deformation exceeds its maximum an-ticipated value, further correction of the signal is not pos-sible and the signal starts to decay as shown in Fig. 3d.Nevertheless, overestimation of the deformation limits canbe employed to allow correction for exaggerated abnormaldeformation levels. It is worth noting, however, that in-creasing the anticipated limits requires decreasing theslice thickness (as �s � �c should be less than 1/L). Thismay lead to a further reduction in the SNR. For example, adeformation limit of 50% requires that the slice thicknessbe less than 3.5 mm (given �m � 0.3 mm-1), which furtherreduces SNR. A remedy for that is to reduce the modulat-ing frequency a little bit; say 0.20 mm�1, which allows useof a slice thickness of 5 mm. Further reduction in themodulating frequency may lead to a loss of some tissue-

FIG. 8. Long-axis images of the canine heart using a high-speedSTEAM pulse sequence. (a.1–5) STEAM images without correction;(b.1–5) corrected STEAM images.

Correcting Deformation Artifact in STEAM 411

to-blood contrast due to the overlapping of the blood FIDecho with the stimulated echo.

CONCLUSION

In this work, we propose a method that enables functionalSTEAM imaging of the heart without signal loss despitethe tissue deformation. Although the method may requiredoubling the number of the acquired images, it does notrequire significant modification of the current standardSTEAM pulse sequences. The method opens the way formany imaging applications that use STEAM sequencesthat were hindered by the deformation-induced artifact.Also, the method inherently produces a black-blood con-trast between the ventricular cavity and the myocardiumand thus enhances the ability to observe the endocardiumthroughout the time frames of the sequence.

ACKNOWLEDGMENTS

The authors thank El-Sayed Ibrahim for his help in devel-oping the pulse sequence. We also thank Dr. Dara L.Kraitchman for her help with the dog experiments. DrStuber is compensated as a consultant by Philips MedicalSystems NL, the manufacturer of equipment described inthis presentation. The terms of this arrangement have beenapproved by the Johns Hopkins University in accordancewith its conflict of interest policies.

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